@inproceedings{88fd0aa6f7014c5486e522be6cbdef99,
title = "Evaluation of operator{\textquoteright}s workload based on EEG signal",
abstract = "The degree of special vehicle{\textquoteright}s automation and intelligent is getting higher and higher. The efficient integration of operator and vehicle will become the fundamental guarantee of full efficiency. The operator{\textquoteright}s ability is the core element of the special vehicle capacity, but the operator{\textquoteright}s ability is limited. The subjective evaluation and objective physiological evaluation are combined in this paper. The operator gives the degree of mental fatigue through the narration after completing the task; at the same time, the operator{\textquoteright}s EEG signal is got. The mapping relation of EEG signal and mental fatigue degree is set up, and then the evaluation mathematical model of operator{\textquoteright}s workload based on EEG is built. This evaluation model can provide technical support for the new style special vehicles{\textquoteright} design and development.",
keywords = "EEG, Evaluation, Mental fatigue",
author = "Haiyan Niu and Shunwang Xiao and Qianxiang Zhou and Yaofeng He",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2018.; 17th International Conference on Man–Machine–Environment System Engineering, MMESE 2017 ; Conference date: 21-10-2017 Through 23-10-2017",
year = "2018",
doi = "10.1007/978-981-10-6232-2\_33",
language = "英语",
isbn = "9789811062315",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "279--286",
editor = "Shengzhao Long and Dhillon, \{Balbir S\}",
booktitle = "Man–Machine–Environment System Engineering - Proceedings of the 17th International Conference on MMESE",
address = "德国",
}