ID | 19600 |
Eprint ID | 19600
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FullText URL | |
Author |
Hiramatsu, Yasutaka
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Abstract | The aim of this study was to propose a useful prediction method of drowsy state of drivers, so that the result is applicable to the development of ITS (Intelligent Transportation System) that can warn drivers of their low arousal state and to prevent driving under low arousal level from occurring. The EEG (electroencephalography) and ECG (electrocardiography) during a monotonous task was measured, and it was investigated how these measures change under the low arousal (drowsy) state. The EEG measurement was added to in order to monitor arousal level more the time series of mean power frequency of EEG was plotted on X-bar control chart. Heart rate variability (HRV) measure RRV3 were derived on the basis of R-R intervals (interbeat intervals) obtained from ECG. Using a Bayesian probability, we tried to predict the timing when the participant actually felt drowsy. As a result, the prediction accuracy differed by the state of participant. When the drowsiness of participant was remarkable, the prediction method was effective to some extent. On the other hand, the proposed method could not predict the drowsy state reliably when the participant did not feel drowsiness to a larger extent.
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Published Date | 2009-11-12
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Publication Title |
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
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Publication Title Alternative | IEEE SMC Hiroshima Chapter
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Volume | volume2009
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Issue | issue1
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Publisher | IEEE SMC Hiroshima Chapter
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Start Page | 348
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End Page | 353
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ISSN | 1883-3977
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NCID | BB00577064
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Content Type |
Conference Paper
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language |
English
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Copyright Holders | IEEE SMC Hiroshima Chapter
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Event Title | 5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
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Event Location | 東広島市
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Event Location Alternative | Higashi-Hiroshima City
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File Version | publisher
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Refereed |
True
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Eprints Journal Name | IWCIA
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