Category
Clinical Biomechanics
Document Type
Paper
Abstract
The aim of the present study was to develop an algorithm to assess the anterior cruciate ligament (ACL) injury risk during the return to sport (RTS) continuum through sport-specific biomechanical testing. Sixty-two players (21 ACLR, 40 healthy controls) performed planned and unplanned football-specific changes of direction in a football pitch. Kinematics were collected through 8 wearable inertial sensors (MTw Awinda, Movella) on lower limbs and sternum. An algorithm to determine the risk of knee loading based on the dangerous movement patterns was provided (“Anterior Cruciate Ligament Injury Risk profile Detection”, ACL-IRD). The algorithm detected at-risk biomechanics in about one-fourth of the trials, mostly when performed with the injured limb. The ACL-IRD algorithm objectively detects injury risk biomechanics in ACLR football players and has the potential to assist the RTS decision making through ecologically valid, data-driven assessments.
Recommended Citation
Di Paolo, Stefano; Mendicino, Margherita; Viotto, Marianna; Grassi, Alberto; and Zaffagnini, Stefano
(2025)
"TESTING ACLR FOOTBALL PLAYERS ON THE FIELD: AN ALGORITHM TO ASSESS CUTTING BIOMECHANICS INJURY RISK THROUGH WEARABLES,"
ISBS Proceedings Archive: Vol. 43:
Iss.
1, Article 19.
Available at:
https://commons.nmu.edu/isbs/vol43/iss1/19
