Research on tiredness detection method based on fusion of face image and EEG information

Drivers in fatigue state tend to have slow response, distraction, and rising operational errors, resulting in reduced reliability of driver-controlled vehicles and increased risk of traffic accidents. It is necessary to detect mental state of drivers, so that we can send out alarm and take corresponding measures timely before traffic accidents. As important physiological indexes of human body, EEG and image have been widely used in medical diagnosis, attention analysis and other fields. This paper mainly studies fatigue feature extraction algorithm and fatigue detection method based on single-mode and multi-modal information. Experiments were also designed to evaluate the proposed fatigue detection methods. The results show that the fatigue detection based on the presented multi-modal information fusion method have greatly improved the accuracy and adaptability.