Peak vertical ground reaction force and linear loading rate can be valuable metrics for return-to-sport assessment because they represent limb loading dynamics; yet, there is no defined cutoff criterion to differentiate between healthy and altered limb loading. Studies have shown that healthy individuals exhibit strong first-order relationships between gait variables whereas individuals with pathological conditions did not. Thus, this study sought to explore and exploit this first-order relationship to define a region of healthy limb dynamics, which individuals with pathological conditions would reside outside of, to rapidly assess individuals with altered limb loading dynamics for return to sport. We hypothesized that there would be a strong first-order linear relationship between vertical ground reaction force peak force and linear loading rate in healthy controls’ limbs, which could be exploited to identify abnormal limb loading dynamics in post–anterior cruciate ligament reconstruction (ACLR) individuals.
Thirty-one post-ACLR individuals and 31 healthy controls performed a running protocol. A first-order regression analysis modeled the relationship between peak vertical ground reaction forces and linear vertical ground reaction force loading rate in the healthy control limbs to define a region of healthy dynamics to evaluate post-ACLR reconstructed limb dynamics.
A first-order regression model aided in the determination of cutoff criteria to define a region of healthy limb dynamics. Ninety percent of the post-ACLR reconstructed limbs exhibited abnormal limb dynamics based on their location outside of the region of healthy dynamics.
This approach successfully delineated between healthy and abnormal limb loadings dynamics in controls and post-ACLR individuals. The findings demonstrate how force and loading rate–dependent metrics can help develop criteria for individualized post-ACLR return-to-sport assessment.