Driver Stress Detection from Physiological Signals by Virtual Reality Simulator

One of the many areas in which artificial intelligence (AI) techniques are used is development systems for recognition vital emotions to control human health and safety. This study biometric sensors a multimodal approach capture signals stressful situations. The great advances technology have allowed portable devices capable monitoring different physiological measures an inexpensive, non-invasive, efficient manner. Virtual reality (VR) has evolved achieve realistic immersive experience contexts. combination AI, signal acquisition devices, VR makes it possible generate useful knowledge even challenging situations daily life, such as when driving. main goal this work combine use possibilities offered by creation system recognizing stress during driving vehicle. We investigated feasibility detecting individuals using collected photoplethysmography (PPG) sensor incorporated into commonly wristwatch. developed environment based on simulate experimental collect information user’s reactions through detection signals. Data simulations taken input several models previously trained machine learning (ML) algorithms obtain that performs driver high-precision classification real time.