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

Author

Picot, Antoine ; Charbonnier, Sylvie ; Caplier, Alice

Author_Institution

Gipsa-lab, 961 rue de la Houille Blanche, Domaine Universitaire - BP 46, 38402 Saint Martin d´´Heres Cedex, France

fYear

2008

fDate

20-25 Aug. 2008

Firstpage

3864

Lastpage

3867

Abstract

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.

Keywords

Detection algorithms; Electroencephalography; Face detection; Independent component analysis; Monitoring; Neural networks; Road safety; Sleep; Testing; Vehicle detection; Accidents, Traffic; Algorithms; Automatic Data Processing; Automation; Automobile Driving; Databases, Factual; Electroencephalography; False Positive Reactions; Humans; Models, Statistical; Pattern Recognition, Automated; Safety; Sleep Stages;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE

Conference_Location

Vancouver, BC

ISSN

1557-170X

Print_ISBN

978-1-4244-1814-5

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2008.4650053

Filename

4650053