Design of a Fatigue Driving Warning System Utilizing Brain-Computer Interface (BCI) Technology

Fatigue driving significantly threatens road safety in China, causing a large number of traffic accidents. Traditional fatigue detection methods, such as facial expression recognition, often fail to accurately reflect a driver’s cognitive state. This paper introduces a brain-computer interface (BCI)-based early warning system for detecting driver fatigue using electroencephalogram (EEG) signals. The system, called the “Brain-Controlled Co-Pilot,” (BCCP) includes hardware for non-invasive EEG signal collection and amplification, along with software for signal processing, feature extraction, pattern recognition, and real-time analysis. By analyzing EEG signals, the system continuously monitors the driver’s attention level and issues timely alerts through visual, auditory, or tactile feedback when signs of fatigue are detected. The system also supports realtime data visualization and offers customizable settings for individual users. Experimental results confirm that the system effectively improves driver attention and reduces the risk of accidents caused by fatigue. The proposed BCI-based system holds significant potential for applications in health monitoring, virtual reality, education, smart homes, and driving safety.