Optimization reduces knee-joint forces during walking and squatting: Validating the inverse dynamics approach for full body movements on instrumented knee prostheses
Heiko Wagner, Kim Joris Bostr\"om, Marc H.E. de Lussanet, Myriam L. de, Graaf, Christian Puta, and Luis Mochizuki

TL;DR
This study validates a computational musculoskeletal model that predicts knee joint forces during walking and squatting, demonstrating that optimization strategies can significantly reduce joint loads, which may inform patient rehabilitation.
Contribution
The paper introduces a validated full-body musculoskeletal model capable of accurately predicting knee joint forces and analyzing the impact of different motor control strategies on joint load reduction.
Findings
Musculoskeletal models predicted knee forces with high accuracy (RMSE <0.5 BW).
Minimizing joint forces yielded the best prediction accuracy.
Force reduction strategies can significantly decrease knee joint loads during movement.
Abstract
Due to the redundancy of our motor system, movements can be performed in many ways. While multiple motor control strategies can all lead to the desired behavior, they result in different joint and muscle forces. This creates opportunities to explore this redundancy, e.g., for pain avoidance or reducing the risk of further injury. To assess the effect of different motor control optimization strategies, a direct measurement of muscle and joint forces is desirable, but problematic for medical and ethical reasons. Computational modeling might provide a solution by calculating approximations of these forces. In this study, we used a full-body computational musculoskeletal model to (1) predict forces measured in knee prostheses during walking and squatting and (2) to study the effect of different motor control strategies (i.e., minimizing joint force vs. muscle activation) on the joint load…
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Taxonomy
TopicsMuscle activation and electromyography studies · Total Knee Arthroplasty Outcomes · Knee injuries and reconstruction techniques
