The Evolving Role of Kinesiologists in the Era of Artificial Intelligence

Article information

Asian J Kinesiol. 2024;26(1):1-2
Publication date (electronic) : 2024 January 31
doi :
1Editorial Board of The Asian Journal of Kinesiology
2Vice President of Korean Academy of Kinesiology
3Division of Sports Science, Baekseok University, Cheonan, Republic of Korea
*Correspondence: Jin-Hee Seo, PhD, Division of Sports Science, Baekseok University, 31065, Baekseokdaehak-ro, Dongnam-gu, Cheonan-si, Chungcheongnam-do, Republic of Korea; E-mail:
Received 2024 January 10; Accepted 2024 January 10.

The integration of artificial intelligence (AI) technologies into various aspects of society has transformed the landscape of healthcare and wellness. Kinesiologists, traditionally focused on the study of human movement and physical activity, find themselves at the forefront of this paradigm shift.

Exercise science is increasingly incorporating AI into research and practices to enhance the understanding of human movement, optimize exercise prescriptions, and improve overall health outcomes. Here are some areas where AI is being applied in exercise science:

In biomechanics and motion analysis, AI algorithms are employed to analyze complex biomechanical data, such as motion capture information, gait analysis, and joint kinetics. This helps in understanding movement patterns, identifying anomalies, and optimizing rehabilitation strategies [1].

Second, an AI-driven models analyze individual health data, including fitness levels, medical history, and goals, to generate personalized exercise prescriptions [2]. These prescriptions take into account a person’s unique characteristics, optimizing the effectiveness of exercise interventions.

Third, Wearable devices equipped with AI algorithms monitor and analyze physical activity, providing real-time feedback to users. These devices track metrics such as steps, heart rate, and sleep patterns, offering insights into overall health and facilitating behavior change [3].

Fourth, AI is used to develop predictive models for injury risk based on biomechanical and physiological data. These models can help identify individuals at higher risk of injuries, allowing for targeted interventions and preventive measures [4].

Fifth, AI is utilized to analyze large datasets generated from athletes’ training routines, performance metrics, and physiological responses. This aids in identifying patterns, optimizing training programs, and predicting peak performance periods [5,6].

Finally, AI-driven chatbots provide virtual health coaching and support, offering guidance on exercise routines, nutrition, and lifestyle choices. These virtual coaches contribute to ongoing support and motivation for individuals pursuing health and fitness goals [7].

The incorporation of AI into exercise science aligns with the broader trend of utilizing technology to personalize interventions, optimize outcomes, and make evidence-based decisions in health and fitness. As technology continues to advance, exercise scientists are likely to explore new applications of AI to further enhance their research and practices. Therefore, the role of kinesiologists in the era of artificial intelligence is very important. Kinesiologists will play a role in providing more accurate and effective exercise and movement management through fusion with artificial intelligence.


1. Ripic Z, Signorile JF, Kuenze C, Eltoukhy M. Concurrent validity of artificial intelligence-based markerless motion capture for over-ground gait analysis: A study of spatiotemporal parameters. J Biomech 2022;143:111278.
2. Ramkumar PN, Luu BC, Haeberle HS, Karnuta JM, Nwachukwu BU, Williams RJ. Sports Medicine and Artificial Intelligence: A Primer. Am J Sports Med 2022;50(4):1166–74.
3. Germini F, Noronha N, Borg Debono V, et al. Accuracy and Acceptability of Wrist-Wearable Activity-Tracking Devices: Systematic Review of the Literature. J Med Internet Res 2022;24(1)e30791.
4. Jauhiainen S, Kauppi JP, Leppänen M, et al. New Machine Learning Approach for Detection of Injury Risk Factors in Young Team Sport Athletes. Int J Sports Med 2021;42(2):175–182.
5. Tack C. Artificial intelligence and machine learning | applications in musculoskeletal physiotherapy. Musculoskelet Sci Pract 2019;39:164–9.
6. Butow P, Hoque E. Using artificial intelligence to analyse and teach communication in healthcare. Breast 2020;50:49–55.
7. Zhang J, Oh YJ, Lange P, Yu Z, Fukuoka Y. Artificial Intelligence Chatbot Behavior Change Model for Designing Artificial Intelligence Chatbots to Promote Physical Activity and a Healthy Diet: Viewpoint. J Med Internet Res 2020;22(9)e22845.

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