Title: A systematic review on detection and estimation algorithms of EEG signal for epilepsy

Authors: Shazia Hasan; Ameya K. Kulkarni; Sebamai Parija; Pradipta Kishore Dash

Addresses: Department of Electrical and Electronics Engineering, BITS Pilani Dubai, International Academic City, Dubai, UAE ' Department of Electrical and Electronics Engineering, BITS Pilani Dubai, International Academic City, Dubai, UAE ' Department of Electronics and Communication, I.T.E.R., Khandagiri, Bhubaneswar, India ' M.D.R.C., S'O'A University, Khandagiri, Bhubaneswar, India

Abstract: Epilepsy is the most common neurological disorder characterised by a sudden and recurrent neuronal firing in the brain. As EEG records the electrical activity of the brain so it helps to detect epilepsy of the subject. Early detection of epileptic seizure using EEG signal is most useful in several diagnoses. So aim of the work is to study and compare the different techniques used for feature extraction and classification algorithm. Epilepsy detection research is oriented to develop non-invasive and precise methods to allow accurate and quick diagnose. In this paper, we present a review of significant researches where we can find most suitable method among existing members to improve computing efficiency and detect epilepsy of the subject efficiently and accurately with lesser computational time. The database which is publicly available at Bonn University is taken.

Keywords: EEG signal; epilepsy; seizure detection algorithm; performance analysis; wavelet; Hilbert transform; empirical mode decomposition; EMD.

DOI: 10.1504/IJMEI.2021.113394

International Journal of Medical Engineering and Informatics, 2021 Vol.13 No.2, pp.143 - 156

Received: 04 Jul 2018
Accepted: 23 Mar 2019
Published online: 03 Mar 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article