A Motion Robust Remote-PPG Approach to Driver's Health State Monitoring
A Motion Robust Remote-PPG Approach to Driver's Health State Monitoring
复制标题
用于监测驾驶员健康状态的运动稳健远程 PPG 方法
DOI：
10.1007/978-3-319-54407-6_31
复制
发表时间：
2016
影响因子：
6.4
通讯作者：
Tzu
中科院分区：
文献类型：
--
作者：
Bing;Yun;Po;Meng;Tzu
随着个人保健意义的日益凸显，驾驶员的生理状态已不再是一个可以忽略的问题。在人类健康状况的所有指标中，心率（HR）是最基本的指标之一。常用的心率测量是接触式的，在车辆应用中可能会导致驾驶员分心和不适。为了解决这个问题，远程光电容积描记术（rPPG）被用于经由网络摄像机在一定距离处监测HR。然而，rPPG并非没有缺陷。rPPG技术的主要关注点是来自任意运动的潜在非鲁棒性结果。因此，本文的贡献在于克服汽车行驶时的运动噪声，并能很好地监测驾驶员的健康状况，提高公共安全。该算法不仅在室内环境中，但以及室外驾驶，其中包含更多的不可预测的运动进行了研究。采用基于色度特征的k-近邻（kNN）分类器，均方误差可从30.6次/min降至2.79次/min，接近医疗仪器水平。该方法可应用于高级驾驶员辅助系统中提高驾驶安全性。
With the surging significance of personal health care, driver’s physiological state is no longer negligible nowadays. Among all the indicators of health state in human, heart rate (HR) is one of the most cardinal indicators. The commonly used HR measurement is contact-type, might result in driver’s distraction and discomfort in the vehicle applications. To cope with this problem, remote photoplethysmography (rPPG) is utilized to monitor HR at a distance via a web camera. Nevertheless, the rPPG is not without its flaw. The main concern of the rPPG technique is the potential not-robustness result from the arbitrary motion. Consequently, the contribution of this paper is to conquer the motion noise when the car is driving and the driver’s health state is well monitored to enhance the public safety. The proposed algorithm is investigated in not only the indoor environment but as well the outdoor driving, which contains much more unpredictable motion. With k-nearest neighbor (kNN) classifier on chrominance-based features, the mean square error can be reduced from 30.6 to 2.79 bpm, approaching the medical instrument level. The proposed method can be applied to human improving driving safety for Advanced Driver Assistance Systems.