An Experimental Study Using EEG to Detect Driver Drowsiness

Drowsy driving is a serious issue in modern transportation. Our review of current ways to detect driver drowsiness revealed that electroencephalography (EEG) has the potential to achieve excellent performance in driver drowsiness recognition. This paper presents an experimental study for finding EEG features that are sensitive to a driver’s drowsiness, yet robust to noise signals. We recorded participants’ EEGs in an alert state and a drowsy state for a driving task performed in a driving simulator. Twelve EEG features were analyzed for their power of distinguishing the alert state from the drowsy state. As a conclusion, specific EEG features can be used to detect drivers’ drowsiness. The classification power of the EEG features depends on the scalp locations where the EEG is measured.