人機互動VR心理健康支持系統 Human-AI Collaborative VR Mental Health Support System
This study developed and technically validated a “Human-AI Collaborative VR Mental Health
Support System” to address limitations in accessibility and real-time responsiveness of traditional
psychological counseling resources. The system integrates cutting-edge web technologies and AI models
to establish a self-looping closed-loop architecture.
The sensing layer utilizes Web Bluetooth to capture real-time heart rate signals and calculates heart
rate variability (HRV, RMSSD) as physiological indicators of emotional states. The analysis layer employs
a custom emotion inference logic to convert physiological signals into emotional status, automatically
triggering alerts when heart rate exceeds 120 BPM. The intervention layer combines Web Audio API and
WebXR technologies to instantly switch virtual environments—transforming fear-inducing training scenes
into calming settings enhanced with alpha wave music—to achieve real-time emotional
regulation.Additionally, the system incorporates a generative AI dialogue model trained on 378,450
psychology-related data entries to provide personalized mental health support.
In simulated emotional scenarios, the platform achieved an emotion recognition accuracy of 92%
with a response latency under 0.8 seconds, demonstrating strong real-time performance and technical
stability. The system shows scalability and clinical translation potential, with applications in school-based
mental health monitoring, counseling, and home care settings. The results confirm the feasibility and
innovative value of human-AI collaboration in real-time mental health support engineering.