Citation

Suo X, Tang W, Li Z. Sensors (Basel) 2024; 24(9).

Copyright

(Copyright © 2024, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s24092947

PMID

38733052

PMCID

PMC11086331

Abstract

Motion capture technology plays a crucial role in optimizing athletes' skills, techniques, and strategies by providing detailed feedback on motion data. This article presents a comprehensive survey aimed at guiding researchers in selecting the most suitable motion capture technology for sports science investigations. By comparing and analyzing the characters and applications of different motion capture technologies in sports scenarios, it is observed that cinematography motion capture technology remains the gold standard in biomechanical analysis and continues to dominate sports research applications. Wearable sensor-based motion capture technology has gained significant traction in specialized areas such as winter sports, owing to its reliable system performance. Computer vision-based motion capture technology has made significant advancements in recognition accuracy and system reliability, enabling its application in various sports scenarios, from single-person technique analysis to multi-person tactical analysis. Moreover, the emerging field of multimodal motion capture technology, which harmonizes data from various sources with the integration of artificial intelligence, has proven to be a robust research method for complex scenarios. A comprehensive review of the literature from the past 10 years underscores the increasing significance of motion capture technology in sports, with a notable shift from laboratory research to practical training applications on sports fields. Future developments in this field should prioritize research and technological advancements that cater to practical sports scenarios, addressing challenges such as occlusion, outdoor capture, and real-time feedback.

Language: en

Keywords

*Sports/physiology; *Wearable Electronic Devices; Artificial Intelligence; Biomechanical Phenomena; Humans; Motion; motion capture; Motion Capture; Movement/physiology; pose estimation; Surveys and Questionnaires; visual recognition; wearable sensors