BMI

Daily Report: August 20,2024
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1. Current Task: Implement a User Interface Web Application for AI platform by using DASH Framework in python.
2. Explored the Fundamentals of DASH Framework on plotly dash platform.
3. Tried to implement some sample code that is useful for creating the user interface.
4. Started Creating User Interface for AI Platform.

Daily Report: 21/08/2024
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1. UI Work in progress: Created two Tabs for training ,testing and validation. Dashboard of the AI platform implemented successfully.
2. Modification is required for user interface.
3. Exploring "dash_bootstrap_components" and bootstrap themes or templates for dash.
4. Installed the "dash_bootstrap_components" package for UI.
5. Started creating UI with the help of bootstrap themes.

Daily Report: 22/08/2024
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1. Preparing PPT for the presentation about DASH framework in python conducting on 27/08/2024.
2. Exploring DASH callbacks and its fundamentals(What is callback,why callbacks are important in dash,how they called,when it executes,basic syntaxes, etc.).
3. Found an ERROR, Successfully Corrected the ERROR "A nonexistent object was used in an Input of a Dash callback.The string ids in the current layout are:
[tabs, button-container, btn-1, btn-2, btn-3, btn-4, btn-5, btn-6, content-area, selected-checkboxes].
4. Successfully Created the Header and DashBoard of the UI using "dash_bootstrap_components" themes.
5. Exploring "dbc" components in DASH Framework.

Daily Report: 23/08/2024
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1. Successfully completed the Train UI implementation for main contents of the General Settings menu(Settings such as Entering volunteer/Patient id,
sampling rate,EEG time Frame,Decision Window size,Overlap Window size).
2. Designed and developed Train UI for main contents of "DATA" menu( Data Upload for Signal,Text,Image,Video).
3. Discussion with PL about the current Train UI Design and Noted Required Changes..
4. Development of Train UI for the "Pre-Processing" menu in the dashboard is in progress.

Daily Report: 24/08/2024
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1. Discussion with PL about the Progress in the Train UI Design and Noted Required changes such as the layout and appearance of the Dashboard buttons, the collapse and Accordion needed for the data Selection Checkbox( corresponding upload components that appear directly under the selected checkbox.).
2. Exploring the implementation of the collapse and Accordion for the requirement mentioned above.
3. Explored the External CSS styling and how it can be included into dash Program with the help of YouTube.
4. Successfully Styled the Buttons of the Dashboard by using External Stylesheet(CSS).
5. Exploring "How to create a pop-up, modal, or confirm dialog".

Daily Report: 28/08/2024
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• Explore "What is openCV and What are the main advantages,working, etc".
• Explore openCV in DASH for "How to stream of video from Webcam.

Daily Report: 30/08/2024
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1. Meeting with Project Lead.
2. Exploring about openCV and its use with DASH framework.
3. Exploring the sample Github code for streaming webcam to DASH app by using openCV.
4. Installation completed for openCV(i.e, cv2) and supporting packages such as plotly.express, numpy,etc.
5. Exploring the Core Functionality of openCV, Mat-The Basic Image Container, how to read an Image, etc.

Daily Report: 02/09/2024
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Daily Report: 03/09/2024
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1. Exploring how to make an interface for webcam using OpenCV.
2. Discussion with Project Lead about the ongoing activities.
3. Successfully Explored the code that stream the webcam video by using openCV,Dash in python.
4. Current Task: How to Detect an Object from a video or image by using webcam with the help of OpenCV Dash Framework in python.

Daily Report: 04/09/2024
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1. Work in Progress: Trying out a sample program that detecting an object from an image in openCV dash framework.
2. Found a cv2.error: OpenCV(4.10.0) D:\a\opencv-python\opencv-python\opencv\modules\dnn\src\darknet\darknet_importer.cpp:210:
error: (-212:Parsing error) Failed to open NetParameter file: yolov3.cfg in function 'cv::dnn::dnn4_v20240521::readNetFromDarknet'.
3. Exploring alternative method for "dash_player" package in html(i.e, html.video component) and correcting the existing code with this component.

Daily Report: 05/09/2024
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Daily Report: 06/09/2024
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1. Successfully designed and referred the face detection of human from a video(in MP4 format) by using OpenCV dash framework in python. In this Code the output will be given in video Format.
2. Discussion with Project Lead about the current tasks and noted the suggestions for improvement.
3. Current Task: How to detect an Object form a live video and give the output in a webpage(user interface)as a video with object within a square and object label.
4. Installed "io" and "base64" package and exploring the main usage of ObjectDetector class and its uses.

Daily Report: 09/09/2024
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1. Discussion with Project Lead about the current task going on.
2. Exploring "how to detect different objects from a video...and it gives output as a video with each objects having their own label within a rectangle..
i need this to be implemented in STREAMLIT framework in python".
3. Successfully Installed Streamlit package and threading for implementing the object detection.
4. Exploring Object detection code in streamlit framework.

Daily Report:10/09/2024
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1. Discussion with Project Lead about the current work.
2. Designing and Developing LED bulb Blinking Detection from a video using DASH and OpenCV.
3. Then found a conflict while displaying the output video(AttributeError: 'tuple' object has no attribute 'flatten'). Also Flickering and unstable output in Dash application.
4. Exploring new methods for fixing the flickering and unstable output(such as Temporal Smoothing).

Daily Report:11/09/2024
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1. Exploring the methods for removing flickering, shattering, blurring the output video when we are detecting the bulb blinking from a video.
2. Successfully removed AttributeError: 'tuple' object has no attribute 'flatten'.
3. Downloaded sample LED bulb blinking videos from the internet for testing.
4. Updation of current task: Implementing a LED Bulb Blinking Detection system that detects the bulb is "on" or "off" by using the DASH, openCV in python.
Some modification and stability in that output is needed.

Daily Report:12/09/2024
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1. Discussion with Project Lead about the Object Detection Task going on.
2. Explored the Object Detection code in streamlit framework successfully.
3. Installed "yt-dlp (version: 2024.7.16) and ultralytics(version 8.2.60)" necessary package for Running the Program.
4. Meeting with PL, Deepak and software development team about the working and Demo Explanation of CCET project.

Daily Report: 13/09/2024
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1. Copied the CCET Project code to PC successfully.
2. Started Exploring the code[classes used in it].

Daily Report:18/09/2024
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1. Exploring about "Concentration and Co-ordination Exercise Tool (CCET)".
2. Tried to Running the CCET project and found some issue while running the project(TypeError: 'module' object is not callable Traceback (most recent call last):
File "F:\testgodbuzzwire\calibratepixmm.py", line 18, in select_points
if len(self.points) < self.comparePoints:
TypeError: 'module' object is not callable).Successfully corrected the ERROR.
3. Installing the Required packages such as "OpenCV", "NumPy", "PyQt5", "sys", "len", "print" according to the particular version.

• Convert the Current working CCET Project to Web Application.
• Explore the following: [Difference between web-server,database server and Web application server, the libraries needed in python to deploy the server in streamlit,
  web application deployment and its steps, web archive, How to train and model can generate in YOLO, Apache and Tomcat servers, static and dynamic websites , etc].

3. Meeting Attended about the Demo of YOLO training model and seizure prediction Project with PL and other members of that project.
4. Exploring the above mentioned areas.

Daily Report:20/09/2024
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1. Exploring the web Application server is used for streamlit framework in python using pycharm coding platform.
2. Discussion with Project Lead about the CCET Project and Web Application Implementation.
3. Discussion with Mr.Shambu About the working and overall idea about CCET Project with the help of Demo.
4. Exploring Main Requirements for the Deployment of web application in streamlit, and its basic steps.

Daily Report: 23/09/2024
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1. Discussion with Project Lead and Mr. Shambu about "How the Streamlit web Application deployed with NginX server for the availability of the object detection using YOLO for all devices who connected to the same network".
2. For the Implementation of deployment with NginX server, Installed Windows Subsystem for Linux(WSL) successfully.
3. Installed NginX for using it as a web Application server for the current Streamlit project(for object detection).
4. Joined a meeting with the Department Head and fellow project team members to celebrate our recent recognition with the United Nations(UN) award.

Daily Report: 24/09/2024
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1. Discussion with Project Lead about the work going on(discussed about the streamlit community cloud and currently available tutorials for deploy streamlit web application).
2. Exploring NGROK tool for creating secure channel that allows to share your local development environment with others by generating a public URL that forwards traffic to your local machine.
3. Attended ISO-awareness training program at HTG1 Conference Hall.
4. Exploring about the streamlit community cloud and tutorials for deploying streamlit web application concept.

Daily Report: 25/09/2024
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1. Discussion with Project Lead about the Progress in Deployment of streamlit object detection project to the local network and Deployment of the sample streamlit project to our server.
2. Successfully configured the Ngrok tool and deployment successfully implemented, Now it is available in a specific address and that can be accessible for all users who need to detetct object.
3. Exploring Appliku and other guides for deploying the streamlit web application to our server.

Daily Report: 26/09/2024
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1. Explored Remote Desktop Protocol(RDP) tool and Its features that is used in the deployment of streamlit web application in our own server.
2. Meeting with Project Leads and Mr.shambu about CCET Project progress.
3. Exploring How to bind or pack the streamlit application in pycharm platform, different platforms and ways to deployment and comparing each of them( Hugging face space,streamlit community cloud,render,github, etc.).

Daily Report: 27/09/2024
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1. Exploring about NginX web server, features, and comparison between Apache and NginX, types of NginX, reverse proxy servers.
2. Tried to find which module in the streamlit package will be helped to the package itself acts like a server for ruuning the Application.
3. Referred the Basic steps needed for deployment of streamlit web application using Nginx.

Daily Report: 30/09/2024
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1. Discussion with Project Lead about the deployment procedure.
2. Exploring about DOCKER platform, it's usage, Architecture, DOCKER objects, etc.
3. Installation successfully completed in Linux-Based system for the deployment of streamlit web application using DOCKER.
4. Trying to install other requirements such as streamlit package in ubuntu system.
5. Some ERRORS found while installing the streamlit on the Linux-Based and when using the docker desktop application. Now Trying to figure it out that problem with DOCKER desktop application.

Daily Report: 01/10/2024
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1. Reinstalled Docker Engine on the Linux Based PC successfully.
2. Fixed the problem of stucking the Docker Engine while using.
3. Installing the required packages such as streamlit, pandas, numpy,
4. Facing some issues while installing the packages ( mainly the version incompatibility).

Daily Report: 03/10/2024
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1. Dicussed with Project Lead about the deployment process and related concerns.
2. Referred internet and other resources for " How to correct the Error: Cannot connect to the Docker daemon at UNIX:///home/cdac/var/.......//: Is daemon Running? ".
3. Successfully corrected the Error and Deployed the project the server. But found some issues with the packages such as Ultralytics, yt-dlp. So now Trying to install that packages and pull that new changes to the docker engine.
4. Found some issues with the above updations.

Daily Report: 04/10/2024
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1. Exploring about "how to fix the problem of logging to ubuntu leading to the initramfs prompt or other boot problems. and their structured approach to help you regain access".
2. Referring about "initramfs(initial RAM filesystem)".
3. Trying to install any packages newly after the web application is run on docker or deployed in docker.
4. Exploring the deployment of web applications with nginx and docker.

• docker: Error response from daemon: driver failed programming external connectivity on endpoint heuristic_tesla (e5faf4a96c94e09e1c840a1d60b3c78a79eaaf3caeeab38d4dcaafb6029e0eae): Bind for 0.0.0.0:8501 failed: port is already allocated.
• ImportError: libGL.so.1: cannot open shared object file: No such file or directory
  2024-10-07 09:06:14.504 Uncaught app exception
  Traceback (most recent call last):
  File "/usr/local/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 589, in run_script
  exec(code, module._dict).

2. Exploring " To install the missing libGL.so.1 library in your Docker container. How do this by adding the necessary packages in Dockerfile."
3. Discussion with Project Lead about the tasks.

• Explore How to convert the whole python project to .exe file(executable file).
• Free up the storage space of the system and Install Virtualbox and install Ubuntu in Windows system.
• Convert the Yolo Object detection project that have the capability to browse it into phone and also take the phone camera for taking the video of the object.
• Complete date based license approving for a particular project settings work with Gowrisree.

• Exploring different methods that is used to convert the whole python project to .exe file(executable file).
• Exploring about pyinstaller, cx_freeze and auto-py-to-exe.

Daily Report: 09/10/2024
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1. Discussion with Project Lead about the work.
2. Installed "pyinstaller", "cx_freeze" and "auto-py-to-exe" successfully.
3. Exploring pyinstaller tool and its key features and comparison between other methods.
4. Started building .exe file with the help of pyinstaller. found an error like this: Traceback (most recent call last): File "Main.py", line 67, in <module> NameError: name 'ctk' is not defined.
5. Exploring the "cx_freeze" tool.

Daily Report: 10/10/2024
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1. Exploring how to combine multiple files into single exe file.
2. Trying the conversion with a sample python project that contain a UI and two other files for the operations and calculations.
3. Created a sample UI that takes some information.
4. Exploring how we can pass the information from the ui to a json file, and that information is passed to that exe file when it runs.

• No module Found named as: "imagGen"
• RecursionError: maximum recursion depth exceeded.

Daily Report: 15/10/2024
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1. Discussion with Project Lead about the Work in progress.
2. Trying to fix the Errors found earlier. Explored the steps to Troubleshoot and resolve the issues of Module not found Error.
3. Changed the Existing paths and directories for each folders/modules, changed the code of setup.py, added some required packages and excluded some unwanted packages.
4. Re-building the "setup.py" according to the changes made in "setup.py" program.

• Copy the generated exe file to other system and test/verify its working or not.
• Build this .exe file with including the Developed License module for the authentication and validation.

Daily Report: 17/10/2024
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1. Discussion with Gowrisree about the development of license module to implement authentication and validation.
2. Current Task: Check the International Conference Inbox E-mails.
3. Checked the Emails, noted the current emails.
4. Discussion with Anusree about the emails of international conference.

• Traceback (most recent call last):File"C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\i mportlib\metadata\_init__.py", line 563, in from_name return next(cls.discover(name=name))
  Stopiteration
• During handling of the above exception, another exception occurred:Traceback (most recent call last):File"C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\s ite-packages\tktooltip\version.py", line 6, in <module> version = version("tkinter-tooltip")
  File
  "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\i mportlib\metadata\_init_.py", line 1008, in version return distribution (distribution_name).version
  File
• "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\i mportlib\metadata\_init__.py", line 981, in distribution return Distribution.from_name(distribution_name) - did not match any documents.

3. Trying to fix the above Errors and exploring each errors.
4. Successfully checked all the new Emails of International Conference and replied for each emails( With the Guidance of Anusree).

• File "EbrainVoicePipeline.py", line 37, in <module>
  C:\Executable\eBrainVoice_V3pt0\eBrainVoice\module\executeexecutePipeline.py", line 29, in <module> from eBrainVoice.module.src.ai.dl.ClassifierTestImgDL import Classifier TestImgDL
• File
  C:\Executable\eBrainVoice_V3pt0\eBrainVoice\module\src\ai\d\ClassifierTestImgDL.py", line 23, in <module>from eBrainVoice.module.src.ai.dl.ClassifierTrainImgDLimport *
• File
  C:\Executable\eBrainVoice_V3pt0\eBrainVoice\module\src\ai\d\ClassifierTrainImgDL.py", line 28, in <module>from eBrainVoice.module.src.ai.dl.ClassifierFunctionsImgDLimport *

• File C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\__init__.py", line 80, in <module>from.import_distributor_init # i: F401
• File C:/Users/hp/AppData/Local/Programs/Python/Python311/Lib/site-packages/sklearn/_distributor_init.py", line 21, in<module> WinDLL(op.abspath(vcomp140_dll_filename))
• File C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\ctypes_init__.py", line 376, in _init_self._handle = _dlopen(self._name, mode)

• Removed the unused or unreached tools from each module such as tkTooktip,glob,re etc..
• Successfully corrected the Errors occured in the way of UI in each module.
• Looking for the solutions for the problem encountered early. Trying to to load vcomp140.dll and msvcp140.dll from a .libs directory located alongside the distributor_init.py file.

• error: [Errno 13] Permission denied: 'C:\\Executable\\eBrainVoice_V3pt0\\build\\exe.win-amd64-3.11'

Daily Report: 24/10/2024
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1. Checked the version compatibility of the packages such as sklearn. Checked the current version of sklearn tool.
2. Re-Installed the package once again.
3. Exploring the how to change the setup configuration file(i.e, setup.py) for including the files such as vmcomp140.dll and msvcp140.dll. (This is for checking the coversion is stuck with this files or not).
4. Encountering the missing dependencies.

• Split up the whole EbrainVoicePipeline_v3pt0 into parts and convert it into .exe file.
• Firstly create a folder that contain the project's pre-processing part and convert it into .exe file.

• "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\cx_Freeze\initscripts\__startup__.py", line 140, in run module_init.run(f"__main__{name}")
  File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\cx_Freeze\initscripts\console.py", line 25, in run exec(code, main_globals)File "EbrainVoicePipeline.py", line 43, in <module>File"C:\Executable\PreprocessingEXE\eBrainVoice\module\src\view\simulator_Ul.py", line 30, in <module>from eBrainVoice.module.execute.machinePipeline import ExecuteRealTimeAnalysis as rta
  File"C:\Executable\PreprocessingEXE\eBrainVoice\module\execute\machinePipeline.py", line 37, in <module>from eBrainVoice.module.src.ai.ml.ClassifierFunctions import continues_predict_detection
  ModuleNotFoundError: No module named'eBrainVoice.module.src.ai

1. Correcting the Errors and Exploring how to remove the errors occurs during the conversion of python project to .exe file with the help of cx_freeze tool.
2. Successfully corrected some of the errors mentioned earlier.
3. Stuck with a package or library named "neurokit2"(package is used in upORdown_sampling.py file) and "antropy"(package is used in frequencyDomainFeature.py file) while converting the file. Looks like the module or some of the dependencies are missing..trying to figure it out that.
4. Exploring "how to convert the python project(i.e, Preprocessing part of EbrainVoicePipelinev3_pt0 project.) to .exe file without removing or commenting the libraries or packages".

2. Checked the international Conference emails and sended the reply emails successfully.

Daily Report: 29/10/2024
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1. Correcting the whole errors occured while the conversion of exe file.
2. Successfully corrected the problem of
File"C:\Executable\PreprocessingEXE\eBrainVoice\module\execute\machinePipeline.py", line 37, in <module>from eBrainVoice.module.src.ai.ml.ClassifierFunctions import continues_predict_detection
ModuleNotFoundError: No module named'eBrainVoice.module.src.ai ....................
3. Cleared the errors of User Interfaces and currently working successfully.
4. Discussion with Project Lead.
5. Merged the ImageGeneration .exe part and PreProcessing part of the "EbrainVoicePipeline_v3pt0" project successfully.
6. Checked the emails of International conference and sended the reply emails successfully.

• .exe file conversion of preprocessing part is completed.
• Currently converting and working on the feature extraction part.
• Combined the files of data,preprocessing ,ImageGeneration and feature modules.
• Found this error and correcting it.
  File "C:\Executable\eBrainVoice_V3pt0\eBrainVoice\module\execute\executePipeline.py", line 35, in <module>from eBrainVoice.module.src.ai.ml.ClassifierTrain import *
  File "C:\Executable\eBrainVoice_V3pt0\eBrainVoice\module\src\ai\ml\ClassifierTrain.py", line 35, in <module>import xgboost as xgb
  File"C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\xgboost__init__.py", line 8, in <module>from.core import......

2. "National Cyber Security Program" Meeting attended.

• Correct the problem of stuck during the Feature Extraction module(i.e, we need to write the selected feature's data into an XL sheet after the feature entered and click onto the execute button.).
• Create a seperate file for AI Technique module in the EbrainVoicePipelin_v3pt0 project for converting it into exe and also for checking the problem with the packages such as sklearn, antropy,imblearn,etc..is it has the problem with the package or not.

3. Checked the emails of International Conference and replied for all the authors who mailed their concerns.

• Successfully completed the conversion of PreProcessing , ImageGeneration and feature extraction part of the eBrainVoicePipeline_v3pt0 project part to exe application file.
• Created a new folder that contains the UI's and AI techniques module and Post-Processing module.

2. Started to convert the above mentioned folder into exe file.
3. Exploring the "CX_FREEZE" tool's Documentation sites for identifying the "Solutions for the problem of encountering a recursion error when trying to compute the list of dependencies, or the lib folder of the frozen application containing many unnecessary packages."

• Converting the AI_techniques module and execute module to .exe file, Correcting the errors occuring while conversion.
• Encountered some new errors with new packages/libraries, they are:
  File"C:\Executable\Al_techniques EX\eBrainVoice\module\src\view\livepredictionmethod_Ul.py", line 23, in <module>from eBrainVoice.module.src.shareRealtimeData.showRealtime Ul import realtime_ui_show_func as srtu
  ModuleNotFoundError: No module named'eBrainVoice.module.src.shareRealtime Data.

2. Attended Vigilance Awareness Week Program with theme: "Culture of Integrity for Nation's Prosperity".
3. Exploring the alternative function for the MinMaxScaler and StandardScaler that is imported from the sklearn package.

• File "<frozen importlib._bootstrap>", line 690, in_load_unlocked File "PyInstaller\loader\pyimod02_importers.py", line 378, in exec_module File "mne\report\report.py", line 101, in <module>
  File "pathlib.py", line 1058, in read_text open File "pathlib.py", line 1044, in
  FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\hp\\AppData\\Local\\Temp\\_MEI19042\\mne\\report\\js_and_css\\report.js'
• A RecursionError (maximum recursion depth exceeded) occurred.
• Python's stack-limit is a safety-belt against endless recursion,eating up memory. PyInstaller imports modules recursively.

• Trying to figure out the error found while the conversion of python project to exe with the help of auto-py-to-exe tool.
• Referred the internet for "how to convert the our python project to exe using "auto-py-to-exe" tool.
• Successfully corrected some of the errors occured yesterday.

2. Discussed with Ms. Dhanya about the Conversion workflow.
3. Found a new error: Failed to collect submodules for 'astropy.tests.figures' because importing 'astropy.tests.figures' raised: ModuleNotFoundError: No module named 'pytest'.

• Unhandled exception in script Failed to execute script 'EbrainVoicePipeline' due to unhandled exception: Cannot find XGBoost Library in the candidate path. List of candidates:
  X- C:\Executable\Al_techniquesEXE\output\EbrainVoicePipeline\_internal\xgboost\lib\xgboost.dll

2. Checking the Missing files that is needed while converting the folder into exe. Also checked the virtual environment Issues because of that exe should run within the same environment.
3. Successfully corrected the errors occured yesterday while the conversion of project into exe.
4. Changed the some Advanced settings while using the "auto-py-to-exe" tool.
5. Exploring how to add and find the location of mne folder that is not found in the executable file folder.
6. Task Completed: Successfully converted the "EbrainVoicePipeline_v3pt0" project to executable file(.exe) by using "Auto-Py-to-exe" Tool. Started testing to check whether it is working correctly or not.

• Create a Document for the Creation or the conversion of a Python project to an exe file by using "Auto-Py-To-Exe tool.
• Create a Document for the step by step procedures that we have to take when Deploying a Streamlit Web Application in Docker.

5. Started Document Creation work.

Daily Report: 11/11/2024
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1. Discussion with Project Lead and shambu about the CCET Project works and ideas to do. Noted the works assigned for me.
2. Successfully Completed the Document creation of How to create .exe(Executable file ) from a python Project.
3. Current work is with the creation of Document for the Deployment of Streamlit Web-Application in a Docker Engine.
4. Making a note(Troubleshooting) that explaining the Possible error and its solution to fix the errors.
5. Referring the previous notes to help that creation of document.

• Added sample console based screenshots of the deployment process into the Document of "deployment".
• Successfully send the completed Document of "exeCreation" to Project Lead,Dhanya and Deepu through email.

• Explore about PostgreSQL
• Update the user manual of MIme Application according to the changes have made now.

3. Noted the Changes needs for the Document of "exeCreation".
4. Current task going on: Updating the Document of exeCreation(adding more details and screenshots(if there)).

• Creating a User-Interface for the CCET Project Settings using flutter in Android app model.
• A sample UI is created using HTML.

2. Discussion with Chris about the flutter and its installation of dependencies such as ,java jdk, visual studio code IDE, Android studio etc.
3. Successfully installed Flutter SDK, and VScode IDE for the Development.

Daily Report: 18/11/2024
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1. Successfully defined the path variable for the Flutter SDK, Java JDK.
2. Referred "How to create a new Project in Visual Studio Code by using flutter as a Programming Language".
3. Successfully installed Java Development Kit(JDK) to the system and configured the path variable, and installed the flutter and Dart in VScode for the Extension.
4. Started Developing User Interface for the CCET project by using flutter.

• Successfully Designed and implemented User Interface for the CCET Project(contains A heading "CCET settings" followed by toggle button options such as "Buzzer","RGB LED", "Vibrator", the value storing in an array)using Flutter.

2. Discussion with Ramesh about the continuation of work in CCET.
3. Exploring "How to print the list of connected devices/embedded system in our system" by using flutter and its package namely "usb_serial".
4. Checked the Emails of International Conference, replied for the necessary mails.

Daily Report: 20/11/2024
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1. Tried a sample code for printing connected serial communication devices such as COM3, COM5,etc...(stuck with the problem of windows incompatibility issues.)
2. Exploring and referring "how to print the connected devices lists in a flutter UI app. using windows based system and vscode for the coding.
3. Checked the Emails of conference and replied for the necessary mails.

Daily Report: 21/11/2024
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1. Creating an app containing the UI for the CCET and stuck with the below "gradle" problem:What went wrong: A problem occurred configuring project ':flutter_libserialport'.

Could not create an instance of type com.android.build.api.variant.impl.LibraryVariantBuilderImpl.> Namespace not specified. Specify a namespace in the module's build file. See https://d.android.com/r/tools/upgrade-assistant/set-namespace for information about setting the namespace.

2. Exploring how to fix the problem mentioned above.
3. Re-installed android studio for setting up the gradle for the app working.

Daily Report: 22/11/2024
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1. Successfully corrected the error mentioned earlier by created a new flutter project file in vscode and opened the "android" folder in android studio and edited.
2. Found another error and corrected succcessfully by adding NDK version into the "build.gradle" file.
3. Stuck with the problem of :: Launching lib\main.dart on sdk gphone6 x86 64 in debug mode...
FAILURE: Build failed with an exception.What went wrong!Execution falled for task app:checkDebugAarRetadata".
4. Checked the conference emails and replied successfully.

Daily Report: 23/11/2024
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1. Work in Progress: Gradle Problem with normal User Interface of CCET fixed by hot reload or hot restarting of Flutter DevTools debugger settings.
2. Still have the gradle problem with the "usb_serial" package.
3. Exploring the forums of flutter and serial port connection for android app.
4. Doing the pending Documentation work.

Daily Report: 25/11/2024
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1. Trying out new alternative package for "usb_serial" to sort out the problem of gradle error such as "////BUILD FAILED in 1s
Error: Gradle task assembleDebug failed with exit code 1/////".
2. Exploring "which framework is the better one for creating mobile application".
3. Referred Android Gradle Plugin(AGP) upgrade Assistant forums.

Daily Report: 26/11/2024
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1. Find outing new packages that is used for displaying the connected USB devices/ any other hardware devices.
2. Changing the current package with new alternatives such as "serial_port_win32" and "flutter_libserialport".
3. Checking the errors occurred while running the flutter app.

Daily Report: 27/11/2024
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1. Exploring flutter and Bluetooth connecting devices in an android App.
2. Referring how to connect a bluetooth device seamlessly to Flutter app, it’s essential to grasp the fundamentals of Bluetooth connectivity.
3. Trying out the sample code for the bluetooth device connection in an app.And correcting the errors of gradle.
4. Checked the emails of Conference and reply mails has been sent successfully.

Daily Report: 28/11/2024
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1. Exploring about the "flutter_blue_plus" package and trying outing to connect with bluetooth devices.
2. Successfully installed visual studio code, flutter sdk, and android studio in an another PC.
3. Successfully installed new supporting packages and dependencies for the app development.
4. Exploring how to open and test the developed flutter app into our own mobile phone.( enabling USB tethering, Developer mode, etc.)

Daily Report: 29/11/2024
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1. Exploring new packages for implementing the Bluetooth devices connect with a flutter android app.
2. Meeting attended with Dhanya about the Explanation of BCI project such as innerspeech,eyeBlink,SSVP, overall ideas about the project, brain lobes, How EEG data collected and storing,
AI Techniques and algorithms used in it, graphical representations etc..

Daily Report: 02/12/2024
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1. Exploring about the new package "flutter_reactive_ble version^5.3.1 " for implementing an app connected with bluetooth devices, their features such as Establishing a BLE connection,
Read / write a characteristic, Observe host device BLE status, etc.
2. Referring the code for implementing this by using the above mentioned package.
3. Trying to implement the referred code.

Daily Report: 03/12/2024
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1. To resolving the Problem with the connection of bluetooth devices in flutter app, going to implement an app that have the access of camera in that particular phone while using it.
2. Exploring "how to Develop a flutter android app that allows the access of camera by capturing image and gives the captured image".
3. Referring the flutter documentations for identifying the built-in plugins or packages.
4. Verified the schedule of iCon-BCI international conference.

Daily Report: 04/12/2024
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1. Referred the implementation code for developing an app that have the access of camera and capable of taking pictures.
2. Exploring the alternative widget components for the "MaterialStateProperty".
3. Successfully implemented the android app in flutter that have the camera access.
4. Checked the Emails of iCon-BCI IEEE international conference and replied for necessary emails.

Daily Report: 05/12/2024
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1. Exploring YOLO based Flutter app for detecting objects for implementing.
2. Exploring Ultralytics package and their features used for creating yolo based flutter app.
3. Meeting attended about the PRSG and the BMI Project.
4. Checked the IEEE Conference Emails and verified.
5. Started Training the UpSampled Combined Volunteer and Patient Data of InnerSpeech approach using Deep Learning BiGRU algorithm.

Daily Report: 06/12/2024
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1. Verified each upsampled data files to check whether each file having 21 channels present or not.
2. Deleted the 16 channel Data and started training with corrected upsampled data.
3. Parallely started traning Machine Learning using Random Forest algorithm in another PC.
4. Checked the iCon-BCI IEEE conference emails and replied successfully.
5. Created a word document for the Quotes about the collaborative partnership with SCTIMST and fee waive for the PhD students.

Daily Report: 07/12/2024
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1. Checked the iCon-BCI IEEE conference emails and replied successfully.
2. Testing the ML for event 8, 10 , 12 for Patient only and Volunteer+Patient and updated the result into the corresponding spreadsheet.
3. Testing ML for all patient data with catBoost algorithm.
4. Exploring about the concept of BiGRU algorithms in machine Learning.

Daily Report: 09/12/2024
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1. Training ML Random Forest Algorithm with Patient + Volunteer new data.
2. Checked the iCon-BCI IEEE International conference emails and replied for necessary mails.
3. Meeting attended for official updates about iCon-BCI IEEE International conference with all HTG members and GH.
4. Exploring about "How Bidirectional Gated Recurrent Unit(BiGRU) works and how it improves on GRU".

Daily Report: 10/12/2024
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1. Started Preparing the profile intro of the technical session speakers who attending the iCon-BCI IEEE international conference.
2. Testing the ML with Random forest algorithm and having some selective features, notch and Bandpass filter having lower 0.1 and upper 45, ICA.
3. Training the ML Catboost algorithm with 55 and 80 bandpass, and tested.
4. Checked the IEEE conference emails.
5. Again Training ML Catboost algorithm with and without ICA and PCA.

Daily Report: 11/12/2024
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1. Copied P(without_EDF)_4096_samples from htgshare and creating and seperating that data eventwise.
2. checked event "2" data(eventwise_patient_only) to check whether they have the data valu "0" or not.
3. Training and testing the patient and volunteer combined data by using ML with Catboost classifier.
4. Updated SVN repository and Training and testing again without closing the UI each time.
5. Preparing the Intro of the technical session speakers.
6. Checked the Emails of IEEE conference and replied for necessary emails successfully.

Daily Report: 12/12/2024
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1. Successfully completed the Profile Intro creation of the speakers for the technical session.
2. Verified the new emails of IEEE International conference.
3. Training the Patient and Volunteer combined data with ML Catboost classifier without applying high-pass filters.
4. Testing the above trained model with same data, new data and eventwise data,etc..
5. Created and seperated a new P&V_combined_patient's ID and Volunteer's ID wise data for each event(such as "2","7","8","10","12").

Daily Report: 13/12/2024
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1. Testing created whole Individual Patient + Volunteer data , testing eventwise.[ Catboost classifier, Patient+Volunteer combined data ]
2. Updating the tested values in spreadsheet for PRSG.
3. Completed testing from patient id-P1 to P115 individual files.

Daily Report: 14/12/2024
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1. Testing created whole Individual Patient + Volunteer data , testing eventwise.[ Catboost classifier, Patient+Volunteer combined data ].
2. Completed testing from patient id-P116 to P125 individual files and V2 to V34.
3. Updating the tested values in spreadsheet for PRSG.
4. Testing created whole Individual Patient-Only, eventwise data in an another PC [Completed testing from P111 to P125].

Daily Report: 16/12/2024
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1. Completed the testing of new data with eventwise (2,8,10,12) by using Catboost model in ML.
2. Successfully updated the result into the shared spreadsheet for PRSG.
3. Successfully Created a Facebook content of iCon-BCI IEEE International conference.
4. Checked the Emails of IEEE Conference and replied for all emails successfully.
5. Updating the Compering scripts.
6. Creating a Write-up about the BMI Project.

Daily Report: 17/12/2024
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1. Modifying the Compering scripts(adding the memento giving sessional scripts,conclusion, etc.)
2. Successfully Completed the word Document for the Write-up about the "BMI" Project.
3. Doing the Corrections in the write-up and sended successfully.
4. Checked the emails of IEEE conference.

Daily Report: 18/12/2024
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1. Attended the BMI Project's PRSG meeting at CIG conference room.
2. Preparing profile Description for Ms. Keerthi Ram Lead Engineer – Imaging | Medical Image Analysis Healthcare Technology Innovation Centre.
3. Successfully completed the Compering scripts for the technical session in IEEE conference.

Daily Report: 19/12/2024
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1. Attended icon-BCIHT IEEE conference Day 1
2. Participated as a volunteer and done the duty of compering, and support for the bouquet and gifts

Daily Report: 20/12/2024
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1. Attended icon-BCIHT IEEE conference Day 2.
2. Volunteering and bouquet and gift support.

Daily Report: 23/12/2024
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1. Current task to complete: Prepare PRSG minutes report.
2. Watching the PRSG meeting recorded video and noting the points members said throughout the meeting.

Daily Report: 24/12/2024
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1. Watching the Recorded video of the PRSG Meeting.
2. Noting the Highlighted Points were discussed in the meeting.
3. Preparing the Minutes Report of the PRSG meeting.
4. Successfully completed the Minutes Report creation.
5. Discussion with Sambhu about the corrections and updations of the report.

Daily Report: 26/12/2024
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1. Exploring Flutter Object Detection App that using YOLOV5 Model for detection.
2. Referring the Existing implemented codes available in Github.
3. Tried a sample code and running on visual studio code platform, and some errors occurred.
4. Checked the iCon-BCIHT emails and collected some of the account details, then Created a new official WhatsApp Group for iCon-BCIHT_speakers only and shared
5. Exploring about the use of flutter_pytorch in the object detection mobile app.

Daily Report: 27/12/2024
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1. Updated SVN repository and Started making a folder structure for the conversion of eBrainVoicePipeline_V3pt1 Project.
2. Created a new folder for the Exe Conversion.
3. Updating and Correcting the BMI project's User Manual word document.
4. Updated the New UI's of BMI projects, changing the Content of the word document according to the flow of the Application working.

Daily Report: 30/12/2024
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1. Started the EXE creation of EbrainVoicePipeline_v3pt1 project.
2. Found some errors while converting the project folder into Executable file(EXE):
Failed to execute script 'EbrainVoicePipeline' due to unhandled exception: [Errno 2] No such file or directory:
'C:\\Executable\\eBrainVoice_V3pt01EXE\\output\\EbrainVoicePipeline\\_internal\\mne\\report\\js_and_css\\report.js'
3. Trying to Correcting the above error.
4. Comparing the Updated User manual of BMI with Test Plan Procedure.

Daily Report: 31/12/2024
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1. Updating user manual with newly integrated EEG Data viewer Module and LoginPage Module.
2. Updated the screenshots of the EEG data viewer and procedures for viewing the EEG ploting in the user manual of BMI.
3. Arranging the whole document with the flow of working of the application.
4. Correcting the errors occurred while the exe creation.

Daily Report: 01/01/2025
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1. Updating the User manual of BMI.
2. Updating the index and contents of the manual.

Daily Report: 02/01/2025
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1. Comparing the BMI user manual with Test Plan Report and Test plan procedure.
2. Correcting the missing implementations that is already available in the current BMI project.
3. Added wavelet feature implementation in the test plan procedure document.
4. Removed the reset and clear from menu's from the document which is not required for the BMI.
5. Referring the Software Requirement Specification document for identifying the missing implementations or terms.

Daily Report: 03/01/2025
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1. Changed the full alignment of the User Manual document of BMI project.
2. Changed the LoginPageUI's screenshot in the User manual.
3. Corrected the indexing and contents of the document.
4. Creating the Overall Work flow or Architecture of MiME Application and updating the corrections.

Daily Report: 06/01/2025
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1. Work completed: Successfully completed the creation of User Manual Document of BMI Project.
2. Current work: Started creating the Installation Manual of BMI project.
3. Added the installation procedures such as how to download the executable file, how to the exe, how to install python and how to install the supporting libraries for this project.
4. Identifying each libraries and their compatible versions that needed for this project from the Pycharm platform.

Daily Report: 07/01/2025
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1. Changed the LoginPageUI alignment of the MiME Application.
2. Committed this change in the LoginPageUI to the SVN Repository and Updated Successfully.
3. Updated LoginPageUI is added to the User Manual.
4. Adding the Training and Testing Procedures seperately with screenshot and Proper manner of workflow.
5. Attended Discussion about the Web Application Developed using FLASK.

Daily Report: 08/01/2025
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1. Added the Overall work flow of MiME application into the user manual document.
2. Updated "How to split the Data for training and testing" into the user manual document.
3. Running the Current new version of EbrainVoicePipline_v4pt0 project for trial test. Found some functionality bugs in the EEGDataViewer and other modules.
4. Updating the overall workflow of the user manual document.

Daily Report: 09/01/2025
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1. Correcting and Updating the Installation manual.
2. Adding a screenshot of Loginpage of MiME after the installation process of Installation Manual.
3. Completed the Installation Manual of BMI project.
4. Updated the SVN repository and checking the functionalities of version 4.

Daily Report: 10/01/2025
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1. Checking the documents of exeCreation, installation manual for further use.
2. Exploring about the FLASK framework in python and its basic fundamentals.
3. Meeting attended about the web application development of MiME with Project Leads and team members.
4. Exploring about the Performance and efficiency of Streamlit, Flask and Django for developing a Web based application for MiME project.

Daily Report: 13/01/2025
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1. Copied the executable document (MiME3.exe) into an another PC for checking the version compatibility issue finding.
2. Successfully tested the previously created exe for the MiME version 3 project. Checked is it running in windows 10 and windows 11 system without having python installed and any other dependencies or not.
3. Referring about the flask WSGI, Werkzeug and Jinja2 template engines.
4. Updated the SVN repository and checked the updated files is running correctly or not.

• Traceback (most recent call last): File "license_validation.py", line 4, in <module> ModuleNotFoundError: No module named 'LoginPageUi'.
• Permission denied problem in licenseValidation.py

Daily Report: 16/01/2025
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1. Corrected the errors previously occurred.
2. New errors occurred are given below:
Failed to execute script 'license_vlidation' due to unhandled exception: No module named 'LicenseUl'.
File "c:\users\hp\appdata\local\programs\python\python311\Lib\shutil.py", line 622, in _rmtree_unsafe onerror(os.unlink, fullname, sys.exc_info())
File "c:\users\hp\appdata\local\programs\python\python311\Lib\shutil.py", line 620, in _rmtree_unsafe os.unlink(fullname)
PermissionError: [WinError 5] Access is denied: 'C:\\exe\\eBrainVoice_V4pt0EXE\\output\\license_vlidation\\license_vlidation.exe'
3. Meeting is attended for Web Application Development of MiME project.

Daily Report: 17/01/2025
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1. Correcting the errors and successfully corrected the errors of Failed to execute script 'license_vlidation' due to unhandled exception: [Errno 2] No such file or directory: 'brain_bg.png'.
2. Successfully corrected the Licensing page errors while the exe creation.
3. Meeting attended about the EEG Hardware device, components and how it is working with team members.
4. Correcting the new error of Failed to execute script 'license_vlidation' due to unhandled exception: No module named 'eBrainVoice', done by correcting the structure of the folder.

• Failed to activate license: [Errno 2] No such file or directory: 'encryption_key.key'.
• Failed to activate license: [Errno 2] No such file or directory: 'scratch.json'.

4. Correcting the above errors by changing the absolute path of the missing folders and structure.

Daily Report: 21/01/2025
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1. Referred the flutter themes and templates for android app creation for CCET project.
2. Meeting attended about the discussion of the topics such as Bootstrap, Rest API, React js, Flask etc..
3. Adding some Changes in the MiME version 4 User Interface.
4. Adding an icon or hint when we browse the data file and when we pointing to the icon a text that displaying about the format and the type of the data file.

Daily Report: 22/01/2025
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1. Successfully added the hint or icon with description about the foramt of data file name to be followed.
2. Added placeholders for the Processing window size, decision window size, overlap window size and save configuration file.
3. Modified the feature extraction part and added mandatory hint texts.
4. Changed the AI techniques check buttons of ML and DL to radio buttons and changed the parameters of the program according to the changes.

Daily Report: 24/01/2025
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PE interview attended......

Daily Report: 27/01/2025
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1. Meeting attended about the discussion of the topic Django and how we can create a folder structure for our project.
2. Meeting attended about the topic, Architecture of Django and how the request and response received through httpresponse, what are the security and authentication methods and functions available in the Django.
3. Adding a Menu in the Tools section in the MiME UI, and added a new utility named "Alert Event Settings".
4. Creating a UI that displays when selecting that menu.

Daily Report: 28/01/2025
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1. Created UI for the "Alert Event Settings" menu and a table with heading event and description.
2. Created an "edit" button for editing the contents of the table and another PopUp UI for editing each row of the table, and save it.
3. Training and testing the ML of MiME application for ensuring all the changes doesn't making any error, using Catboost classifier.
4. Some errors identified and correcting it and exploring the error occuring reasons.

Daily Report: 29/01/2025
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1. Changed the Alignment and position od the General Settings module button (placed after the AI Techniques).
2. Exploring how to load the json file for displaying that data into the event settings UI.
3. Tested the License key generating part of the MiME application and successfully authenticated.
4. Creating a json file for all the events and their descriptions used in the MiME application.

Daily Report: 30/01/2025
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1. Successfully added a new version of BMI project, i.e, MiME_v1pt0 into the SVN repository, committed and updated the folder.
2. Added a new feature in the Alert event Settings UI, i.e, "+add/-remove the event"and its working for deleting a row and adding a new row.
3. Working on the task of loading the event and description of the data into this UI.
4. Adding a new drop down menu for going back to the EEGDataViewer UI.

Daily Report: 31/01/2025
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1. Modified the hardcoded event label part of the EventIdentify() function, and loaded the events and descriptions from the events.json file...
2. Added a new drop down menu for going back to the EEGDataViewer UI and trying to integrate it into the MiME UI.
3. Committed and Updated the current changes to the SVN repository.
4. Error found while integration of EEFDataViewer:
File "F:\SVN_REPOSITORY\MiME_V1pt0\eBrainVoice\module\src\View\EegDataViewer.py", line 761, in offline_analysis_status_function
AttributeError: 'function' object has no attribute.

Daily Report: 03/02/2025
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1. Integrating and Modifying the new work flow of each modules like the given below:
License Validation--->Login to the Application---->MiME UI----->Select "EEG Data Viewer" from Tool menu bar for opening the module.
2. Changing the Connection of Modules from login page to MiME UI page.
3. Activating the license encryption key for running the application from the beginning.
4. Found Some errors related to the path of the json file like given below and correcting it: "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\pathlib.py", line 1044, in open return io.open(self, mode, buffering, encoding, errors, newline) FileNotFoundError: [Errno 2] No such file or directory: 'events.json'.

Daily Report: 04/02/2025
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1. Corrected the error occurred in the "alert event settings" from the beginning of the modules and individual module running.
2. Correcting and trying to solve the below Error occurred while integrating the EEG Data Viewer Module with MiME UI:
File "F:\SVN_REPOSITORY\MiME_V1pt0\eBrainVoice\module\src\View\EegDataViewer.py", line 757, in tool_bat_icon_Callback self.crop_button = tk.Button(self.toolbar_top, image=self.crop_photo, command=self.crop_button) File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\tkinter\__init__.py", line 2706, in init Widget.__init__(self, master, 'button', cnf, kw)
File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\tkinter\__init__.py", line 2628, in _init_self.tk.call(_tkinter.TclError: image "pyimage19" doesn't exist.

Daily Report: 05/02/2025
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1. Identifying the problem of file paths given in the whole programs of MiMe_v1pt0.
2. Changed the method of giving the file name in the license module..
3. An issue found when changing the path of the files given in the programs, that leads to the breakage of other modules, identifying the problem of integrating the module with this.
4. Errors be like : File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\tkinter\__init__.py", line 2628, in init
self.tk.call( _tkinter.TclError: image "pyimage20" doesn't exist

Daily Report: 06/02/2025
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1. Integration of "Alert Event Settings" of the MiME module completed.
2. Copying the exe file of EbrainVoicePipeline_v3pt0 and running into another laptop for the demo presentation.
3. Successfully copied and started testing the BMI Project.
4. Successfully completed the training and testing of the EbrainVoicePipeline_v3pt0 executable file with the help of ML- SVM Algorithm and it is ready for the presentation.

Daily Report: 07/02/2025
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Leave

Daily Report: 10/02/2025
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1. Integrating the EEGDataViewer module into the MiME and Exploring about the Widgets and callbacks of the functions.
2. Correcting the error: File "F:\SVN_REPOSITORY\MiME_V1pt0\eBrainVoice\module\src\View\EegDataViewer.py", line 766, in tool_bat_icon_Callback
self.crop_button = tk.Button(self.toolbar_top, image=self.crop_photo, command=self.crop_button) File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\tkinter\__init__.py", line 2706, in init
Widget.__init__(self, master, 'button', cnf, kw)
3. Meeting attended about the Microstate of EEG signals(preprocessing, segmentation,GFP,peak GFP and plot) and the current status of the deployment of MiMe application and testing & training processes.

Daily Report: 11/02/2025
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1. Explored about the seizure and its different types of events.
2. Collected the Seizure data from the "htgshare" and created a new data that contain the combined event data with training and testing data seperately.
3. Continuing the integration of the "EEG Data Viewer" Module into the MiME UI.

Daily Report: 12/02/2025
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1. Started training and testing of Seizure preduction data by using catboost ML algorithm..
2. Trying to correct the Integration of EEG Data Viewer module.
3. Preparing to create a Demo version of the MiME for the Presentation.
4. Created a new folder with Data, Model, and started testing of Patient and Volunteer Combined data by using Random Forest ML Classifier Model.

Daily Report: 13/02/2025
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1. Started testing the Already trained model with each data.
2. Tested the Random Forest ML classifier model using Splitted_80_20 P&V combined data and got 100% accuracy in trained data and 73% in test data.
3. Testing other Random forest model with Volunteer only data, P&V combined data, and splitted_80_20 data ( some of the model shown errors, removed from the demo folder).

• Renamed the Utitlies option "Image Processing" to "Image Generation".
• Renamed the Buttons "General Settings" to "Configuration Settings" for both training/validation tab and Testing tabs.

4. Currently Modifying the Logic of Work in the PreProcessing module.
5. Adding a new LabelFrame(Results *) for the Results to display and write.

Daily Report: 17/02/2025
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1. Modifying the Post Processing module by adding new components in the UI.
2. Added a new Label frame for Results, "Display" and "Write".
3. Created a new checkboxes named "Display" and "Write" inside the "results" labelFrame.
4. Integrating the Individual file, Row wise, final for Individual file section Label Frame and All merged file section when i click onto the "Display" checkbox.
5. Integrating write to disk part for "Write" checkbox with including Individual file section part.
6. Found some errors : File "F:\SVN_REPOSITORY\MiME_V1pt0\eBrainVoice\module\src\View\EbrainVoicePipeline.py", line 2212, in optionAllFile
self.threshold_eyeblink_detection_enabled = True AttributeError: 'Checkbutton' object has no attribute 'get'

• "Display" checkbox only shows: "Individual File Section" and "All File Merged Section", "Write" checkbox shows: "Individual File Section" ,"All File Merged Section" PLUS "Write to Disk" browsing option Unchecking "Write" removes only the Write section. "Individual File Section" and "All File Merged Section" stay visible if "Display" is still checked.
• Unchecking both removes everything
• Maintains correct alignment under the checkboxes.

Daily Report: 19/02/2025
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1. Found some errors while integration of Results in the post processing part.
File "F:\SVN_REPOSITORY\MiME_V1pt0\eBrainVoice\module\src\postprocessing\EventIdentify.py", line 26, in init
self.event_code = int(event_code)
^^{^^}^^^^^^^^^^
ValueError: invalid literal for int() with base 10: 'F:/Error_test/Writetodisk2\\RandomF_individual_file_final_result.csv'
2. Corrected the above error. And started testing and modifying the backend problems of the write and display checkbuttons..
3. Corrected the problem of multiple predication file generation when we click the both "final" check buttons, then uncheck the other one, So changed the variable states according to that.
4. Correcting the "Event Alert Message" , when we click onto the "text" button, we have to display the final result's text message.

Daily Report: 20/02/2025
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1. Properly corrected the given problem "When we check the "text" and "audio" check buttons in alert event message, then uncheck any of them, but it remains in same state(TRUE), so changed the state of the variables of both checkbuttons"according to the enabling and disabling of buttons.
2. Enabling the Audio checkbox and checking the audio is working or not.
3. Task Completed: Successfully integrated the "Mode of Events" of Decision making part of the Post-processing.
4. Implementing the Decision making part of the Post-processing, i.e, "Evaluation of Continuity".
5. While implementing the "Evaluation of Continuity" found some error:
"C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\internals\construction.py", line 666, in _extract_index raise ValueError("All arrays must be of the same length") ValueError: All arrays must be of the same length

Daily Report: 21/02/2025
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1. Correcting the problem of audio playing when we select audio for the "alert event message".
2. Meeting attended about the Demo presentation of MiME- Inner Speech.
3. Changing the libraries for playing the audio files.
4. Tried with new and older version of the "playsound" libraries for playing the audio files.
5. Modification done in "alert event message" part of post-processing are: it should work like, when we enable "audio" only, then it should only play the audio message as well as when enabled "text" only, then it should only display the text message.
6. Successfully corrected the problem with the "Audio" playing.

• The "All File Merged" section will remain aligned with the "Individual File" section.
• The "Write to Disk" section will appear below them without shifting elements apart.
• The UI will stay aligned whether one or both checkboxes are selected.

3. Renaming each data files by including the Label name after the event for testing and training which makes easy for reading.(e.g, P1S1RA_Vp_7_Left_D_22012024_095010).
4. Preparing a laptop for demo presentation.

Daily Report: 25/02/2025
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1. Preparing a laptop for the demo presentation. Updated the SVN Repository and created a new folder for demo and copied the model, config file.
2. Problem facing when running the MiME_v1pt0 on pycharm. The problem found are: C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\...ModuleNotFoundError: no module found in the name of "h5py", ModuleNotFoundError: no module found in the name of "scipy", ModuleNotFoundError: no module found in the name of "numpy", etc.
3. Importing(installing) each libraries according to the supporting compatible version, changed the python interpreter.
4. Renaming of data file work is ongoing.

Daily Report: 26/02/2025
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1. Successfully renamed the data files of Splitted_data_80_20 data and EventBased_96_Epochs_Each_TrainingData_21-02-2025 data.
2. Resolved the issues from yesterday and began testing MiME_v1pt0 on the laptop.
3. while testing an error found like this: Userwarning: Trying to unpickle estimator DecisionTreeClassifier from version 1.5.2 when using version 1.2.2. This might lead to breaking code or invalid results....
4. Corrected the above error and started testing all subjects each file for each events to identify which file gives more accuracy and correct prediction.

Daily Report: 27/02/2025
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1. Completed the testing of each events ( 2,7,8,10,12) all subjects individual files which file gives more accuracy and correct prediction(Used data is splitted 20% test data).
2. Created a new folder in Htgshare named "Demo_27-02-2025" for demo presentation and copied the trained model, config file and good_testing_data which is got from the testing of individual files.
3. Started arranging the patient_only event wise data for testing individually same like above.

Daily Report: 28/02/2025
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1. Created a new model in Random Forest with 100 no.of estimators and bandpass filter lower(55) and upper(80) due to the modifications in filters.
2. With the new model tested the model with trained data as well as test data from the splitted_80_20 (20% test data). Noted
3. Current task: Started testing the patient only event wise data for identifying which file gives wrong prediction from the all subject's individual data files.
4. Noting the wrong predicted files(. txt) and removing it from the folder and creating a new data set.

Daily Report: 01/03/2025
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1. Continuing the task of testing the patient only event wise data for identifying which file gives wrong prediction from the all subject's individual data files and Noting the wrong predicted files(. txt)
and removing it from the folder and creating a new data set.
2. Exploring about the KNN algorithm in machine learning, How it actually works, how the data taken, how testing takes place, visualization techniques, etc..
3. Noted the count of files for each events of the patient data.

Daily Report: 03/03/2025
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1. Copied a sample .edf format data of volunteer from the htgshare for testing the EEGDataViewer plotting(Standard FFT,Real FFT and Power Spectral density).
2. Testing the plotting of EEG signals with this volunteer data and understanding about the working and their features.
3. Meeting attended about the discussion of Support Vector Machine(SVM) and its basics, work flow, logic and program, Random Forest Algorithm and Naive Bayes Theorem.
4. Testing the EEG signals with filters such as notch, bandpass, lowpass, highpass, bandstop.

Daily Report: 04/03/2025
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1. Successfully created a new dataset from the patient Only eventwise data that contain 8 patients with each patient folder contains 8 files(total 320 files).
2. Created a "README" word file about the Procedure to test the MiME application with heading "How to test MiME_V1pt0".
3. Started Testing all the data with Decision making is "Evaluation of Continuity" using Random Forest model.
4. Testing with trained data, testing with splitted 20% data eventwise.
5. For Demo presentation, setuping laptop, updated SVN repository, Checked the EEG plotting, copied the EEG sample data for EEGViewer.

Daily Report: 05/03/2025
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1. Created a new Random Forest Model(Trained) in MiME_v1pt0 application with newly created dataset named "EventWise_Patient_Only_Balanced_Data" that contains 320 files 8 patients for each event with 8 files.
2. Started testing the Random Forest model and noted the accuracy.
3. Exploring about the KNN algorithm in machine learning and find outing sample collabe or git code of the implementation of the algorithm.
4. Current task: Started creating executable file creation of "MiME_V1pt0".
5. Meeting attended about the explanation of "Linear Regression and its working, logic, code of implementation".

Daily Report: 06/03/2025
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1. Creating Exe for MiME_V1pt0 project with all integrated license validation, Login, MiME application, EEGDataViewer.
2. while creating the exe, found this error: File "PyInstaller\loader\pyimod02_importers.py", line 378, in exec_module
File "mne\report\report.py", line 101, in <module>File "pathlib.py", line 1058, in read_text.. File "pathlib.py", line 1044, in open
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\exe\\MiME_V1pt0\\output\\license_vlidation\\_internal\\mne\\report\\js_and_css\\report.js'
3. Correcting the above error and preparing PPT for KNN algorithm implementation.
4. Successfully presented and attended the Demo presentation of MiME software and noted new modification needed in the MiME software.

Daily Report: 07/03/2025
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1. Meeting Attended about the discussion of "Creation of new design(version) and implementation of MiME_V1pt0.
2. Started creating new UI's for MiME.
3. Successfully created the model creation UI when we click onto the button "Model Creation" from the Main UI.
4. Changing the alignment issues, added the components such as " Load Data", "Preprocessing", "Feature Extraction", AI, Configuration Settings and their components for saving configuration file and Model.

Daily Report: 08/03/2025
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1. Current tasks Ongoing: Successfully included the Data settings contents such as "Sampling Rate", "Processing Window size", "Decision Window Size", "Overlap Window Size" into the EEG Signal UI module.
2. Successfully integrated Menu bar for Train and Test Data Creation such as "Create all subject Data", "Create Single subject data".
3. Successfully integrated Utilities such as "Image generation", "Alert Event Settings", and "EEG Data Viewer" module.
4. Changed the UI look of "Image generation" part and "Event alert settings module" in the Utilities.
5. Added new form of Alert message when we didn't click row for editing a row, changed the look and feel of the UI.

Daily Report: 10/03/2025
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1. Changing the UI appearence of the "Create Single Subject Data" from the Train and Test Data Creation menu.
2. Successfully conducted and presented the explanation about KNN algorithm in Machine Learning with PPT and implemented sample code representation.
3. Attended meeting PL and group members about the explanation of implementation of Naive Bayes Algorithm ad Regression algorithms.
4. Correcting the PPT according to the changes suggested by PL.
5. Updated SVN Repository and Preparing the New model For Demo.

Daily Report: 11/03/2025
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1. Successfully completed the Demo of MiME- InnerSpeech Software Presentation for Techverse.
2. Created a new UI for the Preprocessing module for the Filter selection, Channel Selection and Resampling.
3. Integrated the filter, Channel and Resampling UI with this newly created UI.
4. Modified the Browsing options in Configuration settings part, when file browsing popup comes, then it will ask for folder path(not file). And also Fixed this problem in the model creation module,
5. In the EEGsignalUI, Fixed the problem of the current UI going behind when we browsing the data folder and also added a field for adding Volunteer/Patient ID in the DataSettings Frame.

Daily Report: 12/03/2025
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1. Successfully added Visualization Module in the Model creation part.
2. Added a "Visualization" button in the Model creation and then integrated the DataVisualizationUI with this module.
3. Fixed the problem when we click onto the browsing folder, VisualizationUI going behind of other UI's.
4. Modified the UI of the newly created PreprocessingUI for selecting channels, filters and resampling.
5. Attended 4th iCon-BCI Lecture series and done the Compering task successfully.

Daily Report: 14/03/2025
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1. Integrated channel Selection part such as "Natus", "Emotive", and "Custom Channel" with the UI.
2. Changing the User interface for better look. Changed the Foreground and background colors according to the new color theme.
3. While modifying the UI, one bug is noticed and correcting that issue:
"The issue is that when switching between radio buttons, previous UI elements (like list boxes, buttons, labels) are not being removed, which leads to overlapping elements."
4. Error found while changing the bug:AttributeError: 'NoneType' object has no attribute 'winfo_exists'.
5. Created a new function for handling the removal of all the frames, used whenever they need to be removed.

Daily Report: 17/03/2025
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1. Changed the UI of Resampling option(ResamplingUI.py) and corrected the probem of "1)The folder selection dialog appears on top when opened.
and 2)The main UI does not go behind other windows after selecting or canceling the folder selection".
2. For the purpose of testing of newly created version of MiME_V2pt0 working status, Started create a model and test with sample data.
3. Added the "Alert event message" part in the PostProcessingUI module and fixed the alignment issues.
4. Integrating EEGDataViewer module with MainUI's Utility part. Fixing the error:"C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\tkinter\__init__.py", line 1948, in call
return self.func(*args) TypeError: Bmi_eeg.resize_image() missing 2 required positional arguments: 'width' and 'height'.
5. Task completed: Successfully corrected the error during the integration process and Integrated the EEGDataViewer into the MiME_V2pt0 is Completed.

Daily Report: 18/03/2025
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1. Current Task Completed: In the "Model Creation part, When click onto the buttons such as "Load Data", "Preprocessing", "Feature Extraction","AI", and "Visualization" the button color changed to light shade of blue color, then Button color changes to blue when "Save" is clicked instead of waiting for the window to close.
2. Successfully completed the changes in the button colors when completing each modules and changed the fg color to yellow and bg color to blue and changed the UI's of each module's Save settings parts(EEGSignalUI,PreprocessingUI,Feature_extractiionUI,dataVisualizationUI.
3. Changed the Data Settings Volunteer/Patient ID name to Training ID and Changing the "MiME mindme" Logo label and positioning of the texts.
4. Successfully updated the UI setup "when click "Create Model", close the "Model Creation" UI and come back to MainUI for "Model Execution" ".

Daily Report: 19/03/2025
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1. Meeting with PL and team members about the Progress in the development of MiME_V2pt0 and noted new modifications and changes required.
2. Added MiME logo image in the place of MiME application Heading(MiME mindme).
3. Changed the colors of buttons in the "model creation" part it changed from blue to different green color when the successful completion of each modules(Preprocessing,feature extraction, AI and visualization.
4. Successfully added separate browse options for loading and saving configurations. When you click "Open Configuration",
a browse dialog for opening a file will appear. When click "Save Configuration", a separate browse dialog for saving a file will appear. Both browsing buttons will only become visible after clicking their respective main buttons.
5. Changed the placeholders' color from black to light gray shade and also change to black when the entry path filled.

Daily Report: 20/03/2025
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1. Removed the Background color(colorless) of MiME logo and successfullly added to the MiME application.
2. Successfully added a button for Real Time Prediction in the MiME_V2 UI and integrated the Live Prediction module to this Application.
3. Added the button color change for "Model Execution" module when the model execution UI frame enable(clicks "Execute" button). This for indicating the completion of this module visit.
4. Modfied the "Model Execution" module, when click onto the "Execute" button the UI should be hidden or remove from the display.
5. Training, Testing and debugging of MiME_V2 for ensuring the working of each module.
6. Changed the Background color of EEGDataViewer Module matched with MiME_V2.

Daily Report: 21/03/2025
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1. Fixed the Problem of Prevents multiple instances of the same UI, Destroys the UI before opening a new one and mutliple UI Creation of "Model Creation" part.
2. Solved the issues mentioned above also in the "Model Execution" part.
3. Changed the bg color of the heading and button frame bg in the "Model Creation".
4. Created a new model with Volunteer Only data in MiME_V2 application for the testing purpose of Live Prediction.
5. Started implementation of Validation checks in "Model creation" part.
6. Performed training and testing of the MiME_V2 application for ensuring the working of the application.

Daily Report: 22/03/2025
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1. Changed the Menu buttons and Menu bar frame appearance(modified color of the menu bar, modified the look and interactiveness of the menu ,when cursor move to the menu button the color of the button changed to "blue", changed the view of dropdown menu options) of "MiME_V2" application.
2. Changed the UI of "CombineModelUI" according to other bg color.
3. Successfully implemented validation check of the EEGData Loading part("EEGSignalUI") and performed the following,
added a function validate_data_settings() checks each field of the Data settings part, if any of the required field is missing it will displays alert message with indication of the label name.
4. Solved the problem of the message box appears in front of "EEGSignalUI" and that "EEGSignalUI" remains on top.

Daily Report: 24/03/2025
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1. Started implementing validation check of AI module, the main implementations we need to implement is that, should check whether the "Model Selection" part selected or not, Sub options such as "classifiers"or "Regressor" selected or not, should check whether the "Train Data Settings" part such as "Select Classifier" selected or not and finally "Model path should be filled.
2. Created a new function For checking the Validation in TrainingDataUI and implementing the missing field checking conditions.
3. Created a new show_custom_error function for displaying customized more featured and better look UI for alert message(instead of using message library).
4. Found some errors during the validation check and correcting it: TypeError: TrainingDataUi.show_custom_error() missing 1 required positional argument: 'parent_window'.
5. Updating and adding "Notes" in the PPT of K-Nearest Neighbors Algorithm(KNN).

Daily Report: 25/03/2025
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1. Removed the unnecessary "label frame" form the EEGSignalUI( placed where the browse folder options of each approaches).
2. Removed the bug and UI corrections in the " More Settings" option from the EEGSignalUI.
3. Successfully implemented the validation of "Model selection"part, "Training Data Settings" part and "Model Path"(if any one of these fields missing, the error message will displays).
Pending implementation: (If ML is selected for model creation, user should completes feature extraction module, otherwise it will displays an alert message)
4. Corrected the problem of Menu bar and drop down menu, when select an option the menu button color changes randomly.
5. Setting up the Laptop with created models,configuration files of MiME_V1 and MiME_V2.

Daily Report: 26/03/2025
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1. Started implementing the validation check of Feature Extraction module with AI module.(If ML is selected for model creation, user should completes feature extraction module, otherwise it will displays an alert message.
2. Created a customized error popup UI for Feature extraction validation instead of built-in one, initialized a global variable that indicates the feature extraction module status and that retrieves the argument from the MainUI.
3. Error found while implementing and correcting it: "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\TrainingDataUi.py", line 208, in validate_training_data
if model_type == "ML" and not is_feature:NameError: name 'is_feature' is not defined.
4. Completed the validation implementation of AI-ML part, but some error still in the DL part validation.
5. Created a resume of "Fathima Haneena P" with ICMR biodata format.
6. Corrected the Error of the MiME_V2 for the AI Demo Presentation, and updated the corrected code to the PL.

Daily Report: 27/03/2025
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1. Making corrections and updations in the Proposal for AI-Based Major Depression Screening System Using Multimodal Data for Early Diagnosis and Intervention.
2. Added "Implementation strategy and milestones chart" into the proposal.
3. Created and Edited the "Annexure-V"(Declaration & Attestation) for both C-DAC and GMCT.
4. Created a new Resume for the "Dr. Nitha T J with ICMR CV format.
5. Preparing a word document of "Compering Script for Workshop on Epidemic Forecasting and Disease Modelling" and making updations on it.
6. Attended the iCon-BCI Lecture Series 6.

Daily Report: 28/03/2025
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1. Updated the Compering Script for Workshop on Epidemic Forecasting and Disease Modelling and completed.
2. Successfully added the facility of "Once completed the "Model creation" , then the again we can create model in the same UI", Previously this is not implemented. Now we can again open the "Model creationUI" again for creating models.
3. Implementing the Validation check in AI-DL part and found some error: validation function is incorrectly detecting sub_model_var as empty ("") even when we selected a Deep Learning classifier.
4. Corrected the above error and Successfully added a Deep learning validation check into the AI part, if we did not select any classifier and model path, then alert message will displays.
5. Created a photo collage for including it into 38 Foundation day PPT.

Daily Report: 29/03/2025
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Attended the workshop on "Epidemic Forecasting and Disease Modelling".

Daily Report: 01/04/2025
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1. Started implementing the validation check in Feature extraction part: if any of the required Feature extraction fields such as type of feature domain and select features are empty, then an alert pop up message will display.
2. Created a new function for the validation check in "Feature_ExtractionUI.py" and implementing the validation.
3. Created a customized alert message popup for displaying the alert message UI.
4. Fixed the problem of current Feature_ExtractionUI.py going behind when popup came, and the alert message should be display in front of the Feature_ExtractionUI.

Daily Report: 02/04/2025
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1. Successfully completed the validation check implementation of FeatureExtractionUI part.
2. Additionally need to check the "Load data" should be completed before going for Feature extraction as well as "ML/DL" module.
3. Successfully Added a validation check whether "Load data" completed before going to feature extraction or not.
4. Similarly adding a validation check of "load data" on AI module.
5. Successfully added the facility of "Once completed the "Model Execution" , then the again we can execute model in the same UI",Now we can again open the "Execute_ModelUI" again.

Daily Report: 03/04/2025
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1. Started Fixing the problem of multiple UI's opening when clicking onto the each buttons in the "Model creation" part such as "Load data", "Preprocessing","Feature Extraction", "AI" and "Visualization".
2. Additionally added instances for each UI's and created separate function for handling the closing of the Ui's.
3. Successfully corrected the multiple window opening of "Load data", "Preprocessing","Feature Extraction", "AI" and "Visualization".
4. Work in progress: Started the overall validation implementation of the "Model Creation", that is Checks if Load Data and AI Training are completed before going to "Create model".

Daily Report: 04/04/2025
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1. Successfully completed the overall validation implementation of the "Model Creation", that is Checks if Load Data and AI Training are completed before going to "Create model".
2. Tested the model creation and model execution part to check whether it is working properly and free from bugs.
3. Exploring about "How to solve the issue of resizing the UI when user move from one window to another and came back".

Daily Report: 05/04/2025
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1. Current Task: Exploring the progress bar creation in the LiveUI part.
2. Exploring about how the progress bar implemented in liveui.
3. Exploring the neurotechnology_assistuve_systemUI module for implementing progress bar in this module.
4. Meeting attended about the Discussion of "Big Data Technology", "Hadoop framework", "its architecture","Hadoop HDFS", "Map reduce concepts", "YARN","SPARK" etc...

Daily Report: 07/04/2025
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Daily Report: 08/04/2025
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Vaishnavi S B wrote in #note-161:

Daily Report: 07/04/2025
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Leave

Vaishnavi S B wrote in #note-162:

Daily Report: 08/04/2025
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Vaishnavi S B wrote in #note-161:

Daily Report: 07/04/2025
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Leave

Daily Report: 09/04/2025
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1. Exploring about "How to visualize seizure-related events (like ictal, pre-ictal, post-ictal) in a horizontal subplot — something like a timeline with clickable colored dots,
where each dot represents a moment in time labeled as one of those events".
2. Trying to implement sample Subplotting mechanisms by using "matpoltlib" library.
3. Attended the Meeting of iCon-BCI Lecture Series part 8 about the concept of "EEG-Based Biometric authentication and identification".

Daily Report: 11/04/2025
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1. Trying out the sample Subplot graphs with a stacked dots that makes line and each colored dots represents each events.
2. Searching for a plot that can take 1 hour data sample at a time and plot into plotting frame.
3. For the demonstration purpose started training and testing models for getting good models, but stuck with some error in the model creation part:
File "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\ai\ml\ClassifierTrain.py", line 66, in classfr_json classfier_json = json.loads(gl.classifr_json) # Deserializing JSON here
File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\json\__init__.py", line 339, in loads raise TypeError(f'the JSON object must be str, bytes or bytearray, '
TypeError: the JSON object must be str, bytes or bytearray, not dict.......
4. Referring the code of neuroTechnology_assistive_UI code for the purpose of subplot creation.

Daily Report: 15/04/2025
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1. Added the two model created by MiMeV2 in Htgshare.
2. Current Task: Implementing another validation check in "Model Creation" part when we click onto "Execute" button, its checks based on whether only feature extraction is selected, in which
case it should only validate that data is loaded, and skip AI training validation.
3. Added a new option [" save features"] in "Feature_extraction_UI" for saving the features extracted from data and also the training set.
4. Added a popup UI for selecting options such as "features" and "training set" for selecting and browsing the folder path to save this.

Daily Report: 16/04/2025
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1. Completed task: Successfully completed the validation check in "model creation" for: if Extract Features Only selected, it should validate the data is loaded and skip AI part in validation.
2. Changed the UI appearance for saving the features and training sets ["write_to_disk_ui"] according MiMEV2 and updated to SVN.
3. Implemented a prototype for the subplotting of the seizure event data and adding a functionality such as "onclick to the particular point on the graph should pass event to particular EEG plotting function.
4. Added a "zoom in", "zoom out" and "Reset" mechanism in the subplotting graph.
5. Performing model creation part of the MiMEV2 to check whether the model creation is working or not and found some errors: line 339, in loads raise TypeError(f'the JSON object must be str, bytes or bytearray, ' TypeError: the JSON object must be str, bytes or bytearray, not dict.

Daily Report: 17/04/2025
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1. Successfully created a prototype for the subplotting of the seizure event data and adding a functionality such as "onclick to the particular point on the graph should pass event to particular EEG plotting function.
2. Prototype verified by the PL and Noted the changes in the subplotting and started modifications. Changed the color combinations for the inter_ictal and pre_ictal events.
3. Attended iCon-BCI Lecture Series part9 about the topic on "The Utility of whole person cognition for BCI".

Daily Report: 21/04/2025
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1. Performing training and testing of MiME Version2 for the Demo presentation.
2. Setting up the laptop with Models and testing data, Created a new model using ML Random Forest classifiers.
3. Current Task ongoing: Started the Integration of created prototype of Subplot timeline graph for the "Seizure Prediction" into the Neuro_Assistive_UI module.
4. Referring the code for integrating this graph into this module.

Daily Report: 22/04/2025
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1. Work in progress: Integrating Subplot timeline graph for the "Seizure Prediction" into the Neuro_Assistive_UI module.
2. Created a Frame for placing the subplot of timeline event graph below the real-time EEG visualization frame.
3. Adding the graph contents into this frame and implementing all the features developed in the prototype.
4. Found some errors and correcting it: "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 601, in create_widgets self.progress_frame = tk.Frame(self.root, bg="#1c1c1c")# Dark them AttributeError: 'NeurotechAssistApp' object has no attribute 'root' invalid command name "3044499337728animate"while executing...

Daily Report: 23/04/2025
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1. Corrected the error found yesterday and implementing the Subplot timeline graph for the "Seizure Prediction" with real data.
2. Changed the dummy data and replacing it with real predicted values.
3. Referring the Neurotechnology_assistive_UI functions for getting those predicted data to plo into the graph.
4. Found some errors during the integration of subplot timeline graph and correcting it: File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\lines.py", line 1290, in set_xdata raise RuntimeError('x must be a sequence') RuntimeError: x must be a sequence

Daily Report: 24/04/2025
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1. Work in progress: Partially implemented Subplot timeline graph for the "Seizure Prediction" with real data.
2. Found problem of the graph plotting stopped after sometime and occurred errors: File "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 2191, in next_btn_function
if self.current_index + samples_per_window <= self.final_array.shape [0]: AttributeError: 'NeurotechAssistApp' object has no attribute 'final_array'...
3. For the testing of the graph with new model, creating a new model for the sample seizure data.
4. Attended the icon-BCI Lecture Series part 10 about the discussion on the topic of " Hands on Session on Signal processing and machine learning for BCI".

Daily Report: 25/04/2025
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1. Created a new model for seizure prediction and found some errors:line 339, in loads raise TypeError(f'the JSON object must be str, bytes or bytearray, ' TypeError: the JSON object must be str, bytes or bytearray...
2. Current work in progress: Started the work of plotting the EEG signal segment corresponding to a clicked event from the subplot time-line graph.
3. Referring the "update_visualisation","offline_moving_window_eeg_visualization" functions for understanding the implementation of EEG signal plotting.

Daily Report: 28/04/2025
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1. Implementing the logic of plotting the EEG signal segment corresponding to a clicked event from the subplot time-line graph.
2. while implementing the EEG signal plotting integration with Subplot time-line graph, Error found: "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 2191, in next_btn_function if self.current_index + samples_per_window <= self.final_array.shape⁰:AttributeError: 'NeurotechAssistApp' object has no attribute 'final_array'..
3. Exploring the solution to fix the above error and started creating a new model with updated MiME_V2 application for testing it with the EEG signal plotting visualization.

Daily Report: 29/04/2025
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1. Task completed: Successfully implemented task of creating Subplot time-line graph and the integration of graph with EEG signal plotting in the way of Seizure event predictions in time[second wise].
2. The EEG signal plotting and Subplot time-line graph is testing with sample data and model as well as model created by large data.
3. Work is verified by PL and noted new changes needed and started implement them.
4. Increasing the time-line graph plotting frame.

Daily Report: 30/04/2025
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1. Work in Ongoing: Implementation of another Subplot time-line graph and the integration of graph with EEG signal plotting in the way of event predictions in Frame-wise[12 seconds].
2. Created a new frame and scatter function for plotting the time-line graph in frame-wise.
3. Implementing the logic of finding the frame which we need to display when we click onto a point on the time-line graph in frame-wise.
4. Updating the analyze_data() functions for adding the 12 sec data to the scatter function.

Daily Report: 01/05/2025
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1. Work Ongoing: In the Subplot time-line graph and the integration of graph with EEG signal plotting in the way of event predictions in Frame-wise[12 second frames], successfully mapped the data into this time-line graph and showing the scatter plot updation in every 12 second data.
2. Some problem facing now: A small kind delay in displaying data plotting in both the time-line graphs [second wise and 12 frame wise].
3. Preparing the compering script for the iCon-BCI Lecture Series Part 11.
4. Attended the iCon-BCI Lecture Series Part 11 about the discussion on the topic of "How attentive you are- an EEG based analysis " and completed the compering.

Daily Report: 02/05/2025
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1. Added the features of "Zoom in", "Zoom out", "Reset" options for time-line graph of frame-wise[12 second frames] and Second wise graph separately. Created separate button for frame-wise time-line graph for utilizing the features.
2. Sort outing the problem of delay in the both time-line graph plotting and correcting the analyze data function.
3. Task completed: Successfully completed the implementation of frame-wise and Second wise time-line graph for Seizure prediction without having any delay of plotting.

Daily Report: 05/05/2025
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1. Current task Ongoing: a) Solving the issue of "Time-line graph frame is displaying for all approaches". So making a separate function for to place the Ui components for the time-line graph and it is visible only when "Seizure" approach selected.Updating the "on_approach_selected" function for calling the UI for the time-line graph.
2. Found some errors and correcting:line 641, in build_timeline_graph self.timeline_frame tk.LabelFrame(self.right_frame, text="Time-Line Graph", bg="#1E1E2E", fg="white", AttributeError: 'NeurotechAssistApp' object has no attribute 'right_frame'.
3. b) Adding an another validation in the model creation part, that is, if we are not selecting or browsing configuration settings part, then model creation should not be possible.

Daily Report: 06/05/2025
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1. Successfully completed configuration settings validation of model creation part.
2. Work ongoing: Integrating time-line graph with neural_assistive UI, only display when "Seizure Prediction" approach selected.
3. While Integration, some problems found: The issue is: when we run the application from the Main UI → Neuro Assistive UI, timeline isn't displayed or errors occur, even the approach selection is done in Neuro Assistive UI. But it is still working in neuro assistive Ui itself.
4. Correcting the Error: "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\tkinter\__init__.py", line 3214, in init_ Widget.__init(self, master, 'label', cnf, kw)
File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\tkinter\__init__.py", line 2628, in init self.tk.call(_tkinter.TclError: image "pyimage3" doesn't exist...

Daily Report: 07/05/2025
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1. Solving the Issue of : timeline graph not displaying when running the NeurotechAssistApp from the main_ui, and the additional problem of the neuro assistive UI not working correctly when run independently.
2. Identifying the multiple root causes such as improper initialization and conflicts in the UI setup.
3. Solving the frame creation or widget packing issues and creating multiple windows for "Real time prediction"[neuro_assistive UI].
4. Attended the iCon-BCI Lecture Series part 12 meeting about the topic on "Brain & Machine interface and its advanced technology applications".

Daily Report: 08/05/2025
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1. Successfully solved the issue of timeline graph not displaying when running the NeurotechAssistApp from the main_ui, and the additional problem of the neuro assistive UI not working correctly when run independently.
2. Current task ongoing: Modifications in the existing time line graphs [ second wise and 12 sec frame wise] for Seizure Prediction.
3. Replacing the position of existing legends for ictal,pre-ictal,post-ictal and inter-ictal into the common legends for both time-line graphs.
4. Changing the time-line graph names, currently set as y-axis labels, So changing them with titles for the respective subplots to clearly indicate they are graph names.

Daily Report: 09/05/2025
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1. Successfully completed the modifications in the position of existing legends in the time-line graphs and the time-line graph names.
2. Current task Ongoing: In the Neuro-Assistive UI, started solving the issue of not being able to rerun the EEG plotting and timeline graphs within the same UI session.
3. Adding a "Clear" button that resets the UI to its initial state. placed the button below of the "Start" and "Stop" buttons.
4. Implementing an another method when click onto the "Clear" button to reset the UI components, plots and data.

Daily Report: 13/05/2025
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1. Current task ongoing: Correcting the problem in the EEG signal frame plotting according to the clicked index of the frame in time-line graph.
2. Changing the logic of appending the clicked time index (ie, the 4 second frame) for EEG plotting.
3. Correcting the analyze_data() function to fix the problem in time-line graph.
4. Fixing the error :File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\backends\backend_tkagg.py", line 14, in blit_backend_tk.blit(self._tkphoto, self.renderer.buffer_rgba(),File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\backends\_backend_tk.py", line 116, in blit photoimage.tk.call(_blit_tcl_name, argsid) RuntimeError: main thread is not in main loop

Daily Report: 14/05/2025
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1. Task Ongoing: Creating a seperate time line graph for classifier result-wise and post-processing result-wise.
2. Already created the time line graph for classifier result-wise. Now moving onto the creation of post-processing result-wise time-line graph.
3. Referring the Analyze_data() function for getting the post-processing result (need the mode or continuous pedicted result after the completion of post-processing).
4. Making modification in the current coding pattern. Started creating a reusable function for Mapping numeric predictions to event labels which is obtain from "events.json" file.

Daily Report: 15/05/2025
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1. Modifications done in UI: Changed the legend colors, for additional seizure events. Changed hover label display, and remodified the time index from second(s) to frame. Renamed the both time-linegraph titles.
2. Created new functions for "The event_labels map correctly to the seizure labels."
"The label_colors map correctly to the predefined colors based on those labels."
while the creation found some error and correcting it: neurotechnology_assistive_systemUI.py", line 2075, in <listcomp> label_colors = [self.timeline_colors.get(label, "white") for label in event_labels]
AttributeError: 'NeurotechAssistApp' object has no attribute 'timeline_colors'. Did you mean: 'timeline_canvas'?
3. Attended meeting of iCon-BCI Lecture Series part 13 about the topic on "Advanced signal processing techniques for intracranial EEG analysis".

• Changing the position of legend to the right side of the frame with center position.
• Adjusting the size and reducing the space usage in time-line graph.

Daily Report: 19/05/2025
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1. Current task Ongoing: Integrating the postprocessing result into time-line graph[ for post-processing result -wise] and implementing the prediction for dominant value from three result batches and plotting into the time-line graph.
2. found some errors and correcting it:"F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 2051, in analyze_data for i in range(len(self.three_result_buffer⁰)):
TypeError: object of type 'int' has no len()..
3. Creating a separate function for doing these calculations and passing it to the frame_wise scatter function. Then created a sample model with updated MiME application for testing the time-line graph.
4. Referring methods to find dominant value from a list.

Daily Report: 21/05/2025
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1. Attended meeting of "EEG Device Demo".
2. Work in Progress: Created a post-processing function that calculates the prediction for dominant value from three result batches.
3. Implementing some logics for displaying the EEG signal plotting for Seizure when click onto the second time-line graph with respect to decision window size.

Daily Report: 22/05/2025
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1. Work in progress: Successfully plotted the post-processing result into the 2nd time-line graph.
2. Correcting the on-click logic for calculating the frame which is going to show into EEG signal plotting area, with respect to the user click index from the time-line graph.
3. Attended and completed the task of compering for the iCon-BCI Lecture Series part 14 about on the topic of "Bionic Rehabilitation for Amputees with brain signals".
4. Creating new model and testing with the time-line graph.

Daily Report: 23/05/2025
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1. Correcting the positioning of the zoom options in the time-line graphs such as " Zoom in", "zoom out", and "Reset".
2. Adding icons for each button options instead of using texts.
3. Added new zoom styles in the UI and downloaded some icons and trying to modifying the UI part.
4. Fixed the issue in the 2nd time-line graph's zoom option that , it always placing graph dots in the corner when click onto the "reset" option, corrected the zoom in and zoom out.

Daily Report: 27/05/2025
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1. Current task ongoing: Implementing the Live UI re-run provision.
2. Created a new function that will clear all the variable's value which is get from entry fields when we need to again start the application or plot the EEG signal and the time-line graphs.
3. While implementing the above concept, some errors occurred and correcting them: "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 2063, in classifier_prediction
self.scatter = self.timeline_ax.scatter( AttributeError: 'NoneType' object has no attribute 'scatter'..

Daily Report: 28/05/2025
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1. Implementing the clearing of right frames such as EEG signal plotting frames and time-line graphs frames when we switching approaches.
2. Adding a new method in approach selection area to clear or refresh the timeline graph and EEG visualization content (not the entire frame) when reselecting approaches, you need to target the specific widgets or canvases inside timeline_frame and other visualization frames that hold the plotted data, without destroying the frame itself.
3. Issues facing: Only the second time-line graph is clearing, the EEG plotting area become not working and error found like:File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\axes\_base.py", line 494, in _plot_argsraise ValueError(f"x and y must have same first dimension, but "ValueError: x and y must have same first dimension, but have shapes (2000,) and (400,)

Daily Report: 29/05/2025
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1. Current task Ongoing: Modifying the Neuro-assistive systemUI.
2. Re-arranging the components of Seizure-Prediction approach if selected.
3. Hides the event alert frame when we selecting "seizure" approach using the .pack_forget() method.
4. When selected the "offline data" from data settings, then placed the data browsing option first and followed by the channel selection label and entry, sampling rate label and entry fields.

Daily Report: 30/05/2025
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1. Changed the component flow of "AI Model settings" of left side frames.
2. Making changes such as: Only displaying the "Configure Model" browse button at first, after clicking on the button it will go for the file paths and then only it will displays the "model path" and "Config path" entries and labels.
3. Added a logic in "set_paths" function for only display them after the paths are selected.
4. Trying out to clear the right side frame's previous plotting when browsing the Data again.
5. Attending the iCon-BCI Lecture series part 15 about the topic on "A framework for eeg signal acquisition,processing and application in neurotechnology".

Daily Report: 31/05/2025
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1. Changing the time-line graph size, reducing the space usage.
2. Removing the y-axis ticks and x-axis ticks to reduce the space utilization.
3. Exploring about how to remove the borders of the frames in two time-line graphs, excessive padding.
4. Reduced the data browsing icon size and changed the "Reset" button icon image in the time-line graph.
5. Found some error during clearing the right frame visualization: File "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 945, in on_hover self.annot.set_visible(False) AttributeError: 'NoneType' object has no attribute 'set_visible'

Daily Report: 02/06/2025
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1. Corrected the errors while implementing the clear and re-run the NeuroAssistive_UI when browsing the data again: "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\axes\_base.py", line 494, in _plot_args raise ValueError(f"x and y must have same first dimension, but "ValueError: x and y must have same first dimension, but have shapes (2000,) and (400,)
2. Successfully implemented the clearing visualization and re-run provision when browsing data again in the NeuroAssistive_UI.
3. Started fixing the static EEG signals when changing the "intervals" in signal processing settings.
4. Attending meeting of "EEG Device Demo".

Daily Report: 03/06/2025
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1. Current task Ongoing: Fixing the static EEG signals when changing the "Spacing" in the Signal processing settings.
2. Correcting error while implementing the above: ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (2000,) and arg 1 with shape (4000,).
3. Similarly fixing the EEG signal when changing the "Sensitivity" in the signal processing settings.
4. Attended the "demo of EEG device" meeting.

Daily Report: 04/06/2025
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1. Correcting the logic implemented in the static EEG signals when changing the "Interval", "Spacing", "Sensitivity" in the Signal processing settings.
2. Similarly applying the logic for "Notch", "Highpass" and "Bandpass" filters also..
3. Prepared the i-Con BCI Leacture Series part 16 compering script and done the task of compering and attended the session.
4. Testing the signal processing settings with each components both dynamic state and static state of the EEG signal.

Daily Report: 05/06/2025
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1. Current task ongoing: Facing a problem of non-Working notch filter for the EEG signal plotting. Fixed the problem in the "Notch filter" in the signal processing settings of NeuroAssistiveUI.
2. Added a function call for updating and managing the changes in the notch filter while EEG signal plotting and tested them.
3. Created a merged data set for seizure prediction, merged the subjects 23,24,25,26,27.
4. Creating new models for seizure predictions with new features.

Daily Report: 06/06/2025
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1. Current task: Creating new model for testing the live_UI for seizure_Prediction approach.
2. Created new model with combined iktal files of 23 and 24.
3. Testing the application with new model and preparing the software for Demo.

Daily Report: 08/06/2025
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1. Prepared the application for the Demo.
2. Successfully attended and participated in the Demo of Seizure Prediction and Detection system.

Daily Report: 09/06/2025
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1. Current task Ongoing: Modifying the current NeuroAssistive_UI such as changing the font_size and style of the UI components in "signal processing settings", "Data settings" radio button options. Changed the Select approach naming to "Application".
2. Trying to modify the UI setups of time-line graphs, such as changed the legend size, changed the icon image of zoom in and zoom out, fixed the alignment issue.
3. Trying to fix the size of the "signal processing settings" frame similar to the other frames such as "seizure data visualization" and "Time-line graph".
4. Changed the legend label reading from in-built function to direct reading.

Daily Report: 10/06/2025
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1. Task Ongoing: Corrected the time-line graph titles with bottom placement of each time-line graphs.
2. Fixed the problem of size variation in the "signal processing settings" frame similar to the other frames such as "seizure data visualization" and "Time-line graph".
3. Correcting the bug in the NeuroAssistiveUI clear visualization, plotting and re-run when browsing the "data" path again.
4. fixing the issue while clearing the timeline plotting and found the below error:RuntimeError: main thread is not in main loop Tcl_AsyncDelete: async handler deleted by the wrong thread.

Daily Report: 11/06/2025
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1. Successfully corrected the bug of thread problem facing during the NeuroAssistiveUI clearing all visualization and re-Run.
2. Creating new model with improved number of files and testing that model with Seizure Prediction EEg signal plotting and Visualization(time-line graphs), and checking the prediction accuracy and detecting events.
3. Fixed the problem of zoom in and zoom out option of first time-line graph for placing them into center part according to click in the time-line graph.

Daily Report: 12/06/2025
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1. Created new datasets for training, Combined "23" and "24" files and created 50 iktal files and 40 pre-iktal, post-iktal, inter-iktal.
2. Generated model with normal 5 features such as kurtosis, skewness, variance, mean and median of time-domain features. Also generated with specified features for both time and frequency domain features.
3. Changed the number of iktal files and created models and testing with NeuroAssitive SystemUI for checking the prediction and detection values.

Daily Report: 13/06/2025
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1. Created a new model of file "25" with SVM classifier and specified features of time-domain and frequency-domain and overlap window size 0 and 3 decision window size.
2. Similarly created model of file "25" with SVM classifier and specified features of time-domain and frequency-domain and overlap window size 1 and 9 decision window size.
3. Tested both models in NeuroAssistive systemUI for seizure prediction and found that both models predicting the Post-ictal event only.
4. Preparing PPT for the Demo purpose and referring the global perspective of Seizure prediction and detection system.

Daily Report: 14/06/2025
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1. Started implementing the NeuroAssistive systemUI re-Run provision for while browsing or configure the model path and configuration file path after one successful execution.
2. If again browsing new model and configuration file for processing with same data, need to clear the existing visualization and time-line plottings. So creating a function for clearing them, and updating the "browse_file" function.
3. Prepared the iCon-BCI Lecture series part 18 compering script and successfully attended the session and compared.

Daily Report: 16/06/2025
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1. Creating new model with SVM Classifier and wavelet features only [ wavelet energy, wavelet entropy etc.] with decision window size is 3 and overlap window size is 0.
2. Tested it with neuroassistive systemUI for checking the prediction result and detection result, and the pre-iktal, iktal and post-iktal events detected.
3. Found some error while creating model for "25" subject: File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\utils\validation.py", line 887, in check_array dtype_orig = np.result_type(*dtypes_orig) File "<__array_function__ internals>", line 200, in result_type ValueError: at least one array or dtype is required

Daily Report: 17/06/2025
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1. Creating model of Seizure prediction for the subject 26 with SVM classifier, overlap window size is 0 and decision window size is 3 and bandpass filtered, applied all wavelet features without balanced data.
2. Tested the above model into the neurioassistive systeUI and noted the predictions and detections.
3. Similarly created a model of seizure prediction for Subject "27" with classifier SVM and overlap ws is 0 and decision ws is 3 and bandpass filtered, applied all wavelet domain features and done it in balanced data(39 files each).
4. Tested it with NeuroAssistive systemUI and noted the predictions and detections of the events.

Daily Report: 18/06/2025
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1. Current task Ongoing: Correcting the implementation of Clearing visualizations and plotting of EEG signals and time-line graphs when click onto the "configure model" button.
2. Implemented a new re-Run for the NeuroAssistive systemUI when browsing the model path, and config path.
3. Creating a new model for the subjects combined 23,26,27 with the help of wavelet domain features, bandpass filtered, overlap window size is 0 and decision window size is 3 in SVM classifier.

Daily Report: 19/06/2025
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1. Checking code of the Post-processing methods such as "Evaluation of Continuity" and "Mode of Events", and checking the implementation.
2. Testing the Seizure prediction model in MiME ui, and checking the post processing result by individual file results.
3. Checked the post-processing "Evaluation of Continuity" method with seizure sample datas with number of files, 3, 5 and 11. found that it is working fine and variation of result is with "Mode of events".
4. Preparing Brochure content for Seizure prediction and updated screenshots are placed.

Daily Report: 20/06/2025
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1. Correcting the Brochure content for Seizure prediction.
2. Started testing the Model created for the subject 23 with each event data files.
3. Found a problem in Clear Visualization and Re-Run the Live UI when re entering the both paths for data, model and configuration files.
4. Tested the plotting of wavelet coherent implementation code.

Daily Report: 21/06/2025
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1. Current task Ongoing: EEG data Collection for inner speech by using EMOTIV device.
2. Taking EEG Data collection for EyeBlink detection by using 3 channel E-DAC EEG device.
3. Performing Training of Random Forest Classifier model creation for Seizure Detection and prediction system in another PC. With all Wavelet domain features, Random forest classifier with 100 estimator and random status 42 and depth value is 10 and overlap window is 0 and decision window is 3.

Daily Report: 23/06/2025
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1. Current task: Performing testing of model for the subject 23. Testing 23rd data which are not included for training.
2. Testing 23rd data which are included for training.
3. Started testing other subjects data[ training data, testing data and event wise data].
4. Learned how to setup the EMOTIV EEG device for data collection.
5. Edited the Brochure content and added new screenshots.
6. Correcting the Notch filter function for the visualization of eeg signals with fixing the issue of "notch filter to be applied on the original raw EEG data, not the already processed (possibly filtered) data ".

Daily Report: 24/06/2025
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1. Correcting the notch filter updating function. Removing the filter applying facility to the processed data once we applied the filter. fixing the issue of "notch filter to be applied on the original raw EEG data, not the already processed data ".
2. Performing the testing of notch filter for the eeg signals in the range of 50 and 60hz.
3. Setting up the Laptop for the attending the Demo in techverse program. Configured the MiME_v2 software for seizure detection and prediction.

Daily Report: 25/06/2025
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1. Setting up the Laptop for the attending the Demo in techverse program.
2. Installed the required packages and libraries for running the MiME software[ numpy,pyedf,pyedflib,pyttsx3, etc].
3. Creating a word document for the "User Manual for: Seizure Prediction -Live UI interface. Added the document to the folder for the demo
4. Installed the "FastStone_Capture_v8.9_Activated" software for recording the screen of running live seizure prediction application. Recorded the event prediction.

Daily Report: 26/06/2025
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1. Performing testing of Subject 27's training and testing data, their event wise data by using "model_for_23" [ testing with entirely new subject's data].
2. Noting the accuracy of each data for creating google sheet for storing results.
3. Started testing the other subject's model, i.e, "Model_for_26" with its training data, testing data and their event wise data.

Daily Report: 27/06/2025
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1. Performing the testing of "Model_for_26" with training data of 26 th subject, testing data and event based testing.
2. Testing the above model with other subject's data such as 23 subject's training, testing and event based data, 24 subject's training data, testing data and event based data.
3. Noting the above testing result for updating.

Daily Report: 30/06/2025
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1. Current work in progress: Continuing the testing of model with other subjects : Testing the "model_for_26" with the subject of 27 training data, testing data and their event wise and noted the testing result for updating.
2. Started testing the "model_for_27" with it's training data and their event wise data, then testing data and their event wise data and noting the result.
3. Parallely checking the working of other filters such as high pass and low pass filters in the LiveUI to check whether the changing of eeg data while changing the filters or not.

Daily Report: 01/07/2025
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1. Started testing "Model_for_27" with test data which is not included in the training the model and got 41.91% accuracy.
2. Tested the event wise testing data and got the iktal event-50%, inter-iktal-72%, post-iktal-50%, pre-iktal-0%.
3. Started testing the "Model_for_27" with entirely new subject's train and test data which are not included for training.[ started test with 23 th subject data]. For 23th subject's train data accuracy is 23.27% and for test data is 43.72%.
4. Creating a Project proposal contents such as "Need, forecast and urgency for the technology proposed to be developed with justification" and "Specific Manner in Which Know-How Generated Here is Envisaged to Be Translated into Production" for the project "Neurological disorder screening and cognitive retraining system".

Daily Report: 02/07/2025
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1. Testing the remaining: tested the "model_for_27" with other subject data such as 24 th subject data and got training data accuracy around 19.49% and for 25th subject's training data accuracy is around 48.10%.
2. Created an Excel sheet for updating all the testing results of Seizure Prediction and started updating the results.
3. Attended the meeting about the discussion of dicom conversion and its usage, how it implemented using Reactjs.

Daily Report: 03/07/2025
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1. Successfully completed the updation in the excel sheet for entering the test results of seizure prediction models.
2. Started testing the model created with combined data for the subjects such as 23,26 and 27 by using Random Forest classifier with estimator 100, obtained 83.23% accuracy for the data used for training this model.
3. Attended the HTG connect meeting about the topic on "Docker & Kubernetes: The remix every DevOps needs".
4. Attended the Icon-BCI Lecture Series part 19 about the topic on "Autism detection from EEG signals using deep learning" and done the task of compering for the meeting.

Daily Report: 04/07/2025
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1. Prepared the Seizure Prediction and detection software for the Demonstration.
2. Successfully completed the Demonstration to the team and explained the overall idea of the project.
3. Started exploring about the features such as Lyapunov Exponent and cross correlation for improving the accuracy in seizure prediction and detection system.

Daily Report: 07/07/2025
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1. Exploring about the features such as Lyapunov Exponent and cross correlation for improving the accuracy in seizure prediction and detection system.
2. Exploring the TUH data Readme Files for Data usage.
3. Meeting attended about the Demonstration of EEG device from AXXONET.

Daily Report: 08/07/2025
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1. Started Train a new model with new features such as RMS, Hjorth mobility/complexity, kurtosis, fractal dimensions, zero crossing, average amplitude change, energy and the subject used is "23", then applied Z-score normalization for SVM feature scaling. This for testing is there any accuracy improvement for model or not.
2. Training accuracy got 61.51% and testing accuracy is around 18.96% for training data and 27% for testing data for the subject "23".
3. Attended the demonstration meeting of AXXONET EEG device , connectivity, protocols available,how data exporting, SPU monitor, BESS software usage, cap connection, Saline solution making and procedures.

Daily Report: 10/07/2025
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1. Current Task: Integrating Current Neuro_assistive UI works such as Time-line graphs, Approach selection and UI changes, Seizure detection and Prediction post-processing result, signal processing settings, Re-run when new data browsing, model and configuration file browsing, etc.
2. Successfully completed the integration and checked the working of the integrated offline data module for seizure detection and prediction.
3. Corrected the alignment issues in the signal processing settings part and visualization frames and added the images to SVN repository and committed all the works to SVN.

Daily Report: 11/07/2025
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1. Current task: Started creating a diagramatic representation of work flow for the Ai for a project proposal.
2. By using canva application created a basic structure of the workflow.
3. Changing the diagram with corresponding flow recommended by PL. Started creating a new diagram for the workflow of AI.

Daily Report: 14/07/2025
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1. Current task: Changed the alignment issues in the diagram, changing the alert image used for seizure, replaced the feature extraction processes image with another image.
2. Successfully completed the diagrammatic representation for "workflow of AI".
3. Creating a new model for Seizure prediction and detection system, with new time domain features such as Lyapunov exponent, Cross correlation etc., with SVM classifier.
4. Exploring a new feature " Line Length" in time domain for improving the accuracy of the Seizure prediction and detection.

Daily Report: 15/07/2025
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1. Updated the diagrammatic representation for "workflow of AI", Added a new icon for "i need water", Changed the "AI model" icon and added a new image for "new data" step,
blurred the image of EEG device's face by using pixlr application etc..
2. Meeting attended about the discussion on the PRSG Demo Presentation of projects, MiME software, current tasks, etc.
3. Continuing the Training a new model in SVM classifier with new features and started implementing "Line Length" feature in time domain into our application.

Daily Report: 16/07/2025
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1. Successfully implemented "Line Length" feature for time domain features, for improving the accuracy in seizure prediction and detection.
2. Started creating a new model for the subject "23" data with processing window size is 4 , decision window size is 3 and overlap window size is 0, and new features included the "line length" features with default parameters for the features such as cross correlation,phase lock value amd lyapunov exponent.
3. Started testing the model created, with training data which is included for training and found some error while testing: File "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\feature\TimeDomainFeatures.py", line 122, in timeDomainFeature_Callback emb_dim = gl.lyap_params["emb_dim"]KeyError: 'emb_dim'

Daily Report: 17/07/2025
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1. Updated the SVN repository and started creating the model again with SVN classifier and new features.
2. Started testing the above model created, with training data, event wise training data, testing data and event wise testing data.
3. Got training accuracy is 54.56%, and testing with training data is 36.03%, testing with test data accuracy is 54.54%.
4. Noted that with testing the data, when testing the data with postprocessing method evaluation of continuity have slight more accuracy than mode of events.

Daily Report: 18/07/2025
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1. Making updations on the Workflow of the AI for seizure Prediction and detection.
2. Removed the eeg device figure from the diagram, and added separate arrow for new data and training data.
3. Creating a new model for the subject "26" with SVM classifier , new features included line length feature.

Daily Report: 19/07/2025
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1. Created a model for 26 th subject, by Using SVM Classifier with new features.
2. Started testing the above SVM Model training accuracy is 50%, testing with training data is 53.03%, test data accuracy is 49.50%.
3. Started creating a new Model in Random Forest Classifier, with notch filter, bandpass filter with lower value 0.5 and upper value 40, baseline correction in degree 1, n-estimator 100, max_depth is 10, Random state is 42,
By using "23" subject data.

Daily Report: 21/07/2025
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1. Started testing the model created for the subject "23" in Random Forest Classifier. Training accuracy is 77.06%, testing with training data accuracy is 93.96%, testing with test data accuracy is 72.72%,
also tested with event wise data.
2. Attended a meeting about the topic on " Django basics and how it works, architecture,"etc.
3. Making corrections on the diagrammatic representation of "Workflow of seizure detection and prediction", changed the arrow color for new data testing , added and extra arrow for training data for DL (for skipping feature extraction), added a new legend for each arrow representation.

Daily Report: 22/07/2025
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1. Started creating model for the subject "26" with all wavelet features, bandpass filter[lower-0.5, upper-40],baseline correction in degree 1, notch filter], with n-estimator 100, max-depth-10, random state-42.
2. Started testing the model created for the subject "26" . Training accuracy is 50%, testing with training data accuracy is 53.03%, testing with test data accuracy is 49.50%, also tested with event wise data of training data [ictal-21.25%, inter ictal-96.15%, post-ictal- 38.75%, pre-ictal- 15.0%], tested with event wise test data [ictal- 15%, inter-ictal- 97.43%, post-ictal- 15%, pre-ictal-27.27%].
3. Involved data collection demonstration for the team by using AXXONet EEG device.
4. Created the separate diagram for the workflow of "Seizure Prediction and Detection", "Neurological event prediction" and "inner speech and decoding".

Daily Report: 23/07/2025
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1. Started creating model for the subject "23, 26,27" with all wavelet features, bandpass filter[lower-0.5, upper-40],baseline correction in degree 1, notch filter], with n-estimator 100, max-depth-10, random state-42.
2. Started testing the model created for the subject "23,26,27" . Training accuracy is 84.77%, testing with training data accuracy is 70.05%, testing with training data of 23 subject data accuracy is 37.93%, also tested with event wise data of training data [ictal-3.44%, inter ictal-100%, post-ictal- 27.58%, pre-ictal- 20.68%].
3. Added created model into the neuroAssistive UI and tested the EEG signal plotting,time-line graphs and predictions and detection results.
4. Making modifications on the workflow of inner speech and decoding, changed the flow and direction after the postprocessing step, step numbering changed, for training data step and new data testing step separated by a dotted line.

Daily Report: 24/07/2025
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1. Making modifications on the workflow of neurological event detection and seizure prediction and detection.
2. Created a new model for 24,25 subjects with all wavelet features, bandpass filter[lower-0.5, upper-40],baseline correction in degree 1, notch filter], with n-estimator 100, max-depth-10, random state-42. Then tested successfully.
3. Started creating a model for combined all subject's data[ such as 23,24,25,26,27].
4. Started correcting the "alert event setting_UI" for adding radio buttons for the approaches such as seizure,inner speech, ssvep,eyeblink etc..

Daily Report: 25/07/2025
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1. Started testing the model created by combining all the subject data 23,24,25,26,27 in neuroAssistive UI and checking the prediction and detection results.
2. Setting up the laptop for the demonstration of seizure prediction and detection in NeuroAssistiveUI.
3. Testing the model with Subject specific, Subject "24" tested with Balanced All subject Merged data.
4. Attended the meeting about the discussion on the topic of "How to create components in Reactjs, how components implemented".
5. Updated the "Load_selected_channels_from_meta" function for correcting the meta file error while testing.

Daily Report: 26/07/2025
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1. Completed the setup of laptop for the demonstration of seizure prediction and detection.
2. Meeting in Medical college Hospital with Dr. Chithra about the discussion on the Seizure Prediction and Detection software system.
3. Testing the subject "23" data in NeuroAssistiveUI for checking the working and got some errors and checking it.

Daily Report: 28/07/2025
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1. Started creating data batchwise for each subject data of seizure [such as 23,24,etc.]. Then testing each 1hr and above data in NeuroAssistiveUI for evaluating the results.
2. Tested 23,24 subjects each batch data of "iktal" event using Model of each subjects itself and Balanced merged all subject model also.
3. Referring the "post_process_predictions" result and "classifier_prediction" for implementing the save mechanism of the results into xl files.

Daily Report: 29/07/2025
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1. Current task Ongoing: Adding a frame for saving the results into xl sheets[ postprocessig result and classifier result]. Added two checkboxes for save options. Then added a browsing option for entering or browsing the xl file for saving the results.
2. Created separate functions for saving (writing) the result into browsed file path, and implementing the browse option display just after the selected checkbox option.
3. Called the function implemented after the analysis completed or plotting of the time-line graph on the neuroAssistive UI.
4. Got some error while implementing: from xlsxwriter import Workbook ModuleNotFoundError: No module named 'xlsxwriter'...
Installed the 'xlsxwriter' library for xlwriting.

Daily Report: 30/07/2025
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1. Corrected the error in library got yesterday in saving the postprocessing result and classifier result into xl sheets.
2. Testing a Data with ".edf" format of EEG signal in NeuroAssistiveUI and got some error while loading the edf eeg signal data: and data not loaded into the EEG signal visualization.
3. Correcting the problem of event label in post-processing result saving part.
4. Adding a condition for loading ".edf" format eeg signals in neuroAssistiveUI. Updating the "read_seizure_data" Function.

Daily Report: 31/07/2025
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1. Correcting the problem while loading the edf format eeg signals into "offline_moving_window" function and updating the "read_seizure data function.
2. Setting up the laptop for the deployment process of the seizure prediction and detection system at GMCT.
3. Setting up the MiME software for testing and validation.
4. Successfully implemented the saving result mechanism for post processing result and classifier result.

Daily Report: 01/08/2025
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1. Initiated the step for the Deployment of Seizure prediction and Detection system software at Government Medical College Trivandrum.
2. Collected 47 subject data for Analysis and validation of the Seizure prediction and detection system.
3. Tested some subjects data with software and validated the results through Neuro assistive UI.

Daily Report: 04/08/2025
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1. Creating a Workflow diagram of MiME, and MiME classifiers using Canva application.
2. Correcting the bug facing during the EEG signal Plotting for Seizure prediction and detection system, when clicking on the timeline graph got the issue of plotting particular eeg signal that we clicked on.

Daily Report: 05/08/2025
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1. Created diagram for "Model creation of MiME with steps.
2. Building diagram for Model Execution of Innerspeech decoding with proper pencil drawing images and steps.
3. Created diagram for Model Execution of SSVEP with steps.
4. Updated the diagram of MiME classifiers to AI algorithms.
5. Modified the diagram of Workflow of MiME, with separate ML,DL model creation and execution.
6. Copied the Data collected from the Medical college into PC and started testing and validating.

Daily Report: 06/08/2025
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1. Updated SVN Repository for testing the changes have made, Checked new mechanism added for Multi Label in seizure prediction and detection. Checked the UI components and how its works.
2. Committed the work till now into SVN Repository, Updated Save results of postprocessing and classifier.
3. Error while testing new data from GMCT in neuro Assistive UI: feature_extract_dataframe = extract_feat_pipeline(subject_file_name,
TypeError: feature_extractor() missing 1 required positional argument: 'chunk_data'

Daily Report: 07/08/2025
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1. Online Meeting Attended with Suresh Devasahayam sir and team members about the Demonstration of MiME application for representing before the Final PRSG.
2. Started implementing the problem of Save Results of post processing and classifier results when selecting the innerspeech approach.
3. Correcting the problem of start and stop is out of UI when save results frame's space usage.

Daily Report: 08/08/2025
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1. Adding a Label frame with a toggle button for indication of minimize and maximize, when click onto the icon, contents should disappear, and height collpses, when expanded, all widgets reappear, and layout is restored.
2. Creating a write up for the "seizure prediction and detection system", about the topic on "Need for clinical deployment of seizure prediction and detection system".
3. For updating the test accuracy results started testing the model created by using balanced combined all subject data with training and testing data.

Daily Report: 09/08/2025
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1. Current task Ongoing: Implementing a toggle minimize and maximize facility for the "Save Results" frame.
2. Issues facing now: It won't reducing the space usage for the contents of the frame even if it is minimized, the space for checkboxes and entries for the folder path still using,
So the "stop" and "start" button not visible for the innerspeech approach.
3. Correcting the above problem and referring solutions for it

Daily Report: 11/08/2025
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1. Successfully completed the toggle minimize and maximize facility for the "Save Results" frame.
2. Current task Ongoing: Still have the problem of sufficient space even after the implementation of toggle minimize and maximize facility for the "Save Results" frame.
So started implementing the toggle minimize and maximize facility for "AI Model Settings" frame.
3. Started adding a toggle minimize and maximize option for implementing this facility and creating a function for it.

Daily Report: 12/08/2025
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1. Successfully completed the task of implementing toggle minimize and maximize options for "AI Model Settings" frame.
2. Updated SVN Repository and integrated the development implemented till now.
3. Testing the UI with Data for checking the save result option and plotting, but found some errors: UnicodeDecodeError: 'utf-8' codec can't decode byte 0xa4 in position 9472: invalid start byte, oad_selected_channels_from_meta meta_file_path = meta_file_path⁰ IndexError: list index out of range, etc......
4. Corrected the above errors and Committed the works into SVN Repository.

Daily Report: 13/08/2025
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1. SVN Repository updated and corrected the Save Postprocessing results and classifier result error corrected is committed.
2. Started testing the RealtimeUI with data collected for validating the results of seizure prediction and detection, and found one data with better seizure detection in "Subject 12" dataset.
3. Started implementing the radio option for each approaches with corresponding table with label(event) and their description when selecting each approaches, change the table accordingly.
4. Started training a model for SVM with Balanced merged subject data and specified channel selection( removed unwanted or unnecessary channels such as A1, A2, LOC, EKG etc....), with all wavelet features.

Daily Report: 14/08/2025
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1. Created a Model in SVM classifier, with all wavelet features , specific channels[ removed channels such as LOC,ROC, A1, A2, EKG, etc..] with balanced merged all subject data, training accuracy is 62.96%.
2. Successfully completed the implementation of event and description table according to the selection of approaches such as seizure, innerspeech etc..
3. Started implementing a new additional setup in Real-time UI, removing the existing channel entry field and replaced it with new button "Select Channels".
4. Developing New UI for displaying channels with respect to the devices such as Natus,emotive,etc.. in addition with new two checkbox options of "Analysis" and "Display".

Daily Report: 18/08/2025
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1. Added a new button For channel Selection and replaced the entry fields and label for channels.
2. Connected that button with a new UI, and integrated the ChannelSelectionUI components into this UI and added extra two checkboxes for "Analysis" and "Display".
3. Adding an additional Channel list for Display and existing one is for Analysis channel list.

Daily Report: 20/08/2025
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1. Project Engineer (Fresher) Walkin-interview Attended....

Daily Report: 21/08/2025
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1. Adding removing options for "display channel Lists" as well as "Analysis channel lists"..
2. Attended HTG Connect meeting about the FHIR and ABDM.

• The Channel lists of "Analysis" and "Display" storing in a global variable when submitting the "Save" button.
• Updating the logic of function "set_path_after_popup()".

3. Found Error and correcting it: "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 4172, in offline_seizure_eeg_visualization self.axs.tick_params(axis="y", colors="white", labelleft=True) AttributeError: 'NeurotechAssistApp' object has no attribute 'axs'...

Daily Report: 23/08/2025
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1. Correcting the "offline_seizure_eeg_visualization" function for fixing the correction, because "1-33" entry anymore, but directly use new UI’s global variable.
2. Fixing and adding the logic of replace the parsing logic with code that extracts channel numbers and labels directly from those lists.
3. Testing the Analysis part of the Real-time UI for correct updation of channels and channel is taken from the lists for Evaluation.

Daily Report: 25/08/2025
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1. Correcting the "Analysis" part of the Real-timeUI.
2. Updating the channel variable with the global variable which is storing the Analysis channels list.
3. Changed the ""set_path_after_popup()" function logic to taking the channels from the list.
4. Found some error in channels:File "<__array_function__ internals>", line 200, in concatenate ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 34 and the array at index 1 has size 23

Daily Report: 27/08/2025
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1. Exploring the visualisation function for EEG signal data in Real-time such as " offline_seizure_eeg_visualization" for edf data and "offline_moving_window_eeg_visualization" for ASCI data.
2. Referring the solutions for solving the error of : File "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 4214, in offline_seizure_eeg_visualization
self.axs.tick_params(axis="y", colors="white", labelleft=True) AttributeError: 'NoneType' object has no attribute 'tick_params'
3. Setting up the Laptop for Seizure Prediction and Detection system for the Demo in INNOVEST Technical program.

Daily Report: 01/09/2025
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1. Testing the Subjects data collected from govt. Medical college hospital in Real-time UI for validation of results.
2. Tested Subject 13,14,15,16,17,18 data's and its not have any good detection of seizure also variations in EEG signals are very low.
3. Exploring the "Update visualization function" which is used in this development.

Daily Report: 08/09/2025
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1. Creating a new model with SVM classifier, All Wavelet Features, with removed channels such as ROC,LOC, A1, A2, etc...
2. Found some error while creating model: File "F:\MiMe_backup_10-07-2025\MiME_V2pt0\eBrainVoice\module\src\feature\Feature_Pipeline.py", line 230, in feature_extractor
data_file = gl.loaded_signal[start_row_index:end_row_index, i] IndexError: index 16 is out of bounds for axis 1 with size 16
3. Tested the EEG data collected from GMCT, subject 25,26,27,28,29,30,etc.. and got some seizure detection in the area of variation in EEG signal..

Daily Report: 12/09/2025
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1. Copied the data collected from medical college hospital for seizure Prediction and Detection system into PC and arranged the data subject wise.
2. Started analyzing and validating the results of data collected [total 21 subject data, three of them is seizure data].
3. Tested the subject 1,2, and 3 subject have seizure, and validated the results and got some detection on the eeg signal where signal have variations in frequency.
4. Tested Subject 1 to 4 abnormal data collected from GMCT, and Subject 1 and 2 have only 9 channels and Subject 3 and 4 have 21 channels.

Daily Report: 15/09/2025
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1. Current task Ongoing: Correcting the problem of channel selection of analysis and display for Real-time EEG signal plotting.
2. Updating and changing the logic of "batch_processing_module" function.
3. Changed the line "self.selected_channels_name = gl.channel_list_name_from_edf."
Instead, two separate lists — one for analysis and another for display — that are taken from global variables. then passing the variables for data for taking the respective channel data.
4. Found some errors : File "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 4253, in offline_seizure_eeg_visualization timestamps += self.times_plotting[-1] + 1.0 / self.sampling_rate AttributeError: 'NeurotechAssistApp' object has no attribute 'times_plotting'

Daily Report: 16/09/2025
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1. Corrected the channel_pick step for picking selected channels only both analysis and display part of the "batch_processing_module" function.
2. Correcting the error of :"ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 9 and the array at index 1 has size 815360".
3. Corrected the dimension mismatch problem of the processed_batch array and data_plotting.

Daily Report: 17/09/2025
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1. Setup laptop for the Demo presentation, Testing seizure data collected from the GMCT.
2. Tested full ictal data file collected from SCT, and found prediction of pre-ictal event in 506-520 th frames, 522-523, 527 th frames.
3. Testing other full data for checking the Detection of seizure event.

Daily Report: 20/09/2025
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1. Resolving the problem of EEG signal visualization when selecting the channels from the "channelSelectionUI".
2. Changing the extracting data variable, and creating separate variables for analysis as well as display.
3. found some error while doing the above are: "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 4300, in offline_seizure_eeg_visualization self.data_processed = np.vstack([self.data_processed, filt_samples]) AttributeError: 'NeurotechAssistApp' object has no attribute 'data_processed'

Daily Report: 23/09/2025
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1. Resloving the problem of Display and analysis of Real-time UI.
2. Solved the error of: AttributeError: 'NeurotechAssistApp' object has no attribute 'data_processed'..
3. Referring the "Read_Seizure_data" function, for solving the issue of "Only first 10sec batch data is plotting in visualisation" and analysis still not working.

Daily Report: 24/09/2025
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1. Resolving the problem Display and analysis part of the Real-Time UI.
2. Corrected the function "update_visualisation" for initializing the analysis and display variables which is storing the selected channels from "selectchannels" UI.
3. Adding a logic for extracting the length of the selected channels from the format of channellist global variables " [' 1 - C3', ' 2 - C4', ' 3 - Cz', ' 4 - F3', ' 5 - F4', ' 6 - F7', ' 7 - F8', ' 8 - Fz', ' 9 - Fp1', '10 - Fp2']".

Daily Report: 25/09/2025
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1. Resolving the error while running the real-time UI for seizure detection and prediction, when we select different channels(different number of channels) it showing some errors:
"C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\numpy\lib\stride_tricks.py", line 422, in _broadcast_shape b = np.broadcast(*args[:32])ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (1200,) and arg 1 with shape (400,).
2. Making some changes in the "offline_seizure_eeg_visualization" function , using self.data_processed only for plotting and self.data_processed_analysis only for analysis (ML/feature extraction/etc.).

Daily Report: 26/09/2025
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1. Resolved the issue of giving same number of channels for display and analysis for the seizure prediction, its working on both visualisation( EEG plotting and time-line graph).
2. Current task: Trying to resolve the problem of different number of channels given for display as well as analysis part of the seizure prediction and detection system.
3. Found some errors in the correction of variable of filters applying to the data separately for display and analysis:
in lfilter return _sigtools._linear_filter(b, a, x, axis, zi)ValueError: Unexpected shape for zi: expected (8,6), found (8,7).

Daily Report: 27/09/2025
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1. Correcting the problem of display and analysis part of real-time UI: line 2157, in lfilter return _sigtools._linear_filter(b, a, x, axis, zi)ValueError: Unexpected shape for zi: expected (8,6), found (8,7).
2. Created two independent filter states: self.filt_state_analysis for analysis channels.
self.filt_state_display for display channels. Stored outputs separately in self.data_processed_analysis and self.data_processed.
3. Adding the dual-path filtering logic so that analysis and display are handled separately, each with its own filter state.

Daily Report: 29/09/2025
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1. Resolving the error of display and analysis part (different number of channels given for display as well as analysis part of the seizure prediction and detection system)for the seizure prediction system.
2. Corrected the error of ValueError: ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (1200,) and arg 1 with shape (2000,).
Unexpected shape for zi: expected (8,6), found (8,7).
3. Successfully corrected the problem of analysis and display part when different number of channels given for EDF formatted data.

Daily Report: 30/09/2025
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1. Correcting the issue of analysis and display part when different number of channels given for ASCII formatted data.
2. Changed the else part of "read_seizure_data" function for the offline ASCII data of EEG.
3. Resolving the problems in "offline_moving_window_eeg_visualization" function and correcting the display part of real-time UI.
4. Analysis part of ASCII data is working and now correcting the display part. Need to visualize the eeg signals for selected channels.

Daily Report: 03/10/2025
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1. Current task Ongoing :Resolving the problem of display part of EEG signals for the ASCII formatted data in Real-time UI.
2. Correctly extracted the channel list for display over the channels listed on the meta file.
3. Solved the mismatch of channels for the display with meta data and the selected channels from the user.
4. Successfully corrected the problem of display part of the ASCII data.

Daily Report: 06/10/2025
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1. Current task Ongoing: Changing the EEG signal Visualisation or plotting.
2. Changing frame background of Real-Time Visualisation and related frames for Seizure_data_visualisation etc..
3. Changed the color code of background colors for "axs", "facecolor", "bgcolor", "fgcolor",etc. in update_visualisation function for initializing the frame.
4. Exploring the basic information about "Transformers in ML.

Daily Report: 07/10/2025
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1. Current task Ongoing: Changing the EEG signal Visualisation or plotting channel colors.
2. Making the current color adding scheme of channel( 4 different colors applying alternatively to the selected channels) into changing the colors of channels according to the type of channels or lobes.
3. Selected 3 colors and Fixed a color for Temporal and Frontal channels, then the next one color for central, the last one for parietal.
4. Added more sensitivity options for visualizing more cleared eeg signal patterns.

Daily Report: 08/10/2025
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1. Completed the correction in visualisation of eeg signals according to the channels with their specific colors.
2. Exploring the way to improve the accuracy of current SVM model for seizure prediction and detection system.
3. Exploring the kernel type of SVM classifier such as "linear" and "rbf" for comparing the necessity of the type and which one is more important for eeg signal based seizure detection and prediction.

Daily Report: 09/10/2025
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1. Creating a model in SVM with the SVM kernel "rbf" instead of "linear", all the wavelet features and time domain features such as Hjorth mobility and complexity,Decorrelation and cross correlation, baseline correction degree "1", notch filter, bandpass filter with cutoff's 40 and 80.
2. But found some errors while training the model, time domain feature related error: line 345, in feature_extractor td_fd_feature = channel_feature.reshape(channels_selected, no_of_frames * total_TD), ValueError: cannot reshape array of size 432 into shape (48,8).
3. Creating a model in SVM with the SVM kernel "rbf" instead of "linear", all the wavelet features without adding time and frequency domain.

Daily Report: 10/10/2025
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1. Exploring about the fundamental knowledge of transformers.
2. Exploring the "benefits of transformers", "key features", "why transformers can analyze EEG signals" etc.
3. Searching for the implementation of transformers for EEG signal processing.

Daily Report: 13/10/2025
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1. Exploring about "Transformers and their expanded fields".
2. Referring "Open LTM", "Large Time-Series Models (LTMs)",library used for.
3. Discussion about seizure prediction and detection system ,how it occur,etc with PL and pooja.
4. Exploring use cases for transformers, How it works,etc.

Daily Report: 14/10/2025
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1. Exploring the fundamentals of open LTM and Timer ,How they implemented in python.
2. Referring "How the transformers in Deep learning differ from the other neural networks such as CNN (convolutional neural network), RNN (Recurrent Neural Network)".
3. Exploring Self-attention mechanism in transformers. How it is working on the transformer implementation.

Daily Report: 15/10/2025
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1. Exploring how the normal EEG transformer is working..
2. Exploring the implemented code for reference.
3. Current work ongoing: Adding a new mechanism that taking EEg data and it calculates the Attention score of that particular data.

Daily Report: 16/10/2025
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1. Task Ongoing: Creating a Attention Score progress bar for the EEG signals from the emotive device as well as E-DAC device.
2. Creating an extra approach in Real time-UI as "Attention Score", then hiding the unnecessary elements such as " alert event settings", AI model settings, Save options,etc..
3. Explored the algorithm that finds the "Attention Score" and appending score value as a percentage into a progress bar.
4. Created the progress bar and attention score is displayed as progress bar.

Daily Report: 17/10/2025
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1. Current work Ongoing: Testing the Attention score of a person's EEG signal using Emotiv device.
2. Implemented 3 channel EDAC device EEG signal's attention score calculation also.
3. Exploring "How to improve the attention score accuracy", "How to fine tune the attention score".
4. Testing the attention score progress bar using E-DAC device.

Daily Report: 21/10/2025
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1. Exploring how to improve the attention score computing algorithm by studying about why "Theta staying high ratio while testing.
2. Exploring the practical reasons and why theta stays high.
3. Attended the HTG Connect meeting about the MRI.
4. Exploring the implementation that improves the problem of theta and the accuracy of the attention score.

Daily Report: 22/10/2025
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1. Referred implementation code of attention score calculation, and also reduced over mapping of theta values by cutting the noised signals and low drifts using bandpass filter applying.
2. Integrating the Channel Selection implementation by using separate UI, instead of entry fields, for both ASCII/ CSV and EDF formatted data for committing it into the SVN Repository.
3. Also integrating the attention score implementations into the RealTime UI.

Daily Report: 24/10/2025
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1. Integrated the Colors changed for channels which is based on the type of region into the Real_Time UI code.
2. Integrated the newly created implementation of Attention Score calculation of a person collected throgh "Emotiv" and "E-DAC".
3. Corrected the error while integrating them: ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (1200,) and arg 1 with shape (800,).

Daily Report: 25/10/2025
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1. SVN updated and conflict Occurred. Updated NeuroAssistiveUI python file.
2. Adding the Missing and non updated works into the updated Realtime-UI.

Daily Report: 27/10/2025
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1. Integrated the works such as Channel selection from UI for analysis and display separately, New approach "Attention Score" calculation part with visualisation EEG signal and score calculation in the way of progress bars, EEG signal plotting Channel colors changed for specific regions of the brain, etc.
2. Found some errors while integrating this developments and testing: File "F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py", line 3785, in analyze_data if not self.result_individual_file_all_feature_merged.empty:AttributeError: 'NoneType' object has no attribute 'empty'....

Daily Report: 28/10/2025
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1. Corrected the error mentioned self.result_individual_file_all_feature_merged.empty:AttributeError: 'NoneType' object has no attribute 'empty'... no valid model path found or not in .sav form.
2. Successfully integrated the works done till now into the current version of RealtimeUI.
3. Committed the file into SVN Repository and updated the Files.
4. Exploring the review paper "CNN-Based Transformer and Vision Transformer Models for the Prediction of Epileptic Seizure Using Electroencephalogram in GAERS Model".

Daily Report: 29/10/2025
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1. Exploring the paper "CNN-Based Transformer and Vision Transformer Models for the Prediction of Epileptic Seizure Using Electroencephalogram in GAERS Model".
2. Identifying the Corrections and uncleared portions in the paper's introduction, methods and data used, technology, etc.
3. Exploring the Vision Transformers and CNN based transformers from this paper.

Daily Report: 01/11/2025
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1. Preparing the documents for the new proposal of Seizure Prediction and Detection system.
2. Uploaded the documents into the google drive.

Daily Report: 03/11/2025
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1. Preparing Proposal documents for Seizure prediction and detection system.
2. Created the Architecture of Deployment of Seizure prediction and detection system.
3. Uploaded all the updated documents into the drive.

Daily Report: 07/11/2025
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1. Completed the task of Proposal submission on project title: NeuroAssist an Intelligent EEG based Seizure Prediction and detection system

Daily Report: 11/11/2025
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1. Testing the Seizure prediction and detection system in Real-time UI and found the Re-run of the application when browsing new data and model, config files not working properly.
2. Found some errors and correcting it:
File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\matplotlib\axes\_base.py", line 494, in _plot_args
raise ValueError(f"x and y must have same first dimension, but "ValueError: x and y must have same first dimension, but have shapes (200,) and (400,)

Daily Report: 12/11/2025
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1. Resolving the error of ValueError(f"x and y must have same first dimension, but "ValueError: x and y must have same first dimension.
2. Fixing the issue of self.window_for_plotting or self.sfreq changed between runs, and two arrays drift apart in size.

Daily Report: 13/11/2025
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1. Resolved the issue of self.window_for_plotting or self.sfreq changed between runs, and two arrays drift apart in size.
2. Corrected the another error because of the array mismatch: ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (2000,) and arg 1 with shape (1200,).

Daily Report: 14/11/2025
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1. Updated the SVN Repository and Added the realtimeUI re-run application correction into the SVN repository and committed the work.
2. Referring the papers and implementation of Seizure prediction and detection system by using transformers for improving the model accuracy.

Daily Report: 17/11/2025
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1. Started Exploring the Django framework of python.
2. Referring the transformers which is used for processing abnormal eeg signals.
3. Exploring "how does the django works", model, view, template concepts etc.

Daily Report: 19/11/2025
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1. Exploring the existing transformer implementation working, How data is shaping, label mapping, gpu detection, positional encoding, etc.
2. Referred the current existing code for transformers is apt for seizure prediction and detection system.
3. Explored the multi-head attention mechanism used for transformers implementation.
4. Exploring the corrections needed for making the transformer apt for seizure prediction.

Daily Report:20/11/2025
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1. Exploring the existing code implementation of "Transformers", How it can change to apt for seizure, etc.
2. Referring about the Adam optimizer, early stopping and dropout concepts implemented on the code.
3. Exploring how the temporal ordering needs positional encoding, what is the importance of positional encoding in seizure detection and prediction, and which type of positional encoding is used for this,etc.

Daily Report:21/11/2025
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1. Data Collection : Collected Seizure Data and some epileptic spike and wave data from Govt. Medical College hospital.
2. Started sorting the data separately and moved to the PC and tested seizure data(different session) on the Real-time UI.
3. Checking the modification should be needed for the transformers for seizure prediction and detection system and started changing , creating another separate function for seizure specific case.

Daily Report:24/11/2025
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1. Testing the Data collected from the Govt. Medical college hospital and validating the results of seizure detection and predictions.
2. Exploring about the patterns of seizures, generalized seizures, etc.
3. Installed the library needed(TensorFlow Addons (tfa) v:24.2) for implementing "Transformers for Seizure Prediction and detection system".

Daily Report:25/11/2025
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1. Tested the data collected from govt. medical college Subject's session 5 and session 6, and noted that the signal variance and artifacts.
2. Creating an another function for transformer implementation for specific seizure prediction and detection system.
3. Changing the data, resizing needed for transformer, added the step of creation of 3D data input(batchsize,timesteps,feature_dim).
4. Referring Focal Seizures and their types such as focal aware, focal impaired awareness seizure, etc.

Daily Report: 26/11/2025
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1. Exploring the tonic-clonic seizures and the signal patterns, the features, symptoms,etc.
2. Setting up laptop for Seizure prediction, installing the necessary libraries such as pywt,seaborn,pydeflib, etc.
3. Correcting the error of ModuleNotFoundError: sklearn.metric......

Daily Report: 27/11/2025
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1. Setting up laptop for the demo in Medical college hospital and corrected error found, Moved the current latest model, data, etc. into the laptop.
2. Visited the Government Medical College Hospital and conducted a validation test using real patient EEG data obtained from the ICU.
Discussion with Archana about the Seizure detection and prediction software and validated a patients real data with our software.
3. Testing and verifying the noted time indexes of seizure onset with Realtime UI.

Daily Report: 28/11/2025
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1. Emailed to the PL about the status of our deployment of seizure Prediction and detection system at govt. Medical college hospital with the details of test results and Model Performance (Initial Validation).
and results verifying with PL's.
2. Checking for the implementation of wavelet filters in the current version of MiME.
3. Exploring about the Notch filters and their working.
4. Correcting the error:" from keras.utils import tf_utils ImportError: cannot import name 'tf_utils' from 'keras.utils' (C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\keras\utils\__init__.py).

Daily Report:01/12/2025
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1. Current Work Ongoing: Fixing the components of the left frame placement.
2. Creating a toggle button for minimizing and maximizing the frame components for better space utilization.
3. Added a inner frame for handling the collapse feature, updating the "Data Settings" frame, update_selected_device function, etc..

Daily Report: 02/12/2025
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1. Added " Data Settings" collapses for hiding when clicking onto the minimized toggle, display when clicking the maximized toggle.
2. Created a function for handling the hiding and display of the component for getting the collapses feature.
3. Corrected the Misplacement of the components when we apply the toggle thing, the browsing options and paths entry fields are misplaced.
4. Successfully implemented the collapse mechanism for space utilization of "Data settings" frame, also corrected the "AI Model Settings" part.

Daily Report: 03/12/2025
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1. Started Creating Summary of the Seizure Detection and Prediction results into a frame on the left side.
2. Created a new frame for " EEG Event summary" with a scrollable space for including the info.
3. Implementing the mechanism for results of classifier for writing into the frame as summary.

Daily Report: 04/12/2025
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1. Found some errors while writing the summary of the results into the summary frame:"F:\SVN_REPOSITORY\MiME_V2pt0\eBrainVoice\module\src\View\neurotechnology_assistive_systemUI.py",
line 4177, in analyze_data event_label = result_individual_mode_merged_final_mode_event_detection[-1]TypeError: 'int' object is not subscriptable.
2. Correcting the error and fixing the Issue of writing the same event label and location repeatedly.
3. Adding a mechanism for a clickable text thing for passing the current start time index of the EEG signal for visualisation.

Daily Report: 05/12/2025
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1. Adding a clickable text with underline(for making it is a link that leads you in the visualisation that particular eeg signal of that time index)
for passing the current start time index of the EEG signal for visualisation.
2. Fixing the issue of not properly updating the visualisation of EEG signal plotting: AttributeError: 'NeurotechAssistApp' object has no attribute '_last_appended_event'

Daily Report: 08/12/2025
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1. Successfully corrected the error, and created the Summary Results of Seizure Detection and Prediction events.
2. Done the implementation of clickable event with corresponding location of EEG data with respect to the time index.
3. Modifying the Summary Result frame by increasing the frame size,etc.

Daily Report: 10/12/2025
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1. Adding a indicator note should clearly explain the summary index meaning, each index how many seconds, which is for event index guide.
2. Styling the note with proper fonts,colors,positioned at the top of the summary writing area.
3. Correcting the functions of notch filter apply for eeg signals, referring the corrections needed for the existing function.

Daily Report: 11/12/2025
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1. Trying to correct the notch filter apply in eeg signal,Changing the update_notch filter function and found that only current eeg window is filtered.
2. Integrating the works done in RealtimeUI such as left frame space utilization(shrinking of the frames, collapse mechanism, toggle feature adding), and Summary of Results creation,etc..
3. Updated SVN Repository and correcting the conflicted files.

Daily Report:22/12/2025
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1. Integrated works in Real Time UI and committed into the SVN Repository.
2. Correcting the Error when we browse the ASCII formatted data for evaluation.
3. Correcting the File "C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\numpy\lib\stride_tricks.py", line 422, in _broadcast_shape b = np.broadcast(*args[:32])
ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (2400,) and arg 1 with shape (1600,).

Daily Report:29/12/2025
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1. Successfully corrected the error while visualising the ASCII data, ValueError: shape mismatch: objects cannot be broadcast to a single shape. Mismatch is between arg 0 with shape (2400,) and arg 1 with shape (1600,).
2. Correcting the notch filter applying function on raw EEG data, checking it with applying 50Hz found that the current window is only applies the filter.

Daily Report: 05/01/2026
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1. Started Creating a new model of Subject '23' with SVM classifier and specific features such as Lyapunov exponent,phase Lock value, cross correlation etc.
2. Found some error while training the model after the feature extraction file merge, :"C:\Users\hp\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\indexing.py", line 1557, in _validate_integer raise IndexError("single positional indexer is out-of-bounds") IndexError: single positional indexer is out-of-bounds.
3. Correcting the thickness of the EEG signal while plotting, sensitivity,etc.

Daily Report: 09/01/2026
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1. Tested Multi Labelling of data for training, found some error while training the data with testing the subject 23 long ASCII data
2. Updated SVN repository and started creating Model of SVM by using subject 23, with specific features for testing them.
3. Exploring about the visualization function "def offline_seizure_eeg_visualization", Correcting the clarity of the signal by removing the RMS normalization,etc.

Daily Report: 14/01/2026
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1. Committed the changes done in RealTime UI and updated in SVN Repository.
2. Started creating Model of Random Forest classifier for subject "23" using the features such as correaltion time,decorrelation,variance,skewness,etc.. by using Multilabeling method.
3. Testing the trained model using RealTime UI.

Daily Report: 15/01/2026
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1. Creating Model of Random Forest classifier for Subject "22","24" with some specific features, long data files, 1 for testing.
2. Testing the Model in Real-Time, analyzing the data and events locations, for better indexing.
3. Prepared a content for brochure creation of Seizure Detection and prediction.

Daily Report: 16/01/2026
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1. Creating Random Forest Model for subject "23" with long files of ictal and inter-ictal, specific features, and
Tested it with Real-time UI checking the detection and prediction results and again marking index of events changing and creating models
2. Created SVM model for the subject "23" and tested in RealtimeUI.

Daily Report: 20/01/2026
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1. Creating the Model for subject "24" in Random Forest classifier, with long data, 672 seconds of ictal index with balanced inter ictal, training accuracy is 85.39%.
2. Testing it with Real Time UI, and ictal detection is high(wrong detection also), lesser inter ictal identification.
3. Creating a spreadsheet document for updating the training/testing informations for the later use.

Daily Report: 21/01/2026
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1. Correcting the issue of "the summary result writing indexes are not correct".
2. Corrected the summary result writing index coming incorrect order for ASCII formatted data, not in second wise index, but in framewise indexing.
3. Fixed the hyperlinks that leads to particular eeg data plotting

Daily Report: 23/01/2026
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1. Marking the inter-ictal indices with ignored spikes areas in "subject 24" data file, for training the Model in Random forest and for improving the accuracy.
2. Correcting the problem of incorrect indices of ASCII formatted data's summary.
for rewrite the full ASCII summary portion to use this list exactly like EDF so the summary indices will now be correct while preserving skipped events logic.
3. Updated the SVN repository for training the model by additionally adding spikes from the data.

Daily Report: 27/01/2026
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1. Trained a Random Forest Model by using Subject"24" data, with added spikes marking, added the event spikes while training the data. Got the training accuracy 89.87%
2. Testing the model in Real -time and adding the results into the spreadsheet.
3. Saving the result screenshots into the respective folders where the models stored. updating the reports of testing results.

Daily Report: 02/02/2026
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1. Updated the SVN Repository and committed the works done in correction of hyperlinks of summary box for the eeg data and all.
2. Training the model in Random Forest classifier for the subject "25" and marked the indexes for the data for doing training.
3. Trained the Model for RF and got 83.99 % of training accuracy.

Daily Report: 04/02/2026
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1. Training the model in Random Forest classifier for the subject "25" and inter-ictal added from the same file, no spike added..
2. Preparing the test result report(spreadsheet) of each subjects with training and testing details, the seizure onset information, etc..

Daily Report: 06/02/2026
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1. Trained the subject "26" data by using Random Forest classifier, with marked 4 ictal file for training and 1 ictal file for testing.
2. Marked the events indices and inter ictal taken from the same ictal file and got training accuracy of 83.74%.
3. Testing the "23" subject model with each ictal files and updating the testing report spreadsheet.

Daily Report: 09/02/2026
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1. Tested the models created for subject 23 and Updated the subject "23" data test results for two models in spreadsheet with added the training and test data testing information.
2. Testing the subject "24" data with model having separate interictal file, then the model with interictal on the same file, and updating the test results into test report spreadsheet.
3. Saving the screenshots of the results into folder as well as in the report also..

Daily Report: 10/02/2026
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1. Completed the test report creation for subject 23,24 and updated the analysis result.
2. Testing the subject 26 Model with interictal on same file, and updating the test analysis report of each trained data individually.

Daily Report: 13/02/2026
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1. Started testing the model of subject "25" with interictal marked on same file, but the ictal detection is high and accuracy of training is 83.99%. Added the test report on spreadsheet.
2. Created new model for subject "25" with interictal from seperate file and interictal identification is high and accuracy of training is 86.44% . Updating the report as well.
3. Created a model for handling the problems of detection switched the training data for teach model with good pattern and got training accuracy 95.36%.

Daily Report: 16/02/2026
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1. Creating Model for subject 26 with Random Forest classifier, interictal on same file with marked events such as ictal, preictal,postictal,.. got training accuracy 83.74%.
2. Adding test report of the results into the spreadsheet with screenshots.
3. Creating Model for subject 26 with Random Forest classifier , interictal from different file of that subject as well.

Daily Report: 17/02/2026
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1. Adding results of the model created for subject "26" with Random Forest classifier , interictal from different file of that subject into the spreadsheet. Got training accuracy of 82.73%.
2. Creating another model for subject "26' with adjusted interictal marking from the same file of ictal[100s-240s etc..]got the training accuracy of 83.91%.
3. Attended the "Hindi Workshop".

Daily Report: 18/02/2026
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1. Adding the test result of model created for subject "26" into the spreadsheet and completed the 3 models updations
by testing each 4 training data individually as well the test data which is not included for training.
2. Attended the second day of "Hindi Workshop" Meeting.

Daily Report: 19/02/2026
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1. Testing interictal files of model of "23" and adding the comparison with MatLab.
2. Adding the test report into spreadsheet. all remaining interictal files of 25 th subject by using 3 models.

Daily Report: 23/02/2026
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1. Implementing the Postprocessing method for Continuity check of events for seizure detection and prediction.
2. Creating a function for checking the each classifier results comes, then checking the consecutively three times an event coming from the result variable,
it will suddenly passing to the scatter function for plotting the event into the graph.

Daily Report: 26/02/2026
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1. Successfully completed the task of implementation of "evaluation of continuity " for events, postprocessing method.
2. Added the hover and event describer feature for the postprocessing wise graph.
3. Attending Course of "cyber security awareness for employees" through CAKES.

Daily Report: 27/02/2026
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1. Completed the Karmayogi courses
2. Attended Course of "cyber security awareness for employees" through CAKES and completed.
3. Started testing interictal files of 23 subject's data with corrected postprocessing method. Updating the result into the test report.

Daily Report: 02/03/2026
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1. Testing the interictal files of 25,26 subjects with each subject's models which includes interictal from same file as well as from other files. and adding the results into the spreadsheets.
2. Found 23 subject's result is much better and got interictal and ictal detection correctly for each models.
3. Added the works done for implementing the Evaluation of continuity technique( postprocessing methods )and committed the functions into the SVN Repository.

Daily Report: 06/03/2026
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1. Creating A Model for subject "27" with Random Forest Classifier, inter ictal events are taken from the ictal files itself and got the training accuracy of 80.04%.
2. Testing the model created with all training, testing and interictal data files individually in realtime UI and output analysis report is updating into the Spreadsheet.

Daily Report: 07/03/2026
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1. Creating A Model for subject "27" with Random Forest Classifier, inter ictal events are taken from the ictal files itself and got the training accuracy of 75.41%.
2. Updating the results of testing each individual files used for training as well as not included for training(testing), and interictal files, in realtime ui,
and found the model detecting the ictal event well, fault detection reduced compared to the first model.

Daily Report: 09/03/2026
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1. Creating a document for the overall test report of seizure detection and Prediction system.
2. Updating the summary report of all the subjects 23,25,26 and 27 into the document.
3. Started exploring the papers and currently existing softwares for seizure detection and prediction.

Daily Report: 10/03/2026
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1. Testing the subject 24 Models with the interictal files individually. Updating the analysis result into the overall test report.
2. Referring the IEEE paper on the topic "AI-Enabled Epileptic Seizure Detection and Prediction System using Random Forest and LightGBM in Internet of Healthcare Things (IoHT)"

Daily Report: 11/03/2026
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1. Created a separate overall report of all subjects test report of seizure detection and Prediction.
2. Meeting of HTG connect about the content creation of web platform.
3. Created the content of "about of Health tech connect" add into the web platform.

Daily Report: 13/03/2026
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1. Referring an IEEE paper on the topic on "An Epileptic Seizure Detection System based on Mediapipe and Deep Learning-2024".
2. Exploring the methodology used, literature reviews, advantages and limitations of the proposed system.
3. Noting the overall idea of the paper into a document for future reference.

Daily Report: 16/03/2026
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1. Exploring the IEEE paper on the topic of "Epileptic Seizure Prediction Using Machine Learning Techniques on Real-Time EEG Signals-2021".
2. Done the HTG connect event management and technical support for the event(session) conduct on the topic of " Real-Time Surveillance for Disease Outbreaks.”
3. Created a dataset folder which contains all the subjects long ASCII data for creating generalized model for seizure detection and prediction.
Parallely doing the preparation of making abstract of the paper writing.

Daily Report: 18/03/2026
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1. Trained a new model with combined all subject's data set for generalizing model for identifying events of all subjects data, got training accuracy of 83.24% by using Random Forest classifier.
2. Created an XL sheet report for updating the training model information.
3. Started writing the draft abstract for Main Paper of Seizure detection and Prediction system.

Daily Report: 23/03/2026
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1. Prepared a documents for noted errors, spelling mistakes and suggestions on the paper for review "DEEP LEARNING MODEL FOR ICTAL EPILEPSY USING BRAIN
SIGNALS".
2. Started Testing the generalized model created with all the subjects data, tested the subject 23 data's ictal and interictal files and updating the result into the test report.
3. Creating contents for the HTG connect web application, collected event past event photos, the purpose of the event, all the information about the event into a doc.

Daily Report: 24/03/2026
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1. Testing the generalized model with all the ictal and interictal files of subject "24", and updating the results into the test report.
2. Similarly Testing the subject "25" data's interictal and ictal files analyzing and updating it into test report.
3. Parallely getting ideas for writing the abstract of the paper on seizure detection and prediction.