Himanshu Kumar, Ph.D.

Himanshu Kumar, Ph.D.

Assistant Professor, Mehta Family School of Biosciences and Biomedical Engineering, IIT Indore. Neural signal processing, AI for healthcare, and brain network neuroscience.

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles

Identifiability of Spectral Graph Model Parameters in Clinical MEG: Implications for Biophysical Interpretation and SOZ Localization

Published in IEEE Transactions on Biomedical Engineering, 2026

Systematic evaluation of practical identifiability and clinical utility of local spectral graph model (SGM) parameters estimated from resting-state MEG in drug-resistant epilepsy, showing gain parameters capture excitatory-inhibitory imbalance in the seizure onset zone.

Recommended citation: Kumar, H., Seshadri, N. P. G., Nair, N., Najm, I., Burgess, R., Alexopoulos, A., Murakami, H., & Krishnan, B. (2026). "Identifiability of Spectral Graph Model Parameters in Clinical MEG: Implications for Biophysical Interpretation and SOZ Localization." IEEE Transactions on Biomedical Engineering. DOI: 10.1109/TBME.2026.3730069
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Subject-independent emotion recognition with EEG bispectral quadratic phase coupling features and explainable machine learning

Published in Biomedical Physics & Engineering Express, 2026

Subject-independent emotion recognition using EEG bispectral quadratic phase coupling features with explainable machine learning approaches.

Recommended citation: Kumar, H., Ganapathy, N., Puthankattil, S.D., & Swaminathan, R. (2026). "Subject-independent emotion recognition with EEG bispectral quadratic phase coupling features and explainable machine learning." Biomedical Physics & Engineering Express. DOI: 10.1088/2057-1976/ae711a
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EEG-Based Emotion Recognition using Super-Resolution Superlet Transform and Self-Attention Convolutional Neural Network

Published in Biomedical Signal Processing and Control, 2026

EEG-based emotion recognition combining super-resolution superlet transform with self-attention convolutional neural network for improved classification performance.

Recommended citation: Kumar, H., Govindarajan, S., Ramakrishnan, M.S., Karthick, P.A., & Ganapathy, N. (2026). "EEG-Based Emotion Recognition using Super-Resolution Superlet Transform and Self-Attention Convolutional Neural Network." Biomedical Signal Processing and Control.
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Three-Phase Seizure Segmentation in Stereotactic EEG Using Envelope-Based Multivariate Changepoint Analysis

Published in Annals of Biomedical Engineering, 2026

Semi-supervised framework that automatically delineates three distinct seizure phases—ictal onset, intra-ictal transition, and seizure termination—from SEEG recordings using envelope-based features and PELT changepoint detection.

Recommended citation: Kumar, H., Seshadri, N.P.G., Martinez, D., Najm, I., Alexopoulos, A., Bulacio, J.C., Serletis, D., & Krishnan, B. (2026). "Three-Phase Seizure Segmentation in Stereotactic EEG Using Envelope-Based Multivariate Changepoint Analysis." Annals of Biomedical Engineering. DOI: 10.1007/s10439-026-04097-7
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Analysis of Dynamics of EEG Signals in Emotional Valence Using Super-Resolution Superlet Transform

Published in IEEE Sensors Letters, 2025

EEG-based emotional state assessment using super-resolution superlet transform for time-frequency analysis of emotional valence dynamics.

Recommended citation: Kumar, H., Ganapathy, N., & Swaminathan, R. (2025). "Analysis of Dynamics of EEG Signals in Emotional Valence Using Super-Resolution Superlet Transform." IEEE Sensors Letters, 9, 1–4. DOI: 10.1109/LSENS.2025.3526907
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Functional Brain Networks of Trait Impulsivity: A Connectome-Based Predictive Modeling Analysis

Published in Human Brain Mapping, 2024

Functional brain networks of trait impulsivity investigated using connectome-based predictive modeling analysis.

Recommended citation: Hüpen, P., Kumar, H., Swaminathan, R., Habel, U., & Wagels, L. (2024). "Functional Brain Networks of Trait Impulsivity: A Connectome-Based Predictive Modeling Analysis." Human Brain Mapping, 45, e70059. DOI: 10.1002/hbm.70059
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Assessment of EEG-PPG Cross Frequency Coherence under Evoked Emotional Arousal

Published in Current Directions in Biomedical Engineering, 2024

Assessment of EEG-PPG cross frequency coherence under evoked emotional arousal states.

Recommended citation: Banik, S., Kumar, H., Ganapathy, N., & Swaminathan, R. (2024). "Assessment of EEG-PPG Cross Frequency Coherence under Evoked Emotional Arousal." Current Directions in Biomedical Engineering, 10(4), 49–52. DOI: 10.1515/cdbme-2024-2012
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Analysis of EEG Fluctuation Patterns using Nonlinear Phase-Based Functional Connectivity Measures for Emotion Recognition

Published in Fluctuation and Noise Letters, 2024

Analysis of EEG fluctuation patterns using nonlinear phase-based functional connectivity measures for emotion recognition.

Recommended citation: Kumar, H., Ganapathy, N., Puthankattil, S.D., & Swaminathan, R. (2024). "Analysis of EEG Fluctuation Patterns using Nonlinear Phase-Based Functional Connectivity Measures for Emotion Recognition." Fluctuation and Noise Letters, 23(5). DOI: 10.1142/S0219477524500512
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Exploring Central-Peripheral Nervous System Interaction Through Multimodal Biosignals: A Systematic Review

Published in IEEE Access, 2024

A systematic review exploring central-peripheral nervous system interaction through multimodal biosignals.

Recommended citation: Banik, S., Kumar, H., Ganapathy, N., & Swaminathan, R. (2024). "Exploring Central-Peripheral Nervous System Interaction Through Multimodal Biosignals: A Systematic Review." IEEE Access, 12, 60347–60368. DOI: 10.1109/ACCESS.2024.3392069
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Impulsivity Classification Using EEG Power and Explainable Machine Learning

Published in International Journal of Neural Systems, 2023

Impulsivity classification using EEG power features and explainable machine learning approaches. Joint first authorship.

Recommended citation: Hüpen*, P., Kumar*, H., Shymanskaya, A., Swaminathan, R., & Habel, U. (2023). "Impulsivity Classification Using EEG Power and Explainable Machine Learning." International Journal of Neural Systems, 33(2), 2350006. (*Joint first author) DOI: 10.1142/S0129065723500065
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A Systematic Review of Sensing and Differentiating Dichotomous Emotional States Using Audio-Visual Stimuli

Published in IEEE Access, 2021

A systematic review of sensing and differentiating dichotomous emotional states using audio-visual stimuli.

Recommended citation: Veeranki, Y.R., Kumar, H., Ganapathy, N., Natarajan, B., & Swaminathan, R. (2021). "A Systematic Review of Sensing and Differentiating Dichotomous Emotional States Using Audio-Visual Stimuli." IEEE Access, 9, 124434–124451. DOI: 10.1109/ACCESS.2021.3110773
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EEG Based Emotion Recognition Using Entropy Features and Bayesian Optimized Random Forest

Published in Current Directions in Biomedical Engineering, 2021

EEG-based emotion recognition using entropy features and Bayesian optimized random forest classifier.

Recommended citation: Kumar, H., Ganapathy, N., Puthankattil, S.D., & Swaminathan, R. (2021). "EEG Based Emotion Recognition Using Entropy Features and Bayesian Optimized Random Forest." Current Directions in Biomedical Engineering, 7(2), 767–770. DOI: 10.1515/cdbme-2021-2196
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Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolutional Neural Network

Published in Journal of Medical Systems, 2021

Emotion recognition using electrodermal activity signals and multiscale deep convolutional neural network.

Recommended citation: Ganapathy, N., Veeranki, Y.R., Kumar, H., & Swaminathan, R. (2021). "Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolutional Neural Network." Journal of Medical Systems, 45, 49. DOI: 10.1007/s10916-020-01676-6
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Conference Papers & Abstracts

Optimal Temporal Resolution for Detecting Functional Connectivity Microstates During Epileptic Seizures Using SEEG

Published in American Epilepsy Society Annual Meeting, 2025

Determining optimal temporal resolution for detecting functional connectivity microstates during epileptic seizures using SEEG.

Recommended citation: Banappa, H.S., Kumar, H., Seshadri, G., Alexopoulos, A., Martinez, D., Najm, I., Bulacio, J.C., Serletis, D., & Krishnan, B. (2025). "Optimal Temporal Resolution for Detecting Functional Connectivity Microstates During Epileptic Seizures Using SEEG." American Epilepsy Society Annual Meeting.
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Unsupervised Learning of Ictal Patterns from Stereo EEG using Contrastive Latent Representation

Published in American Epilepsy Society Annual Meeting, 2025

Unsupervised learning of ictal onset patterns from SEEG using contrastive latent representations, presented at AES Annual Meeting 2025.

Recommended citation: Kumar, H., Seshadri, G., Martinez, D., Najm, I., Alexopoulos, A., Bulacio, J.C., Serletis, D., & Krishnan, B. (2025). "Unsupervised Learning of Ictal Patterns from Stereo EEG using Contrastive Latent Representation." American Epilepsy Society Annual Meeting.
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Assessment of Valence Emotional State Using EEG-EDA Coupling and Explainable Classifiers

Published in Medical Informatics Europe (MIE) — Studies in Health Technology and Informatics, 2024

Assessment of valence emotional state using EEG-EDA coupling and explainable classifiers.

Recommended citation: Banik, S., Kumar, H., Ganapathy, N., & Swaminathan, R. (2024). "Assessment of Valence Emotional State Using EEG-EDA Coupling and Explainable Classifiers." Studies in Health Technology and Informatics, 316, 953–957. DOI: 10.3233/SHTI240569
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Assessment of Emotional States in EEG Signals Using Multi-Frequency Power Spectrum and Functional Connectivity Patterns

Published in 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022

Assessment of emotional states in EEG signals using multi-frequency power spectrum and functional connectivity patterns, presented at IEEE EMBC 2022, Glasgow.

Recommended citation: Kumar, H., Ganapathy, N., Puthankattil, S.D., & Swaminathan, R. (2022). "Assessment of Emotional States in EEG Signals Using Multi-Frequency Power Spectrum and Functional Connectivity Patterns." IEEE EMBC 2022, pp. 280–283. DOI: 10.1109/EMBC48229.2022.9871510
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Impulsivity Classification Using EEG-Based Features

Published in Organization for Human Brain Mapping (OHBM) Annual Meeting, 2022

Impulsivity classification using EEG-based features, presented at the Organization for Human Brain Mapping Annual Meeting 2022.

Recommended citation: Kumar, H., Hüpen, P., Swaminathan, R., & Habel, U. (2022). "Impulsivity Classification Using EEG-Based Features." Organization for Human Brain Mapping (OHBM) Annual Meeting.

Classification of Emotional States Using EEG Signals and Wavelet Packet Transform Features

Published in Medical Informatics Europe (MIE) — Studies in Health Technology and Informatics, 2022

Classification of emotional states using EEG signals and wavelet packet transform features, presented at Medical Informatics Europe 2022.

Recommended citation: Kumar, H., Ganapathy, N., Puthankattil, S.D., & Swaminathan, R. (2022). "Classification of Emotional States Using EEG Signals and Wavelet Packet Transform Features." Studies in Health Technology and Informatics, 294, 943–944. DOI: 10.3233/SHTI220632
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Time and Frequency Domain Analysis of APB Muscles Abduction in Adult Dominant Hand Using Surface Electromyography Signals

Published in IEEE International Symposium on Medical Measurements and Applications (MeMeA), 2022

Time and frequency domain analysis of APB muscle abduction in dominant hand using surface electromyography signals.

Recommended citation: Kumar, H., & Swaminathan, R. (2022). "Time and Frequency Domain Analysis of APB Muscles Abduction in Adult Dominant Hand Using Surface Electromyography Signals." IEEE MeMeA 2022. DOI: 10.1109/MeMeA54994.2022.9856551
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Assessment of Emotional States in EEG Signals Using Phase Slope Index Based Functional Connectivity Features

Published in Recent and Modern Biomedical Studies (RMBS), 2022

Assessment of emotional states in EEG signals using phase slope index based functional connectivity features.

Recommended citation: Kumar, H., Ganapathy, N., Puthankattil, S.D., & Swaminathan, R. (2022). "Assessment of Emotional States in EEG Signals Using Phase Slope Index Based Functional Connectivity Features." Recent and Modern Biomedical Studies (RMBS).

Emotion Recognition in EEG Signals Using Decision Fusion Based Electrode Selection

Published in Studies in Health Technology and Informatics, 2021

Emotion recognition in EEG signals using a decision fusion-based electrode selection strategy.

Recommended citation: Kumar, H., Ganapathy, N., Puthankattil, S.D., & Swaminathan, R. (2021). "Emotion Recognition in EEG Signals Using Decision Fusion Based Electrode Selection." Studies in Health Technology and Informatics, 281, 153–157. DOI: 10.3233/SHTI210139
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Analysis of EEG Response for Audio-Visual Stimuli in Frontal Electrodes at Theta Frequency Band Using Topological Features

Published in Recent and Modern Biomedical Studies (RMBS), 2021

Analysis of EEG response for audio-visual stimuli in frontal electrodes at theta frequency band using topological features.

Recommended citation: Kumar, H., Puthankattil, S.D., & Swaminathan, R. (2021). "Analysis of EEG Response for Audio-Visual Stimuli in Frontal Electrodes at Theta Frequency Band Using Topological Features." Recent and Modern Biomedical Studies (RMBS).

Correlation of the sEMG Signal and Muscle Stiffness during Fatiguing Isometric Contraction of Bicep Brachii Muscle in Dominant and Non-Dominant Hand

Published in International Conference on Mechanics of Functional Materials and Biological Tissues (ICMMB), 2017

Correlation of sEMG signal and muscle stiffness during fatiguing isometric contraction of bicep brachii in dominant and non-dominant hand.

Recommended citation: Navaneethkrishna, M., Nitinram, S., Kumar, H., Lasya, L., & Swaminathan, R. (2017). "Correlation of the sEMG Signal and Muscle Stiffness during Fatiguing Isometric Contraction of Bicep Brachii Muscle in Dominant and Non-Dominant Hand." ICMMB.