Sleep Disorder Detection and Identification

Electroencephalogram (EEG) has been widely used for capturing the electrical human's brain activities for diagnosis and treatment purposes. One of the applications of EEG is to detect the sleep disorders include insomnia and stress-related disorder depend on the severity of the disorders. In this study, Ensemble Empirical Mode Decomposition (EEMD) method which is modified original Empirical Mode Decomposition (EMD) algorithm will be employed for recognition and identification of the EEG patterns and features. Besides that, ICA was applied to assist the process of isolating noise components and to explain the functions of different brain parts through the topographical scalp map. The application of ICA has shown to be an efficient tool for artifact extraction from EEG. Finally, with the combination of EEMD and ICA methods, the music stimulation has been proved that it can enhance the sleep quality of human compare to non-music stimulation.