Enabling the Evaluation of Driver Physiology Via Vehicle Dynamics

Autores: Rodrigo Ordoñez Bo Wen Nicholas Barra Ryan Vimba Sergio Cabrero Barros Sergiy Zhuk Jeffrey L. Rogers

Fecha: 02.07.2023


Abstract

Driving is a daily routine for many individuals across the globe. This paper presents the configuration and methodologies used to transform a vehicle into a connected ecosystem capable of assessing driver physiology. We integrated an array of commercial sensors from the automotive and digital health sectors along with driver inputs from the vehicle itself. This amalgamation of sensors allows for meticulous recording of the external conditions and driving maneuvers. These data streams are processed to extract key parameters, providing insights into driver behavior in relation to their external environment and illuminating vital physiological responses. This innovative driver evaluation system holds the potential to amplify road safety. Moreover, when paired with data from conventional health settings, it may enhance early detection of health-related complications.

BIB_text

@Article {
title = {Enabling the Evaluation of Driver Physiology Via Vehicle Dynamics},
pages = {195-201},
keywds = {
Cognition; Digital Health; Driving; IoT; Lidar
}
abstract = {

Driving is a daily routine for many individuals across the globe. This paper presents the configuration and methodologies used to transform a vehicle into a connected ecosystem capable of assessing driver physiology. We integrated an array of commercial sensors from the automotive and digital health sectors along with driver inputs from the vehicle itself. This amalgamation of sensors allows for meticulous recording of the external conditions and driving maneuvers. These data streams are processed to extract key parameters, providing insights into driver behavior in relation to their external environment and illuminating vital physiological responses. This innovative driver evaluation system holds the potential to amplify road safety. Moreover, when paired with data from conventional health settings, it may enhance early detection of health-related complications.


}
isbn = {979-835034103-4},
date = {2023-07-02},
}
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