Detection of Operator Drowsiness Using Google Glass

Abstract

Background: Drowsiness is one of the major factors that cause accidents in driving and aviation. Existing drowsiness detection systems using camera and EEG have several limitations, such as price, intrusiveness, and reliability. A Google-Glass-based drowsiness detection system was developed and tested to explore the feasibility of using the sensors of wearable devices to detect drowsiness. Methods: The technology uses the accelerometer and proximity sensors of Google Glass to detect eye blinks, a commonly used indicator of drowsiness. Results: A simulated driving study showed that drowsy drivers differed significantly in the frequency of eye blinks compared to when they were attentive. A threshold algorithm for proximity sensor can reliably detect eye blinks, and proved the feasibility to use Google Glass to detect operator drowsiness. Applications: This technology can reduce drowsiness-related accidents in driving and aviation.