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Volume 23
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10.3390/s23229025
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Article

Biofeedback Respiratory Rehabilitation Training System Based on Virtual Reality Technology

by
Lijuan Shi
1,2,3,†,
Feng Liu
1,†,
Yuan Liu
1,
Runmin Wang
1,
Jing Zhang
1,
Zisong Zhao
4 and
Jian Zhao
2,3,5,*
1
College of Electronic Information Engineering, Changchun University, Changchun 130022, China
2
Jilin Provincial Key Laboratory of Human Health Status Identification Function & Enhancement, Changchun 130022, China
3
Key Laboratory of Intelligent Rehabilitation and Barrier-Free for the Disabled, Changchun University, Ministry of Education, Changchun 130012, China
4
College of Cyber Security, Changchun University, Changchun 130022, China
5
College of Computer Science and Technology, Changchun University, Changchun 130022, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sensors 2023, 23(22), 9025; https://doi.org/10.3390/s23229025
Submission received: 14 September 2023 / Revised: 27 October 2023 / Accepted: 3 November 2023 / Published: 7 November 2023
(This article belongs to the Section Biosensors)
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Abstract

Traditional respiratory rehabilitation training fails to achieve visualization and quantification of respiratory data in improving problems such as decreased lung function and dyspnea in people with respiratory disorders, and the respiratory rehabilitation training process is simple and boring. Therefore, this article designs a biofeedback respiratory rehabilitation training system based on virtual reality technology. It collects respiratory data through a respiratory sensor and preprocesses it. At the same time, it combines the biofeedback respiratory rehabilitation training virtual scene to realize the interaction between respiratory data and virtual scenes. This drives changes in the virtual scene, and finally the respiratory data are fed back to the patient in a visual form to evaluate the improvement of the patient’s lung function. This paper conducted an experiment with 10 participants to evaluate the system from two aspects: training effectiveness and user experience. The results show that this system has significantly improved the patient’s lung function. Compared with traditional training methods, the respiratory data are quantified and visualized, the rehabilitation training effect is better, and the training process is more active and interesting.
Keywords: virtual reality; biofeedback; breathing interaction; rehabilitation training virtual reality; biofeedback; breathing interaction; rehabilitation training

Share and Cite

MDPI and ACS Style

Shi, L.; Liu, F.; Liu, Y.; Wang, R.; Zhang, J.; Zhao, Z.; Zhao, J. Biofeedback Respiratory Rehabilitation Training System Based on Virtual Reality Technology. Sensors 2023, 23, 9025. https://doi.org/10.3390/s23229025

AMA Style

Shi L, Liu F, Liu Y, Wang R, Zhang J, Zhao Z, Zhao J. Biofeedback Respiratory Rehabilitation Training System Based on Virtual Reality Technology. Sensors. 2023; 23(22):9025. https://doi.org/10.3390/s23229025

Chicago/Turabian Style

Shi, Lijuan, Feng Liu, Yuan Liu, Runmin Wang, Jing Zhang, Zisong Zhao, and Jian Zhao. 2023. "Biofeedback Respiratory Rehabilitation Training System Based on Virtual Reality Technology" Sensors 23, no. 22: 9025. https://doi.org/10.3390/s23229025

APA Style

Shi, L., Liu, F., Liu, Y., Wang, R., Zhang, J., Zhao, Z., & Zhao, J. (2023). Biofeedback Respiratory Rehabilitation Training System Based on Virtual Reality Technology. Sensors, 23(22), 9025. https://doi.org/10.3390/s23229025

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