AI-Powered running coach aims to predict and prevent shin splints and Runner's knee

NCT ID NCT07689916

First seen Jul 08, 2026 · Last updated Jul 09, 2026 · Updated 1 time

Summary

This study uses machine learning to identify biomechanical risk factors for common running injuries like shin splints, runner's knee, and Achilles tendon pain in recreational runners. Participants undergo motion capture and muscle activity analysis while running, then are followed for six months to track injuries. After that, some receive an 8-week precision exercise program with stretching, strength training, and real-time feedback, while others continue their usual routine. The goal is to see if personalized exercises can improve running mechanics and reduce injury risk.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance
precision exercise program (stretching, strength training, real-time movement feedback)
What this could lead to
If successful, this could lead to personalized exercise programs that prevent common running injuries like shin splints and runner's knee.
What could go wrong
This is a small, early-stage study with 204 participants. The machine learning approach may not translate to all runners, and the exercise program may not outperform general training advice.

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Conditions

The condition(s) this trial relates to.

Medial Tibial Stress Syndrome patellofemoral pain syndrome tendinosis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Locations

  • Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education, East China Normal University

    Shanghai, Minhang District, 200241, China

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