IWCIA10-12-PG080017.pdf 423 KB
村田 厚生 Graduate School of Natural Science and Technology, Okayama University Kaken ID publons researchmap
西嶋 和之 Graduate School of Natural Science and Technology, Okayama University
The aim of this study was to identify a useful measure to estimate an arousal level of drivers, to apply the result to develop ITS (Intelligent Transportation System) that can warn drivers of their low arousal state and to prevent driving under low arousal level from occurring and contribute to the reduction of traffic accidents. The EEG(electroencephalography) during a monotonous task was measured, and it was investigated how these measures change under the low arousal (drowsy) state. The time series of mean power frequency of EEG was plotted on Xbar control chart. Under the low arousal state (drowsy state), the mean power frequency tended to be lower than central line (CL) and range between CL and lower control limit (LCL). Under the worst case, the mean power frequency was lower than LCL. The ratio of such intervals to total measurement period tended to increase under drowsy state. The mean power frequency was found to be effective for evaluating drowsiness of drivers.
Proceedings : Fourth International Workshop on Computational Intelligence & Applications
IEEE SMC Hiroshima Chapter
Fourth International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter ： IWCIA 2008
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