Human Leg Model Predicts Ankle Muscle-Tendon Morphology, State, Roles and Energetics in Walking

Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
PLoS Computational Biology (Impact Factor: 4.62). 03/2011; 7(3):e1001107. DOI: 10.1371/journal.pcbi.1001107
Source: PubMed


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.

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Available from: Pavitra Krishnaswamy, Nov 04, 2014
    • "This requires a musculoskeletal modeling method that accounts for physiological muscle recruitment strategies and contraction dynamics. In this study we address this challenge by using an EMG-driven musculoskeletal model of the human leg (Lloyd and Besier, 2003; Buchanan et al., 2004; Krishnaswamy et al., 2011; Sartori et al., 2012b; Farris et al., 2014). The term " leg " is used throughout this manuscript according to its anatomical definition. "
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    • "Subsequently , EMG-linear envelopes have been used to drive neuromusculoskeletal models (i.e. EMG-driven modeling) during a variety of dynamic motor tasks and predict resulting joint moments (Besier et al., 2009; Krishnaswamy et al., 2011; Manal et al., 2002; Sartori et al., 2012a). In these, the underlying musculoskeletal model is scaled and calibrated to an individual's anthropometry and EMG-force generating properties. "
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