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Seizure Detection by Analyzing EEG Signals Using Deep Learning Networks

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Advances in Data-Driven Computing and Intelligent Systems (ADCIS 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 891))

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Abstract

Epileptic seizures is a well-known and the most chronic neurological disorder and it is observed highly in infants and elderly people. Symptoms of epileptic seizures are very dangerous; they lead to injuries due to falling because of jerking movements of the arms and legs that can’t be controlled. Electroencephalography (EEG) signals are prominent tools to analyze brain activities and detect seizures. Learning machines are promising in detecting seizures by analyzing EEG signals. This study proposes a customized deep learning network for seizure detection, i.e., DLN-SD utilizing EEG signals. The publicly available CHB-MIT Scalp EEG dataset is considered. It is empirically compared with pre-trained models, namely AlexNet and GoogleNet and observed that the proposed model (DLN-SD) brings 96.0% precision, 98.0% recall, and 98.0% accuracy and performs best among all three models. It is concluded that the DLN-SD shows an improvement of 15% over AlexNet and 9% over GoogleNet to detect seizures from the EEG dataset.

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Authors and Affiliations

  1. Manipal University Jaipur, Jaipur, Rajasthan, 303007, India

    Amber Agarwal, Rishikesh Trivedi & Somya R. Goyal

  2. Osaka Metropolitan University, Osaka, Japan

    Istiaque Ahmed

Authors
  1. Amber Agarwal
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  2. Rishikesh Trivedi
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  3. Somya R. Goyal
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  4. Istiaque Ahmed
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Corresponding author

Correspondence to Somya R. Goyal .

Editor information

Editors and Affiliations

  1. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

  2. Department of Computer Science and Information Systems, Birla Institute of Technology and Science, Pilani, Sancoale, Goa, India

    Snehanshu Saha

  3. Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico

    Carlos A. Coello Coello

  4. Department of Mathematics, South Asian University, New Delhi, Madhya Pradesh, India

    Jagdish C. Bansal

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Agarwal, A., Trivedi, R., Goyal, S.R., Ahmed, I. (2024). Seizure Detection by Analyzing EEG Signals Using Deep Learning Networks. In: Das, S., Saha, S., Coello Coello, C.A., Bansal, J.C. (eds) Advances in Data-Driven Computing and Intelligent Systems. ADCIS 2023. Lecture Notes in Networks and Systems, vol 891. Springer, Singapore. https://doi.org/10.1007/978-981-99-9524-0_6

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  • DOI: https://doi.org/10.1007/978-981-99-9524-0_6

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  • Online ISBN: 978-981-99-9524-0

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