Feasible muscle activation ranges based on inverse dynamics analyses of human walking

Abstract

Although it is possible to produce the same movement using an infinite number of different muscle activation patterns owing to musculoskeletal redundancy, the degree to which observed variations in muscle activity can deviate from optimal solutions computed from biomechanical models is not known. Here, we examined the range of biomechanically permitted activation levels in individual muscles during human walking using a detailed musculoskeletal model and experimentally-measured kinetics and kinematics. Feasible muscle activation ranges define the minimum and maximum possible level of each muscle’s activation that satisfy inverse dynamics joint torques assuming that all other muscles can vary their activation as needed. During walking, 73% of the muscles had feasible muscle activation ranges that were greater than 95% of the total muscle activation range over more than 95% of the gait cycle, indicating that, individually, most muscles could be fully active or fully inactive while still satisfying inverse dynamics joint torques. Moreover, the shapes of the feasible muscle activation ranges did not resemble previously-reported muscle activation patterns nor optimal solutions, i.e. static optimization and computed muscle control, that are based on the same biomechanical constraints. Our results demonstrate that joint torque requirements from standard inverse dynamics calculations are insufficient to define the activation of individual muscles during walking in healthy individuals. Identifying feasible muscle activation ranges may be an effective way to evaluate the impact of additional biomechanical and/or neural constraints on possible versus actual muscle activity in both normal and impaired movements.

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“…This diluted effect might be difficult to verify in EMG signals with relatively high variability. Additionally, recorded muscle activity may not have changed despite decreased joint moments if changes occurred in non-superficial muscles that are unmeasurable with surface electromyography (Bernstein, 1967;Martelli et al, 2015;Simpson et al, 2015). Alternatively, because metabolic power results from a combination of factors including muscle activation, muscle fiber length and velocity (kinematics), and mechanical work done by the muscle fibers (Umberger, 2010;Umberger et al, 2003), muscle activity need not change, though joint moments and metabolic power did.…”

Suboptimal Muscle Synergy Activation Patterns Generalize their Motor Function across Postures

“…However, experimental evidence suggests that there is no single muscle activation pattern used across individuals despite similar motor outputs (Torres-Oviedo et al, 2006 ; Torres-Oviedo and Ting, 2007 ; Clark et al, 2010 ; Chvatal et al, 2011 ; Frère and Hug, 2012 ). Our recent work suggests that muscle activity for performing a motor task in a single condition is largely unconstrained (Sohn et al, 2013 ; Simpson et al, 2015 ). Instead, a large number of “good-enough” solutions can be identified to perform any motor task (Raphael et al, 2010 ; Loeb, 2012 ), demonstrating our ability to take advantage of the highly redundant motor solution space.…”

The cost of being stable: Trade-offs between effort and stability across a landscape of redundant motor solutions

“…For reactive balance tasks in cats, we explicitly showed individualspecific differences in motor modules that receive similar neural commands and produce equivalent motor outputs in healthy, trained, animals [9]. Through analysis of musculoskeletal models, we found the biomechanics of the limb and task requirements to impose few constraints on feasible muscle activation patterns [10][11][12][13]. These results indicate that there is ample room in the nullspace, i.e.…”

“…It is also possible that motor solutions differ across individuals because the nullspace of motor solutions has many local minima in terms of their functional properties. While previous works have identified wide bounds in nullspace of motor solutions [10,12,13], and spatial structure in multitude of muscle activation patterns that lie within that space [49], it remains unknown whether such redundancy also generate functional equivalence in many different solutions. The existence of functionally equivalent motor solutions could explain how two people could arrive on different solutions yet with seemingly similar performance [2,9,50,51].…”