Design of a non-invasive system for a real-time monitoring of driver's drowsiness and fatigue through the analysis of cardiac signals

The development and spread of human-centered products that are increasingly simple and affordable has seen their application areas increase over the years, as well as their effectiveness and reliability. Real-time monitoring physiological conditions, such as fatigue and sleepiness, offers useful support in both clinical and driving safety fields and it is essential in accident prevention. This research proposes a detection platform without direct contact with the skin capable of acquiring cardiac signals and it develops a fatigue-related sleepiness detection algorithm based on the analysis of the pulse rate variability generated by the heartbeat and validates the proposed method by comparing it with an objective indicator of sleepiness (PERCLOS). Changes in alert conditions affect the autonomic nervous system (ANS) and therefore heart rate variability (HRV), modulated in the form of a wave and monitored to detect long-term changes in the driver's condition using real-time control. The performance of the algorithm was evaluated through an experiment carried out in a road vehicle. In this experiment, data was recorded by 3 participants in different driving sessions and their conditions of fatigue and sleepiness were documented on both a subjective and objective basis. The validation of the results through PERCLOS showed a 63% adherence to the experimental findings. The present study confirms the possibility of continuously monitoring the driver's status through the detection of the activation/deactivation states of the ANS based on HRV. The proposed method can help prevent accidents caused by drowsiness while driving. [edited by Author]