An affordable approach for detecting drivers' drowsiness using EEG signal analysis

Traffic-related reports identify drowsiness as an important factor in traffic accidents. Mitigating traffic-related accidents due to drowsiness requires a driver's drowsiness monitoring system, followed by an alert mechanism. This paper proposes a new technique that instantaneously detects whether the driver is awake or in stage-one sleep condition. The proposed technique is based on a real-time system that monitors and analyzes the EEG signal of the driver using a single dry-sensor EEG headset. Using this system, we were able to detect the driver's state in real time. When the EEG waves of the driver match that of the stage-one sleep, the system produces an audible alarm to alert him. The system has reached an average accuracy of 97.6% detecting sleep in a sample of 60 subjects using the statistical characteristics of the EEG waves. Compared with similar approaches, the proposed approach is more affordable, time-efficient and less complex.