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Review and perspective: neuromechanical considerations for predicting muscle activation patterns for movement
Author(s) -
Ting Lena H.,
Chvatal Stacie A.,
Safavynia Seyed A.,
Lucas McKay J.
Publication year - 2012
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.2485
Subject(s) - motor control , computer science , task (project management) , physical medicine and rehabilitation , movement (music) , redundancy (engineering) , artificial intelligence , psychology , neuroscience , medicine , engineering , philosophy , systems engineering , operating system , aesthetics
SUMMARY Muscle coordination may be difficult or impossible to predict accurately based on biomechanical considerations alone because of redundancy in the musculoskeletal system. Because many solutions exist for any given movement, the role of the nervous system in further constraining muscle coordination patterns for movement must be considered in both healthy and impaired motor control. On the basis of computational neuromechanical analyses of experimental data combined with modeling techniques, we have demonstrated several such neural constraints on the temporal and spatial patterns of muscle activity during both locomotion and postural responses to balance perturbations. We hypothesize that subject‐specific and trial‐by‐trial differences in muscle activation can be parameterized and understood by a hierarchical and low‐dimensional framework that reflects the neural control of task‐level goals. In postural control, we demonstrate that temporal patterns of muscle activity may be governed by feedback control of task‐level variables that represent the overall goal‐directed motion of the body. These temporal patterns then recruit spatially‐fixed patterns of muscle activity called muscle synergies that produce the desired task‐level biomechanical functions that require multijoint coordination. Moreover, these principles apply more generally to movement, and in particular to locomotor tasks in both healthy and impaired individuals. Overall, understanding the goals and organization of the neural control of movement may provide useful reduced dimension parameter sets to address the degrees‐of‐freedom problem in musculoskeletal movement control. More importantly, however, neuromechanical analyses may lend insight and provide a framework for understanding subject‐specific and trial‐by‐trial differences in movement across both healthy and motor‐impaired populations. Copyright © 2012 John Wiley & Sons, Ltd.

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