| Estimation of drowsiness level based on eyelid closure and heart rate variability. | |
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MedLine Citation:
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PMID: 19964977 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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This paper presents a novel method that uses eyelid closure and heart rate variability to estimate the driver's drowsiness level. Laboratory experiments were conducted by using a proprietary driving simulator, which induced drowsiness among the test drivers. The purposes of these experiments were to obtain the electrocardiogram (ECG) and the eye-blink video sequences. Also the drivers were monitored through a video camera. The changes in facial expression of the drivers were used as a standard index of drowsiness level. Error-Correcting Output Coding (ECOC) was employed as a multi-class classifier to estimate the drowsiness level. We extended the ordinary ECOC using a loss function for decoding procedure to obtain class tendencies of each drowsiness level. We used the Loss-based Decoding ECOC (LD-ECOC) to classify the drowsiness level. As a result, we obtained an extraordinarily high accuracy for estimation of drowsiness level. |
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Authors:
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Ayumi Tsuchida; Md Bhuiyan; Koji Oguri |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference Volume: 1 ISSN: 1557-170X ISO Abbreviation: Conf Proc IEEE Eng Med Biol Soc Publication Date: 2009 |
Date Detail:
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Created Date: 2009-12-07 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101243413 Medline TA: Conf Proc IEEE Eng Med Biol Soc Country: United States |
Other Details:
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Languages: eng Pagination: 2543-6 Citation Subset: IM |
Affiliation:
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Graduate school of Information Science and Technology, Aichi Prefectural University, Aichi 480-1198, Japan. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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