BMI

Daily Tasks 22-09-2023
--------------------------------
1. Train and Tested Different Volunteers of 256 Hz Sampling EEG Data using various implemented Deep Learning Models
2. Discussed with seniors regarding Advanced Image Processing Techniques for Convolutional Neural Network Model
3. Attended Review Meeting regarding 2nd PRSG Preparation of various modules reports creation and PPT slides preparation.

Daily Tasks 25-09-2023
------------------------------
1. Created CNN architecture for training the various types of EEG signal images.
2. Modifying the image size for the input-compatible requirement for CNN Architecture.
3. Discussion with colleagues regarding the images.

Daily Tasks 26-09-2023
------------------------------
1. Tried out with different hyperparameters tuning for the CNN architecture.
2. Developed AlexNet Model for EEG Signals Images.
3. Referred a research article based on the UCI ML Repository of EEG Signals dataset classification using the CNN method.
4. Attended Doubt clearing session regarding the challenges and solutions for developing the EEG Signals Image-based Classification.
5. Had discussions with various colleagues to understand the input structure format of data.

Daily Tasks 27-09-2023
-----------------------
1. Trained and Tested BiGRU Model using different volunteers 256HZ EEG signals data.
2. Debugged some parts of CNN code.
3. Modify the data sheet of DL.

Daily Tasks 29-09-2023
----------------------
1. Trained LSTM, GRU, BiLSTM, and BiGRU Models using different volunteer's 256HZ EEG signals data.
2. Updated the Data Sheet
3. Explored various predefined DL models.

Daily Tasks 03-10-2023 & 04-10-2023
-----------------------------------
1. Two Days Leave

Daily Tasks 05-10-2023
-----------------------------------
1. Created a Custom CNN Model having a separate method for training and testing new input EEG Images i.e., suitable for Inner speech, Eye blink and SSVEP Signal Images.
2. Removed learning rate callback and included early stopping for better traceability.
3. Removed the disable option of tensorflow2.x behavior along with the weight histogram function.
4. Added the plotting function of loss and accuracy, scatter plot, histogram, confusion matrix, and ROC curve in the CNN model.
5. Test Debugging is still in progress.

Daily Tasks 06-10-2023
-----------------------------------
1. Created Monochrome and Colour Images for all SSVEP 256 Hz sampling data of volunteers.
2. Train and Tested the SSVEP Images using Custom CNN.
3. Resolved errors in the Test Case.

Daily Tasks 09-10-2023
-----------------------------------
1. Started CNN Integration with existing Ebrainvoicepipeline.
2. Trained Scalp Map EEG Image using Custom CNN Model.
3. Edited the docs.

Daily Tasks 10-10-2023
----------------------
1. Explored the concept of Genomics and Human Genome Project
2. Gone through Digipatho Project materials.
3. Gone through the strategies of Breast Cancer Prognostic Prediction.
4. Trained DL models
5. CNN integration is being developed.

Daily Tasks 11-10-2023
--------------------------------
1. Discussion of various user interface components for CNN integration in the existing pipeline.
2. A JSON deserialization bug was fixed during the test phase with a colleague.
3. Trained and tested Coiflet wavelet features in the BiLSTM and BiGRU models.
4. Noted down the various necessary parameters creation in the DL Models test case.
5. Data shape issue debugging for the RNN, ANN, BiRNN, and EEGNet Models is started.

Daily Tasks 12-10-2023
--------------------------------
1. CNN Train Module Integration with proper UI Components
2.Resolved the bugs in workflow.
3. Learned Histology workflow.
4. Gone through Genome Biology

Daily Tasks 13-10-2023
--------------------------------
1. Attended 2nd PRSG Planning Meeting
2. Presented the workflow of CNN in a separate meeting.
3. Hand over the CNN Architecture to EB and SSVEP Approach holders.
4. Trained and Tested EB Scalogram using CNN Architecture.
5. Trained and Tested SSVEP Spectrogram using CNN Architecture.
6. Created separate worksheets for 3 approaches CNN Architecture.

Daily Tasks 16-10-2023
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One day Leave

Daily Tasks 17-10-2023
--------------------------------
1. Updated the DL sheet with all other currently integrated algorithms with approaches.
2. Trained and tested different volunteers’ data using GRU, LSTM, BiGRU, and BiLSTM using the wavelet Coiflet feature.
3. Discussion with Sir regarding the work status of the DL results.
4. Prepared glimpse of Disease Prognostication using AI techniques
5. Gone through various literature surveys for vector-borne and water-borne from local detection to global epidemic monitoring and control.

Daily Tasks 18-10-2023
--------------------------------
1. Trained and tested SSVEP Channelwise Scalogram Image using CNN Architecture.
2. Trained and tested Inner Speech Signals volunteers’ data using BiGRU Architecture.
3. Tried the training of Scalp Maps Inner speech signal images using 2 classifier CNN Architecture.
4. Postponed the debugging of CNN architecture utilized for Scalp maps.
5. Attended Machine Learning Class.

Daily Tasks 19-10-2023
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1. Prepared Deep Learning Architectures ppt.
2. Trained and tested Inner Speech Signals volunteers’ data using BiGRU and BiLSTM Architecture.
3. Gone through various articles regarding multiomics analysis.
4. Prepared Correlating with Genomics ppt.

Daily Tasks 20-10-2023
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1. Generated Channelwise Scalogram Images for Inner speech signals.
2. Finalized 4 Classes with Eyes Open and Eyes Closed Mapping for CNN Model in Inner Speech Approach.
3. Discussion with Sujathan Doctor and Deepak Sir regarding the Genomics, immunohistochemistry, and pathological grading features.
4. Attended meeting with Malabar Cancer Centre (MCC), Thalassery for PathSCAN Project.

Daily Tasks 25-10-2023
--------------------------------------
1. Generated Channelwise Scalogram Images for Inner speech signals for volunteers and patients.
2. Updated the CNN_IS sheet with trained and test accuracy.
3. The creation of PPT is still in progress.
4. Trained and tested the BiLSTM Model with 256Hz sampling data.

Daily Tasks 26-10-2023
--------------------------------------
1. Created Deep Learning Algorithms for EEG Signal Processing technical presentation.
2. Updated the BiLSTM and BiGRU sheet with trained and test accuracy.
3. The creation of 2nd PRSG PPT DL slides is still in progress.

Daily Tasks 27-10-2023
--------------------------------------
1. Completed the assigned activity of preparing technical PPT for 2nd PRSG on DL for Data Preparation and Test results for Individual volunteers and combinations of volunteers.
2. Completed the Deep Learning Algorithms for EEG Signal Processing technical presentation.
3. Presented the DL Algorithms working principle to Mani Sir.

Daily Tasks 30-10-2023 to 02-11-2023
----------------------------------------------------
1. Tried out the live prediction implementation using the MIME Application at C-DAC, Delhi.
2. Preparation for the 2nd PRSG Meeting
3. Attended the 2nd PRSG Meeting at AIIMS, Delhi.

Daily Tasks 03-10-2023
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One day Leave

Daily Tasks 06-10-2023
-------------------------------------------
1. Downloaded TCGA BRCA clinical and biospecimen dataset
2. Gone through the Genomic Data Commons Data Portal to understand the procedures and experimental strategies.
3. Attended the 2nd PRSG Review discussion status and future action activities meeting.
4. Drafted MoM contents of the 2nd PRSG meeting.
5. Reviewed the draft for further modifications

Daily Tasks 07-10-2023
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1. Created the final MoM contents of the 2nd PRSG meeting.
2. Gone through various procedures and protocols for implementing the tcga dataset.
3. Referred MLP algorithm-based implementation for the tcga dataset.
4. Discussed with Mani Sir and Deepak Sir regarding the data identification for the TNBC prognosis score prediction.

Daily Tasks 08-10-2023
---------------------------
1. Learned Informatics in multi-omics and application.
2. Referred to various research articles and implementation mechanisms of gene techniques.
3. Discussion regarding User Manual Documents for modules and techniques design.

Daily Tasks 09-10-2023
----------------------------
1. Explored the Pan-cancer Atlas program for 12 tumor-type samples along with their multi-omics characteristics.
2. Attended Live prediction demonstration for eye blink detection using an OpenBCI EEG device.
3. Learned the experimental strategy types of data samples.
4. Referred Bioinformatics tutorials.
5. Learned the techniques mentioned in the Digipatho TNBC workflow.

Daily Tasks 10-10-2023
------------------------------------------
1. Understand the basic macro molecule structures with their representation format.
2. Implemented the cancer prediction using ML Algorithms from the Gene Expression Dataset.
3. Completed all the tour claim procedures.
4. Explained the learned concepts to Mani, Sir.

Daily Tasks 13-10-2023
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One day Leave

Daily Tasks 14-10-2023
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1. Scalp Map Image generated for V1 Va 256 Hz data.
2. Trained and Tested Scalp Map Images with a Custom CNN Model using 4 classes.
3. Created SSVEP Scalp Map Images for V10 all session data.
4. Updated the DL Result Sheet.

Daily Tasks 15-10-2023
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1. Started the pending integration work of DL Pipeline.
2. Initiated Server Configuration setup for training various DL Models.

Daily Tasks 16-10-2023
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1. DL Training and Testing using signal-based data.
2. Discussion regarding the technical class session.
3. Meeting regarding the integration of Image-based components in the MiME Application.

Kausalya S wrote in #note-17:

Daily Tasks 26-10-2023
--------------------------------------
1. Created Deep Learning Algorithms for EEG Signal Processing technical presentation.
2. Updated the BiLSTM and BiGRU sheet with trained and test accuracy.
3. The creation of 2nd PRSG PPT DL slides is still in progress.

Daily Tasks 27-10-2023
--------------------------------------
1. Completed the assigned activity of preparing technical PPT for 2nd PRSG on DL for Data Preparation and Test results for Individual volunteers and combinations of volunteers.
2. Completed the Deep Learning Algorithms for EEG Signal Processing technical presentation.
3. Presented the DL Algorithms working principle to Mani Sir.

Daily Tasks 30-10-2023 to 02-11-2023
----------------------------------------------------
1. Tried out the live prediction implementation using the MIME Application at C-DAC, Delhi.
2. Preparation for the 2nd PRSG Meeting
3. Attended the 2nd PRSG Meeting at AIIMS, Delhi.

Daily Tasks 03-11-2023
-------------------------------------------
One day Leave

Daily Tasks 06-11-2023
-------------------------------------------
1. Downloaded TCGA BRCA clinical and biospecimen dataset
2. Gone through the Genomic Data Commons Data Portal to understand the procedures and experimental strategies.
3. Attended the 2nd PRSG Review discussion status and future action activities meeting.
4. Drafted MoM contents of the 2nd PRSG meeting.
5. Reviewed the draft for further modifications

Daily Tasks 07-11-2023
------------------------------------------------
1. Created the final MoM contents of the 2nd PRSG meeting.
2. Gone through various procedures and protocols for implementing the tcga dataset.
3. Referred MLP algorithm-based implementation for the tcga dataset.
4. Discussed with Mani Sir and Deepak Sir regarding the data identification for the TNBC prognosis score prediction.

Kausalya S wrote in #note-18:

Daily Tasks 08-11-2023
---------------------------
1. Learned Informatics in multi-omics and application.
2. Referred to various research articles and implementation mechanisms of gene techniques.
3. Discussion regarding User Manual Documents for modules and techniques design.

Daily Tasks 09-11-2023
----------------------------
1. Explored the Pan-cancer Atlas program for 12 tumor-type samples along with their multi-omics characteristics.
2. Attended Live prediction demonstration for eye blink detection using an OpenBCI EEG device.
3. Learned the experimental strategy types of data samples.
4. Referred Bioinformatics tutorials.
5. Learned the techniques mentioned in the Digipatho TNBC workflow.

Kausalya S wrote in #note-19:

Daily Tasks 10-11-2023
------------------------------------------
1. Understand the basic macro molecule structures with their representation format.
2. Implemented the cancer prediction using ML Algorithms from the Gene Expression Dataset.
3. Completed all the tour claim procedures.
4. Explained the learned concepts to Mani, Sir.

Daily Tasks 13-11-2023
------------------------------------------
One day Leave

Kausalya S wrote in #note-20:

Daily Tasks 14-11-2023
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1. Scalp Map Image generated for V1 Va 256 Hz data.
2. Trained and Tested Scalp Map Images with a Custom CNN Model using 4 classes.
3. Created SSVEP Scalp Map Images for V10 all session data.
4. Updated the DL Result Sheet.

Daily Tasks 15-11-2023
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1. Started the pending integration work of DL Pipeline.
2. Initiated Server Configuration setup for training various DL Models.

Kausalya S wrote in #note-21:

Daily Tasks 16-11-2023
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1. DL Training and Testing using signal-based data.
2. Discussion regarding the technical class session.
3. Meeting regarding the integration of Image-based components in the MiME Application.

Daily Tasks 17-11-2023
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1. Worked with pending integration of DL pipeline.

Daily Tasks 20-11-2023
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1. Created work report for performance review
2. Code walkthrough meeting of Deepu Created Modules in MiME application.
3. Resolved the Signal-based DL function.

Daily Tasks 21-11-2023
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1. Edited the final work report for performance review
2. Trained LSTM, GRU, BiLSTM, and BiGRU DL algorithms with and without selecting features.

Daily Tasks 22-11-2023
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1. Resolved the Mani Sir observed and trained the model with raw EEG signals.
2. Updated the Sheets.
3. Started to resolve the DL Test module.

Daily Tasks 23-11-2023
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One day Leave

Daily Tasks 24-11-2023
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1. Resolve the ANN model error in the Training Module.
2. Involved in the DL module testing for training cases with various algorithms.
3. Started to resolve the DL Test module.

Daily Tasks 28-11-2023
----------------------------------------------------
1. Trained and saved the Bidirectional Long Short-Term Memory model for all Volunteers present in 256 Hz.
2. Tested with different volunteers using the same model.

Daily Tasks 29-11-2023
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1. Prepared for performance review.

Daily Tasks 30-11-2023
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1. Prepared for performance review.
2. Attended the review.

Daily Tasks 01-12-2023
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1. Discussion with Mani Sir regarding the DL Concepts.
2. Started to include the DL modules of Data balancing and eye open/eye close conditions.

Daily Tasks 04-12-2023
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1. Worked with data balancing and eye open/eye close conditions.
2. Tried to resolve the bug that occurred in the ANN model.

Daily Tasks 05-12-2023
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1. ANN training function shape issue resolved.
2.Trained with 256Hz V5 S3 Va and Vp data.

Daily Tasks 06-12-2023
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1. Integrated data balancing and eye open/eye close conditions along with empty folder checking conditions with Deepu.
2. Discussion regarding the testing assignments of DL Algorithms.

Daily Tasks 07-12-2023
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1. Resolved the bug that occurred in the balancing approach.
2. Resolved some plotting issues.

Daily Tasks 08-12-2023
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1. Integrated preprocessing part of code along with up sampling and down sampling in the training case of DL with Mani Sir and Deepu.
2. Integrated the separate 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)'.
3. Added the up-sampling and down-sampling functionality in the test case of DL along with Deepu.

Daily Tasks 11-12-2023
----------------------------------------------
1. Discovered the error causing the file in new patient epoched data.
2. Manually checked all the new patient’s data and reported the issue to Archana.
3. Tried out using 250 Hz patients by upsampling into 256 Hz.
4. Trained LSTM and GRU using 250HZ patients’ data.
5. Debugging is still in pending for the test case upsampling data due to shape issues.

Daily Tasks 12-12-2023
------------------------------------
1. Updated all DL Algorithms Result Sheets with new fields of Split data, Channel selection option, Feature protocol, and Training evaluation metrics along with test case result information tables.
2. Trained and Tested Patient 250 Hz EEG data with GRU Model.
3. Find out some issues with P36 EEG Signals channels data and discussed with Archana.
4. Trained and Tested Patient 256 Hz EEG data with LSTM & Bi-GRU Model.
5. Trained and Tested Patient 250 Hz EEG data with EEGNET Model.

Daily Tasks 13-12-2023
------------------------------------
1. Updated the DL result sheet to a new format for all integrated algorithms.
2. Integrated Statistical Classification matrix of tp, tn, fp, fn, ppv, etc., in ML visualization with Dhanya.
3. Deep learning featured-based training function was implemented with Deepu.
4. Dropped the unsupervised learning models of LSM, RBM, SNN, ESN for further process to integrate into MiME application.
5. Tried BiLSTM model training with time and frequency domain features.

Daily Tasks 14-12-2023
------------------------------------
1. Learned about the Statistics for AI concepts.
2. Trained and tested the EEGNET model with patient data.
3. DL featured-based test function is still in debug.

Daily Tasks 15-12-2023
------------------------------------
1. Submitted Purchase order for Server.
2. Trained and tested with LSTM, GRU, BiLSTM, and BiGRU model for V4 SSVEP EEG Signals data.
3. Trained all 4096 Hz epoched data by downsampling it into 256Hz using GRU and EEGNet Model.
4. Checked all files that caused mismatch columns in 4096Hz Volunteers.

Daily Tasks 18-12-2023 & 19-12-2023
-----------------------------------
Two days Leave

Daily Tasks 20-12-2023
------------------------------------
1. Resolved the shape issue that occurred in the Patient data.
2. Discuss the prefixing saving results option in the training dataset with Dhanya.
3. Started to resolve the feature-based DL issue.
4. Trained and tested patients’ data with Reshma and Dhanya.

Daily Tasks 21-12-2023
------------------------------------
1. Resolved the feature-based DL Labels prediction issue with Deepu.
2. Attended the knowledge-sharing session of Asha Ma’am in Scalp Maps, Seizure Prediction, and QEEG Project.

Daily Tasks 22-12-2023
------------------------------------
Christmas Celebration Function

Daily Tasks 26-12-2023
------------------------------------
1. Resolved the feature-based DL Labels prediction issue with Deepu.
2. Attended the knowledge-sharing session of Asha Ma’am in Scalp Maps, Seizure Prediction, and QEEG Project.

Daily Tasks 27-12-2023
------------------------------------
1. Trained and Tested S250CH21 Patients' data using EEGNET.
2. Attended Hindi as an Official Language Workshop.
3. Modified UI and its components for Image-based DL with Reshma.
4. Resolved Individual file-based results displayed in the DL case with Dhanya.
5. Resolved file update of peak detection with Rashmi.

Daily Tasks 28-12-2023
------------------------------------
1. Generated EEG signals-based images on monochrome, grayscale, color, scalogram, spectrogram, and Scalp maps for all Patients using these S256CH26, and S250CH21 channels.
2. Started to debug Pywavelets with Deepu.

Daily Tasks 29-12-2023
------------------------------------
1. Pending Image-based DL Integration
2. Read research articles and implementation strategies of various hybrid Deep learning models.

Daily Tasks 01-01-2024
------------------------------------
One Day Leave

Daily Tasks 02-01-2024
------------------------------------
1. Trained and tested patient data using the EEGNet Model.
2. Learned the various parameter possibilities in the DL architectures.

Daily Tasks 03-01-2024
------------------------------------
1. Debug the Classifier Train Image-based DL plotting functions.
2. Begin the implementation of UI fields needed for Image-Based DL Models with Reshma.

Daily Tasks 04-01-2024
------------------------------------
1. Debug the Classifier Train Image-based DL plotting functions.
2. Adding the proper functionality calling for image-based DL in Ebrainvoicepipeline.

Daily Tasks 05-01-2024
------------------------------------
1. Debug the training UI with Reshma.
2. Meeting with Team members.

Daily Tasks 08-01-2024
------------------------------------
1. Discussion with GH.
2. Pending debugging code.
3. Discussion with Mani, Sir.

Daily Tasks 09-01-2024
------------------------------------
1. The Training Module of Image-Based DL is completed and working properly.
2.Debugging of the test module is started.

Daily Tasks 10-01-2024
------------------------------------
1. Test Module of Image-based DL is in progress.
2. Resolved the issues that occurred in Anu PC and started to use the Image-based DL training for the Channelwise Scalogram of patients.

Daily Tasks 11-01-2024
------------------------------------
1. Learned BERT and Deep Belief Algorithms.

Daily Tasks 12-01-2024
------------------------------------
1. Testing UI components for deep learning is finalized and completed with Reshma.
2. Debugging of AlexNet layers.

Daily Tasks 15-01-2024
------------------------------------
One Day Leave

Daily Tasks 16-01-2024
------------------------------------
1. Attended BMI Project review meeting.
2. Prepared minutes of meeting.
3. Planned to cancel AlexNet because of its incompatibility issues after several complications.

Daily Tasks 17-01-2024
------------------------------------
1. Removed AlexNet from Image image-based deep learning classifier.
2. Learned GAN Architecture.
3. Studied Human centred Artificial Intelligence approach to enhancing the current algorithms.

Daily Tasks 18-01-2024
------------------------------------
1. Deep Learning Imaged Based Testing Function pending debugging work is completed with Dhanya.
2. EEGNET Model is included in image-based deep learning.

Daily Tasks 19-01-2024
------------------------------------
1. ANN, RNN Model problem resolved and started to be working properly.
2. Removed BiRNN Model after its incompatibility.
3. Resolved Json and various variables issues that occurred in the MiME with Dhanya.

Daily Tasks 22-01-2024
------------------------------------
1. Trained P250CH21 using wavelet-based scalogram images using Custom CNN.
2. Combined all Va & Vp with EO& EC of similar events for the creation of patients’ image datasets.
3. Trained and Tested with BiGRU, EEGNet Signal-based DL using epoched EEG Signals data.
Daily Tasks 23-01-2024
------------------------------------
1. Copied all the Old EEG Projects Repository to the MRI server.
2. Checked and verified the V256 EEG Signals data collected from the Natus Device for Exhibition purposes.
3. A Deep Learning Demo procedure setup was drafted.

Daily Tasks 24-01-2024
------------------------------------
1. Trained and Tested SSVEP OpenBCI EEG Signals data using BiGRU Model.
2. Trained and Tested Eyeblink without features approach by using BiGRU Model.
3. Trained and Tested Eyeblink in Custom CNN model using wavelet-based multichannel scalogram.
Daily Tasks 25-01-2024
------------------------------------
1. Completed the DL demo setup on the laptop and explained it to Reshma.
2. Attended knowledge transfer session of Demo Workflow.
3. Prepared Script for Fundus Camera after discussion with PL Basith.
4. Learned about the hardware principles applied in the prototype of the fundus camera.

Daily Tasks 29-01-2024
------------------------------------
1. Attended Digital Dentistry and Oral Health Workshop and Product Expo at C-DAC, Technopark.

Daily Tasks 30-01-2024
------------------------------------
1. Discussion with Sir regarding the creation of pre-trained model approach for new data along with pending documentation works.
2. Started to prepare Responsible AI themes in Health care applications.

Daily Tasks 31-01-2024
------------------------------------
1. Referred various articles about Liver cirrhosis with their examination of identification using different strategies.
2. Drafted one executive summary regarding Liver Cirrhosis.
3. Removed BMI-based Responsible AI Proposal.

Daily Tasks 01-02-2024
------------------------------------
1. Proposal preparation for EOI on Responsible AI in Liver Cirrhosis.
2. Dropped EOI on Responsible AI in Liver Cirrhosis for temporary after discussion.
3. Discussion with Mani Sir regarding Machine Unlearning technique using DL algorithms.

Daily Tasks 02-02-2024
------------------------------------
1. Prepared Sleep disorder analysis technical content for the EOI on Responsible AI proposal preparation.
2. Discussion with EEG Technician regarding the suitable identification of a Brain device for sleep disorder analysis.

Daily Tasks 05-02-2024 to 08-02-2024
------------------------------------
1. Preparation for Technical talk activities.
2. Attended preparation meetings with BMI team members.
3. Created DL results slides for demonstration.
4. Started the slide preparation.

Daily Tasks 09-02-2024
------------------------------------
1. Discussed with Rashmi regarding the Eyeblink threshold and AI methods.
2. Attended Women in Cyber Security Online Talk organized by C-DAC, Pune.

Daily Tasks 12-02-2024
------------------------------------
1. Discussed with Rashmi regarding all the parameters used to identify the peaks in the Eyeblink Approach.
2. Discussed with Anusree regarding the protocol setup along with the content preparation for SSVEP.
3. Learned about various filters used in the signal processing techniques.

Daily Tasks 13-02-2024
------------------------------------
1. Finalized the feature list after discussion with Mani, Sir.
2. Created a separate flowchart for various image generation functions.
3. Finalized the Models based on the results of training and test results.

Daily Tasks 14-02-2024
------------------------------------
1. Draft Version of PPT slides discussed with Mani Sir, for further modification.

Daily Tasks 15-02-2024 to 20-02-2024
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Four days Leave

Daily Tasks 21-02-2024 to 23-02-2024
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1. Discussed with PL regarding the Liver Proposal for Ethical Clearance.
2. Prepared for ISO Audit along with CCI Created for DL files in MiME Application.
3. Learned various scanning techniques involved in gastrointestinal problems.
4. Finalized the count of events and channels for PowerPoint preparation.
5. Discussed the pre-trained model approach for training new data.
6. Attended the Micro Plan initial meeting with BMI Team members.
7. Began the work according to the Micro Plan and agenda.

Daily Tasks 26-02-2024 to 01-03-2024
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1. Discussed the different datasets of patients to showcase the results on March 1 with PL.
2. Attended the Micro Plan Talk meeting with the BMI team.
3. Prepared Deep Learning training and test results for ANN, RNN, LSTM, GRU, BiLSTM, BiGRU, and EEGNet using a dataset with fewer relaxation events from patients.
4. Discussed the Deep Learning algorithm workflow along with various hyperparameters used in the models with PL.
5. Conducted a rehearsal for the March 1 Technical Event at the Amphitheatre with BMI team members.
6. Edited the presentation slides for the March 1 project discussions.
7. Prepared an Executive Summary for GH.
8. Attended a project discussion with BMI team members to ask for suggestions from Devasahayam Sir.
9. Attended a talk on "Sensors and Instrumentation for Human Machine Interfaces" by Professor Dr. Suresh Devasahayam.

Daily Tasks 04-03-2024 to 07-03-2024
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1.Attended a review meeting with team members on Sensors and Instrumentation in HMI.
2.Learned about the IEEE Transactions Journal format.
3.Prepared DL visualizations for a write-up.
4.Started preparing the IRC format for an ICMR proposal.
5.Created a Software Requirement Specification (SRS) document for Deep Learning functions.
6.The ICMR proposal preparation was cancelled due to the completed deadline.
7.Started preparing a MeitY proposal.

Daily Tasks 11-03-2024 to 13-03-2024
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1.Discussed the proposal write-up for Artificial Intelligence (AI) Solutions for Liver Wellness in Cirrhosis Care with the project lead.
2.Finalized cirrhosis as the focus disease from among all liver diseases.
3.Changed the Deep Learning Model from a Hybrid Convolutional Neural Network-Capsule Network to a Densely Connected Convolutional Network (DenseNet) optimized using Nadam (Nesterov-accelerated Adaptive Moment Estimation).
4.Attended a meeting on writing for the IEEE Transactions Journal.
5.Edited the capital budget and revised it according to traditional calculations.
6.Prepared and completed the proposal write-up for Artificial Intelligence (AI) Solutions for Liver Wellness in Cirrhosis Care.

Daily Tasks 14-03-2024 to 15-03-2024
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1.Attended the technical talk program by Ms. Khushboo Srivastava, CEO of One Learning Solutions.
2.Edited the write-up for Artificial Intelligence (AI) Solutions for Liver Wellness in Cirrhosis Care as per the suggestions of PL.
3.Attended a Mental Health Awareness Program and Women Empowerment program on both days as part of Women’s Day Celebration Function.
4.Edited the capital budget and revised it according to traditional calculations.
5.Submited the revised final version of Proposal.

Daily Tasks 18-03-2024 to 20-03-2024
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1.Prepared the plan to train Scalp Maps images by using patients’ dataset.
2.Discussed with team members, regarding the structural perspective of journal writing as per the novel work implementation.
3.Discussed with PL and team members, regarding the submitted Expert Systems journal referred by other authors still under the preprint DOI.
4.Discussed with PL regarding the patent DL approach along with the usage of DL techniques in journal.

Daily Tasks 21-03-2024 to 22-03-2024
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1. Debugged the module of the Scalp Map key axis issue.
2. Discussed with PL regarding the format of project content in journal paper writing.
3. Chosen the DL Models for the paper.

Daily Tasks 25-03-2024
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One Day leave

Daily Tasks 26-03-2024 to 29-03-2024
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1. BiLSTM Model trained and tested with Wavelet features.
2. Scalogram Image generated for all patients’ datasets.
3. Discussed with PL regarding the BCI Standardization.
4. Discussed with PL regarding the paper doubts.
5. All patient's Scalogram images were trained and tested using the CNN model.

Daily Tasks 01-04-2024 to 04-04-2024
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1. Eyeblink data in DL is not producing validation accuracy issue identified and started the debugging.
2. Discussed with PL regarding the Deployable approach of the DL Model.
3. Discussed with PL regarding the pickle and saving the model different approaches.
4. Attended one meeting regarding the further technical works pending in BMI projects.
5. Discussed the test code alteration in image perspective along with post-processing techniques pending inclusion.
6. Faced issue in the image generation of 4096 HZ Volunteers data.
7. Attended Singular Value Decomposition (SVD) Technical Class by Anusree.

Daily Tasks 05-04-2024
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1. Trained BiLSTM Model using patients’ data of Inner Speech Selected Channels along with Coiflet wavelet features.
2. Trained and tested Custom CNN model using Scalogram Image of Patients data.
3. Attended Random Forest Class discussed by Dhanya.

Daily Tasks 09-04-2024 to 12-04-2024
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1. Attended the C-DAC Foundation Day Function.
2. Attended a detailed status meeting on the current progress of the BMI Project.
3. Edited the final draft of the Annual Report for 2023-2024.
4. Scheduled training for Deep Learning Models using specific channels, selected preprocessing techniques, and selected wavelet features to achieve a higher precision rate.
5. Prepared notes on Deep Learning for the class.

Daily Tasks 15-04-2024 to 17-04-2024
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1. Studied various LLMs and their strategies.
2. Studied various brain disorders to identify the exact brain pattern representation in the outputs.
3. Trained an RNN model using S250 CH21 Patients Data.
4. Trained an EEGNet model using S250 CH21 Patients Data.
5. Trained an ANN model using S250 CH21 Patients Data.
6. Preparing a new journal paper based on the real-time experience with BMI.

Daily Tasks 18-04-2024
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1. Completed the Detailed Design Document for Train Data UI, Test Data UI, DL Classifier Training, DL Classifier Function, and DL Classification Modules.

Daily Tasks 22-04-2024 to 24-04-2024
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1. Trained and tested all patients' dataset on Recurrent Neural Networks and updated the results in the DL sheet.
2. Provided suggestions and recommendations for improving the journal paper created by a team member.
3. Writing the paper according to the novel approach.
4. Had discussion with PL regarding the suggestions for the 3rd PRSG preparation.
5. Started to prepare the slides regarding the 3rd PRSG based on the reviews from the 2nd PRSG.

Daily Tasks 29-04-2024
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1. Attended C-DAC’s Intellectual Property Right (IPR) Day function.
2. Preparing the draft slides for 3rd PRSG Meeting

Daily Tasks 30-04-2024 to 03-05-2024
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1.Updated the monthly progress report.
2.Asked for suggestions from the PL regarding the outline of the PRSG Slides preparation.
3.Writing the research article on Electroencephalography Network-based Brain-Computer Interface for Inner Speech Identification.
4.Created the Hybrid CNN-LSTM Model specifically for SSVEP Approach.
5.Debugging the reshape issues that occurred in the CNN-LSTM DL Model.

Daily Tasks 06-04-2024 to 07-05-2024
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1.Resolved shape issue in the input step for the Hybrid CNN-LSTM Model.
2.Training and test modules for the Hybrid CNN-LSTM Model are working on both raw signal-based and feature-based selection techniques.
3.Added some channels in the Natus selection in the Channel Selection UI.
4.Had a discussion with PL regarding DG Awards.
5.Created a 1D CNN-BiLSTM Hybrid Model for the Signals-based mode capable of working on both raw signal-based and feature-based selection techniques.