Utilization of a combined EEG/NIRS system to predict driver drowsiness

Collection with item attached
2017
Item details URL
http://open-repository.kisti.re.kr/cube/handle/open_repository/486803.do
DOI
10.1038/srep43933
Title
Utilization of a combined EEG/NIRS system to predict driver drowsiness
Description
This work was supported by Hyundai Next Generation Vehicle (NGV (SCJ)),Basic Science Research Program (#2013R1A1A1A2009029 (SCJ),#2013R1A1A2013625 (JGK)), SGER grant (#2015R1D1A1A02062382 (JGK)) andBrain Research Program (#2016M3C7A1905475 (JGK, SCJ)) through theNational Research Foundation of Korea funded by the Ministry of Science,ICT & Future Planning, the Traditional Korean Medicine R&D Programfunded by the Ministry of Health and Welfare through the Korea HealthIndustry Development Institute (HI15C0190 (JGK)), a grant from Small andMedium Business Administration (S2273981), GIST Research Institute (JGK,SCJ), and "Biomedical Integrated Technology Research" Project through agrant provided by GIST in 2016 (JGK). We would like to send a specialthanks to Ms. Eloise Anguluan and Mr. Soongho Park for their help incorrecting grammar.
abstract
The large number of automobile accidents due to driver drowsiness is a critical concern of many countries. To solve this problem, numerous methods of countermeasure have been proposed. However, the results were unsatisfactory due to inadequate accuracy of drowsiness detection. In this study, we introduce a new approach, a combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG and NIRS signals have been measured during a simulated driving task, in which subjects underwent both awake and drowsy states. The blinking rate, eye closure, heart rate, alpha and beta band power were used to identify subject's condition. Statistical tests were performed on EEG and NIRS signals to find the most informative parameters. Fisher's linear discriminant analysis method was employed to classify awake and drowsy states. Time series analysis was used to predict drowsiness. The oxyhemoglobin concentration change and the beta band power in the frontal lobe were found to differ the most between the two states. In addition, these two parameters correspond well to an awake to drowsy state transition. A sharp increase of the oxy-hemoglobin concentration change, together with a dramatic decrease of the beta band power, happened several seconds before the first eye closure.
provenance
Made available in Cube on 2018-09-28T16:17:21Z (GMT). No. of bitstreams: 0
language
English
author
Thien Nguyen
Ahn, Sangtae
Jang, Hyojung
Jun, Sung Chan
Kim, Jae Gwan
orcid
Ahn, Sangtae/0000-0001-9487-5649; JUN, SUNG CHAN/0000-0001-5357-4436
accessioned
2018-09-28T16:17:21Z
available
2018-09-28T16:17:21Z
issued
2017
citation
SCIENTIFIC REPORTS(7)
issn
2045-2322
uri
http://open-repository.kisti.re.kr/cube/handle/open_repository/486803.do
Funder
보건복지부
Funding Program
한의약선도기술개발
Project ID
1465020768
Jurisdiction
Rep.of Korea
Project Name
Technology development of blood flow and metabolism measurement during cupping therapy with a variation of vacuum pressure and time
rights
openAccess
type
article


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