An attempt to predict drowsiness by Bayesian estimation

Atsuo Murata, Yusuke Matsuda, Makoto Moriwaka, Takehito Hayami

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

15 Citations (Scopus)

Abstract

In this study, EEG (EEG-MPF, EEG-α/β), heart rate variability (RRV3), tracking error and subjective rating of fatigue (drowsiness) while performing a simulated driving task were measured. The relation between these measurements and drowsiness was analyzed. As a result, EEG-MPF tended to decrease with the increase of drowsiness. It tended that EEG-α/β, RRV3 and tracking error increased with the increase of drowsiness. Then, a method for predicting drowsiness by applying Bayesian estimation to physiological measurements was proposed. Bayesian estimation carries out a statistical inference using some kind of evidences or observations and calculating the probability that a hypothesis is true. An attempt was made to predicting drowsiness by applying Bayesian estimation to psychological parameters such as EEG-MPF, EEG-α/β, RRV3. As a result, it was suggested that the proposed method can predict the symptom of decreased consciousness (drowsiness).

Original languageEnglish
Title of host publicationProceedings of the SICE Annual Conference
Pages58-63
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

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Keywords

  • Bayesian estimation
  • drowsiness
  • EEG
  • HRV

ASJC Scopus subject areas

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

Cite this

Murata, A., Matsuda, Y., Moriwaka, M., & Hayami, T. (2011). An attempt to predict drowsiness by Bayesian estimation. In Proceedings of the SICE Annual Conference (pp. 58-63). [6060576]