EEG Analysis of Wake-sleep Data using UMACE filter

Electroencephalogram (EEG) signal has been found to be the most predictive and reliable indicator in wake-sleep research. It is a real time signal that reflects the brain states of a subject including the alertness. However the study of wake-sleep condition using EEG signal is difficult due to the complexity of the EEG signal itself. The exact underlying dynamics of the EEG data is still questionable. EEG signal varies from one individual to another and has an inter variability in the same physiological state. It is hard to compare the EEG to the specific pattern of individual or situation. This paper tries to investigate the use of UMACE in distinguish between awake and sleep state of a subject. Normal EEG data from individual is used as an input in building UMACE filter. From the result, we find UMACE has the capability to distinguish awake and sleep state of a subject.