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    Stockwell transform for epileptic seizure detection from EEG signals

    , Article Biomedical Signal Processing and Control ; Volume 38 , 2017 , Pages 108-118 ; 17468094 (ISSN) Kalbkhani, H ; Shayesteh, M. G ; Sharif University of Technology
    Epilepsy is the most common disorder of human brain. The goal of this paper is to present a new method for classification of epileptic phases based on the sub-bands of electroencephalogram (EEG) signals obtained from the Stockwell transform (ST). ST is a time-frequency analysis that not only covers the advantages of both short-time Fourier transform (FT) and wavelet transform (WT), but also overcomes their shortcomings. In the proposed method, at first, EEG signal is transformed into time-frequency domain using ST and all operations are performed in the new domain. Then, the amplitudes of ST in five sub-bands, namely delta (δ), theta (θ), alpha (α), beta (β), and gamma (γ), are computed. In...