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Driver drowsiness detection: A comparison between intrusive and non-intrusive signal acquisition methods
University of Porto.
University of Porto.
Instituto Superior de Engenharia de Lisboa.
Swedish National Road and Transport Research Institute, Traffic and road users, Human Factors in the Transport System.ORCID iD: 0000-0003-4134-0303
2019 (English)In: Proceedings - European Workshop on Visual Information Processing, EUVIP, Institute of Electrical and Electronics Engineers Inc. , 2019, article id 8611704Conference paper, Published paper (Refereed)
Abstract [en]

Driver drowsiness is a major cause of road accidents, many of which result in fatalities. A solution to this problem is the inclusion of a drowsiness detector in vehicles to alert the driver if sleepiness is detected. To detect drowsiness, physiologic, behavioral (visual) and vehicle-based methods can be used, however, only measures that can be acquired non-intrusively are viable in a real life application. This work uses data from a real-road experiment with sleep deprived drivers to compare the performance of driver drowsiness detection using intrusive acquisition methods, namely electrooculogram (EOG), with camera-based, non-intrusive, methods. A hybrid strategy, combining the described methods with electrocardiogram (ECG) measures, is also evaluated. Overall, the obtained results show that drowsiness detection performance is similar using non-intrusive camera-based measures or intrusive EOG measures. The detection performance increases when combining two methods (ECG + visual) or (ECG + EOG).

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2019. article id 8611704
Keywords [en]
Fatigue (human), Detection, Driver, Measurement, Eye movement, Camera, ECG
National Category
Applied Psychology
Research subject
80 Road: Traffic safety and accidents, 841 Road: Road user behaviour; 90 Road: Vehicles and vehicle technology, 914 Road: ITS och vehicle technology
Identifiers
URN: urn:nbn:se:vti:diva-13724DOI: 10.1109/EUVIP.2018.8611704Scopus ID: 2-s2.0-85062709894ISBN: 9781538668979 (print)OAI: oai:DiVA.org:vti-13724DiVA, id: diva2:1313222
Conference
7th European Workshop on Visual Information Processing, EUVIP 2018, 26 November 2018 through 28 November 2018
Available from: 2019-05-02 Created: 2019-05-02 Last updated: 2019-06-27Bibliographically approved

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Ahlström, Christer

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf