Towards to a System for Predicting an Insufficient Wake State in Professional Drivers

Abstract

Sleep is one of the major responsible for road accidents. Their early detection can prevent many of these types of accidents. The current sleep detection systems are based mainly on the evaluation of the behaviour of the driver, which is expressed by the steering wheel movement, facial expression or eyes movement monitored by a camera. However, these systems only detect a sleep situation when it already exists, what is proved to be insufficient. It is fundamental to anticipate this state more than to realize that the driver is in the state of drowsiness, alerting the driver while he is still awake for the necessity to stop and rest. Nowadays, the technology focused on the health and well-being has been making considerable progress. Mobile and wearable devices, among other equipment with multiple sensors, are being used more frequently in areas which are directly or indirectly related to health. The increased quality and accuracy of these devices improves their reliability and credibility, allowing them to be used in more sensitive contexts, particularly in the health area. The current wearable devices have a set of sensors that allow the evaluation of biometric parameters, as well as information about body movement that can help to predict sleep state. This technology can be used to prevent accidents.