Feature Extraction Method for EEG Waves by Using MAP Detector of Input Signals with Multi-Discrete-Level Amplitude

摘要

In this paper, a dynamical model is introduced to develop a new automatic stage determination system of human sleep electroencephalogram (EEG) not using the wave pattern recognition step. The EEG generating mechanism is modeled by a damped system excited by impulse input process which subjects to Poission process whose amplitude has a transition property. Furthermore, A Maximum A Posteriori (MAP) method is modified to be applicable to the model. We can then extract useful information which is directly related to sleep stages based on the model and MAP detector.