Epileptic seizure identification using entropy of FBSE based EEG rhythms.
Biomedical Signal Processing and Control(2019)
摘要
•The Fourier–Bessel series expansion (FBSE) based rhythms separation has been introduced for electroencephalogram (EEG) signals classification which includes healthy subjects and epilepsy patients.•The weighted multiscale Renyi permutation entropy (WMRPE) feature has been explored which gives amplitude information of patterns as well as multi scale analysis of these EEG signals.•The proposed method has been also tested with additive white Gaussian noise (AWGN) at different signal to noise ratio (SNR) levels.•The research work also includes seven different classification problems in order to detect epileptic seizure with good classification accuracy results.
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关键词
Electroencephalogram (EEG),Rhythms,Fourier–Bessel series expansion (FBSE),Entropy,Classification
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