Document Type
Abstract
Publication Date
1-14-2026
Abstract
The rapid development of artificial intelligence (AI) technology has provided important support for the scientific, personalized, and intelligent physical training, and its application in the fields of sports performance optimization, injury prevention, and training program design has become the focus of sports science research. Method: In this study, we used the China Knowledge Network (CNKI) database as the data source, screened 428 core literatures in the intersection of artificial intelligence and physical training between 2000 and 2024, and analyzed the bibliometrics and knowledge mapping using CiteSpace software, to systematically reveal the knowledge structure, evolution path, and cutting-edge trends of AI-enabled physical training, with the aim of providing a new perspective for professional athletes' physical training and health management. The results of the study show that the evolution path is divided into three phases, i.e., the technology germination period (2000-2010), the technology integration period (2011-2020), and the application deepening period (2021-present). Three major clusters are identified through the cluster analysis of research hotspots: 1. “Intelligent motion recognition and evaluation”, covering motion gesture capture, motion quality scoring, etc., with emergent terms such as “LSTM”, “3D motion analysis”; 2. “Data-driven training optimization”, which involves physiological indicator monitoring and load adaptive adjustment, with emergent terms such as ‘wearable devices’ and ‘reinforcement learning’; 3. “AI and Sports Injury Prevention”, focusing on injury risk prediction and rehabilitation program design, with keywords such as “biomechanical modeling”, “dynamic stability analysis”. His current research still has problems, such as insufficient technological depth and limited practical application scope. Future research should strengthen technological innovation, broaden the practical application scenarios, and promote a deeper and broader combination of physical training, in order to improve the quality and efficiency of physical training and help the development of sports.
DOI
https://doi.org/10.18122/ijpah.5.1.139.boisestate
Recommended Citation
Liu, Mengxiao
(2026)
"A139: Evolution, Hot Spotlight, and Frontier Exploration of AI Applications in Physical Training: CiteSpace-Based Visualization Analysis,"
International Journal of Physical Activity and Health: Vol. 5:
Iss.
1, Article 139.
DOI: https://doi.org/10.18122/ijpah.5.1.139.boisestate
Available at:
https://scholarworks.boisestate.edu/ijpah/vol5/iss1/139
Included in
Exercise Science Commons, Health and Physical Education Commons, Public Health Commons, Sports Studies Commons
