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Applied Bionics and Biomechanics
Volume 2018, Article ID 3615368, 15 pages
https://doi.org/10.1155/2018/3615368
Review Article

A Systematic Review on Muscle Synergies: From Building Blocks of Motor Behavior to a Neurorehabilitation Tool

1Department of System Engineering, George W. Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock, Little Rock, AR 72204, USA
2Department of Engineering Technology, George W. Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock, Little Rock, AR 72204, USA
3School of Counseling, Human Performance and Rehabilitation, University of Arkansas at Little Rock, Little Rock, AR 72204, USA
4Department of Biochemistry and Molecular Biology, College of Medicine, University of Florida, Gainesville, FL 32610, USA

Correspondence should be addressed to Kamran Iqbal; ude.rlau@labqixk

Received 22 November 2017; Accepted 29 January 2018; Published 22 April 2018

Academic Editor: Panagiotis K. Artemiadis

Copyright © 2018 Rajat Emanuel Singh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The central nervous system (CNS) is believed to utilize specific predefined modules, called muscle synergies (MS), to accomplish a motor task. Yet questions persist about how the CNS combines these primitives in different ways to suit the task conditions. The MS hypothesis has been a subject of debate as to whether they originate from neural origins or nonneural constraints. In this review article, we present three aspects related to the MS hypothesis: (1) the experimental and computational evidence in support of the existence of MS, (2) algorithmic approaches for extracting them from surface electromyography (EMG) signals, and (3) the possible role of MS as a neurorehabilitation tool. We note that recent advances in computational neuroscience have utilized the MS hypothesis in motor control and learning. Prospective advances in clinical, medical, and engineering sciences and in fields such as robotics and rehabilitation stand to benefit from a more thorough understanding of MS.