A Physiological Sensor-Based Android Application Synchronized with a Driving Simulator for Driver Monitoring

Abstract

In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.

Organization of a Wireless System for Individual Biomedical Data Collection

“…For remote control via a mobile application on Android use network Bridges, Smart Hub or Gateway [6]- [9].…”

Dashboard Layout Effects on Drivers' Searching Performance and Heart Rate: Experimental Investigation and Prediction

“…On the part of car driving, the alteration of information input would give rise to the variation of stress level and then the fluctuation of HR, which was the physiological connection between HR and stress (30). Literatures (31)(32)(33) all applied ECG signals to analyze human-vehicle interaction behaviors. The measurement and analysis of driver ECG is a common research method from the field of neuropsychology, but from the perspective of driver visual attention, few studies combined ECG signal with eye movement.…”

Design of Smart Steering Wheel for Unobtrusive Health and Drowsiness Monitoring

“…The study of the current state helped us identify critical parameters for measuring the driver’s cardiovascular health or drowsiness [ 20 , 21 , 22 ]. This research shows that the steering wheel collecting health describing data is very possible in the research area [ 17 , 19 , 23 ].…”