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alpha-rhythm
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Investigation of the modulation between EEG alpha waves and slow/fast delta waves in children in different depths of Desflurane anesthesia
, Article IRBM ; Volume 31, Issue 1 , 2010 , Pages 55-66 ; 19590318 (ISSN) ; Shamsollahi, M. B ; Tirel, O ; Vosoughi Vahdat, B ; Wodey, E ; Senhadji, L ; Sharif University of Technology
2010
Abstract
Objectives: Investigation of the amplitude modulation of alpha-band EEG oscillations (i.e., grouping of alpha-band activities) by delta-band EEG activities in various depths of anesthesia (DOA). Methods: This modulation, which is a sort of phase dependent amplitude modulation, is studied in 10 children in various depths of Desflurane anesthesia. Two parameters are defined to quantify the modulation: strength of modulation (SOM) and phase of modulation (POM). SOM indicates to what extent delta and alpha activities are related to each other, and POM is the delta phase in which the alpha amplitude is maximal. These parameters are analyzed in different DOA for various formations of delta...
Properties of functional brain networks correlate frequency of psychogenic non-epileptic seizures
, Article Frontiers in Human Neuroscience ; Issue DEC , 2012 ; 16625161 (ISSN) ; Joudaki, A ; Jalili, M ; Rossetti, A. O ; Frackowiak, R. S ; Knyazeva, M. G ; Sharif University of Technology
Frontiers Media S. A
2012
Abstract
Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness metrics, respectively. Yet the number of PNES attacks per month correlated with a...
Stockwell transform for epileptic seizure detection from EEG signals
, Article Biomedical Signal Processing and Control ; Volume 38 , 2017 , Pages 108-118 ; 17468094 (ISSN) ; Shayesteh, M. G ; Sharif University of Technology
Abstract
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...