Masters Theses

Date of Award

8-2024

Degree Type

Thesis

Degree Name

Master of Science

Major

Kinesiology

Major Professor

Joshua T. Weinhandl

Committee Members

Joshua T. Weinhandl, Kevin Becker, Songning Zhang

Abstract

Anterior cruciate ligament injuries are among the most severe in sports, with significant long-term consequences for athletes, including a high risk of re-injury and early-onset osteoarthritis. Current rehabilitation methods and return-to-sport assessments often fall short in preventing re-injury, primarily due to a reliance on performance symmetry and strength profiles that do not adequately account for movement strategies. This study aims to bridge the gap between advanced biomechanical assessments and practical rehabilitation methods by investigating the potential of inertial measurement units to serve as reliable surrogates for traditional force plate measurements in assessing kinetic variables during ACLR rehabilitation.

The study involved a healthy population to establish baseline measures unaffected by existing health conditions. Multilevel linear regression models were used to evaluate the effectiveness of predicting GRF outcomes from accelerometer and gyroscopic metrics. It was hypothesized that IMU-derived metrics would strongly correlate with kinetic variables.

Contrary to the hypothesis that IMU-derived metrics would strongly correlate with kinetic variables, the results revealed only one strong correlation across all three movements, with the rest being either moderate or weak. Despite this, most of the regression models demonstrated high explanatory power, accounting for a significant percentage of the variance in the force plate metrics.

These findings suggest that IMU-derived metrics may not directly correlate strongly with force plate measurements, but they can still be valuable predictors when used in comprehensive modeling approaches. This demonstrates the potential for integrating IMUs into practical rehabilitation and return-to-sport assessments, providing a more accessible and versatile method for monitoring kinetic variables and enhancing current ACLR rehabilitation protocols.

Download
Files over 3MB may be slow to open. For best results, right-click and select "save as..."

Share

COinS