Application of Portable EEG Device in Detection and Classification Drowsiness by Support Vector Machine

Abstract

Sleeplessness and driver’s drowsiness is one of the reasons leading to accidents. Many studies as well as applied products have been recently developed and integrated into car. However, almost research concentrated on eyes-movement and pupillary stretch. Especially, mobile Electroencephalography (EEG) measurement device becomes new trend thanks to its convenience and affordable price. This research focused on using portable EEG device—EPOC Emotiv for detecting sleep-onset by analyzing power spectrum after filtering frequency band of brain waves. The processed features become the input of Support Vector Machine (SVM) classification and the prerequisite for real-time drowsiness detection. The changes of vigilance state classified by SVM in analysis show the result with over 70% data samples, reliably used in driving safety system in the future.