Unobtrusive Multimodal Monitoring of Physiological Signals for Driver State Analysis

This research introduces the second version of ANGELS, an embedded system designed to analyze PPG and EDA signals in the context of driver monitoring. ANGELS is a cost-effective and energy-efficient solution that performs real-time acquisition and processing of PPG and EDA signals, enabling continuous monitoring of driver physiological parameters. Notably, ANGELS operates autonomously without needing accelerometer data to mitigate distortions caused by vehicle motion. Following an initial validation in collaboration with Maserati, supplementary experiments were conducted within our laboratory-level driving simulator. ANGELS v2 integrates an additional EDA sensor compared to its predecessor. Despite its unobtrusive nature, ANGELS v2 features a mean absolute error of 1.19 BPM in heart rate detection and 1.9 misdetected peaks per minute in EDA peak detection, which is the standard metric to evaluate EDA. These results are achieved within a power envelope of 230 mW. These results underscore the reliability and promising potential of ANGELS v2 to enhance driver safety.