Driver's EEG Eye Movement Fatigue Detection Based on CMAC

Abstract

This paper mainly studies the EEG signals, eye movement signals, ECG signal analysis under natural humancomputer interaction and the fusion of multiple information sources to generate decision signals to judge whether the driver is fatigued or not. It is mainly used to automatically monitor the driver’s mental state in real time while the vehicle is running. Alerts when the driver just shows signs of fatigue. Forced deceleration or even forced parking in the event of a dangerous situation. The analysis of EEG signals mainly includes EEG signal acquisition, feature extraction and classification. The analysis of eye movement signals mainly includes face detection, human eye positioning, pupil and eye angle detection, etc. Integration and implementation mainly include the integration of multiple information sources, decision signal transmission, and fatigue driving monitoring system design.