Spectral information of EEG signals with respect to epilepsy classification

• Main Author: Markos G. Tsipouras
• Format: Article
• Language: English
• Published: SpringerOpen 2019-02-01
• Series: EURASIP Journal on Advances in Signal Processing
• Subjects: EEG signal processing; EEG spectral analysis; EEG frequency sub-bands; Epilepsy
• Online Access: http://link.springer.com/article/10.1186/s13634-019-0606-8

Abstract Background The spectral information of the EEG signal with respect to epilepsy is examined in this study. Method In order to assess the impact of the alternative definitions of the frequency sub-bands that are analysed, a number of spectral thresholds are defined and the respective frequency sub-band combinations are generated. For each of these frequency sub-band combination, the EEG signal is analysed and a vector of spectral characteristics is defined. Based on this feature vector, a classification schema is used to measure the appropriateness of the specific frequency sub-band combination, in terms of epileptic EEG classification accuracy. Results The obtained results indicate that additional frequency band analysis is beneficial towards epilepsy detection. Conclusions This work includes the first systematic assessment of the impact of the frequency sub-bands to the epileptic EEG classification accuracy, and the obtained results revealed several frequency sub-band combinations that achieve high classification accuracy and have never been reported in the literature before.