An Integrated Platform Combining Immersive Virtual Reality and Physiological Sensors for Systematic and...

Stress is a pervasive issue in modern society, manifesting in various forms such as emotional, physical, and work-related stress, each with distinct impacts on individuals and society. Traditional stress studies often rely on psychological, performance, or social tests; however, recently, immersive virtual reality (VR), which provides a sense of presence and natural interaction, offers the opportunity to simulate real-world tasks and stressors in controlled environments. Despite its potential, the use of VR to investigate the multifaceted manifestations of stress has not been thoroughly explored.

This study aimed to explore the feasibility of using a VR-based platform, bWell, to elicit multifaceted stress responses and measure the resulting behavioral and physiological changes. Specifically, we aimed to design various VR stress exercises based on neurocardiac models to systematically test cardiac functioning within specific contexts of self-regulation (executive functioning, physical efforts, and emotional regulation).

The development process adhered to guidelines for VR clinical trials and complex health interventions, encompassing 3 phases: preparation, development, and verification. The preparation phase involved a comprehensive literature review to establish links between stress, the heart, and the brain, leading to the formulation of a conceptual model based on the Neurovisceral Integration Model (NVIM) and Vagal Tank Theory (VTT). The development phase involved designing VR exercises targeting specific stressors and integrating physiological sensors such as photoplethysmography (PPG) and electromyography (EMG) to capture heart rate variability (HRV) and facial expressions. The verification phase, conducted with a small number of trials, aimed to design a study and implement a workflow for testing the feasibility, acceptability, and tolerability of the VR exercises. In addition, the potential for capturing physiological measures along with subjective ratings of stress for specific dimensions was assessed.

Verification trials demonstrated that the VR exercises were well tolerated, with negligible cybersickness and high user engagement. The different VR exercises successfully elicited the intended stress demands, along with the physiological responses.

The study presents a novel VR-based experimental setup that allows a systematic and individualized assessment of stress responses, paving the way for future research to identify features that confer stress resilience and help individuals manage stress effectively. While our conceptual model highlights the role of HRV in providing valuable insights into stress responses, future research will involve multivariate and machine learning analyses to predict individual stress responses based on comprehensive sensor data, including EMG and the VR-based behavioral data, ultimately guiding personalized stress management interventions.