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Ergonomics Volume 60, 2017 - Issue 5
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Articles

A method for predicting the risk of virtual crashes in a simulated driving task using behavioural and subjective drowsiness measures

Atsuo MurataDepartment of Intelligent Mechanical Systems, Graduate School of Natural Science and Technology, Okayama University, Okayama, JapanCorrespondence[email protected]
,
Kensuke NaitohDepartment of Intelligent Mechanical Systems, Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan
&
Waldemar KarwowskiDepartment of Industrial Engineering & Management Systems, University of Central Florida, Orlando, FL, USA
Pages 714-730 | Received 06 Jul 2015, Accepted 08 Aug 2016, Published online: 29 Aug 2016

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Read on this site (1)

Sylwia I. Kaduk, Aaron P. J. Roberts & Neville A. Stanton. (2021) The circadian effect on psychophysiological driver state monitoring. Theoretical Issues in Ergonomics Science 22:5, pages 619-649.
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Articles from other publishers (4)

Atsuo Murata, Toshihisa Doi & Waldemar Karwowski. (2022) Sensitivity of PERCLOS70 to Drowsiness Level: Effectiveness of PERCLOS70 to Prevent Crashes Caused by Drowsiness. IEEE Access 10, pages 70806-70814.
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Venkata Phanikrishna Balam & Suchismitha Chinara. (2021) Development of single-channel electroencephalography signal analysis model for real-time drowsiness detection. Physical and Engineering Sciences in Medicine 44:3, pages 713-726.
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Atsuo Murata, Ippei Kita & Waldemar Karwowski. (2018) Assessment of Driver’s Drowsiness Based on Fractal Dimensional Analysis of Sitting and Back Pressure Measurements. Frontiers in Psychology 9.
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Muhammad Rizwan Ullah, Muhammad Aslam, Muhammad Imran Ullah & Martinez-Enriquez Ana Maria. 2018. Advances in Computational Intelligence. Advances in Computational Intelligence 272 281 .

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