ID | 19600 |
Eprint ID | 19600
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フルテキストURL | |
著者 |
平松 靖隆
Okayama University
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抄録 | 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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発行日 | 2009-11-12
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出版物タイトル |
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
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出版物タイトル(別表記) | IEEE SMC Hiroshima Chapter
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巻 | 2009巻
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号 | 1号
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出版者 | IEEE SMC Hiroshima Chapter
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開始ページ | 348
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終了ページ | 353
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ISSN | 1883-3977
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NCID | BB00577064
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資料タイプ |
会議発表論文
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言語 |
英語
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著作権者 | IEEE SMC Hiroshima Chapter
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イベント | 5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
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イベント地 | 東広島市
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イベント地の別言語 | Higashi-Hiroshima City
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論文のバージョン | publisher
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査読 |
有り
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Eprints Journal Name | IWCIA
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