Editorial
Bio-Aesthetic Resonance: Design and Evaluation of a Physiological Signal-Driven Immersive Art Therapy System for Personalized Stress Reduction
@ARTICLE{10.4108/eetpht.11.11055, author={Dongjun Wu and Xiaoli Shen and Qianzi You and Jiangping Yang and Lingyan Zhang}, title={Bio-Aesthetic Resonance: Design and Evaluation of a Physiological Signal-Driven Immersive Art Therapy System for Personalized Stress Reduction}, journal={EAI Endorsed Transactions of Pervasive Health and Technology}, volume={11}, number={1}, publisher={EAI}, journal_a={PHAT}, year={2026}, month={1}, keywords={Immersive Art Therapy, Physiological Feedback, Personalized Intervention, Heart Rate Variability, Deep Reinforcement Learning}, doi={10.4108/eetpht.11.11055} }- Dongjun Wu
Xiaoli Shen
Qianzi You
Jiangping Yang
Lingyan Zhang
Year: 2026
Bio-Aesthetic Resonance: Design and Evaluation of a Physiological Signal-Driven Immersive Art Therapy System for Personalized Stress Reduction
PHAT
EAI
DOI: 10.4108/eetpht.11.11055
Abstract
The escalating prevalence of chronic stress necessitates development of highly personalized non-pharmacological interventions. Traditional art therapy lacks real-time adaptability to match individuals' fluctuating physiological states. This paper introduces the Bio-Aesthetic Resonator (BAR), a novel closed-loop immersive art therapy system driven by real-time physiological feedback. The BAR integrates biosensors for continuous monitoring of Heart Rate Variability (HRV) and Galvanic Skin Response (GSR), utilizing deep reinforcement learning (DRL) to dynamically generate immersive visual and auditory artscapes. We conducted a pilot randomized controlled trial (pRCT) with 60 participants with mild-moderate anxiety. The BAR intervention significantly reduced perceived stress scores (PSS-10: Cohen's d = 0.65, 95% CI [0.22, 1.08], p = 0.003) and increased high-frequency HRV (HF-HRV: Cohen's d = 0.92, 95% CI [0.48, 1.36], p < 0.001) compared to a sham-adaptive control. These results support bio-aesthetic resonance as a viable framework for personalized digital therapeutics.
Copyright © 2026 Dongjun Wu et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
