Adaptive EEG-Based Alertness Estimation System by Using ICA-Based Fuzzy Neural Networks

Drivers' fatigue has been implicated as a causal factor in many accidents. The development of human cognitive state monitoring system for the drivers to prevent accidents behind the steering wheel has become a major focus in the field of safety driving. It requires a technique that can continuo...

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Veröffentlicht in:	IEEE transactions on circuits and systems. I, Regular papers Jg. 53; H. 11; S. 2469 - 2476
Hauptverfasser:	Lin, Chin-Teng, Ko, Li-Wei, Chung, I-Fang, Huang, Teng-Yi, Chen, Yu-Chieh, Jung, Tzyy-Ping, Liang, Sheng-Fu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2006 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accidents Adaptive systems Alertness Alertness estimation Drivers Driving Dynamical systems electroencephalogram (EEG) Fatigue Fuzzy Fuzzy neural networks Humans ICA-mixture- model-based self-constructing fuzzy neural networks (ICAFNN) Independent component analysis independent component analysis (ICA) Interference Monitoring Neural networks power spectrum analysis Safety Spectrum analysis Studies Wheels Working environment noise
ISSN:	1549-8328, 1558-0806
Online-Zugang:	Volltext
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