DocumentCode :
718343
Title :
Evaluating driving fatigue detection algorithms using eye tracking glasses
Author :
Xiang-Yu Gao ; Yu-Fei Zhang ; Wei-Long Zheng ; Bao-Liang Lu
Author_Institution :
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2015
fDate :
22-24 April 2015
Firstpage :
767
Lastpage :
770
Abstract :
Fatigue is a status of human brain activities, and driving fatigue detection is a topic of great interest all over the world. In this paper, we propose a measure of fatigue produced by eye tracking glasses, and use it as the ground truth to evaluate driving fatigue detection algorithms. Particularly, PERCLOS, which is the percentage of eye closure over the pupil over time, was calculated from eyelid movement data provided by eye tracking glasses. Experiments of a vigilance task were carried out in which both EOG signals and eyelid movement were recorded. The evaluation results of an effective EOG-based fatigue detection algorithm convinced us that our proposed measure is an appropriate candidate for evaluating driving fatigue detection algorithms.
Keywords :
biomechanics; electro-oculography; fatigue; gaze tracking; medical signal processing; EOG signals; PERCLOS; driving fatigue detection algorithms; eye tracking glasses; eyelid movement; vigilance task; Detection algorithms; Electrooculography; Eyelids; Fatigue; Feature extraction; Glass; Tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on
Conference_Location :
Montpellier
Type :
conf
DOI :
10.1109/NER.2015.7146736
Filename :
7146736
Link To Document :
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