Work

BioVR: An Exploratory Study of Biofeedback-Driven Adaptive VR for Personalized and Sustained Fitness Intensity

Year: 2025

Type: conference-paper

Abstract: BioVR explores the integration of biofeedback into immersive virtual reality (VR) to create personalized fitness experiences.The prototype leverages heart rate data from smartwatches to dynamically adapt VR environments, encouraging users to sustain exercise intensity levels tailored to their biometric profiles.This study addresses key gaps in current VR fitness systems by focusing on realtime adaptability, engagement, and exercise intensity maintenance while mitigating challenges such as overexertion and disengagement during exercise.Additionally, this project explores a novel interaction method in VR, enabling users to gain a more tailored and immersive experience based on their internal physiological status.A pilot study was conducted to explore exercise intensity trends and user experience, revealing that participants in the BioVR condition maintained a moderate fitness level for a longer duration and reported a more satisfying experience.Future work will include formal user testing and expanding the system's applications, contributing to the evolving paradigm of human-computer integration in health and fitness.

Source: ACM Designing Interactive Systems Conference (DIS)

DOI: 10.1145/3715668.3736380

Authors: Yuchen Zhao, Jay David Bolter, Kexin Chen, Xuerui Wang, Xintong Jiang, Zhao Ni

Institutions: Georgia Institute of Technology, City University of Hong Kong, Xiamen University, Yale University

Language: English

Topic: Virtual Reality Applications and Impacts

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4412045102

FWCI: 3.136

Cites: 39

Cited by: 3

Related to: 10