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Peer-reviewedCC BYFrontiers in public health

Building smarter surveillance: a framework for artificial intelligence-enabled monitoring of overuse injuries in youth sports.

  • Patrick Mayolo1
  • Zachary A Blashinsky1
  • John Wahl1
  • Alexander Bouterse1
  • Felix Oettl2
  • James A Pruneski1
  • Kristian Samuelsson3,4,5
5 affiliations
  1. 1Department of Orthopaedic Surgery, Tripler Army Medical Center, Honolulu, HI, United States.
  2. 2Department of Orthopaedic Surgery, Balgrist University Hospital, University of Zürich, Zurich, Switzerland.
  3. 3Sahlgrenska Sports Medicine Center, Gothenburg, Sweden.
  4. 4Department of Orthopaedics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  5. 5Department of Orthopaedics, Sahlgrenska University Hospital, Mölndal, Sweden.
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Abstract

Early sport specialization (ESS), defined as intensive, year-round training in a single sport at the exclusion of others, has become increasingly prevalent among youth athletes. This trend has coincided with a rise in overuse injuries, and premature attrition. Concurrently, advances in wearable sensors and artificial intelligence (AI) enable real-time quantification of training load, biomechanical deviations, and recovery. However, a translational gap remains: existing AI surveillance models are predominantly validated in elite adult male cohorts, leaving youth athletes underserved. To address this gap, we propose a translational four-pillar framework for ESS-aware AI injury monitoring in youth sport. Bridging technological capabilities with developmental physiology through structured AI surveillance provides a structured risk-monitoring roadmap with the potential to inform preventative strategies, optimize physical readiness, and support long-term musculoskeletal health in youth athletes.

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Cite

BibTeXRIS
BibTeX
@article{mayolo2026building,
  title = {{Building smarter surveillance: a framework for artificial intelligence-enabled monitoring of overuse injuries in youth sports.}},
  author = {Patrick Mayolo and Zachary A Blashinsky and John Wahl and Alexander Bouterse and Felix Oettl and James A Pruneski and Kristian Samuelsson},
  journal = {Frontiers in public health},
  year = {2026},
  month = oct,
  doi = {10.3389/fpubh.2026.1966293},
  url = {https://europepmc.org/article/MED/42909112},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Building smarter surveillance: a framework for artificial intelligence-enabled monitoring of overuse injuries in youth sports.
AU  - Patrick Mayolo
AU  - Zachary A Blashinsky
AU  - John Wahl
AU  - Alexander Bouterse
AU  - Felix Oettl
AU  - James A Pruneski
AU  - Kristian Samuelsson
PY  - 2026
DA  - 2026/10/07
JO  - Frontiers in public health
DO  - 10.3389/fpubh.2026.1966293
UR  - https://europepmc.org/article/MED/42909112
AB  - Early sport specialization (ESS), defined as intensive, year-round training in a single sport at the exclusion of others, has become increasingly prevalent among youth athletes. This trend has coincided with a rise in overuse injuries, and premature attrition. Concurrently, advances in wearable sensors and artificial intelligence (AI) enable real-time quantification of training load, biomechanical deviations, and recovery. However, a translational gap remains: existing AI surveillance models are predominantly validated in elite adult male cohorts, leaving youth athletes underserved. To address this gap, we propose a translational four-pillar framework for ESS-aware AI injury monitoring in youth sport. Bridging technological capabilities with developmental physiology through structured AI surveillance provides a structured risk-monitoring roadmap with the potential to inform preventative strategies, optimize physical readiness, and support long-term musculoskeletal health in youth athletes.
SN  - 2296-2565
ER  -