A SHAP-based machine learning approach to decoding the relationship between running posture features and tibial load in novice runners with MTSS: towards accurate and intelligent rehabilitation strategies
Ting Fan, Xiaomin Wu, Zeyi Zhang, Youping Sun · 2026
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Description
Ting Fan and three co-authors use machine learning to link running form with shin bone load in novice runners who have medial tibial stress syndrome. The painful condition, often called shin splints, troubles many new runners. One hundred seventy-four novices ran in a lab while motion and force data were recorded.
Of three models tried, a boosting model predicted shin load best. An explanation method then showed where load jumped: when the body's center sat low, when the ankle rolled inward past a small angle, and when the knee rotated inward past another threshold. The links were curved, not straight. The authors suggest coaching on body height and strength work for ankle and knee muscles.
Catalog record
| CREATOR | Ting Fan, Xiaomin Wu, Zeyi Zhang, Youping Sun |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 44 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |