ROC Analysis of EEG Subbands for Epileptic Seizure Detection using Naïve Bayes Classifier

Authors

  • Mustafa Sameer Department of Electronics and Communication Engineering, National Institute of Technology Patna, Ashok Rajpath, Patna 800005, India https://orcid.org/0000-0003-3819-7825
  • Bharat Gupta Department of Electronics and Communication Engineering, National Institute of Technology Patna, Ashok Rajpath, Patna 800005, India https://orcid.org/0000-0002-4705-700X

DOI:

https://doi.org/10.13052/jmm1550-4646.171315

Keywords:

EEG subbands, Haralick features, Naive Bayes, ROC Analysis, epileptic seizures

Abstract

This paper presents analysis of Electroencephalograms (EEGs) and subbands (delta, theta, alpha, beta, gamma) using image descriptors for epileptic seizure detection. Short-time Fourier transform (STFT) has been utilized to convert 1-D EEG data into image. All subbands are separated from the time-frequency (t-f) matrix and Haralick features of each subband is fed in the Naïve Bayes (NB) classifier. Receiver operating characteristic (ROC) analysis has been used for performance evaluation of classifier. Among all subbands, gamma band alone shows a maximum AUC of 0.98 to classify between ictal and healthy class, while beta band shows a maximum AUC of 0.96 to differentiate between ictal and interictal class. Significance of this work is it shows the medical advantage of different subbands for the detection process.

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Author Biographies

Mustafa Sameer, Department of Electronics and Communication Engineering, National Institute of Technology Patna, Ashok Rajpath, Patna 800005, India

Mustafa Sameer received his M. Tech Degree in Electronics Engineering from Indian Institute of Technology, Banaras Hindu University, Varanasi in 2012. He worked as Research Assistant in School of Computer and System Sciences, Jawaharlal Nehru University, New Delhi. Presently he is working towards PhD from National Institute of Technology Patna in the area of epileptic seizure detection. His research interests include machine learning, deep learning etc.

Bharat Gupta, Department of Electronics and Communication Engineering, National Institute of Technology Patna, Ashok Rajpath, Patna 800005, India

Bharat Gupta is attached to the field of education and research for last fifteen years. He is a senior member of IEEE (USA). He did his graduation in (honors) 2000 and post-graduation in 2003. He did his doctorate from University of Rome, Tor Vergata, Italy. Presently, He is working as an Associate Professor in Department of Electronics & Communication Engineering, National Institute of Technology Patna, Bihar. Dr. Gupta is handling two projects funded by MeitY. He has delivered many lectures in International & National conferences and workshops. He has published more than 60 papers in International and National Journals and conferences. He has acted as reviewer of many international conferences & journals. He was in Advisory Committee in National Conference and has also chaired many sessions in conferences. He has organized the workshops at national and international level. His research area covers mainly Wireless Body Area Network, Routing and MAC protocol for Medical Wireless Communication, ICT for Health care, Internet of Thing (IoT), Internet of Medical Thing (IoMT), FMUWB communication technology, Biomedical signal processing, Machine Learning, etc.

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Published

2021-02-03

How to Cite

Sameer, M., & Gupta, B. (2021). ROC Analysis of EEG Subbands for Epileptic Seizure Detection using Naïve Bayes Classifier. Journal of Mobile Multimedia, 17(1-3), 299–310. https://doi.org/10.13052/jmm1550-4646.171315

Issue

2021: Vol 17 Iss 1-3

Section

CONASENSE