Advancing Sport Biomechanics with Depth Cameras: Systematic Review of Current Applications and Future Directions

Konrad Maciejewski; Francisco Martins; Diogo Martinho; Maciej Śliż; Hugo Sarmento; Élvio Rúbio Gouveia; Krzysztof Przednowek

doi:10.2478/ijcss-2025-0009

Abstract

Computer sports methods use computational techniques to analyse and optimise athletic performance. Computer vision (CV) has emerged as a tool that offers objective data on techniques and tactics. Depth camera technology can support markerless kinematic analyses. This systematic review, following the Preferred Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, examined the integration and impact of depth camera technology in sports biomechanics over the past decade. Using databases such as PubMed, Web of Science, and Scopus, we identified and analysed 14 relevant studies. Depth cameras such as Microsoft Kinect and Intel RealSense have been used to analyse performance in various sports by providing biomechanical feedback in real time, improving athlete training, and implementing injury prevention strategies. This review highlights the technology’s cost-effectiveness and accessibility, extending from elite sports to community programs. It suggests further advancements with AI and machine learning to enhance personalised training and integrate virtual and augmented reality, which is promising for the development of sports biomechanics.

References

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Advancing Sport Biomechanics with Depth Cameras: Systematic Review of Current Applications and Future Directions

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