Kim Youn Sung, Baek Hyun Jae, Kim Jung Soo, Lee Haet Bit, Choi Jong Min, Park Kwang Suk
The Interdisciplinary Program in Medical and Biological Engineering, Graduate School, Seoul National University, Seoul, Republic of Korea.
Eur J Appl Physiol. 2009 Feb;105(3):365-72. doi: 10.1007/s00421-008-0912-6. Epub 2008 Nov 12.
A helmet-based system that was able to monitor the drowsiness of a soldier was developed. The helmet system monitored the electrocardiogram, electrooculogram and electroencephalogram (alpha waves) without constraints. Six dry electrodes were mounted at five locations on the helmet: both temporal sides, forehead region and upper and lower jaw strips. The electrodes were connected to an amplifier that transferred signals to a laptop computer via Bluetooth wireless communication. The system was validated by comparing the signal quality with conventional recording methods. Data were acquired from three healthy male volunteers for 12 min twice a day whilst they were sitting in a chair wearing the sensor-installed helmet. Experimental results showed that physiological signals for the helmet user were measured with acceptable quality without any intrusions on physical activities. The helmet system discriminated between the alert and drowsiness states by detecting blinking and heart rate variability (HRV) parameters extracted from ECG. Blinking duration and eye reopening time were increased during the sleepiness state compared to the alert state. Also, positive peak values of the sleepiness state were much higher, and the negative peaks were much lower than that of the alert state. The LF/HF ratio also decreased during drowsiness. This study shows the feasibility for using this helmet system: the subjects' health status and mental states could be monitored without constraints whilst they were working.
开发了一种能够监测士兵嗜睡情况的头盔式系统。该头盔系统可不受限制地监测心电图、眼电图和脑电图（阿尔法波）。六个干电极安装在头盔的五个位置：双侧颞部、额头区域以及上下颌带。电极连接到一个放大器，该放大器通过蓝牙无线通信将信号传输到笔记本电脑。通过将信号质量与传统记录方法进行比较来验证该系统。从三名健康男性志愿者身上获取数据，他们每天两次坐在椅子上戴着安装有传感器的头盔，持续12分钟。实验结果表明，头盔使用者的生理信号能够以可接受的质量进行测量，且不会对身体活动造成任何干扰。头盔系统通过检测从心电图中提取的眨眼和心率变异性（HRV）参数来区分警觉状态和嗜睡状态。与警觉状态相比，嗜睡状态下的眨眼持续时间和睁眼时间增加。此外，嗜睡状态的正峰值比警觉状态高得多，负峰值比警觉状态低得多。嗜睡期间低频/高频比值也降低。这项研究表明了使用这种头盔系统的可行性：在受试者工作时可以不受限制地监测他们的健康状况和精神状态。
