Driver drowsiness detection via PPG biosignals by using multimodal head support

Sukgyu Koh, Bo Ram Cho, Jong Il Lee, Soon O. Kwon, Suwoong Lee, Joon Beom Lim, Soo Beom Lee, Hyeok Dong Kweon

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

24 Scopus citations

Abstract

Drowsy driving can lead to accidents. Therefore, finding methods by which drowsy driving can be prevented is essential. This paper proposes a method of detecting drowsy driving that utilizes the Low Frequency (LF), High Frequency (HF), and LF/HF values of photoplethysmography (PPG) signals measured on fingers and earlobes. In experiments conducted, of 20 subjects, drowsiness was identified in 14 through PPG signals from their fingers. Further, of those 14 drowsy drivers, PPG signals from the earlobes of eight were also used to determine whether they were drowsy while driving.

Original languageEnglish
Title of host publication2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages383-388
Number of pages6
ISBN (Electronic)9781509064656
DOIs
StatePublished - 8 Nov 2017
Event4th International Conference on Control, Decision and Information Technologies, CoDIT 2017 - Barcelona, Spain
Duration: 5 Apr 20177 Apr 2017

Publication series

Name2017 4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
Volume2017-January

Conference

Conference4th International Conference on Control, Decision and Information Technologies, CoDIT 2017
Country/TerritorySpain
CityBarcelona
Period5/04/177/04/17

Keywords

  • Biosignals
  • Drowsy driving
  • Electrocardiogram (ECG)
  • Photoplethysmography (PPG)

Fingerprint

Dive into the research topics of 'Driver drowsiness detection via PPG biosignals by using multimodal head support'. Together they form a unique fingerprint.

Cite this