BMI

daily activity - 26/09/2023
---------------------------------------****
> Explored one hot encoding
> Offline Post processing tested.
-> modification in test report

Dhanya MR wrote in #note-2:

25/09/2023

• -------------------------------------------------*
  Implement the code with feature extraction for ML/DL and without feature extraction for DL
  Updated and tested the application.

Dhanya MR wrote in #note-3:

daily activity - 26/09/2023
---------------------------------------****

> Explored one hot encoding
> Offline Post processing tested.
-> modification in test report

daily activity - 26/09/2023
---------------------------------------****

Explored one hot encoding
Offline Post processing tested.
modification in test report

25/09/2023

• -------------------------------------------------*

>Implement the code with feature extraction for ML/DL and without feature extraction for DL
>Updated and tested the application.

• -------------------------------------------------*

Implement the code with feature extraction for ML/DL and without feature extraction for DL
Updated and tested the application.

Dhanya MR wrote in #note-3:

daily activity - 26/09/2023
---------------------------------------****
> Explored one hot encoding
> Offline Post processing tested.
-> modification in test report

25/09/2023
-------------------------------------------------*

Implement the code with feature extraction for ML/DL and without feature extraction for DL
Updated and tested the application.

Dhanya MR wrote in #note-6:
daily activity - 26/09/2023
---------------------------------------****

Explored one hot encoding
Offline Post processing tested.
modification in test report

daily activity - 27/09/2023
--------------------------------------------------------***

1.Modified and tested the code for Offline Post processing(individual-final and allfile-merged-final)
2.Label series error solved
3.Data balance issue at the time of testing is solved
4.Tested the Volunteer-V33-256(sampling rate) using random forest
5.Tested the Volunteer-V1-256(sampling rate) using random forest for selected channels

daily activity - 28/09/2023
--------------------------------------------------------***
HOLIDAY

Daily activity - 29/09/2023
-----------------------------------------------------------------------------------------------------------***
1.Discussion with Mani sir about the wrong prediction of class 12 which is not in the training set.
2.Testing of the application : Training data Test and New Data Test for volunteer V1,V3,V5,V15,V17,V19,V33

02/09/2023
--------------------------------------------------------***
HOLIDAY

Daily activity - 03/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Split the dataset using tool then test the application using trained dataset and new data set for all channel and selected channels for the volunteers V1,V3,V5,V15,V17,V19,V33.
2.Bug found in application and solved.

Dhanya MR wrote in #note-14:

02/10/2023
--------------------------------------------------------***
HOLIDAY

Daily activity - 04/10/2023
-----------------------------------------------------------------------------------------------------------***
1..Train and test the volunteers V1,V2,V3, at 4096 sampling rate using channel frame feature protocol for all channels except A1,A2 and FpREF
2.Train and Test SSVP data
3.Split the SSVP dataset using tool then Train and Test using catboost ML model
3.Created result sheet for wavelet transform
4.Explored Machine learning for 2nd PRSG

Daily activity - 05/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Train and test the volunteers V4,V5,V6,V11,V12,V13 at 4096 sampling rate using channel frame feature protocol for all channels except A1,A2 and FpREF
2.Explored Machine learning for 2nd PRSG

Daily activity - 06/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Attended Project Engineer interview.
2.Involved in the discussion about Wavelet module.

Daily activity - 09/10/2023
-----------------------------------------------------------------------------------------------------------***

1.completed and submitted the work report for the year 2023.
2.participated in a meeting regarding PSRG preparation.
3.Analyse the number of classes in the training set revealed an imbalance issue.

Daily activity - 10/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Data collection for s2 and s3 at 256 Hz sampling rate in GMCT

Daily activity - 11/10/2023
-----------------------------------------------------------------------------------------------------------***
1.JSON deserialization bug during the test phase was fixed
2.Developed code to calculate the Test accuracy for Eye open/Eye close.
3.Train and test the volunteers V14,V15,V16,V17,V18,V19 and V20 at 4096 sampling rate using channel frame feature protocol for all channels except A1,A2 and FpREF

Daily activity - 12/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Resolved the bug in the confusion matrix which displays exponential values.
2.Display machine learning plots based on the Enable/Disable ML/DL visualization button.
3.Integration of CNN train module in main application.

Daily activity - 13/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Attended the meeting regarding PSRG II.
2.Train and test channel frame feature completed for 256 sampling rate
3.Prepared discussion points in the meeting

Daily activity - 16/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Train and test completed for Voice Absent 256 sampling rate
2.Completed test report for Voice Absent 256 sampling rate
3.Prepared PPT for classifier module.

Daily activity - 17/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Train and test completed for Voice Absent 4096 sampling rate All channel and selected channels
2.Train and test completed for Voice Absent 256 sampling rate for all volunteer
3.Prepared PPT for classifier module-Random Forest.

Daily activity - 18/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Prepared PPT for classifier module-Random Forest.
2.Train and test completed for Voice Absent 4096 sampling rate All channels for Split method.
3.Presented on the topic random forest classifier

Daily activity - 19/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Prepared word document for classifier module
2.Train and test completed for Voice Absent 4096 sampling rate.
3.Created model for live data testing.
4.Completed test report for Voice Absent 4096 sampling rate

Daily activity - 20/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Train and test voice absent all volunteer at 256 sampling rate
2.Completed test report for voice absent all volunteer at 256 sampling rate for with split and without split case
3.Train and test EC/EO mappining( Va and Vp) for all volunteer at 256 sampling rate without split case
4.Completed test report for EC/EO mappining( Va and Vp) for all volunteer at 256 sampling rate without split case
5. Presentation on various classifiers such as catboost,SVM and K nearest neighbor
6. Discussion with team members about how to create and analyze a work report that covers the training and testing for different cases

21/10/2023 - 24/10/2023
--------------------------------------------------------***
HOLIDAY

25/10/2023 - 27/10/2023
--------------------------------------------------------***
HOLIDAY

25/10/2023 - 27/10/2023
--------------------------------------------------------***
Leave

Daily activity - 30/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Explored how to improve model accuracy in machine learning classifiers
2.Explored hyper parameters of classifiers

Daily activity - 31/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Explored hyper parameters of CatBoost and random forest classifier
2.Explored box constraint in SVM

Daily activity - 31/10/2023
-----------------------------------------------------------------------------------------------------------***
1.Explored technical content related to ML for PRSG
2.Attended second PRSG II

Daily activity - 01/11/2023
-----------------------------------------------------------------------------------------------------------***
1.Explored technical content related to ML for PRSG
2.Attended second PRSG II

Daily activity - 02/11/2023 to 03/11/2023
-----------------------------------------------------------------------------------------------------------***
1.Explored the technical content recommended by by PRSG II

Daily activity - 06/11/2023 to 08/11/2023
-----------------------------------------------------------------------------------------------------------***
1.Involved in MOM document creation by cross checking with recorded audio.
2.Proposal writing on title - Disease screening System: A Path to Mind Body Vitality
3.Participated in the discussion about creation of detailed design document.

Daily activity - 06/11/2023 to 08/11/2023
-----------------------------------------------------------------------------------------------------------***

1.Attended Live prediction demonstration for eye blink detection using an OpenBCI EEG device.
2.Template creation of the proposal "Disease screening System: A Path to Mind Body Vitality" for ethical clearance.

Daily activity - 09/11/2023
-----------------------------------------------------------------------------------------------------------***

1.Attended Live prediction demonstration for eye blink detection using an OpenBCI EEG device.
2.Template creation of the proposal "Disease screening System: A Path to Mind Body Vitality" for ethical clearance.

Daily activity - 10/11/2023
-----------------------------------------------------------------------------------------------------------***
1.Template creation(IRC) of the proposal "Disease screening System: A Path to Mind Body Vitality" for ethical clearance - Completed.

Daily activity - 13/11/2023 to 24/11/2023
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 28/11/2023
-----------------------------------------------------------------------------------------------------------***
1.Participated in discussion about detailed design document.
2.Detailed design document for ML module started.

Daily activity - 29/11/2023
-----------------------------------------------------------------------------------------------------------***
1.Explored epidemy mathematical models
2.Explored epidemy AI models

Daily activity - 30/11/2023
-----------------------------------------------------------------------------------------------------------***
1.Explored on AI in epidemy
2.Presentation on the topic epidemy models

Daily activity - 01/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Participated in the Joining procedure as Project engineer
2.Attended the meeting regarding Epidemy

Daily activity - 04/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Detailed design Documentation of train Ui.
2.Explored the information regarding the proposal Hybrid Multimodal Cyber‑Physical Neuro-Robotics Wheelchair system

Daily activity - 05/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Attended meeting regarding modification Va/Vp/EO/EC mapping
2.Detailed design Document classify module.
3.Demonstration and Discussion of MiME application.

Daily activity - 06/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Preparation of EOI of the proposal Hybrid Multimodal Cyber‑Physical Neuro-Robotics Wheelchair system started.
2.Discussion of UI design of Va/Vp/EO/EC mapping.
3.Discussion of testing of application using deep learning

Daily activity - 07/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Preparation of EOI of the proposal Hybrid Multimodal Cyber‑Physical Neuro-Robotics Wheelchair system -50% completed.

Daily activity - 08/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Preparation of EOI of the proposal Hybrid Multimodal Cyber‑Physical Neuro-Robotics Wheelchair system -completed.
2.Excel sheet creation for ML type I and type II errors

Daily activity - 11/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Modification of EOI of the proposal Hybrid Multimodal Cyber‑Physical Neuro-Robotics Wheelchair system -completed.
2.Explore NSF guidelines for submitting proposal.

Daily activity - 12/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Modification of EOI of the proposal Hybrid Multimodal Cyber‑Physical Neuro-Robotics Wheelchair system -completed.
2.Training of all volunteer raw epoc signal without split case using GRU DL algorithm - Completed

1.Develop display result sheet for the training values using the following metrics 'Total Population', 'Condition Positive (P)',' Condition Negative (N)', Sensitivity, Recall, Hit Rate, or True Positive Rate(TPR)',' Specificity, Selectivity or True Negative Rate (TNR)', 'Type I Error, False Positive Rate (FPR)', Type II Error, False Negative Rate (FNR)', 'Precision or Positive Predictive Value (PPV)', 'False Discovery Rate (FDR)', False Omission Rate (FOR)', 'Positive Likelihood Ratio (LR+)', 'Negative Likelihood Ratio (LR-)', 'Prevalence Threshold (PT)', 'Critical Success Index (CSI)', 'Prevalence', 'Accuracy', 'Balanced Accuracy (BA)', 'F1 Score (Harmonic Mean of PR and RC)', 'Phi Coefficient (φ or rφ) or Matthews correlation coefficient (MCC)', 'Fowlkes-Mallows Index (FM)', 'Informedness (Youdens Index or Receiver Operating Characteristic)', Bookmaker Informedness (BM)', 'Markedness (MK) or DeltaP (Δp)', 'Diagnostic Odds Ratio (DOR)'.Integrated to MIME software.

2.Patient dataset trained using GRU DL algorithm.

3.Discussion on the creation of results sheet for deep learning.

Daily activity - 13/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Develop display result sheet for the training values using the following metrics 'Total Population', 'Condition Positive (P)',' Condition Negative (N)', Sensitivity, Recall, Hit Rate, or True Positive Rate(TPR)',' Specificity, Selectivity or True Negative Rate (TNR)', 'Type I Error, False Positive Rate (FPR)', Type II Error, False Negative Rate (FNR)', 'Precision or Positive Predictive Value (PPV)', 'False Discovery Rate (FDR)', False Omission Rate (FOR)', 'Positive Likelihood Ratio (LR+)', 'Negative Likelihood Ratio (LR-)', 'Prevalence Threshold (PT)', 'Critical Success Index (CSI)', 'Prevalence', 'Accuracy', 'Balanced Accuracy (BA)', 'F1 Score (Harmonic Mean of PR and RC)', 'Phi Coefficient (φ or rφ) or Matthews correlation coefficient (MCC)', 'Fowlkes-Mallows Index (FM)', 'Informedness (Youdens Index or Receiver Operating Characteristic)', Bookmaker Informedness (BM)', 'Markedness (MK) or DeltaP (Δp)', 'Diagnostic Odds Ratio (DOR)'.Integrated to MIME software.

2.Patient dataset trained using GRU DL algorithm.

3.Discussion on the creation of results sheet for deep learning.

Daily activity - 14/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Testing of patient data with 256 sampling rate and 21 channels.
2.EOI preparation with new template-Submitted for verification.
3.Training of balanced patient dataset with 256 sampling rate for 21 channels.
4.Testing of patients - P3,P4,P5,P18 and P23 with 256 sampling rate for 21 channels.

Daily activity - 15/12/2023
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 18/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Modification in the ML part of detailed document(DD).
2.Detected and solved the issue in deep learning with feature conditions at execute pipeline with team member.
3.Involved in discussion of eye blink integration with peak detection.

Daily activity - 19/12/2023
-----------------------------------------------------------------------------------------------------------***
1.ML visualization graphs like classification report, confusion matrix ,statistical report by clicking corresponding buttons.
2.Eye blink integration with ML started.

Daily activity - 20/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Eye blink integration with ML 50% completed
2.Training of balanced patient dataset with 256 sampling rate for 21 channels.

Daily activity - 21/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Eye blink integration with ML 80% completed
2.Found an error in channel wise peak detection.

Daily activity - 22/12/2023
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 26/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Eyeblink Data recording using open BCI
2.Solved Bug in the scatter plot display function.
3.Eyeblink integration with ML and found bug in channel wise peak when text file was loaded.

Daily activity - 27/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Eyeblink Data recording using open BCI
2.Training of Patient data with 250 sampling rate and found bug in training set of random forest classifier.
3.Tried to solve the Nan value issue in random forest classifier

Daily activity - 28/12/2023
-----------------------------------------------------------------------------------------------------------***
1.Found Zero division error in DL and tracked the reason behind it.
2.Eyeblink Data recording using open BCI

Daily activity - 29/12/2023
-----------------------------------------------------------------------------------------------------------***
leave

Daily activity - 1/1/2024
-----------------------------------------------------------------------------------------------------------***
1.Attended new year celebration function
2.Did modification in detailed design document
3.Identified and tracked the issue related to Nan Value.

Daily activity - 2/1/2024
-----------------------------------------------------------------------------------------------------------***
1.identified the feature producing nan vale
2.Eyeblink integration with ML

Daily activity - 3/1/2024 - 5/1/2024
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 8/1/2024
-----------------------------------------------------------------------------------------------------------***
1.Exploring Analysis of EEG Microstates as Biomarkers in Neuropsychological processes -Review paper
2.implemtation of XG boost classifier

Daily activity - 9/1/2024
-----------------------------------------------------------------------------------------------------------***
1.Implemtation of XG boost classifier - 100% completed
2.Integration of CNN in mime pipeline
3.Exploring review paper " Analysis of EEG Microstates as Biomarkers in Neuropsychological processes "

Daily activity - 10/1/2024
-----------------------------------------------------------------------------------------------------------***
1.Modified the test plan excel sheet for ML and sent for verification.
2.Disscussion with team member about the review paper " Analysis of EEG Microstates as Biomarkers in Neuropsychological processes ".

Daily activity - 11/1/2024 - 12/1/2024
-----------------------------------------------------------------------------------------------------------***
1.Tried to test live eye blink prediction with rashmi but system was not working properly.
2.Debug the live prediction code with rashmi for display the blink list in real time UI.
3.Exploring review paper " Analysis of EEG Microstates as Biomarkers in Neuropsychological processes "

Daily activity - 15/1/2024 - 16/1/2024
-----------------------------------------------------------------------------------------------------------***

1.Disscussed and tried to implement enable beep logic for eyeblink with team member but its not working as per requirement.
2.Review meeting with PL and PM on inner speech, Eye blink and SSVEP.
3.Modified test plan excel sheet as per requirement.
4.Started ML testing using XGBoost classifier but shows IndexError: index 21 is out of bounds for axis 1 with size 21 in feature pipeline.
5.Exploring review paper " Analysis of EEG Microstates as Biomarkers in Neuropsychological processes "

Daily activity - 17/1/2024 - 19/1/2024
-----------------------------------------------------------------------------------------------------------***
1.Fixed the bugg in the integration of Eyeblink visualization.
2.Testing of all patient data using split method.
3.Debugg test case for CNN DL algorithm based on images.
4.Fixed the index error in channel selection.

Daily activity - 22/1/2024 - 24/1/2024
-----------------------------------------------------------------------------------------------------------***

1. Resolved Json and various variables issues that occurred in the MiME application.
2. Trained and Tested with XGBoost ML using epoched EEG Signals data.
3. Checked and verified the V256 EEG Signals data collected from the Natus Device for workshop.
4. A Machine Learning Demo procedure setup was drafted.

Daily activity - 25/1/2024
-----------------------------------------------------------------------------------------------------------***

1. Completed the ML demo setup on the laptop .
2. Attended knowledge transfer session of Demo Workflow
3. Learned the basics of Drishti project

Daily activity - 26/1/2024
-----------------------------------------------------------------------------------------------------------***
1. Prepared Script for Drishti project for workshop.
2. Learned the basics software part of Drishti project.
3. Arranged the dataset for memo and setup application for Demo.
4. Explained basics of BMI and demonstrated our application to Dhanyasree, Jiji and Team.

Daily activity - 29/1/2024 30/1/2024
----------------------------------------------------------------------------------------------------------***
1. Attended Digital Dentistry and Oral Health Workshop and Product Expo at C-DAC, Technopark.

Daily activity - 31/1/2024
-----------------------------------------------------------------------------------------------------------***

1.Exploring Analysis of EEG Microstates as Biomarkers in Neuropsychological processes -Review paper
2.Explored microstate A,B,C and D
2.Explored spatial and temporal characteristics of distinct EEG microstates

Daily activity - 29/1/2024 to 30/1/2024
----------------------------------------------------------------------------------------------------------***
1. Attended Digital Dentistry and Oral Health Workshop and Product Expo at C-DAC, Technopark.

Daily activity - 31/1/2024
-----------------------------------------------------------------------------------------------------------***

1.Exploring Analysis of EEG Microstates as Biomarkers in Neuropsychological processes -Review paper
2.Explored microstate A,B,C and D
2.Explored spatial and temporal characteristics of distinct EEG microstates

Daily activity - 1/2/2024
-----------------------------------------------------------------------------------------------------------***
Explored the paper "A Lightweight Neural Network with Multiscale Feature Enhancement for Liver CT Segmentation"

Daily activity - 2/2/2024
-----------------------------------------------------------------------------------------------------------***
1.Explored the paper "Perspectives on the technological aspects and biomedical applications of Virus-like-particles/ Nanoparticles in reproductive biology: Insights on the medicinal and
toxicological outlook"
2.wrote an answer in the abstract to the question "contribution is missing" for the review paper

Daily activity - 5/2/2024
-----------------------------------------------------------------------------------------------------------***
1.wrote an answer in the introduction part to the question "aim of the was missing " for the review paper
2.wrote an answer to the query "inclusion and exclusion criteria are very limited"
3.Elaborated disscussion section.

Daily activity - 6/2/2024 - 8/2/2024
-----------------------------------------------------------------------------------------------------------***
1.Answered all comments of reviewer related to microstate review paper.
2.Created revised Manuscript Clean analysis of EEG Microstates review paper.
3.Created Revised manuscript with highlights of EEG Microstates review paper.
4.Completed tasks related to the microstate review paper and submitted verification to PL.
5.Participated in a meeting related to the technical talk with BMI team members.

Daily activity - 9/2/2024
-----------------------------------------------------------------------------------------------------------***
Explored AI assisted Screening of Cognitive Decline/Dementia using Quantitative EEG analysis for submit proposal to ICMR.

Daily activity - 12/2/2024
-----------------------------------------------------------------------------------------------------------***
Attended an ISO 13485 certification class.

Daily activity - 13/2/2024
-----------------------------------------------------------------------------------------------------------***
Attended an ISO 13485 certification class.

Daily activity - 14/2/2024
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 15/2/2024
-----------------------------------------------------------------------------------------------------------***
1.Disscussion with PL about ISO 13485
2.Review meeting with PL about channel selection for inner speech.
3.PPT for ML-Inner speech ongoing

Daily activity - 16/02/2024
-----------------------------------------------------------------------------------------------------------***

1.Revised the test plan in accordance with the feedback provided during the meeting .
2.Train ML random forest algorithm with channels FP1,Fp2,F3,F4,F7,F8,T3,T4,T5,T6,C3,C4,P3,P4 at 250 sampling rate
3.Test ML random forest algorithm with channels FP1,Fp2,F3,F4,F7,F8,T3,T4,T5,T6,C3,C4,P3,P4 at 250 sampling rate
4.Explored Singular Value Decomposition (SVD) technique

Daily activity - 19/02/2024
-----------------------------------------------------------------------------------------------------------***

1.Setup patient data offline testing using random forest classifier
2.Tested live prediction of inner speech using the OpenBCI device. Encountered an issue during the testing phase.
3.Made modifications to the PowerPoint presentation for the BMI workshop

Daily activity - 20/02/2024
-----------------------------------------------------------------------------------------------------------***
1.Participated in an ISO internal audit for the BMI project.
2.Debugged live inner speech code to address issues with text message and audio alert functionality.
3.Modified the DDD of the BMI project and sent it to the PL for verification.
4.Modified the SRS of the BMI project and sent it to the PL for verification.

Daily activity - 21/02/2024 - 23/02/2024
-----------------------------------------------------------------------------------------------------------***
1.Presented PPT for technical talk to the team
2.Modified the PPT for technical talk based on the suggestion's from the PLs and sent for verification

Daily activity - 26/02/2024 - 01/03/2024
-----------------------------------------------------------------------------------------------------------***

1.Conducted training and testing of patient data using Random Forest, SVM, KNN, and CatBoost algorithms.
2.Tabulated and analyzed the test results.
3.Revised the PowerPoint presentation by incorporating hardware details.
4.Updated the PowerPoint presentation to include SSVEP details.
5.Demo setup for the inner speech-based mime software.
6.Explored various machine learning approaches.
7.Engaged in activities related to technical talks.
8.Participated in discussions with Suresh Devasahayam sir regarding the BMI project.
9.Participated in technical talk on the topic sensors and instrumentation in human machine interfaces

Daily activity - 04/03/2024
-----------------------------------------------------------------------------------------------------------***
1.Attended a meeting with PL and team members
2.Exploring IEEE transaction paper related with inner speech and ML.

Daily activity - 05/03/2024 13/03/2024
----------------------------------------------------------------------------------------------------------***
1.Explored the paper "Can Machine Learning Algorithms Classify Inner Speech from EEG Brain Signals?"
2.Explored the paper "Inner speech classification based on electroencephalography (EEG) signals and support vector machine (SVM)"
3.Explored the paper "Optimized Rational Dilation Wavelet Transform for Automatic Imagined Speech Recognition"
4.Explored the paper "Interpreting Imagined Speech Waves with Machine Learning techniques"
5.Started to write a journal paper related to inner speech based on machine learning techniques
6.Explored IEEE guidelines.
7.Attended meeting regarding IEEE guidelines presented by Deepu SS.
8.Prepared part I of the proposal liver cirrhosis .
9.Registered a motherboard-related issue with HP support and followed up until it was resolved by their representative visiting to address the problem
10.Installed MS office and renew license in 3 computers

Daily activity - 14/03/2024
-----------------------------------------------------------------------------------------------------------***
1.Introduction part of the journal paper related with inner speech based on machine learning techniques completed- 60%
2.Attended technical talk presented by Khushboo Srivastava ONELearning

Daily activity - 15/03/2024
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 18/03/2024
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 19/03/2024
-----------------------------------------------------------------------------------------------------------***
1.Introduction part of the journal paper related with inner speech based on machine learning techniques completed
2.Methodology part of the journal paper related with inner speech based on machine learning techniques started- 40% completed
3.Learn about the classification of words in detail from the study "Decoding Inner Speech Using Electrocorticography: Progress and Challenges Towards a Speech Prosthesis"

Daily activity - 20/03/2024
-----------------------------------------------------------------------------------------------------------***
wrote methodology part of the journal paper related with inner speech based on machine learning techniques-50% completed

Daily activity - 21/03/2024
-----------------------------------------------------------------------------------------------------------***

1.Modified introduction part of the journal paper related with inner speech based on machine learning techniques
2.Methodology part of the journal paper related with inner speech based on machine learning techniques-Ongoing
3.Tried to train the balanced patient data with 30 epoch ,but shows an error in feature extraction part

Daily activity - 25/03/2024
-----------------------------------------------------------------------------------------------------------***
1.Started to prepare abstract of journal paper related with inner speech based on machine learning technique
2.Started to create workflow slide of BMI project

Daily activity - 26/03/2024
-----------------------------------------------------------------------------------------------------------***
1.Completed workflow diagram using EdrawMax tool
2.Train the data using wavelet features, detect a bug in the feature area, and unable to identify the specific problematic feature.

Daily activity - 27/03/2024
-----------------------------------------------------------------------------------------------------------***
1.Methodology part of the journal paper related with inner speech based on machine learning techniques completed
2.Train the volunteer dataset using Mean(TD),Variance(TD),Kurtosis(TD),Skewness(TD),Median(TD),Energy(TD),Phase Lock Value(TD),Cross Correlation(TD),Decorrelation Time(TD),Standard Deviation(TD)

Daily activity - 28/03/2024
-----------------------------------------------------------------------------------------------------------***
1.Abstract of the journal paper completed.
2.The results section of the journal paper is currently in progress.

Daily activity - 1/04/2024
-----------------------------------------------------------------------------------------------------------***
1.Analyzing F1 score, Precision and accuracy for the journal paper
2.Train the volunteer data and tabulating the result for the journal paper
3.Attended meeting with PL regarding K-Means and DBSCAN

Daily activity - 2/04/2024
-----------------------------------------------------------------------------------------------------------***
Absent

Daily activity - 3/04/2024
-----------------------------------------------------------------------------------------------------------***
1.Attended the meeting with PL and Team members about singular value decomposition
2.The results section of the journal paper is currently in progress.

Daily activity (04/04/2024 - 05/04/2024 )
-----------------------------------------------------------------------------------------------------------***
1.Trained a random forest classifier separately for each of the volunteers V1 ,V2, V3, V15, V18, and V19 and created a table
2.Trained a SVM classifier separately for each of the volunteers V1 , V3, V15 and V19
3.Created a PowerPoint presentation and delivered a discussion on the random forest classifier in the presence of the project leader and team members
4.Examining the outcomes of the machine learning output

Daily activity (08/04/2024 - 09/04/2024 )
-----------------------------------------------------------------------------------------------------------***
1.write-up on the topic of inner speech and machine learning in progress
2.prepared Demo set for inner speech is ready and presented to the team members
3.Created folder structure for inner speech ML demo

Daily activity (11/04/2024 - 12/04/2024 )
-----------------------------------------------------------------------------------------------------------***
1.Video recorded for inner speech ML approach
2.write-up on the topic of inner speech and machine learning completed and send to PL
3.Discussion area of the paper related to ML approach in progress

Daily activity (15/04/2024 - 16/04/2024 )
-----------------------------------------------------------------------------------------------------------***
Leave

Daily activity - 17/04/2024
-----------------------------------------------------------------------------------------------------------***
1.Explored information required for conference sponsorship
2.Changed color of MiME(MindMe) to yellow instructed by PL and updated in svn .
3.Explored CMT site request
4.Trained volunteer dataset -V!8,V19 using SVM ML Algorithm and tabulated the result

Daily activity - 18/04/2024
-----------------------------------------------------------------------------------------------------------***
1.Trained volunteer dataset -V1,V2 using Catboost and tabulated the result
2.Currently in progress: Developing a separate module Classify and EventIdentify for the Delhi team

Daily activity - 19/04/2024
-----------------------------------------------------------------------------------------------------------***
1.Developing a separate module Classify and EventIdentify for the Delhi team -70% completed
2.Trained volunteer dataset -V3 using Catboost and tabulated the result

Daily activity - 22/04/2024 23/04/2024
----------------------------------------------------------------------------------------------------------***
1.Converted the .py file of the MindMelite application into a .exe file
2.Solving the issue with the .exe file: after double-clicking the converted icon, it disappears shortly thereafter.

.

Daily activity - 24/04/2024
----------------------------------------------------------------------------------------------------------***
The problem with the .exe file has been resolved: it no longer disappears shortly after being double-clicked.

Daily activity - 25/04/2024
----------------------------------------------------------------------------------------------------------***
An .exe file has been generated for the MindMeLite application.

Daily activity - 29/04/2024
----------------------------------------------------------------------------------------------------------***
1.Participated in an OrCAD training session.
2.Tried to input data path, sampling rate, window size, and model path for the .exe file, but it ended with exit code 1.
3.Attended a presentation on the topic epidemic model by prasidh

Daily activity - 30/04/2024
----------------------------------------------------------------------------------------------------------***
Exploring conversion python module to API

Daily activity - (01/05/2024 - 03/05/2024)
----------------------------------------------------------------------------------------------------------***

1.Updated the monthly progress report.
2.Shared and explained ML based train and test result of patient and volunteer dataset for journal paper to archana
3.Exploring conversion python module to API

Daily activity - (06/05/2024 - 07/05/2024)
----------------------------------------------------------------------------------------------------------***
Python Package or API generation for integrating CDAC T software module with web based application of CDAC Delhi-80% completed

Daily activity - (08/05/2024 - 10/05/2024)
----------------------------------------------------------------------------------------------------------***
Python Package or API generation for integrating CDAC T software module with web based application of CDAC Delhi

Daily activity - 07/06/2024
----------------------------------------------------------------------------------------------------------***
Revised the content of the journal paper about machine learning.

Daily activity - 25/06/2024
----------------------------------------------------------------------------------------------------------***
1.Attended a meeting with the Delhi BMI team regarding tasks to be completed for the upcoming PRSG.
2.Shared the channels that we are currently using for EEG signal recording with Delhi team members.
3.Uploaded a new set of balanced training datasets, each containing 80 epochs.
4.Added equations related to features in the journal paper.
5.Included more references in the journal paper.

Daily activity - 26/06/2024-28/06/2024
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1.Presented the basics of non-linear signals to the team members.
2.Attended a knowledge-sharing session by the team members.
3.Created a table comparing different classifiers based on results such as accuracy, F1 score, precision, and recall.
4.Checked the dataset and uploaded the testing dataset to the HTG share.
5.Trained and tested a newly developed event selection module using patient data.
6.Created PPT for presentation for the topic volterra series

Daily activity - 01/07/2024-02/07/2024
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1.Integrated the SMOTE-Tomek method into classifier training and updated in SVN repository.
2.Presented the basics of Volterra series to team members.
3.Trained a Random Forest model with the SMOTE-Tomek method.

Daily activity - 03/07/2024
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1.Took over deep learning work from Kausalya.
2.Tabulated the results including average accuracy and the average of classification matrix.
3.Analyzed the results and updated the analysis in the journal paper.

Daily activity - 04/07/2024
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1.Explored the disscussion part of an ML based inner speech journal paper
2.Modifying the result part of journal paper

Daily activity - 04/07/2024
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Leave

Daily activity - 05/07/2024
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1.Explored the discussion part of an ML based inner speech journal paper
2.Modifying the result part of journal paper

Daily activity - 08/07/2024
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Developing python code for Exclude training dataset for new data testing - 50% completed

Daily activity - 09/07/2024 to 09/07/2024
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1.Developing python code for Exclude training dataset for new data testing - 80% completed
2.Attended webinar on topic "ESSENTIAL SIGNAL PROCESSING FOR BRAINMACHINE INTERFACES"

Daily activity - 09/07/2024 to 10/07/2024
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1.Developing python code for Exclude training dataset for new data testing - 80% completed
2.Attended webinar on topic "ESSENTIAL SIGNAL PROCESSING FOR BRAINMACHINE INTERFACES"

Daily activity 11/07/2024 to 12/07/2024
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1.Developed python code for Exclude training dataset for new data testing - 100% completed
2.Tested the normal method and exclude train data method.

Daily activity - 22/07/2024 to 23/07/2024
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1.Modified the module for exclude trained data selection as per the suggestion by PL.
2.integrated the Event selection module in execute pipeline
3.Tested the exclude trained data method and event selection method-working perfectly
4.Developed the code for both exclude trained data selection and event selection enabled at a time

Daily activity - 24/07/2024
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1.Fixed warning related to pickle()
2.Trained and tested 350 Epoch Balanced data - error occurred due to different sampling rate
3.Trained and tested 350 Epoch Balanced data - error occurred due empty files

Daily activity - 25/07/2024
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1.Implemented the code for display the Seizure events in python file such as postproceesing,RealtimeUi,executepipeline
2.Traine and tested balanced 80 Epoch 250 SR

Daily activity - 26/07/2024
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1.Designed, Implemented and integrated Smote-Tomek package for imbalanced classification in Mime Application
2.Train and tested SVM, Random Forest classifier using Smote-Tomek method
3.created an Excel sheet for the test plan for the upcoming PRSG.

Daily activity - 29/07/2024-30/07/2024
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1.Trained and tested the random forest classifier using Random Forest, SVM, and CatBoost classifier – Shows NaN value error.
2.Implemented the SimpleImputer package to handle NaN values in the classifiertrain.py and classify.py modules of the Mime application -resolved the Nan value error.
3.Verified all patient and volunteer data at a 250 sampling rate to check for any occurrences of 0 KB data.
4.Removed the 29 and 30 event datasets from the 350 balanced Epoch folder, which contained events 2, 7, 8, 10, and 12.

Daily activity - 01/08/2024-02/08/2024
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1.Attended presentation on the topic Hadoop
2.Participated in an online demo of the EEG device Axxonet.
3.Increased the display size and font size for individual results and the final result in the displayclassifier.py module.
4.Checked 29 and 30 events present in the balanced 350 epoch Data

Daily activity - 05/08/2024-06/08/2024
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1.Presented training and testing procedure of Mime application to the newly joined team members
2.Attended a presentation on the simulator module.
3.Setup offline demo of Mime application based on inner speech dataset

Daily activity - 07/08/2024
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1.Resolved issue related to accuracy is showing different in console and train accuracy pop up
2.Modified the color theme of Mime UI version -2

Daily activity - 0/08/2024
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Leave

Daily activity - 12/08/2024-14/08/2024
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Designed and developed the Train UI- including the General Settings, Data Selection, and AI Technique sections for MiMe application version 3.

Daily activity - 16/08/2024
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Designed and developed the Test UI - including the AI Technique and Post Processing sections for MiMe application version 3.

Daily activity - 19/08/2024 20/08/2024
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1.Designed and developed EEG signal Ui for EEG signal (Inner speech, Eyeblink, SSVEP, Seizure) input data selection for training
2.Designed and developed EEG signal Ui for EEG signal (Inner speech, Eyeblink, SSVEP, Seizure) input data selection for testing

Daily activity - 19/08/2024 - 20/08/2024
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1.Designed and developed EEG signal Ui for EEG signal (Inner speech, Eyeblink, SSVEP, Seizure) input data selection for training
2.Designed and developed EEG signal Ui for EEG signal (Inner speech, Eyeblink, SSVEP, Seizure) input data selection for testing

Daily activity - 21/08/2024 - 22/08/2024
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1.Implemented placeholder text in the General Settings section under Testing.
2.Redesigned and developed the AI Techniques section under Testing.
3.Fixed alignment issues with buttons and label frames in the UI.
4.Presented the latest UI version of the MiMe application.

Daily activity - 23/08/2024 - 24/08/2024
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Modified Feature UI in training portion

Daily activity - 25/08/2024 - 27/08/2024
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holiday

Daily activity - 28/08/2024
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1.Attended GOT training in bigdata and data science
2.Discussion with PL about the modification in UI like Eye blink Testing tool, general settings, more settings in data under training portion of UI

Daily activity - 29/08/2024
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1.Attended GOT training in bigdata and data science
2.Prepared writeup for annual performance review for the year 2024
3.Modified alignment of preprocessing portion under training UI

Daily activity - 30/08/2024
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1.Attended GOT training in bigdata and data science.
2.Updated train general settings by giving provision for save the configuration file for all parameters entered in the train UI.
3.Modified data selection by adding detection and prediction options in the Seizure data selection.
4.Modified and submitted write up for annual performance review.

Daily activity - 02/09/2024
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1.Attended GOT training in bigdata and data science.
2.Added more settings options in EEG UI under TrainUi
3.Added Extract feature only, Extract feature to ML/DL in feature portion under Traininui

Daily activity - 03/09/2024-05/09/2024
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1.Added EEG display options in Train Ui for seizure prediction
2.Discussion with PL and team members about postprocessing of seizure prediction
3.Designed,developed and integrated result ui display and saving result
4.Added decision making and event alert Type option in post processing under Test portion

Daily activity - 06/09/2024
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1.Integration of trainui with execute pipeline is started
2.Involved in the seizure prediction integration related with bar chart creation

Daily activity - 09/09/2024 - 10/09/2024
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1.Attended GOT training in bigdata and data science.
2.Attended annual performance review of year 2024
3.Integration of modules of MiME v2 to MiME V3

Daily activity - 11/09/2024 - 12/09/2024
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1.Participated in the assessment test for the GOT training in big data and data science.
2.Completed the creation and update of configuration files in MiME version 3.
3.Included individual JSON files, such as EEGsignalUIParameters_json, waveletJson, saveOption_json, filters_json, classifier_json, and Visualization_json, in the configuration_json.
4.Added write to disk functionality in preprocessing
5.Integrated visualization functionality in train ai technique
6.UPdated gl.settings_json in execute pipeline, preprocessing, feature extraction, classifier train

Daily activity - 13/09/2024
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1.Configuration Json updated based on testing conditions
2.Updated individual JSON files, such as EEGsignalUIParameters_json, waveletJson, saveOption_json, filters_json, classifier_json, and Visualization_json bsased on the testing condition
3.Updated gl.settings_json in execute pipeline
4.Integration of Training and testing completed and updated in svn

Daily activity - 23/09/2024 - 27/09/2024
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1.Attended meeting with Delhi team about upcoming PRSG meeting
2.Attened Demo of EEG device by Axxonet at GMCT
3.Presented Delhi team how to run MiME lite and MiME V2
4.Discussion with team members about the integration of progressbar in MiME V3\
5.Modifed Feature UI by creating single block for Extract feature ml?dl and extract feature only
6.Modified testEEGsignal UI by creating option for Exclude trained files or events
7.Modified post processing UI by creating option for threshold method

Daily activity - 30/09/2024 - 4/10/2024
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1.Created monthly report and sent to PL
2.Enable and disable the test and train UI based on button action-50% completed
3.Created test report of inner speech using ML for the technical talk and updated in ppt
4.Training and testing of LSTM Deep learning model

Daily activity - 7/09/2024 - 11/10/2024
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1.Solved graphs alignment and font issue in Dl graphs such as Scatter plot, histogram , confusion matrix, validation loss and accuracy plot, Training and validation learning curve, Evaluation matrix, ROC and AUC curve, classification report
2.Solved graphs alignment and font issue in ML graphs such as Scatter plot, histogram, confusion matrix, Evaluation matrix, classification report
3.Resolved the resolution error while open the application in Laptop

Daily activity - 14/09/2024 - 18/10/2024
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1.Fixed the error: "pandas.errors.InvalidIndexError: Reindexing only valid with uniquely valued Index objects."
2.Resolved the audio alert issue related to event notifications.
3.Debugged and identified the cause of an error in the seizure progress bar code.
4.Attended the UN-IATF award function at the amphitheater.
5.Traineded the Deep Learning Artificial Neural Network (DL ANN) model.
6.Verified the functionality of all machine learning models.
7.Beautification of all pop up UI of MiMe v3.
8.Created a dataset and model for a demo on my laptop for a technical talk.
9.fixed TypeError: the JSON object must be str, bytes or bytearray, not dict
10.Reduced the fond size and aligned display classifier result sheet
11.Fixed the error related to resampling

Daily activity - 22/10/2024
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1.Training of LSTM dl model using 400 epochs balanced data-Automatically exit the code
2.Training of LSTM dl model using patient data balanced data-got accuracy of 57 % for training and for testing 27%
3.Modified the train and test UI by enabling the currently active button

Daily activity - 23/10/2024
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1.Testing of filters such as notch filter,bpf,Bsf,lpf,hpf,gaussian filter,normalization.detrending.baseline correction and savizky-golay filter
2.Introduced scroolbar on filterbasic ui
3.Beatification of result ui progress
4.solved the error while uploading ssvep data for ann algoritham

Daily activity - 24/10/2024
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1.Beatification of resultui is completed
2.Created ppt for inner speech
3.Discussed the errors while browsing image data-pending.
4.Identified the cause of the error related to resample_json = json.loads(gl.resamplingJson)

Daily activity - 25/10/2024
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1.Modified EEG signal Ui like alignment and font adjustment
2.Modified exclude trained data like alignment and font adjustment
3.Modification testsignal Ui-pending
4.Scrollbars implementation for both the EEG UI and Test EEG UI are pending

Daily activity - 28/10/2024
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1.Modified testEEGUI and updated it in SVN.
2.Added prediction, detection, and no. of seconds in a page to the seizure labelframe.
3.Updated the excludetrain popup window.
4.Modified FilterBasicUI and updated in SVN.
5.Modified ChannelSelectionUI and updated in SVN.
6.Created a dataset to analyze and compare patient and volunteer data at 4096 and 250 sampling rates.

Daily activity - 29/10/2024
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1.Modified resampling and updated it in SVN.
2.Modified visualizationui and updated it in SVN.
3.Resolved the no attribute error in case of no.of pages in a page in testEEGui
4.Modified writetodiskui and updated it in SVN.
5.Modified mlui and dlui and updated it in SVN.

Daily activity - 30/10/2024
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1.Demonstrated and explained the workflow of AI PLATFORM to the team and PLs
2.After completing one session of training and testing, can’t perform the training from the same UI unless the entire UI is closed- bug resolved.

Daily activity - 4/10/2024 - 6/10/2024
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1.Modified filter basic ui as per suggestion from the PL
2.Modified write to disk ui as per suggestion from the PL
3.Attended the LSTM presentation by Mr.suraj
4.Discussed and identified the reasons for the bugs related to auto-py-to-exe conversion with Vaishnavi.

Daily activity - 4/11/2024 - 6/11/2024
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1.Modified filter basic ui as per suggestion from the PL
2.Modified write to disk ui as per suggestion from the PL
3.Attended the LSTM presentation by Mr.suraj
4.Discussed and identified the reasons for the bugs related to auto-py-to-exe conversion with Vaishnavi.

Daily activity - 7/11/2024
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1.Modified Visualization ui as per suggestion from the PL
2.ML graphs stored in a particular folder facility is enabled

Daily activity - 8/11/2024
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1.Integrated Python code to save graphs and matrices for Machine Learning (ML) and 2.Deep Learning (DL) models.
3.Fixed the incorrect alert message for seizure prediction.
4.Enabled the status button to show the current active training or testing process.
5.Modified the training data UI as per the suggestions from the PL (Project Lead).
6.Data visualization entry box on focus out and on focus in is enabled
7.Window going back to main ui in case of Resampling ui, write to disk ,display save ui-Solved

Daily activity - 11/11/2024 12/11/2024
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1.Trained the up sampled 4096 patient and volunteer data, achieved 98.18% accuracy.
2.Created 400 epochs balanced up sampled dataset of patient and volunteer data and uploaded in HTGShare.
3.Debugged error in the configuration file where the kernel was different from the one used in training.
4.Enabled a pop-up UI to indicate training completion.
5.Enabled a pop-up UI to indicate testing completion.

Daily activity - 11/11/2024 to 12/11/2024
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1.Trained the up sampled 4096 patient and volunteer data, achieved 98.18% accuracy.
2.Created 400 epochs balanced up sampled dataset of patient and volunteer data and uploaded in HTGShare.
3.Debugged error in the configuration file where the kernel was different from the one used in training.
4.Enabled a pop-up UI to indicate training completion.
5.Enabled a pop-up UI to indicate testing completion.