Traffic fatalities in recent years have become a serious concern to our society. Accidents caused by drivers' drowsiness have a high fatality rate due to the decline of drivers' abilities in perception, recognition, and vehicle control abilities while sleepy. Preventing such an accident requires a technique for detecting, estimating, and predicting the level of alertness of a driver and a mechanism to maintain the driver's maximum performance of driving. This paper proposed a system that combines electroencephalogram (EEG) power spectra estimation, independent component analysis and fuzzy neural network models to estimate drivers' cognitive state in a dynamic virtual-reality-based driving environment. Experimental results show that the quantitative driving performance can be accurately and successfully estimated through analyzing driver's EEG signals by the proposed system.
|頁（從 - 到）||152-155|
|期刊||Proceedings - IEEE International Symposium on Circuits and Systems|
|出版狀態||Published - 2005 十二月 1|
|事件||IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 - Kobe, Japan|
持續時間: 2005 五月 23 → 2005 五月 26
All Science Journal Classification (ASJC) codes