標題: Assessment of Mental Fatigue: An EEG-based Forecasting System for Driving Safety
作者: Liu, Yu-Ting
Lin, Yang-Yin
Wu, Shang-Lin
Hsieh, Tsung-Yu
Lin, Chin-Teng
電控工程研究所
腦科學研究中心
Institute of Electrical and Control Engineering
Brain Research Center
關鍵字: Electroencephalography (EEG);functional-link recurrent self-evolving fuzzy neural network (FL-RSEFNN);brain-computer interface (BCI);driving safety
公開日期: 1-一月-2015
摘要: This study proposes an EEG-based forecasting system based on a functional-link recurrent self-evolving fuzzy neural network (FL-RSEFNN) for assessing mental fatigue during a highway driving task. Drivers\' cognitive states significantly affect driving safety, especially for fatigue or drowsy driving which is one of common factors to endanger individuals and the public safety. In this study, a FL-RSEFNN employs an on-line gradient descent (GD) learning rule to address the EEG regression problem in brain dynamics for estimation of driving fatigue. We analyze brain dynamics in a car driving task, which is constructed in a simulated virtual reality (VR) environment. The EEG-based forecasting system is evaluated using the generalized cross-subject approach, and the results indicate that the FL-RSEFNN is superior to state-of-the-art models regardless of the use of recurrent or non-recurrent structures.
URI: http://dx.doi.org/10.1109/SMC.2015.561
http://hdl.handle.net/11536/129828
ISBN: 978-1-4799-8696-5
ISSN: 1062-922X
DOI: 10.1109/SMC.2015.561
期刊: 2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS
起始頁: 3233
結束頁: 3238
顯示於類別:會議論文