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Sleep spindle detection in sleep EEG signal using sparse bump modeling
, Article 2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011, Sharjah, 21 February 2011 through 24 February 2011 ; 2011 , Pages 196-199 ; 9781424470006 (ISBN) ; Ghanbari, Z ; Molaee-Ardekani, B ; Shamsollahi, M. B ; Penzel, T ; Sharif University of Technology
2011
Abstract
Sleep spindle is the hallmark of second stage of sleep in human being, which is defined as a rhythmic sequence with waxing and waning waves, whose frequency is approximately between 8 to 14 Hz, and its time duration is between 0.5 to 2 seconds. Bump modeling is a method for extracting regions with higher amounts of energy in a related time-frequency map. The bump model of the sleep spindle consists of a group of high energy bumps concentrating in approximately 8 to 14 Hz frequency band. In this study, it will be shown that the power of bumps of EEG can be used in automated detection of sleep spindle. The presented method sensitivity is 99.41% which shows high correctly detection rate, and...
Sleep spindles analysis using sparse bump modeling
, Article 2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011, Sharjah, 21 February 2011 through 24 February 2011 ; 2011 , Pages 37-40 ; 9781424470006 (ISBN) ; Najafi, M ; Shamsollahi, M. B ; Sharif University of Technology
Abstract
Sleep Spindle is the hallmark of the second stage of sleep in EEG signal. It had been analyzed using different methods, including Fourier transform, parametric and non-parametric models, higher order statistics and spectra, and also time-frequency methods such as wavelet transform, and matching pursuit. In this study, bump modeling has been used to analyze sleep spindle. Bump modeling is a method which represents the time-frequency map of signals with a number of elementary functions. Results of this work demonstrate that bump modeling is capable of analyzing different sleep spindle patterns in sleep EEG signals successfully