In-clinic Functional Measurement and Analysis of Knee Osteoarthritis Patients Undergoing Total Knee Replacement
Abstract
Prevalence of osteoarthritis is increasing as individuals are remaining active later in life. Since the knee is one of the most commonly affected joints and is involved in almost all daily activities, functional impairment has a substantial impact on overall health. Despite this increase, there currently exists no disease modifying drugs or treatments. Mild cases are managed with physiotherapeutic exercises and common anti-inflammatories but surgical intervention is required for more severe disease progression.
Total knee replacement as a treatment for osteoarthritis is a highly successful surgery that is effective at restoring knee function and reducing pain but still requires further refinement. Over 70,000 of these surgeries are performed annually in Canada with 99% for the treatment of degenerative arthritis. Despite improvements to surgical technique and implant designs, studies report up to 20% of patients remain dissatisfied with their knee replacement up to the point of not undergoing the surgery again if it were an option. A singular cause for this dissatisfaction has not been pinpointed but strong influencers are pain, low functional improvement, and unmet expectations.
Early detection of functional problems permits further intervention through targeted physiotherapy or additional surgeries before problems escalate and cause patient dissatisfaction or implant revision. Current methods of patient evaluation rely on self-reported measures, which suffer from ceiling and floor effects often masking inter-patient differences. These measures are also influenced from patient expectations and what a patient reports they "can'' do, is not always representative of their true functional ability.
Wearable sensors permit objective functional measurement of the knee as a supplement to patient-reported measures. Instrumented performance tests can measure patient function and compare to similar recoveries to highlight deficiencies or positive recovery traits. This thesis outlines the development of such a wearable system for in-clinic measurement and the extraction of functional parameters to predict future outcomes and give surgeons the earliest indications for intervention. This information can also help surgeons realistically adjust patient expectations for recovery, even before undergoing surgery. It is expected that these individualized assessments to set expectations before surgical intervention will help address the persistently high patient dissatisfaction.