2023_Delrobaei_Preprint_Driver_Drowsiness_Detection_with_Commercial_EEG_Headsets.pdf (671.15 kB)
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Driver Drowsiness Detection with Commercial EEG Headsets

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posted on 2023-04-10, 16:07 authored by Qazal Rezaee, Mehdi DelrobaeiMehdi Delrobaei

Driver Drowsiness is one of the leading causes of road accidents. Electroencephalography (EEG) is highly affected by drowsiness; hence, EEG-based methods detect drowsiness with the highest accuracy. Developments in manufacturing dry electrodes and headsets have made recording EEG more convenient. Vehicle-based features used for detecting drowsiness are easy to capture but do not have the best performance. In this paper, we investigated the performance of EEG signals recorded in 4 channels with commercial headsets against the vehicle-based technique in drowsiness detection. We recorded EEG signals of 50 volunteers driving a simulator in drowsy and alert states by commercial devices. The observer rating of drowsiness method was used to determine the drowsiness level of the subjects. The meaningful separation of vehicle-based features, recorded by the simulator, and EEG-based features of the two states of drowsiness and alertness have been investigated. The comparison results indicated that the EEG-based features are separated with lower p-values than the vehicle-based ones in the two states. It is concluded that EEG headsets can be feasible alternatives with better performance compared to vehicle-based methods for detecting drowsiness.


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Submitting Author's Institution

K. N. Toosi University of Technology

Submitting Author's Country

  • Iran