期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2019
卷号：7
期号：6
页码：3366-3376
DOI：10.15680/IJIRCCE.2019. 0706019
出版社：S&S Publications
摘要：Driver fatigue is a leading factor in road accidents that can cause severe accidents. Existing fatigue
detection works focus on vision and electroencephalography(EEG) based means of detection. However, vision-based
approaches suffer from view-blocking or vision distortion problems and EEG-based systems are intrusive, and the
drivers have to use/wear the devices with inconvenience or additional costs. In our work, we propose a novel Wi-Fi
signals based fatigue detection approach, called WiFind to overcome the drawbacks as associated with the current
works. WiFind is simple and (wearable) device-free. It can detect the fatigue symptoms in the vehicle without relying
on any visual image or video. By applying self-adaptive method, it can recognize the body features of drivers in
multiple modes. It applies Hilbert-Huang transform(HHT) based pattern extract method results in accuracy increase in
motion detection mode. WiFind can be easily deployed in a commodity Wi-Fi infrastructure, and we have evaluated its
performance in real driving environments. The experimental results have shown that WiFind can achieve the
recognition accuracy of 89.6% in a single driver scenario.
关键词：Driver fatigue detection; Channel State Information; Wireless signal processing;
