Researchers have traditionally used motion capture to quantify discrete biomechanical data points (peak values) during hop testing. However, these analyses provide a narrow view of movement as they restrict the evaluation to a single time point (i.e. certain percentage of stance). The application of more comprehensive analyses may identify important characteristics that are masked by discrete analyses often used to screen patients for activity.


To examine the utility of functional data analyses to reveal asymmetries that are undetectable by discrete (i.e. single time point) evaluations in those with a history of anterior cruciate ligament reconstruction (ACLR) who achieve clinical hop symmetry.


Cross- sectional study.



Patients or Other Participants

15 subjects with unilateral ACLR (age=21±3yrs; time from surgery= 4±3yrs) and 15 healthy controls (age=23±2yrs) participated.


Lower extremity biomechanics were collected during the triple hop for distance task.

Main Outcome Measure(s)

Peak sagittal plane joint power, joint work, and power profiles were determined.


Discrete analyses identified significantly lower peak knee power and work in the ACLR limb compared to contralateral and control limbs (p<0.05), but were unable to identify differences at the ankle or hip. Functional data analyses identified significant asymmetries at the ankle, knee, and hip between ACLR and contralateral or control limbs throughout stance (p<0.05) and revealed that these asymmetries stemmed from knee power deficits that were prominent during early loading.


Despite achieving hop distance symmetry, ACLR knees absorbed less power. While this information was revealed with the discrete (i.e. single time point) analyses, underlying asymmetries at the ankle and hip were masked. Functional data analyses identified inter-limb asymmetries at the ankle, knee, and hip throughout ground contact and more fully elucidate the extent and source of asymmetries that can be utilized by clinicians and researchers alike to guide clinical decision making.

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