On-line automatic detection of driver drowsiness using a single electroencephalographic channel

Antoine Picot (1) , Sylvie Charbonnier (1) , Alice Caplier (2)

1 GIPSA-SA-IGA - GIPSA - Signal et Automatique pour le Diagnostic et la Surveillance
2 GIPSA-GPIG - GIPSA - Géométrie, Perception, Images, Geste

In this paper, an on-line drowsiness detection algorithm using a single electroencephalographic (EEG) channel is presented. This algorithm is based on a means comparison test to detect changes of the alpha relative power ([8-12]Hz band). The main advantage of the method proposed is that the detection threshold is completely independent of drivers and does not need to be tuned for each person. This algorithm, which works on-line, has been tested on a huge dataset representing 60 hours of driving and give good results with nearly 85% of good detections and 20% of false alarms.

Mots clés: drowsiness detection; EEG; mean comparison test

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Antoine Picot, Sylvie Charbonnier, Alice Caplier. On-line automatic detection of driver drowsiness using a single electroencephalographic channel. EMBC 2008 - 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Aug 2008, Vancouver, Canada. pp.3864-3867, ⟨10.1109/IEMBS.2008.4650053⟩. ⟨hal-00359392⟩