Identifying the different neural strategies that a person may adopt to perform simple locomotor tasks, such as walking, may enable the definition of rehabilitation plans aimed to reduce joint loads while preserving joint kinematics. Abnormal detrimental loading conditions that would likely reduce a person’s quality of life, especially among the elderly, could thus be prevented. Leveraging on previous works, we employed musculoskeletal models and biomechanical simulations (1) to explore how healthy young and elder adults recruit their muscles to perform a walking task, and (2) to determine whether the use of electromyography data to inform the simulations would allow to reduce the solution space. For the 15 tested subjects (10 young, 5 elderly), we estimated 10k sets of muscle and knee joint contact forces combining a static optimization approach with a Markov-chain Monte Carlo algorithm. We observed that the bands of solutions were narrower among the young adults than the elderly, showing how different neural strategies that prioritize the use of different muscles while ensuring the same kinematics are more likely to result in larger changes in the joint contact forces among older adults. In addition, while the neural strategies associated to the maximal knee contact forces were similar between populations, some differences emerged when analysing the strategies to minimise the knee loads. Last, the use of electromyography data allowed for a reduction of the solution band by up to 69%.
Davico et al. (Thu,) studied this question.