A subject-specific musculoskeletal model to predict the tibiofemoral contact forces during daily living activities

Scalable musculoskeletal model for dynamic simulations of lower body movement

A musculoskeletal (MSK) model is an important tool for analysing human motions, calculating joint torques during movement, enhancing sports activity, and developing exoskeletons and prostheses. To enable biomechanical investigation of human motion, this work presents an open-source lower body MSK model. The MSK model of the lower body consists of 7 body segments (pelvis, left/right thigh, left/right leg, and left/right foot). The model has 20 degrees of freedom (DoFs) and 28 muscle torque generators (MTGs), which are developed from experimental data. The model can be modified for different anthropometric measurements and subject body characteristics, including sex, age, body mass, height, physical activity, and skin temperature. The model is validated by simulating the torque within the range of motion (ROM) of isolated movements; all simulation findings exhibit a good level of agreement with the literature.

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

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.

Can a Musculoskeletal Model Adapted to Knee Implant Geometry Improve Prediction of 3D Contact Forces and Moments?

Tibiofemoral contact loads are crucial parameters in the onset and progression of osteoarthrosis. While contact loads are frequently estimated from musculoskeletal models, their customization is often limited to scaling musculoskeletal geometry or adapting muscle lines. Moreover, studies have usually focused on superior-inferior contact force without investigating three-dimensional contact loads. Using experimental data from six patients with instrumented total knee arthroplasty (TKA), this study customized a lower limb musculoskeletal model to consider the positioning and the geometry of the implant at knee level. Static optimization was performed to estimate tibiofemoral contact forces and contact moments as well as musculotendinous forces. Predictions from both a generic and a customized model were compared to the instrumented implant measurements. Both models accurately predict superior-inferior (SI) force and abduction-adduction (AA) moment. Notably, the customization improves prediction of medial-lateral (ML) force and flexion-extension (FE) moments. However, there is subject-dependent variability in the prediction of anterior-posterior (AP) force. The customized models presented here predict loads on all joint axes and in most cases improve prediction. Unexpectedly, this improvement was more limited for patients with more rotated implants, suggesting a need for further model adaptations such as muscle wrapping or redefinition of hip and ankle joint centers and axes.

Computational biomechanics of human knee joint in stair ascent: Muscle-ligament-contact forces and comparison with level walking

About a third of knee joint disorders originate from the patellofemoral (PF) site that makes stair ascent a difficult activity for patients. A detailed finite element model of the knee joint is coupled to a lower extremity musculoskeletal model to simulate the stance phase of stair ascent. It is driven by the mean of measurements on the hip-knee-ankle moments-angles as well as ground reaction forces reported in healthy individuals. Predicted muscle activities compare well to the recorded electromyography data. Peak forces in quadriceps (3.87 BW, body weight, at 20% instance in our 607 N subject), medial hamstrings (0.77 BW at 20%), and gastrocnemii (1.21 BW at 80%) are estimated. Due to much greater flexion angles-moments in the first half of stance, large PF contact forces (peak of 3.1 BW at 20% stance) and stresses (peak of 4.83 MPa at 20% stance) are estimated that exceed their peaks in level walking by fourfold and twofold, respectively. Compared with level walking, ACL forces diminish in the first half of stance but substantially increase later in the second half (peak of 0.76 BW at 75% stance). Under nearly similar contact forces at 20% of stance, the contact stress on the tibiofemoral (TF) medial plateau reaches a peak (9.68 MPa) twice that on the PF joint suggesting the vulnerability of both joints. Compared with walking, stair ascent increases peak ACL force and both peak TF and PF contact stresses. Reductions in the knee flexion moment and/or angle appear as a viable strategy to mitigate internal loads and pain.