Sensor fusion-based virtual reality for enhanced physical training
Robotic Intelligence and Automation
ISSN: 2754-6969
Article publication date: 6 March 2024
Issue publication date: 29 March 2024
Abstract
Purpose
This study aims to offer a comprehensive exploration of the potential and challenges associated with sensor fusion-based virtual reality (VR) applications in the context of enhanced physical training. The main objective is to identify key advancements in sensor fusion technology, evaluate its application in VR systems and understand its impact on physical training.
Design/methodology/approach
The research initiates by providing context to the physical training environment in today’s technology-driven world, followed by an in-depth overview of VR. This overview includes a concise discussion on the advancements in sensor fusion technology and its application in VR systems for physical training. A systematic review of literature then follows, examining VR’s application in various facets of physical training: from exercise, skill development and technique enhancement to injury prevention, rehabilitation and psychological preparation.
Findings
Sensor fusion-based VR presents tangible advantages in the sphere of physical training, offering immersive experiences that could redefine traditional training methodologies. While the advantages are evident in domains such as exercise optimization, skill acquisition and mental preparation, challenges persist. The current research suggests there is a need for further studies to address these limitations to fully harness VR’s potential in physical training.
Originality/value
The integration of sensor fusion technology with VR in the domain of physical training remains a rapidly evolving field. Highlighting the advancements and challenges, this review makes a significant contribution by addressing gaps in knowledge and offering directions for future research.
Keywords
Acknowledgements
Funding: This study was supported by the project Research on the Standardization Development Strategy of Central Plains Wushu of Henan Provincial Sports Bureau under Grant No. 202327.
Conflict of interest: The authors declare that there is no conflict of interest.
Since submission of this article, the following authors has updated their affiliations: Xiaohui Li is at the Department of History and Pakistan, University of the Punjab, Lahore, Pakistan; Owen Omalley is at the NexTech Innovations, Mountain View, California, USA.
Citation
Li, X., Fan, D., Deng, Y., Lei, Y. and Omalley, O. (2024), "Sensor fusion-based virtual reality for enhanced physical training", Robotic Intelligence and Automation, Vol. 44 No. 1, pp. 48-67. https://doi.org/10.1108/RIA-08-2023-0103
Publisher
:Emerald Publishing Limited
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