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Detection of High Frequency Oscillations in EEG Recordings
, M.Sc. Thesis Sharif University of Technology ; Shamsollahi, Mohammad Bagher (Supervisor)
Abstract
EEG Signal Processing has really important role in study of nerves system and nervous diseases. In most applications, signals occur in the frequency band ranging below 100 Hz are considered. In this study, the higher frequency components of the signal, especially in patients with epilepsy, reported which they are called high frequency oscillations (HFOs). Some sources considered that HFOs are up to 1000 Hz and some other considered up to 2500 Hz. In study of HFOs, the high frequencies between 100 and 200 Hz that are called ripple and seen in normal mode are separated from the faster frequencies from 200 to 500 Hz and these components can accurately help to detect epileptic foci generator (to...
Detection of fast ripples using Hidden Markov Model
, Article 2014 21st Iranian Conference on Biomedical Engineering, ICBME 2014, 26 November 2014 through 28 November 2014 ; November , 2014 , Pages 348-352 ; 9781479974177 (ISBN) ; Montazeri, N ; Shamsollahi, M. B ; Kachenoura, A ; Wendung, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2014
Abstract
Studies show that High frequency oscillations (HFOs) can be used as a reliable biomarker of epileptogenic zone, thus many algorithms have been proposed to detect HFOs. Among the wide variety of HFOs, fast ripples (FRs) are important transient oscillations occurring in the frequency band ranging from 250 Hz to 600 Hz. The automatic detection of FRs can be degenerated by the presence of some 'pulse-like' events (commonly, the component of interictal epileptic spikes) associated with an increase of the signal energy in the high frequency bands, exactly as in the case of real FRs. The goal of this study is to propose a new method for automatic detection of fast ripples by using Hidden Markov...