Sleep spindles analysis using sparse bump modeling

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.