What is it about?
This paper proposes a protocol for the acquisition and processing of biophysical signals in virtual reality applications, particularly in phobia therapy experiments. This protocol aims to ensure that the measurement and processing phases are performed effectively, to obtain clean data that can be used to estimate the users’ anxiety levels.
Featured Image
Why is it important?
The protocol has been designed after analyzing the experimental data of seven subjects who have been exposed to heights in a virtual reality environment. The subjects’ level of anxiety has been estimated based on the real-time evaluation of a nonlinear function that has as parameters various features extracted from the biophysical signals. The highest classification accuracy was obtained using a combination of seven heart rate and electrodermal activity features in the time domain and frequency domain.
Perspectives
The integration of protocol at biophysical measurements in Virtual Reality environments for anxiety detection can have numerous implications in both practice and research. For clinical applicability, we can mention the treatment of anxiety by the VR immersion therapy, ideal being the development of a system with the dual operation: (i) For subclinical forms, the system can be implemented autonomously, like a biofeedback application or possibly with remote targeting by the therapist; (ii) for the clinical forms, the direct intervention of the therapist is needed, with a control panel for the permanent monitoring of the evolution of the treatment and of the patient’s condition (by monitoring the physiological parameters). As a research target, the protocol can be used as a method of developing and testing applications that require real-time evaluation of the user’s emotional response (medical, educational applications, military, or sports training).
Livia Petrescu
University of Bucharest
Read the Original
This page is a summary of: Integrating Biosignals Measurement in Virtual Reality Environments for Anxiety Detection, Sensors, December 2020, MDPI AG,
DOI: 10.3390/s20247088.
You can read the full text:
Resources
Contributors
The following have contributed to this page
