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Predicting Sports Injuries with Wearable Technology and Data Analysis

Author

Listed:
  • Amir Zadeh

    (Wright State University)

  • David Taylor

    (Wright State University)

  • Margaret Bertsos

    (Wright State University)

  • Timothy Tillman

    (Wright State University)

  • Nasim Nosoudi

    (Marshall University)

  • Scott Bruce

    (Arkansas State University)

Abstract

Injuries resulting from sports and physical activities can be persistent and pose a substantial problem for player’s economic wellbeing and quality of life. Wearable technologies in conjunction with analytics can help mitigate the risk to players by identifying injury risk factors and focusing on risk reduction. Prior to engaging in strenuous sport activities, wearables can be employed to facilitate the quantification of relevant functional capabilities, ultimately advancing the field of sports injury management. In this paper, we discuss how wearable technologies can improve the health and athletic performance of athletes by monitoring participants across many variables. A cohort of 54 army ROTC cadets participated in this study. Using Zephyr BioHarness Wearable technology, we gathered quantifiable data to generate insights that allow us to predict and prevent injuries related the wearer’s physical exertion during sporting activities. This study finds that a combination of high BMI and high mechanical loads could result in injury. Therefore, in creating an exercise program, it is imperative to ensure that mechanical load is incrementally increased through the practice season as athletes become conditioned. While, a high level repetitious mechanical load with unconditioned athletes could cause injuries in short time, it is important to impose enough mechanical loads in the training program to ensure good musculoskeletal development. While our analyses identified several factors associated with injury data during ROTC activities, other wearable variables might become significant in other situations. In summary, results from this study demonstrate that wearable technology allows players with an increased risk of injury to be identified and targeted for intervention.

Suggested Citation

  • Amir Zadeh & David Taylor & Margaret Bertsos & Timothy Tillman & Nasim Nosoudi & Scott Bruce, 2021. "Predicting Sports Injuries with Wearable Technology and Data Analysis," Information Systems Frontiers, Springer, vol. 23(4), pages 1023-1037, August.
  • Handle: RePEc:spr:infosf:v:23:y:2021:i:4:d:10.1007_s10796-020-10018-3
    DOI: 10.1007/s10796-020-10018-3
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    References listed on IDEAS

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    1. Gary B. Wilkerson & Ashish Gupta & Marisa A. Colston, 2018. "Mitigating Sports Injury Risks Using Internet of Things and Analytics Approaches," Risk Analysis, John Wiley & Sons, vol. 38(7), pages 1348-1360, July.
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    Cited by:

    1. Pedro Morouço, 2024. "Wearable Technology and Its Influence on Motor Development and Biomechanical Analysis," IJERPH, MDPI, vol. 21(9), pages 1-9, August.
    2. Pascal Fechner & Fabian König & Jannik Lockl & Maximilian Röglinger, 2024. "How Artificial Intelligence Challenges Tailorable Technology Design," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(3), pages 357-376, June.

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