Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition

Erhan Bergil; Murat Yıldız

TR

Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition

Abstract

Several features are used in order to evaluate the epileptic components of the Electroencephalogram (EEG) signals. The generated feature matrices are applied to different classifiers as input. It is aimed to detect different epileptic stage. In this study, performances of Wavelet Transform and Empirical Mode Decomposition methods which are used commonly to extract feature in epilepsy studies have been compared. EEG signals, which contain normal and seizure stages, have been divided into 5 sub-bands including different frequency components via both methods. Feature matrices have been obtained by calculating mean, standard deviation, entropy and power for each sub-band. The feature matrices have been classified by k-nearest neighbor algorithm and results have been compared for both feature extraction methods. Analysis has been implemented patient-specifically for 14 patients with epilepsy.

Keywords

Seizure detection,feature extraction; wavelet transform; empirical mode decomposition

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Details

Primary Language

English

Subjects

-

Journal Section

-

Authors

Erhan Bergil

Murat Yıldız This is me

Publication Date

November 7, 2016

Submission Date

November 25, 2016

Acceptance Date

-

Published in Issue

Year 2016 Volume: 5

IZ

https://izlik.org/JA69TM42LN

APA

Bergil, E., & Yıldız, M. (2016). Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition. Journal of New Results in Science, 5, 288-297. https://izlik.org/JA69TM42LN

AMA

1.Bergil E, Yıldız M. Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition. JNRS. 2016;5:288-297. https://izlik.org/JA69TM42LN

Chicago

Bergil, Erhan, and Murat Yıldız. 2016. “Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition”. Journal of New Results in Science 5 (November): 288-97. https://izlik.org/JA69TM42LN.

EndNote

Bergil E, Yıldız M (November 1, 2016) Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition. Journal of New Results in Science 5 288–297.

IEEE

[1]E. Bergil and M. Yıldız, “Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition”, JNRS, vol. 5, pp. 288–297, Nov. 2016, [Online]. Available: https://izlik.org/JA69TM42LN

ISNAD

Bergil, Erhan - Yıldız, Murat. “Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition”. Journal of New Results in Science 5 (November 1, 2016): 288-297. https://izlik.org/JA69TM42LN.

JAMA

1.Bergil E, Yıldız M. Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition. JNRS. 2016;5:288–297.

MLA

Bergil, Erhan, and Murat Yıldız. “Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition”. Journal of New Results in Science, vol. 5, Nov. 2016, pp. 288-97, https://izlik.org/JA69TM42LN.

Vancouver

1.Erhan Bergil, Murat Yıldız. Comparison of Seizure Detection Performances of Features Based on Wavelet Transform and Empirical Mode Decomposition. JNRS [Internet]. 2016 Nov. 1;5:288-97. Available from: https://izlik.org/JA69TM42LN