Sun Ye, Yu Xiong Bill
IEEE J Biomed Health Inform. 2014 Nov;18(6):1932-9. doi: 10.1109/JBHI.2014.2305403.
This paper describes an in-vehicle nonintrusive biopotential measurement system for driver health monitoring and fatigue detection. Previous research has found that the physiological signals including eye features, electrocardiography (ECG), electroencephalography (EEG) and their secondary parameters such as heart rate and HR variability are good indicators of health state as well as driver fatigue. A conventional biopotential measurement system requires the electrodes to be in contact with human body. This not only interferes with the driver operation, but also is not feasible for long-term monitoring purpose. The driver assistance system in this paper can remotely detect the biopotential signals with no physical contact with human skin. With delicate sensor and electronic design, ECG, EEG, and eye blinking can be measured. Experiments were conducted on a high fidelity driving simulator to validate the system performance. The system was found to be able to detect the ECG/EEG signals through cloth or hair with no contact with skin. Eye blinking activities can also be detected at a distance of 10 cm. Digital signal processing algorithms were developed to decimate the signal noise and extract the physiological features. The extracted features from the vital signals were further analyzed to assess the potential criterion for alertness and drowsiness determination.
本文介绍了一种用于驾驶员健康监测和疲劳检测的车载非侵入式生物电位测量系统。先前的研究发现，包括眼部特征、心电图（ECG）、脑电图（EEG）及其二级参数（如心率和心率变异性）在内的生理信号是健康状态以及驾驶员疲劳的良好指标。传统的生物电位测量系统需要电极与人体接触。这不仅会干扰驾驶员操作，而且对于长期监测目的而言也不可行。本文中的驾驶员辅助系统可以在不与人体皮肤进行物理接触的情况下远程检测生物电位信号。通过精密的传感器和电子设计，可以测量心电图、脑电图和眨眼情况。在高保真驾驶模拟器上进行了实验，以验证系统性能。结果发现该系统能够隔着衣物或头发检测心电图/脑电图信号，而无需接触皮肤。在10厘米的距离处也能检测到眨眼活动。开发了数字信号处理算法以减少信号噪声并提取生理特征。对从生命信号中提取的特征进行了进一步分析，以评估用于警觉性和嗜睡判定的潜在标准。
