An Electro-Oculogram (EOG) Sensor's Ability to Detect Driver Hypovigilance Using Machine Learning.

Driving safely is crucial to avoid death, injuries, or financial losses that can be sustained in an accident. Thus, a driver's physical state should be monitored to prevent accidents, rather than vehicle-based or behavioral measurements, and provide reliable information in this regard. Electrocardiography (ECG), electroencephalography (EEG), electrooculography (EOG), and surface electromyography (sEMG) signals are used to monitor a driver's physical state during a drive.

Detection and analysis: driver state with electrocardiogram (ECG).

Driver drowsiness, fatigue and inattentiveness are the major causes of road accidents, which lead to sudden death, injury, high fatalities and economic losses. Physiological signals provides information about the internal functioning of human body and thereby provides accurate, reliable and robust information on the driver's state. In this work, we detect and analyse driver's state by monitoring their physiological (ECG) information.