Abstract
Total knee arthroplasty is a common surgical treatment to improve ambulatory function for individuals with end-stage osteoarthritis of the knee. Functional and self-reported measures are widely used to assess functional ability and impairment before and after total knee arthroplasty. However, clinical assessments have limitations and often provide subjective and limited information. Seamless gait characteristic monitoring in the real-world condition is a viable alternative to address these limitations, but the effectiveness of using wearable sensors for knee treatment is unclear. The purpose of this study was to determine if inertial gait variables from wearable sensors effectively estimate the questionnaire, performance (6-min walk test, timed up and go, and 30-s chair stand test), and isometric measure outcomes in individuals after unilateral total knee arthroplasty. Eighteen subjects at least 6 months post-surgery participated in the experiment. In one session, three tasks, including self-reported surveys, functional testing, and isometric tests were conducted. In another session, the participants' gait patterns were measured during a 1-min walking test at their self-selected gait speed with two accelerometers worn above the lateral malleoli. Session order was inconsistent between subjects. Significant inertial gait variables were selected using stepwise regressions, and the contributions of different categories of inertial gait variables were examined using hierarchical regressions. Our results indicate inertial gait variables were significantly correlated with performance test and questionnaire outcomes but did not correlate well with isometric strength measures. The findings demonstrate that wearable sensor-based gait analysis may be able to help predict clinical measures in individuals after unilateral knee treatment.
Highlights
Knee osteoarthritis (OA) is a common degenerative joint disease that decreases an individual’s functional ability and overall quality of life (Ruiz et al, 2013; Palazzo et al, 2016)
Inertial variables were significantly correlated with self-reported survey and performance test results (Table 2)
Impulse and magnitude inertial variables including vertical heel-strike magnitude and vertical heel-strike impulse were significantly correlated with self-reported survey and performance tests (Table 3)
Summary
Knee osteoarthritis (OA) is a common degenerative joint disease that decreases an individual’s functional ability and overall quality of life (Ruiz et al, 2013; Palazzo et al, 2016). Previous research has clearly demonstrated that patientreported outcomes alone do not accurately describe recovery post-TKA (Mizner et al, 2011), and that a combination of patient-reported and performance-based measures are needed to identify patients with functional deficits (Mizner et al, 2011; Bolink et al, 2015; Hossain et al, 2015). Functional performance tests can objectively capture a patient’s mobility, but each test only addresses a small aspect of physical function not fully capturing the subject’s true experiences in everyday life. Given these challenges and short-comings, there has been great interest in using lowcost wearable sensors to develop mobile and remote tools for obtaining functional patient data. Previous studies exploring the use of sensor-based assessment post-TKA are limited to simple signal metrics such as spatiotemporal (Bolink et al, 2015) or peak acceleration measures (Christiansen et al, 2015), with no correlation to insightful biomechanical or performance based measures
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