Date of Award

Spring 2016

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Biomedical Engineering

First Advisor

Harris, Gerald F.

Second Advisor

Vetter, Carole

Third Advisor

Kipp, Kristoff

Abstract

Injury to the anterior cruciate ligament (ACL) has been widely investigated through observational video analysis and laboratory based cadaveric, motion capture and computer simulation models. With the greater incidence of injury in the female population, recent emphasis has been placed on understanding ACL injury mechanisms in females. By using our understanding of injury mechanisms and prospective studies, injury prediction methods can be created. Once injury can be reliably predicted, training methods can be implemented to reduce likelihood of injury and avoid devastating consequences. There is a need for a reliable way to reduce motion capture data obtained in a laboratory setting to viable measures that characterize the entire data set and correlate such measures to clinically relevant tests. The present study performed motion analysis on healthy active young adult females during drop jump landings to characterize normal jump landing dynamics. Kinematic and kinetic data was reduced using principal component analysis to objectively determine variables of importance. Five principal components represented a cumulative 87.41% of the data set variance. Using principal component scores, significant associations were identified between principal component four (base of support at initial contact, peak knee abduction moment and 100 ms after initial contact) and knee flexion to extension isokinetic strength ratio. Additional significant correlation was found between principal component five (initial contact coronal knee moment and transverse knee moment) and abduction to adduction isokinetic strength ratio tested at 90°/sec. These results suggest principal component analysis is a viable method to reducing dynamic motion capture data. Further, principal component scores are a possible way to predict isokinetic strength ratios obtained in the clinic.

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