Co-simulation of neuromuscular dynamics and knee mechanics during human walking

人体行走过程中神经肌肉动力学和膝关节力学的协同仿真

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Abstract

This study introduces a framework for co-simulating neuromuscular dynamics and knee joint mechanics during gait. A knee model was developed that included 17 ligament bundles and a representation of the distributed contact between a femoral component and tibial insert surface. The knee was incorporated into a forward dynamics musculoskeletal model of the lower extremity. A computed muscle control algorithm was then used to modulate the muscle excitations to drive the model to closely track measured hip, knee, and ankle angle trajectories of a subject walking overground with an instrumented knee replacement. The resulting simulations predicted the muscle forces, ligament forces, secondary knee kinematics, and tibiofemoral contact loads. Model-predicted tibiofemoral contact forces were of comparable magnitudes to experimental measurements, with peak medial (1.95 body weight (BW)) and total (2.76 BW) contact forces within 4-17% of measured values. Average root-mean-square errors over a gait cycle were 0.26, 0.42, and 0.51 BW for the medial, lateral, and total contact forces, respectively. The model was subsequently used to predict variations in joint contact pressure that could arise by altering the frontal plane joint alignment. Small variations (±2 deg) in the alignment of the femoral component and tibial insert did not substantially affect the location of contact pressure, but did alter the medio-lateral distribution of load and internal tibia rotation in swing. Thus, the computational framework can be used to virtually assess the coupled influence of both physiological and design factors on in vivo joint mechanics and performance.

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