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Automated epilepsy detection techniques from electroencephalogram signals: a review study

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Abstract

Epilepsy is a serious neurological condition which contemplates as top 5 reasons for avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy can be reduced by developing efficient automated epilepsy detection or prediction machines or software. To develop an automated epilepsy detection framework, it is essential to properly understand the existing techniques and their benefit as well as detriment also. This paper aims to provide insight on the information about the existing epilepsy detection and classification techniques as they are crucial for supporting clinical-decision in the course of epilepsy treatment. This review study accentuate on the existing epilepsy detection approaches and their drawbacks. This information presented in this article will be helpful to the neuroscientist, researchers as well as to technicians for assisting them in selecting the reliable and appropriate techniques for analyzing epilepsy and developing an automated software system of epilepsy identification.

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  1. Institute for Sustainable Industries & Liveable Cities, Victoria University, Footscray, Australia

    Supriya Supriya, Siuly Siuly, Hua Wang & Yanchun Zhang

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  1. Supriya Supriya
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Supriya, S., Siuly, S., Wang, H. et al. Automated epilepsy detection techniques from electroencephalogram signals: a review study. Health Inf Sci Syst 8, 33 (2020). https://doi.org/10.1007/s13755-020-00129-1

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