A decision support system for real-time stress detection during virtual reality exposure

Area of Science:

• Psychophysiology
• Virtual Reality (VR) applications
• Clinical decision support systems

Background:

• Virtual Reality (VR) is increasingly utilized in mental health research and therapy for distress assessment.
• Analyzing multiple psycho-physiological measures for stress is time-consuming and requires specialized expertise, limiting clinical accessibility.
• Existing methods for VR-based stress assessment lack automated, integrated analysis of diverse biosignals.

Purpose of the Study:

• To design and develop an automated Decision Support System (DSS) for classifying stress levels during VR exposure.
• To integrate various biosensor (ECG, breathing rate, EEG) and behavioral data for a comprehensive stress assessment.
• To provide clinicians with an accessible tool for objective stress evaluation in VR therapy.

Main Methods:

• Development of a DSS integrating electrocardiogram (ECG), breathing rate, electroencephalogram (EEG), and behavioral data (body gestures).
• Training the DSS using self-rated and clinician-rated stress levels as ground truth for stress classification.
• Implementing a web-based interface for therapists to access aggregated stress values (0-1) and graphical displays.

Main Results:

• The DSS successfully integrates multi-modal data for automatic stress level classification in VR environments.
• The system provides an aggregated stress score and graphical representation, simplifying interpretation for therapists.
• The DSS addresses the need for efficient and skilled-independent analysis of physiological stress indicators.

Conclusions:

• The developed DSS offers an automated and efficient solution for assessing stress levels during VR exposure.
• This technology can significantly aid clinicians in interpreting complex physiological and behavioral data for mental health therapy.
• The DSS has the potential to improve the accuracy and accessibility of VR-based stress assessment in clinical practice.