Validation of an EEG-based Neurometric for online monitoring and detection of mental drowsiness while driving.


Journal

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
ISSN: 2694-0604
Titre abrégé: Annu Int Conf IEEE Eng Med Biol Soc
Pays: United States
ID NLM: 101763872

Informations de publication

Date de publication:
07 2022
Historique:
entrez: 10 9 2022
pubmed: 11 9 2022
medline: 14 9 2022
Statut: ppublish

Résumé

The driving drowsiness has been identified as one of the major causes of road traffic accidents, causing fatalities and permanent injuring. Drowsy drivers are prone to suddenly lose control of the car, mostly without any prior behavioral cue. The present study involved 19 participants in a simulated driving protocol, designed to induce mental drowsiness into the drivers. The objective of the study consisted in testing an innovative Electroencephalographic (EEG)-based index, the MDrow index, in detecting the driving drowsiness. Such an index, derived from parietal EEG channels, was already validated in our previous work achieving outstanding performance with respect to more conventional techniques. In this study, the possibility of obtaining a similar index from the frontal sites in order to foster its exploitation in real environments has been investigated. The results demonstrated the capability of the "frontal" MDrow index in evaluating the driving drowsiness experienced by the participants with performance comparable to that one previously validated over parietal sites. Also, the impact of the reduction of the electrodes number on index reliability has been investigated, in order to evaluate its compatibility with current wearable EEG devices.

Identifiants

pubmed: 36086194
doi: 10.1109/EMBC48229.2022.9871505
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3714-3717

Auteurs

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Classifications MeSH