Title :
Comparing accuracy of two algorithms for detecting driver drowsiness — Single source (EEG) and hybrid (EEG and body movement)
Author :
Pritchett, Stacey ; Zilberg, Eugene ; Xu, Zheng Ming ; Karrar, Murad ; Burton, David ; Lal, Sara
Author_Institution :
Univ. of Technol. Sydney (UTS), Broadway, NSW, Australia
Abstract :
Driver fatigue is acknowledged to have similar effects on driving performance as driving under the influence of alcohol. As such, drowsiness detection systems should prove to be valuable in-vehicle safety measures. There are many algorithms that are currently being developed for this purpose, however, they often utilise a single source of data to detect drowsiness onset. It is anticipated that using hybrid data sources would increase the accuracy of such devices. The objective of this analysis was to compare the performance of a hybrid drowsiness detection algorithm with its single source counterpart. Addition of the body movement data to form a hybrid algorithm improved drowsiness detection performance over its EEG only (single source) counterpart, such that area under the ROC curve values increased from 0.764 (single source) to 0.783 (hybrid).
Keywords :
biomechanics; driver information systems; electroencephalography; fatigue; medical signal detection; road safety; EEG; ROC curve values; body movement data; detecting driver drowsiness; driver fatigue; driving performance; drowsiness detection systems; hybrid algorithm; hybrid data sources; hybrid drowsiness detection algorithm; in-vehicle safety measures; single source drowsiness detection; Algorithm design and analysis; Australia; Detection algorithms; Electroencephalography; Indexes; Sensitivity; Driver drowsiness; EEG; Fatigue; body movement;
Conference_Titel :
Broadband and Biomedical Communications (IB2Com), 2011 6th International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-0768-0
DOI :
10.1109/IB2Com.2011.6217916