Peak Tibiofemoral Contact Forces Estimated Using IMU-Based Approaches Are Not Significantly Different from Motion Capture-Based Estimations in Patients with Knee Osteoarthritis

Abstract

Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context.

Population-based analysis of knee joint loading in a knee osteoarthritis cohort: the impact of PCA-derived gait kinematic variations on estimated medial knee contact forces

“…This study aimed to identify population-specific kinematic variations or so-called gait primitives in healthy or knee OA populations and how they affected knee joint loading. To this end we applied PCA to a large set of gait kinematics data from both healthy and knee OA population combined with a previously developed MSK modelling workflow [37].…”

Population-based analysis of knee joint loading in a knee osteoarthritis cohort: the impact of PCA-derived gait kinematic variations on estimated medial knee contact forces

“…This approach allowed for a targeted and isolated analysis of each mode and their contribution to the knee loading parameters. Each reconstructed gait pattern represented by each individual mode +/-1 standard deviation were utilized as input in a previously developed pipeline that integrated probabilistic principal component analysis (PPCA) [37], [54] and the zero moment point (ZMP) methods [55], [56] to estimate ground reaction forces, moments (GRFM), and the center of pressure (COP) and subsequently estimate the knee joint loading parameters (pressure, contact force, contact area) [26], [28], [52]. Thus, the impact of the reconstructed gait patterns, represented by each individual mode, on the change in knee contact force (KCF) peaks was investigated.…”

“…We investigated the effect of the observed gait primitives on estimated knee contact force defined by the modes from the healthy and KOA population. Specifically, each single unique gait pattern for each unique mode was used as input in a previously developed MSK modeling workflow [37] to estimate the knee contact forces (Fig 2 and 3 bottom right panel). As such, we can examine how the joint variations illustrated in Fig.…”