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.

Figure 1

A: Graphical illustration of muscle activation during a step in the generic model with normal muscle strength and B: in the same model but with 40 percent weakened muscles. The muscle colors represent the level of activation on a scale from dark blue (no activation) to bright red (full activation). C: Steps for generating simulations using normal-strength () and weak () models. In blue: inputs to the simulation; in yellow: analysis steps; in orange: outcomes of the simulation. M-S: Musculoskeletal, IK: Inverse Kinematics, RRA: Residual Reduction Algorithm, CMC: Computed Muscle Control. See text for details.

Figure 2

Simulated muscle activations (blue lines) and experimental EMG (black lines), for all five muscles of which EMG was collected. Shaded areas show standard deviations. Experimental EMG data are rectified and bi-directionally low-pass filtered at 6 Hz, and their peak value is normalized to the peak value of the simulated muscle activation per subject. All data are averages over 5 subjects, one subject had to be excluded because of artifacts in the EMG.

Figure 3

Total joint moments and reserve joint actuator moments as a function of the gait cycle, at varying levels of generalized muscle weakness. Each line represents the average over 6 subjects. The presence of reserve actuators indicates the inability of muscles to deliver enough joint moment to produce normal gait.

Figure 4

Examples of the effect of local muscle weakness on muscle forces during gait. Top row: GMED weakness; middle row: plantarflexor (GAS+SO) weakness; bottom row: iliopsoas (PSO+IL) weakness. Lighter colors give strength values at increasing levels of weakness, from black = normal force (0% weakness) to light blue = total strength loss (100% weakness). 100% weakness was not possible for plantarflexors. Each line represents the average over 6 subjects. Abbreviations: GMED, gluteus medius; GMIN, gluteus minimus; GMAX, gluteus maximus; TFL, tensor fascia lata; SMM, semimembranosus; PSO, psoas; GAS, gastrocnemius; SO, soleus; TP, tibialis posterior; PERL, peroneus longus; BFS, biceps femoris short head; TA, tibialis anterior; IL, iliacus; RF, rectus femoris; ADL, adductor longus.

Figure 5

Increase in total muscle cost with increasing levels of weakness (20% to 80% strength loss) for all evaluated muscle groups.