Monitoring drowsiness on-line using a single encephalographic channel

ISBN 978-953-307-013-1 20 pagesInternational audienceIn 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) and the beta relative power ([12-20]Hz band). The detection on these two bands are then merged using fuzzy logic. 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. An artefact detection is also processed on the EEG signal to avoid false detection. 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