Wearable sensors and AI could predict leg injuries before they happen
NCT ID NCT07289828
First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 2 times
Summary
This study looked at 108 healthy sports science students to see if past leg injuries leave lasting changes in walking and running patterns. Participants wore small sensors on their legs while walking and running, and filled out questionnaires about their injury history. The goal was to use AI to find patterns linked to previous knee and ankle injuries, which could one day help predict and prevent future injuries.
What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
What this could lead to
If successful, this could lead to a simple, non-invasive way to predict and prevent lower extremity injuries using wearable sensors and AI.
What could go wrong
This is an early, completed study with 108 healthy students. The AI algorithm needs further validation in larger, more diverse groups before it can be used in practice.
Disclaimer
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This is a summary of
the original study
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Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
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Locations
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TUM University Hospital
Munich, Bavaria, 81675, Germany