How robust is human gait to muscle weakness?
ABSTRACT Humans have a remarkable capacity to perform complex movements requiring agility, timing, and strength. Disuse, aging, and disease can lead to a loss of muscle strength, which frequently limits the performance of motor tasks. It is unknown, however, how much weakness can be tolerated before normal daily activities become impaired. This study examines the extent to which lower limb muscles can be weakened before normal walking is affected. We developed muscle-driven simulations of normal walking and then progressively weakened all major muscle groups, one at the time and simultaneously, to evaluate how much weakness could be tolerated before execution of normal gait became impossible. We further examined the compensations that arose as a result of weakening muscles. Our simulations revealed that normal walking is remarkably robust to weakness of some muscles but sensitive to weakness of others. Gait appears most robust to weakness of hip and knee extensors, which can tolerate weakness well and without a substantial increase in muscle stress. In contrast, gait is most sensitive to weakness of plantarflexors, hip abductors, and hip flexors. Weakness of individual muscles results in increased activation of the weak muscle, and in compensatory activation of other muscles. These compensations are generally inefficient, and generate unbalanced joint moments that require compensatory activation in yet other muscles. As a result, total muscle activation increases with weakness as does the cost of walking. By clarifying which muscles are critical to maintaining normal gait, our results provide important insights for developing therapies to prevent or improve gait pathology.
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ABSTRACT: Muscle-driven simulations of human and animal motion are widely used to complement physical experiments for studying movement dynamics. Musculotendon models are an essential component of muscle-driven simulations, yet neither the computational speed nor the biological accuracy of the simulated forces has been adequately evaluated. Here we compare the speed and accuracy of three musculotendon models: two with an elastic tendon (an equilibrium model and a damped equilibrium model) and one with a rigid tendon. Our simulation benchmarks demonstrate that the equilibrium and damped equilibrium models produce similar force profiles but have different computational speeds. At low activation, the damped equilibrium model is 29 times faster than the equilibrium model when using an explicit integrator and 3 times faster when using an implicit integrator; at high activation, the two models have similar simulation speeds. In the special case of simulating a muscle with a short tendon, the rigid-tendon model produces forces that match those generated by the elastic-tendon models, but simulates 2-54 times faster when an explicit integrator is used and 6-31 times faster when an implicit integrator is used. The equilibrium, damped equilibrium, and rigid-tendon models reproduce forces generated by maximally-activated biological muscle with mean absolute errors less than 8.9%, 8.9%, and 20.9% of the maximum isometric muscle force, respectively. When compared to forces generated by submaximally-activated biological muscle, the forces produced by the equilibrium, damped equilibrium, and rigid-tendon models have mean absolute errors less than 16.2%, 16.4%, and 18.5%, respectively. To encourage further development of musculotendon models, we provide implementations of each of these models in OpenSim version 3.1 and benchmark data online, enabling others to reproduce our results and test their models of musculotendon dynamics.Journal of Biomechanical Engineering. 02/2013; 135(2):021005.