An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods

Shen, Mingkan and Wen, Peng ORCID: https://orcid.org/0000-0003-0939-9145 and Song, Bo and Li, Yan ORCID: https://orcid.org/0000-0002-4694-4926 (2022) An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods. Biomedical Signal Processing and Control, 77:103820. pp. 1-8. ISSN 1746-8094


Abstract

Epilepsy is one of the most common complex brain disorders which is a chronic non-communicable disease caused by paroxysmal abnormal super-synchronous electrical activity of brain neurons. This paper proposed an electroencephalogram (EEG) based real-time approach to detect epilepsy seizures. Discrete wavelet transform and eight eigenvalues’ algorithms are applied to extract features in different sub-frequency bands. Then support vector machine is employed for three-classes classification of health control, seizure free and seizure active, and finally RUSBoosted tree Ensemble method is used for real-time seizure onset detection. The proposed algorithm is evaluated using two public datasets: one short-term dataset named UB and one long-term dataset named CHB-MIT. The results show that the algorithm achieves 97% accuracy and 96.67% sensitivity in the three-classes classification of health control, seizure-free and seizure-active groups in UB dataset, and 96.38% accuracy, 96.15% sensitivity, 3.24% false positive rate for the real time seizure onset detection in CHB-MIT Dataset.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Engineering (1 Jan 2022 -)
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Mathematics, Physics and Computing (1 Jan 2022 -)
Date Deposited: 25 Jul 2022 03:19
Last Modified: 10 Oct 2022 01:07
Uncontrolled Keywords: Discrete wavelet transform; EEG; Real-time seizure detection; RUSBoosted tree Ensemble; Support vector machine
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460207 Modelling and simulation
40 ENGINEERING > 4003 Biomedical engineering > 400303 Biomechanical engineering
Identification Number or DOI: https://doi.org/10.1016/j.bspc.2022.103820
URI: http://eprints.usq.edu.au/id/eprint/50199

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