Using Computational Modeling To Estimate Changes In Joint Reaction Forces In The Knee Of Symptomatic Osteoarthritis Participants Using A Gait Retraining Intervention With Real-time Biofeedback

dc.contributor.advisorEddo, Oladipo
dc.creatorPrebble, Matthew
dc.date.accessioned2023-03-17T19:05:42Z
dc.date.available2023-03-17T19:05:42Z
dc.date.issued2022
dc.description.abstractThis dissertation evaluates the effect of gait modifications on the joint reaction forces (JRF) estimated via computer simulation using the OpenSim software tool. Osteoarthritis (OA) of the knee is a common and progressive condition that can lead to the need for a full or partial joint replacement. Identifying interventions that can slow the progression of the disease can help improve the quality of life and reduce impairments to activities of daily living in those diagnosed with knee OA. Modified gait interventions are a common approach that seek to reduce the loading in the knee joint, and significant research has demonstrated gait modifications’ effect on the knee adduction moment (KAM) and knee flexion moment (KFM). The KAM and KFM are common surrogate measures of joint loading and many gait interventions have been shown to reduce KAM and/or KFM. Recent advances in computer technology have enabled more efficient and practical use of simulation for estimating the joint reaction forces in the knee during a variety of tasks, such as walking and running. These approaches are often validated using data from subjects with instrumented knee implants and their accuracy and use have been growing. This dissertation covers 3 independent studies that sought to estimate the effect of gait interventions on the JRF in the knee. The first study used existing data published in the biomechanics community, via the Grand Challenge Competition to Predict in Vivo Knee Loads, to validate the use of the Lerner knee model in participants implementing 2 common gait interventions: the medial knee thrust (MKT) and the lateral trunk lean (LTL). The second study built on the first and implemented the simulation approach in 20 healthy participants who performed 3 gait modifications: the toe-in gait (TIG), the MKT, and the LTL. The final project of this dissertation research was a 10-week randomized controlled trial (RCT) that used real-time biofeedback (RTB) to implement the LTL in participants diagnosed with medial compartment knee OA. The results of this work validated the use of the Lerner knee model in modified gait, such as MKT and LTL. They also provided evidence to suggest that the LTL may not be as effective as previously thought at lowering the JRF in the medial compartment of the knee. Further work is needed to validate these findings and directions of future research are also discussed.
dc.format.extent209 pages
dc.format.mediumdoctoral dissertations
dc.identifier.urihttps://hdl.handle.net/1920/13176
dc.language.isoen
dc.rightsCopyright 2022 Matthew Prebble
dc.rights.urihttps://rightsstatements.org/vocab/InC/1.0
dc.subjectBiomechanics
dc.subjectGait
dc.subjectGait modifications
dc.subjectKnee osteoarthritis
dc.subjectReal-time biofeedback
dc.subjectSimulation
dc.subject.keywordsKinesiology
dc.subject.keywordsBiomechanics
dc.titleUsing Computational Modeling To Estimate Changes In Joint Reaction Forces In The Knee Of Symptomatic Osteoarthritis Participants Using A Gait Retraining Intervention With Real-time Biofeedback
dc.typeText
thesis.degree.disciplineEducation
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral
thesis.degree.namePh.D. in Education

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