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Distress detection in VR environment using Empatica E4 wristband and Bittium Faros 360
Jelena Medarević1, Nadica Miljković1,2, Kristina Stojmenova Pečečnik1
1Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia.
Frontiers in Physiology
|March 20, 2025
Summary
This study compared two wearable devices for detecting user distress in virtual reality. Both devices captured physiological signals, with Faros showing better consistency, and both detected more distress in interactive VR scenarios.
Area of Science:
- Physiological computing
- Virtual reality systems
- Wearable sensor technology
Background:
- Virtual reality (VR) offers potential for improved user experiences and therapeutic interventions by monitoring emotional states.
- Accurate distress detection in VR requires reliable physiological sensing.
Purpose of the Study:
- To evaluate the performance of the Empatica E4 wristband and Faros 360 in detecting user distress within an interactive VR environment.
- To compare the devices' ability to capture heart rate variability metrics indicative of distress.
Main Methods:
- Participants were exposed to baseline, non-interactive, and interactive VR scenes.
- Heart rate data (mean heart rate, RMSSD) were collected using Empatica E4 and Faros 360 devices.
- Subject-specific thresholds were used to analyze distress intensity and frequency.
Main Results:
- Both Faros and E4 sensors captured physiological signals, with Faros exhibiting a higher signal-to-noise ratio.
- Moderate positive correlations and small errors indicated good agreement between devices for heart rate measurement.
- Both devices detected significantly more high- and medium-level distress events in the interactive VR scene compared to the non-interactive scene.
Conclusions:
- Wearable devices can detect distress in VR, with performance varying between devices.
- Device-specific characteristics influence the accuracy and consistency of distress detection in VR environments.
