TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Epileptic seizure classification of EEG time-series using rational discrete short-time fourier transform

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Artikkeli6909003
Sivut541-552
Sivumäärä12
JulkaisuIEEE Transactions on Biomedical Engineering
Vuosikerta62
Numero2
DOI - pysyväislinkit
TilaJulkaistu - 1 helmikuuta 2015
OKM-julkaisutyyppiA1 Alkuperäisartikkeli

Tiivistelmä

A system for epileptic seizure detection in electroencephalography (EEG) is described in this paper. One of the challenges is to distinguish rhythmic discharges from nonstationary patterns occurring during seizures. The proposed approach is based on an adaptive and localized time-frequency representation of EEG signals by means of rational functions. The corresponding rational discrete short-time Fourier transform (DSTFT) is a novel feature extraction technique for epileptic EEG data. A multilayer perceptron classifier is fed by the coefficients of the rational DSTFT in order to separate seizure epochs from seizure-free epochs. The effectiveness of the proposed method is compared with several state-of-art feature extraction algorithms used in offline epileptic seizure detection. The results of the comparative evaluations show that the proposed method outperforms competing techniques in terms of classification accuracy. In addition, it provides a compact representation of EEG time-series.

!!ASJC Scopus subject areas

Tutkimusalat

Julkaisufoorumi-taso