Develop a portable device for real time drowsiness detection using DSP chip

• Main Authors: Pai-Yuan Tsai, 蔡百原
• Other Authors: Liang-Yu Shyu
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/37503259160187530089

碩士 === 中原大學 === 醫學工程研究所 === 95 === The existing statistical data and survey reports indicate that the driver’s fatigue is one of the major causes of traffic accidents. Fatigue can easily lead to drowsiness. However, driving in this situation may cause dangerous accident. Electroencephalogram (EEG) signals give important information about the vigilance states of any subject. In the past, EEG vigilance states used computer for off-line analysis and lacked real-time processing capability. Therefore, this study constructs a real-time EEG-based system for detecting driver drowsy. The proposed system uses a six channels active dry electrode system to acquire EEG non-invasively. In addition, it uses TMS320VC5510 DSP chip as the algorithm processor, and MSP430F149 chip as a controller to achieve portable real-time system. This study extracts two features of EEG signal: integral of EEG and zero crossings, and uses back propagation neural network to classify vigilance states. This system can discriminate alertness and drowsiness. When the system detects drowsiness, it will warn drivers against accident. The accuracy of the ANN is 79.1% for alertness and 90.91% for drowsiness state. Additionally, this custom-made dry electrode is better then traditional EEG electrodes. It can easily measure EEG through hair. We hope this dry electrode can replace traditional EEG electrode and applies in the daily life.