Review on diverse approaches used for epileptic seizure detection using EEG signals

Authors

  • K Baskar Department of ECE, Pavai College of Technology, Affiliated to Anna University, Chennai
  • C Karthikeyan Department of EEE, K.S.Rangasamy college of Engineering, Affiliated to Anna University, Chennai

DOI:

https://doi.org/10.3329/bjms.v17i4.38307

Keywords:

Epileptic seizure detection, Electroencephalography, Automated epilepsy diagnosis, Neuro-informatics

Abstract

Epileptic seizure detection is a common diagnosis practiced by the expert clinicians through direct visual observation from the electroencephalography (EEG) signal. This detection by the expert clinicians is considered sensitive to bias and time consuming. Further, it suffers from various problems like unsustainability in larger dataset processing and low power detection. Hence, many computerized detection approaches are highly preferred to eliminate the aforementioned problems and to expedite the research in epilepsy seizure detection for aiding the medical professionals. Many such automated epilepsy diagnosis framework has been designed by various researches, which is made to operate in a single or in a combined manner with other domains. This study reviews different approaches, which is been designed to aid the human diagnosis using new avenues that explains the causes of epilepsy and seizures. Further, this study summarizes various methods used previously to analyze the epilepsy and seizures based on its state of art approach. Also, investigations are carried out in terms of performance evaluation to find the best suitable epileptic seizure detection technique in the application of Neuro-informatics.

Bangladesh Journal of Medical Science Vol.17(4) 2018 p.526-531

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Published

2018-09-19

How to Cite

Baskar, K., & Karthikeyan, C. (2018). Review on diverse approaches used for epileptic seizure detection using EEG signals. Bangladesh Journal of Medical Science, 17(4), 526–531. https://doi.org/10.3329/bjms.v17i4.38307

Issue

Vol. 17 No. 4 (2018)

Section

Review Article

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