TY - JOUR
T1 - Stretchable, transparent triboelectric nanogenerator as a highly sensitive self-powered sensor for driver fatigue and distraction monitoring
AU - Lu, Xiao
AU - Zheng, Li
AU - Zhang, Haodong
AU - Wang, Wuhong
AU - Wang, Zhong Lin
AU - Sun, Chunwen
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/12
Y1 - 2020/12
N2 - The ever-increasing automobiles have caused large number of traffic accidents every year. Fatigue driving and distracted driving are two main reasons for most of traffic accidents. Thus, intelligent transportation has attracted much attention. In this work, a stretchable polyacrylamide (PAAM) -LiCl-based triboelectric nanogenerator (PL-TENG) is utilized for the first time to monitor driver fatigue and distraction by attaching them to the face and neck of a driver. These PL-TENG sensors can detect eye closure, mouth closure, and neck rotation with high accuracy. Eye blink duration (BD), blink interval duration (BID), percentage of eyelid closure over time (PERCLOS) and yawn frequency (YF) are chosen as indicators of driver fatigue, while mouth closure and head positioning are chosen as indicators of driver distraction. The PL-TENG sensor has the characteristics of high voltage, high sensitivity and good biocompatibility, which demonstrates that the PL-TENG sensors are more sensitive than traditional fatigue detection systems. This work paves a new way for designing highly sensitive self-powered sensor in an intelligent transportation system.
AB - The ever-increasing automobiles have caused large number of traffic accidents every year. Fatigue driving and distracted driving are two main reasons for most of traffic accidents. Thus, intelligent transportation has attracted much attention. In this work, a stretchable polyacrylamide (PAAM) -LiCl-based triboelectric nanogenerator (PL-TENG) is utilized for the first time to monitor driver fatigue and distraction by attaching them to the face and neck of a driver. These PL-TENG sensors can detect eye closure, mouth closure, and neck rotation with high accuracy. Eye blink duration (BD), blink interval duration (BID), percentage of eyelid closure over time (PERCLOS) and yawn frequency (YF) are chosen as indicators of driver fatigue, while mouth closure and head positioning are chosen as indicators of driver distraction. The PL-TENG sensor has the characteristics of high voltage, high sensitivity and good biocompatibility, which demonstrates that the PL-TENG sensors are more sensitive than traditional fatigue detection systems. This work paves a new way for designing highly sensitive self-powered sensor in an intelligent transportation system.
KW - Driver fatigue and distraction detecting
KW - Intelligent transportation system
KW - Self-powered sensor
KW - Triboelectric nanogenerator
UR - http://www.scopus.com/inward/record.url?scp=85091342046&partnerID=8YFLogxK
U2 - 10.1016/j.nanoen.2020.105359
DO - 10.1016/j.nanoen.2020.105359
M3 - Article
AN - SCOPUS:85091342046
SN - 2211-2855
VL - 78
JO - Nano Energy
JF - Nano Energy
M1 - 105359
ER -