Why the study?
A protocol was needed for the acquisition and processing of biophysical signals in virtual reality applications to ensure effective measurement and clean data for estimating anxiety levels.
Can biophysical signals (heart rate and electrodermal activity) accurately detect anxiety levels in subjects exposed to virtual reality environments?
Can biophysical signals (heart rate and electrodermal activity) accurately detect anxiety levels in subjects exposed to virtual reality environments?
A combination of heart rate and electrodermal activity features can be used to estimate anxiety levels in virtual reality environments.
Supports multimodal HR/EDA anxiety detection in VR; hypothesis-generating and requires prospective validation before clinical use.
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. 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.
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Petrescu et al. (2020) studied this question.
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