Exploring the roles of artificial intelligence and wearable feedback technologies in figure skating performance analysis A scoping review
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The application of artificial intelligence (AI) unlocks an exciting perspective for performance analysis in figure skating. A better understanding of AI and wearable feedback technologies of figure skating is warranted. The purpose of this study is to overview the roles of AI and wearable feedback technologies in figure skating performance analysis. Systematic searches through PubMed, Web of Science, and Scopus online databases were conducted for articles reporting AI and wearable feedback technologies applied to figure skating. Twelve studies were included in the review; three themes of AI and wearable feedback technologies emerged as being applied in figure skating. Emerging themes were wearable inertial and force sensors, marker less computer vision systems, and pose (marker) based deep learning. Body‑worn IMU systems primarily support jump detection and counting, achieving very high accuracy for discrete event identification in controlled or semi‑controlled settings. Body-worn IMU systems primarily support jump detection and counting, achieving very high accuracy. The current state of technology used for performance analysis in the area proposes a promising future with regard to figure skating. Further evaluation research based on real figure skaters is warranted to establish the predictive performance of specific AI and wearable technologies.
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