Neural Network Based Epileptic EEG Detection and Classification

  • Shivam Gupta
    Indian Institute of Information Technology shivi98g[at]
  • Jyoti Meena
    National Institute of Technology
  • O.P Gupta
    Punjab Agricultural University


Timely diagnosis is important for saving the life of epileptic patients. In past few years, a lot of treatment are available for epilepsy. These treatments involve use of medicines. But these are not effective in controlling frequency of seizure. There is need of removal of affected region using surgery. Electroencephalogram (EEG) is a widely used technique for monitoring the brain activity and widely popular for seizure region detection. It is used before surgery for locating affected region. This manual process using EEG graphs is time consuming and requires deep expertise. In the present paper, a model has been proposed that preserves the true nature of EEG signal in form of textual one dimensional vector. The proposed model achieves a state of art performance for Bonn University dataset giving an average sensitivity, specificity of 81% and 81.4% respectively for classification among all five classes. Also for binary classification achieving 99.9%, 99.5% score value for specificity and sensitivity instead of 2D models used by other researchers. Thus developed system will significantly help neurosurgeons in increasing their performance.
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[12] downloaded, Jan 2020.
Gupta, S., Meena, J., & Gupta, O. (2020). Neural Network Based Epileptic EEG Detection and Classification. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 9(2), 23–32.


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Author Biographies

Shivam Gupta

Indian Institute of Information Technology
Department of Computer Engineering, Indian Institute of Information Technology (Mentor National Institute of Technology, Kurukshetra), Sonepat, Haryana, India

Jyoti Meena

National Institute of Technology
Department of Computer Engineering, National Institute of Technology, Kurukshetra, Haryana, India

O.P Gupta

Punjab Agricultural University
Incharge, IT Section, COA, Punjab Agricultural University, Ludhiana, Punjab, India