Quantifying varus thrust in knee osteoarthritis using wearable inertial sensors: A proof of concept

Costello, Kerry E, Eigenbrot, Samantha, Geronimo, Alex, Guermazi, Ali, Felson, David T, Richards, James orcid iconORCID: 0000-0002-4004-3115 and Kumar, Deepak (2020) Quantifying varus thrust in knee osteoarthritis using wearable inertial sensors: A proof of concept. Clinical Biomechanics, 80 . p. 105232. ISSN 0268-0033

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Official URL: https://doi.org/10.1016/j.clinbiomech.2020.105232


Varus thrust during walking, visualized as excessive frontal plane knee motion during weight acceptance, is a modifiable risk factor for progression of knee osteoarthritis. However, visual assessment does not capture thrust severity and quantification with optical motion capture is often not feasible. Inertial sensors may provide a convenient alternative to optical motion capture. This proof-of-concept study sought to compare wearable inertial sensors to optical motion capture for the quantification of varus thrust. Twenty-six participants with medial knee osteoarthritis underwent gait analysis at self-selected and fast speeds. Linear regression with generalized estimating equations assessed associations between peak knee adduction velocity or knee adduction excursion from optical motion capture and peak thigh or shank adduction velocity from two inertial sensors on the lower limb. Relationships between inertial measures and peak external knee adduction moment were assessed as a secondary aim. Both thigh and shank inertial sensor measures were associated with the optical motion capture measures for both speeds (P < 0.001 to P = 0.020), with the thigh measures having less variability than the shank. After accounting for age, sex, body mass index, radiographic severity, and limb alignment, thigh adduction velocity was also associated with knee adduction moment at both speeds (both P < 0.001). An inertial sensor placed on the mid-thigh can quantify varus thrust in people with medial knee osteoarthritis without the need for optical motion capture. This single sensor may be useful for risk screening or evaluating the effects of interventions in large samples. [Abstract copyright: Copyright © 2020 Elsevier Ltd. All rights reserved.]

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