This paper studied the rule for the change of vigilance based on pulse wave. 10 participants were recruited in a 95-minute Mackworth clock test (MCT) experiment. During the experiment, the vigilance of all participants were evaluated by Karolinska sleepiness scale (KSS) and Stanford sleepiness scale (SSS), and behavior data (the reaction time and the accuracy of target) and pulse wave signal of the participants were recorded simultaneously. The result indicated that vigilance of the participants can be divided into 3 classes: the first 30 minutes for high vigilance level, the middle 30 minutes for general vigilance level, and the last 30 minutes for low vigilance level. Besides, time domain features such as amplitude of secondary peak, amplitude of peak and the latency of secondary peak decreased with the decrease of vigilance, while the amplitude of troughs increased. In terms of frequency domain features, the energy of 4 frequency band including 8.600 ~ 9.375 Hz, 11.720 ~ 12.500 Hz, 38.280 ~ 39.060 Hz and 39.060 ~ 39.840 Hz decreased with the decrease of vigilance. Finally, under the recognition model established by the 8 characteristics mentioned above, the average accuracy of three-classification results over the 10 participants was as high as 88.7%. The results of this study confirmed the feasibility of pulse wave in the evaluation of vigilance, and provided a new way for the real-time monitoring of vigilance.
Citation： CAO Yong, JIAO Xuejun, PAN Jinjin, JIANG Jin, FU Jiahao, XU Fenggang, YANG Hanjun. Research on vigilance detection based on pulse wave. Journal of Biomedical Engineering, 2017, 34(6): 817-823. doi: 10.7507/1001-5515.201704071 Copy