The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article)

Negin Melek

doi:10.35377/saucis...1436915

EN

The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article)

Abstract

Electroencephalography (EEG), used to record the random electrical activity in brain, is a known medical test. In this test, a graphical waveform is obtained by measuring the electrical activity of the cells. In the medical world, the relationship between epilepsy and EEG can be understood by examining changes in brain activity during or between epileptic seizures. EEG is a useful tool in the early treatment and diagnosis of epilepsy. Whether seizures, generally known as abnormal electrical discharges in brain cells, are of epileptic origin, comes to light through EEG. The main goal of our study was to demonstrate the EEG rhythm effectiveness for the diagnosis of epilepsy in EEG data obtained from the epilepsy center of Bonn Freiburg University Hospital. Time domain feature extraction of EEG band classification results was examined in detail against the classification results of frequency domain feature extraction of EEG rhythms in healthy subjects and subjects with epilepsy. By extracting effective features from EEG data in both time and frequency domains, the k nearest neighbor (KNN) algorithm was used for the time and frequency domain. It cannot be overlooked that among the four methods used for performance evaluation in the designed model, the classification success of frequency domain features was more successful than that of time domain features. Using the KNN algorithm, healthy individuals and epilepsy patients with seizures were classified with 100% success.

Keywords

References

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Details

Primary Language

English

Subjects

Software Engineering (Other)

Journal Section

Research Article

Authors

Negin Melek ^*
0000-0001-5297-5545
Türkiye

Early Pub Date

August 23, 2024

Publication Date

August 31, 2024

Submission Date

February 14, 2024

Acceptance Date

May 30, 2024

Published in Issue

Year 2024 Volume: 7 Number: 2

DOI

https://doi.org/10.35377/saucis...1436915

IZ

https://izlik.org/JA79ZB32SB

Cite

RIS / Bibtex

APA

Melek, N. (2024). The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article). Sakarya University Journal of Computer and Information Sciences, 7(2), 138-155. https://doi.org/10.35377/saucis...1436915

AMA

1.Melek N. The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article). SAUCIS. 2024;7(2):138-155. doi:10.35377/saucis.1436915

Chicago

Melek, Negin. 2024. “The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article)”. Sakarya University Journal of Computer and Information Sciences 7 (2): 138-55. https://doi.org/10.35377/saucis. 1436915.

EndNote

Melek N (August 1, 2024) The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article). Sakarya University Journal of Computer and Information Sciences 7 2 138–155.

IEEE

[1]N. Melek, “The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article)”, SAUCIS, vol. 7, no. 2, pp. 138–155, Aug. 2024, doi: 10.35377/saucis...1436915.

ISNAD

Melek, Negin. “The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article)”. Sakarya University Journal of Computer and Information Sciences 7/2 (August 1, 2024): 138-155. https://doi.org/10.35377/saucis. 1436915.

JAMA

1.Melek N. The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article). SAUCIS. 2024;7:138–155.

MLA

Melek, Negin. “The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article)”. Sakarya University Journal of Computer and Information Sciences, vol. 7, no. 2, Aug. 2024, pp. 138-55, doi:10.35377/saucis. 1436915.

Vancouver

1.Negin Melek. The Importance of Rhythm Activity in Epilepsy EEG Signal Classification (An Educational Article). SAUCIS. 2024 Aug. 1;7(2):138-55. doi:10.35377/saucis. 1436915