@inproceedings{0a88e3134e584a2bbcb3d0e25d4cb5b1,
title = "Design and Application of Mental Fatigue Detection System Using Non-Contact ECG and BCG Measurement",
abstract = "Real-time mental fatigue monitoring system is very important in reducing safety accidents caused by fatigue driving. Adding complex monitoring devices and auxiliary equipment will put pressure on and even distract the user, so the unobtrusive monitoring system is currently the research hotspot. In this system, an unobtrusive mental fatigue assessment system was designed. ECG and Ballistocardiogram (BCG) can be captured by methods based on adaptive filter with such a design. After collecting step was finished, heart rate variability (HRV) and heart rate (HR) can be used for mental fatigue analysis according to data of 1-hour duration among 5 groups. The system can accurately and stably evaluate the mental fatigue state of the person without disturbance, which has certain application significance for mental fatigue and health monitoring in various scenarios such as cabs, factories, hospitals.",
keywords = "Capactive ECG, Fatigue, HRV, Unobtrusive",
author = "Yonghao Ma and Fuze Tian and Qinglin Zhao and Bin Hu",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 ; Conference date: 03-12-2018 Through 06-12-2018",
year = "2019",
month = jan,
day = "21",
doi = "10.1109/BIBM.2018.8621578",
language = "English",
series = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1508--1513",
editor = "Harald Schmidt and David Griol and Haiying Wang and Jan Baumbach and Huiru Zheng and Zoraida Callejas and Xiaohua Hu and Julie Dickerson and Le Zhang",
booktitle = "Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018",
address = "United States",
}