Dataset Information

Human leg model predicts ankle muscle-tendon morphology, state, roles and energetics in walking.

ABSTRACT: A common feature in biological neuromuscular systems is the redundancy in joint actuation. Understanding how these redundancies are resolved in typical joint movements has been a long-standing problem in biomechanics, neuroscience and prosthetics. Many empirical studies have uncovered neural, mechanical and energetic aspects of how humans resolve these degrees of freedom to actuate leg joints for common tasks like walking. However, a unifying theoretical framework that explains the many independent empirical observations and predicts individual muscle and tendon contributions to joint actuation is yet to be established. Here we develop a computational framework to address how the ankle joint actuation problem is resolved by the neuromuscular system in walking. Our framework is founded upon the proposal that a consideration of both neural control and leg muscle-tendon morphology is critical to obtain predictive, mechanistic insight into individual muscle and tendon contributions to joint actuation. We examine kinetic, kinematic and electromyographic data from healthy walking subjects to find that human leg muscle-tendon morphology and neural activations enable a metabolically optimal realization of biological ankle mechanics in walking. This optimal realization (a) corresponds to independent empirical observations of operation and performance of the soleus and gastrocnemius muscles, (b) gives rise to an efficient load-sharing amongst ankle muscle-tendon units and (c) causes soleus and gastrocnemius muscle fibers to take on distinct mechanical roles of force generation and power production at the end of stance phase in walking. The framework outlined here suggests that the dynamical interplay between leg structure and neural control may be key to the high walking economy of humans, and has implications as a means to obtain insight into empirically inaccessible features of individual muscle and tendons in biomechanical tasks.

SUBMITTER: Krishnaswamy P

PROVIDER: S-EPMC3060164 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Human leg model predicts ankle muscle-tendon morphology, state, roles and energetics in walking.

Krishnaswamy Pavitra P Brown Emery N EN Herr Hugh M HM

PLoS computational biology 20110317 3

A common feature in biological neuromuscular systems is the redundancy in joint actuation. Understanding how these redundancies are resolved in typical joint movements has been a long-standing problem in biomechanics, neuroscience and prosthetics. Many empirical studies have uncovered neural, mechanical and energetic aspects of how humans resolve these degrees of freedom to actuate leg joints for common tasks like walking. However, a unifying theoretical framework that explains the many independ ...[more]

PMID: 21445231

Similar Datasets

Project description:BACKGROUND:Controllers for assistive robotic devices can be divided into two main categories: controllers using neural signals and controllers using mechanically intrinsic signals. Both approaches are prevalent in research devices, but a direct comparison between the two could provide insight into their relative advantages and disadvantages. We studied subjects walking with robotic ankle exoskeletons using two different control modes: dynamic gain proportional myoelectric control based on soleus muscle activity (neural signal), and timing-based mechanically intrinsic control based on gait events (mechanically intrinsic signal). We hypothesized that subjects would have different measures of metabolic work rate between the two controllers as we predicted subjects would use each controller in a unique manner due to one being dependent on muscle recruitment and the other not. METHODS:The two controllers had the same average actuation signal as we used the control signals from walking with the myoelectric controller to shape the mechanically intrinsic control signal. The difference being the myoelectric controller allowed step-to-step variation in the actuation signals controlled by the user's soleus muscle recruitment while the timing-based controller had the same actuation signal with each step regardless of muscle recruitment. RESULTS:We observed no statistically significant difference in metabolic work rate between the two controllers. Subjects walked with 11% less soleus activity during mid and late stance and significantly less peak soleus recruitment when using the timing-based controller than when using the myoelectric controller. While walking with the myoelectric controller, subjects walked with significantly higher average positive and negative total ankle power compared to walking with the timing-based controller. CONCLUSIONS:We interpret the reduced ankle power and muscle activity with the timing-based controller relative to the myoelectric controller to result from greater slacking effects. Subjects were able to be less engaged on a muscle level when using a controller driven by mechanically intrinsic signals than when using a controller driven by neural signals, but this had no affect on their metabolic work rate. These results suggest that the type of controller (neural vs. mechanical) is likely to affect how individuals use robotic exoskeletons for therapeutic rehabilitation or human performance augmentation.

Project description:BackgroundElastic ankle exoskeletons with intermediate stiffness springs in parallel with the human plantarflexors can reduce the metabolic cost of walking by ~ 7% at 1.25 m s- 1. In a move toward 'real-world' application, we examined whether the unpowered approach has metabolic benefit across a range of walking speeds, and if so, whether the optimal exoskeleton stiffness was speed dependent. We hypothesized that, for any walking speed, there would be an optimal ankle exoskeleton stiffness - not too compliant and not too stiff - that minimizes the user's metabolic cost. In addition, we expected the optimal stiffness to increase with walking speed.MethodsEleven participants walked on a level treadmill at 1.25, 1.50, and 1.75 m s- 1 while we used a state-of-the-art exoskeleton emulator to apply bilateral ankle exoskeleton assistance at five controlled rotational stiffnesses (kexo = 0, 50, 100, 150, 250 Nm rad- 1). We measured metabolic cost, lower-limb joint mechanics, and EMG of muscles crossing the ankle, knee, and hip.ResultsMetabolic cost was significantly reduced at the lowest exoskeleton stiffness (50 Nm rad- 1) for assisted walking at both 1.25 (4.2%; p = 0.0162) and 1.75 m s- 1 (4.7%; p = 0.0045). At these speeds, the metabolically optimal exoskeleton stiffness provided peak assistive torques of ~ 0.20 Nm kg- 1 that resulted in reduced biological ankle moment of ~ 12% and reduced soleus muscle activity of ~ 10%. We found no stiffness that could reduce the metabolic cost of walking at 1.5 m s- 1. Across all speeds, the non-weighted sum of soleus and tibialis anterior activation rate explained the change in metabolic rate due to exoskeleton assistance (p < 0.05; R2 > 0.56).ConclusionsElastic ankle exoskeletons with low rotational stiffness reduce users' metabolic cost of walking at slow and fast but not intermediate walking speed. The relationship between the non-weighted sum of soleus and tibialis activation rate and metabolic cost (R2 > 0.56) indicates that muscle activation may drive metabolic demand. Future work using simulations and ultrasound imaging will get 'under the skin' and examine the interaction between exoskeleton stiffness and plantarflexor muscle dynamics to better inform stiffness selection in human-machine systems.

Dataset Information

Human leg model predicts ankle muscle-tendon morphology, state, roles and energetics in walking.

Publications

Human leg model predicts ankle muscle-tendon morphology, state, roles and energetics in walking.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets