PUBLICATIONS

Journals

1. Govarthan, Praveen, Peddapalli, S. K., Ganapathy, N., & Ronickom, J. F. A.(2024). Emotion classification using electrocardiogram and machine learning: A study on the effect of windowing techniques. Expert Systems with Applications, 254, Article: 124371. https://doi.org/10.1016/j.eswa.2024.124371 (Elsevier, IF: 8.5)

2. Peddapalli, S. K., Govarthan, Praveen, Aleem S. G. A., Ganapathy, N., & Ronickom, J. F. A.(2024). Deep Learning-Based Automated Emotion Recognition Using Multimodal Physiological Signals and Time-Frequency Methods. IEEE Transactions on Instrumentation & Measurement. https://doi.org/10.1109/TIM.2024.3420349 (IEEE publishers, IF: 5.6)

3. Pragya, P., Govarthan, Praveen, Nayak, M., Mukherjee, S., & Agastinose Ronickom, J. F. (2024). Establishment of Three Gene Prognostic Markers in Pancreatic Ductal Adenocarcinoma Using a Machine Learning Approach. Journal of Medical and Biological Engineering, 1-9. https://doi.org/10.1007/s40846-024-00859-7 (Springer publishers, IF: 2)

4. Peddapalli, Sriram & Govarthan, Praveen & Ganapathy, Nagarajan & Fredo, Jack. (2023). A Comparative Analysis of EDA Decomposition Methods for Improved Emotion Recognition. Journal of Mechanics in Medicine and Biology. 2340043. https://doi.org/10.1142/S0219519423400432 (World Scientific, IF: 0.8)

5. Peddapalli, Sriram & Govarthan, Praveen & Ganapathy, Nagarajan & Fredo, Jack. (2023). Electrodermal activity-based analysis of emotion recognition using temporal-morphological features and machine learning algorithms. Journal of Mechanics in Medicine and Biology. 2340044 https://doi.org/10.1142/S0219519423400444  (World Scientific, IF: 0.8)

6. Govarthan, Praveen & Prakash, S. & Sangeetha, B. & Asha, R. & Suganthi, L. & Balathay, Divya. (2020). Wireless Real-Time Electrogastrography Monitoring System. Journal of Computational and Theoretical Nanoscience. 17. 3724-3732. https://doi.org/10.1166/jctn.2020.9268 (American Scientific Publishers)

Conferences

1. Govarthan, P. K., Ronickom, J. F. A. & Swaminathan, R. (2025). Age-Specific Hub Gene Identification in Early-Stage Cervical Cancer using Gene Co-expression and Protein Interaction Networks. Recent Advances in Medical Science and Technology (RAdMed-2025), IIT Kharagpur, West Bengal, India, December 17-19, 2025. (Accepted)

2. Govarthan, P. K., Ronickom, J. F. A. & Swaminathan, R. (2025). Age-Associated Differential Gene Expression in Early-Stage Cervical Cancer Patients. 9th International Conference on Advances in Computing and Data Sciences (ICACDS)-2025, Tallinn, Estonia, August 28-29, 2025. (Accepted)

3. Pragya, Jaya Devi KM, Govarthan, P. K., & Ronickom, J. F. A. (2025). Exploring Machine Learning Applications in Estimating Binding Energies of Therapeutics for PDAC Targets. 12th International Conference on Soft Computing & Machine Intelligence, Rio de Janeiro, Brazil, November 21-23, 2025. (Accepted)

4. Pragya, Govarthan, P. K., Sinha, K., Mukherjee, S., & Agastinose Ronickom, J. F. (2023). Differential Gene Expression Data Analysis of ASD Using Random Forest. Studies in health technology and informatics, 302, 1047–1051. https://doi.org/10.3233/SHTI230344

5. Govarthan, P. K., Kumar, P. S., Ganapathy, N., & Ronickom, J. F. A. (2023, October). Investigating Windowing Techniques in Emotion Classification with ECG and Machine Learning. In 2023 IEEE 5th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA) (pp. 348-353). IEEE. https://doi.org/10.1109/ICCCMLA58983.2023.10346740

6. Nivedhitha, S., Akshaya, M. V., Govarthan, P. K., Munirathnam, R., Ramaniharan, A. K., & Ronickom, J. F. A. (2023, October). Deep Learning-Based Diagnosis of ASD Using Pre-Trained Convolutional Neural Network. In 2023 IEEE 5th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA) (pp. 584-589). IEEE. https://doi.org/10.1109/ICCCMLA58983.2023.10346883

7. Jeswani, D., Govarthan, P. K., Selvaraj, A., Thomas, J., Thomas, J., & Agastinose Ronickom, J. F. (2023). ECG-based Categorical emotion classification using time-domain features and Machine Learning. Current Directions in Biomedical Engineering. https://doi.org/10.1515/cdbme-2023-1174

8. Swarubini, P.J., Sriram Kumar P, Govarthan, P. K., Purkayastha, M., Deb, P., Sairam, S., Asaithambi, M., & Agastinose Ronickom, J. F. (2023). A feasibility study on using EEG for Biometric Trait Authentication System. Current Directions in Biomedical Engineering. https://doi.org/%2010.1515/cdbme-2023-1173

9. Govarthan, P. K., Sriram Kumar P, Ganapathy, N., & Agastinose Ronickom, J. F. (2023). Deep Learning Framework for Categorical Emotional States Assessment Using Electrodermal Activity Signals. Studies in health technology and informatics, 305, 40–43. https://doi.org/10.3233/SHTI230418

10. Lebaka, L. N., Sriram Kumar P, Govarthan, P. K., Rani, P., Ganapathy, N., & Agastinose Ronickom, J. F. (2023). Automated Emotion Recognition System Using Blood Volume Pulse and XGBoost Learning. Studies in health technology and informatics, 305, 52–55. https://doi.org/10.3233/SHTI230422

11. Barigala, V. K., Sriram Kumar P, Govarthan, P. K., Pj, S., Aasaithambi, M., Ganapathy, N., Pa, K., Kumar, D., & Agastinose Ronickom, J. F. (2023). Identifying the Optimal Location of Facial EMG for Emotion Detection Using Logistic Regression. Studies in health technology and informatics, 305, 81–84. https://doi.org/10.3233/SHTI230429

12. Sriram Kumar P, Govarthan, P. K., Ganapathy, N., & Agastinose Ronickom, J. F. (2023). Comparative Analysis of Electrodermal Activity Decomposition Methods in Emotion Detection Using Machine Learning. Studies in health technology and informatics, 302, 73–77. https://doi.org/10.3233/SHTI230067

13. Jeswani, J., Govarthan, P. K., Selvaraj, A., Prince, A., Thomas, J., Kalathe, M., Subramaniam, V., & Agastinose Ronickom, J. F. (2023). Low Valence Low Arousal Stimuli: An Effective Candidate for EEG-Based Biometrics Authentication System. Studies in health technology and informatics, 302, 257–261. https://doi.org/10.3233/SHTI230114

14. Govarthan, P. K., Ganapathy, N., & Agastinose Ronickom, J. F. (2022). Deep-learning framework for ECG based categorical emotional states assessment. XXII International Conference on Mechanics in Medicine and Biology, University of Bologna, Bologna, Italy. 32. https://doi.org/10.6092/unibo/amsacta/7024