Prediction of drowsiness using multivariate analysis of biological information and driving performance

Atsuo Murata, Yutaka Ohkubo, Makoto Moriwaka, Takehito Hayami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

The aim of this study was to predict drowsy states by applying multivariate analysis such as discrimination analysis and logistic regression model to biological information and establish a method to properly warn drivers of drowsy state. EEG, heart rate variability, EOG, and tracking error were used as evaluation measures of drowsiness. The drowsy states were predicted by applying discrimination analysis and logistic regression to these evaluation measures. The percentage correct prediction for discrimination analysis and logistic regression were 85% and 93%, respectively. The logistic regression model was found to lead to higher prediction accuracy.

Original languageEnglish
Title of host publicationProceedings of the SICE Annual Conference
Pages52-57
Number of pages6
Publication statusPublished - 2011
Event50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
Duration: Sep 13 2011Sep 18 2011

Other

Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011
CountryJapan
CityTokyo
Period9/13/119/18/11

Fingerprint

Logistics
Electroencephalography
Multivariate Analysis

Keywords

  • biological information
  • discrimination analysis
  • drowsiness
  • logistic regression
  • multivariate analysis
  • prediction technique

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Murata, A., Ohkubo, Y., Moriwaka, M., & Hayami, T. (2011). Prediction of drowsiness using multivariate analysis of biological information and driving performance. In Proceedings of the SICE Annual Conference (pp. 52-57). [6060575]

Prediction of drowsiness using multivariate analysis of biological information and driving performance. / Murata, Atsuo; Ohkubo, Yutaka; Moriwaka, Makoto; Hayami, Takehito.

Proceedings of the SICE Annual Conference. 2011. p. 52-57 6060575.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Murata, A, Ohkubo, Y, Moriwaka, M & Hayami, T 2011, Prediction of drowsiness using multivariate analysis of biological information and driving performance. in Proceedings of the SICE Annual Conference., 6060575, pp. 52-57, 50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011, Tokyo, Japan, 9/13/11.
Murata A, Ohkubo Y, Moriwaka M, Hayami T. Prediction of drowsiness using multivariate analysis of biological information and driving performance. In Proceedings of the SICE Annual Conference. 2011. p. 52-57. 6060575
Murata, Atsuo ; Ohkubo, Yutaka ; Moriwaka, Makoto ; Hayami, Takehito. / Prediction of drowsiness using multivariate analysis of biological information and driving performance. Proceedings of the SICE Annual Conference. 2011. pp. 52-57
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