Date Available

4-29-2022

Year of Publication

2020

Degree Name

Master of Science (MS)

Document Type

Master's Thesis

College

Education

Department/School/Program

Kinesiology and Health Promotion

First Advisor

Dr. Brian Noehren

Abstract

Recovery from anterior cruciate ligament reconstruction (ACLR) commonly results in undesirable physical and patient-reported outcomes (PROs). Identification of modifiable factors such as knee contact force (KCF) early in rehabilitation that can improve these outcomes is important due to the rapid decrease in function, quality of life, and joint health in this population. Additionally, if noninvasive measurement of KCFs outside of a traditional laboratory were possible, clinicians could optimize patient treatment with personalized care. Therefore, there are two primary aims to this thesis: 1) quantify the link between KCF and PROs which measure pain, ability to perform activities of daily living, and quality of life 6 months after ACLR; and 2) develop a novel method to monitor KCF outside the laboratory using unobtrusive wearable sensors. To address the first aim, eighty subjects were enrolled six months following ACLR. Patient-reported quality of life, ability to perform activities of daily living, and pain were evaluated with the KOOS QOL, ADL, and Pain subscales, respectively. A musculoskeletal model was utilized to estimate peak KCF. Subjects with scores above the patient acceptable symptom state (PASS) threshold for the KOOS QOL and ADL demonstrated greater ACLR limb peak KCF (p = 0.001 and p = 0.017, respectively), which was not found with KOOS Pain-dichotomized groups (p = 0.079). To address the second aim, nine healthy subjects walked at a wide range of speeds on an instrumented treadmill. Thirteen insole force features were calculated as potential predictors of peak KCF and KCF impulse per step, estimated with musculoskeletal modeling. Prediction error was calculated as 10-fold cross validated median symmetric accuracy. Pearson product-moment correlation coefficients defined the relationship between variable pairs. Models developed per-limb demonstrated lower prediction error (KCF impulse: 2.19%; peak KCF: 3.50%) than those developed per-subject (KCF impulse: 3.40%; peak KCF: 6.47%). A number of insole features were associated with peak KCF (7 strong, 4 moderate), but not KCF impulse (all negligible). The findings from the first aim demonstrate that subjects with poor quality of life or ability to complete everyday activities underload their knee, possibly accelerating their path to osteoarthritis development. The findings from the second aim suggest that KCFs can be monitored with force-sensing insoles.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2020.093

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