Alpha 2.0
Login Register
» Articles » PMID: 29849756

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

Overview
Journal Appl Bionics Biomech
Publisher Wiley
Date 2018 Jun 1
PMID 29849756
Citations 34
Authors
Rajat Emanuel Singh
Kamran Iqbal
Gannon White
Tarun Edgar Hutchinson
Affiliations
Soon will be listed here.
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.

Citing Articles

Combined transcriptomic and proteomic analyses reveal relevant myelin features in mice with ischemic stroke.

Qian Q, Lyu H, Wang W, Wang Q, Li D, Liu X Funct Integr Genomics. 2025; 25(1):64.

PMID: 40085348 DOI: 10.1007/s10142-025-01573-6.

Dynamic modulations of effective brain connectivity associated with postural instability during multi-joint compound movement on compliant surface.

Lehmann T, Visser A, Havers T, Buchel D, Baumeister J Exp Brain Res. 2025; 243(4):80.

PMID: 40029432 PMC: 11876271. DOI: 10.1007/s00221-025-07039-2.

Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges.

Ghosh S, Yadav R, Soni S, Giri S, Muthukrishnan S, Kumar L Front Hum Neurosci. 2025; 19:1532783.

PMID: 39981127 PMC: 11839673. DOI: 10.3389/fnhum.2025.1532783.

Minimum Electromyography Sensor Set Needed to Identify Age-Related Impairments in the Neuromuscular Control of Walking Using the Dynamic Motor Control Index.

Collimore A, Pohlig R, Awad L Sensors (Basel). 2024; 24(23).

PMID: 39685979 PMC: 11644056. DOI: 10.3390/s24237442.

Comparison of Lower-Limb Muscle Synergies Between Young and Old People During Cycling Based on Electromyography Sensors-A Preliminary Cross-Sectional Study.

Kong L, Yang K, Li H, Wu X, Zhang Q Sensors (Basel). 2024; 24(20).

PMID: 39460234 PMC: 11511221. DOI: 10.3390/s24206755.

References
1.
Kristiansen M, Samani A, Madeleine P, Hansen E . Effects of 5 Weeks of Bench Press Training on Muscle Synergies: A Randomized Controlled Study. J Strength Cond Res. 2015; 30(7):1948-59. DOI: 10.1519/JSC.0000000000001282. View
2.
Banks C, Pai M, McGuirk T, Fregly B, Patten C . Methodological Choices in Muscle Synergy Analysis Impact Differentiation of Physiological Characteristics Following Stroke. Front Comput Neurosci. 2017; 11:78. PMC: 5583217. DOI: 10.3389/fncom.2017.00078. View
3.
Nishida K, Hagio S, Kibushi B, Moritani T, Kouzaki M . Comparison of muscle synergies for running between different foot strike patterns. PLoS One. 2017; 12(2):e0171535. PMC: 5291492. DOI: 10.1371/journal.pone.0171535. View
4.
Tresch M, Cheung V, dAvella A . Matrix factorization algorithms for the identification of muscle synergies: evaluation on simulated and experimental data sets. J Neurophysiol. 2006; 95(4):2199-212. DOI: 10.1152/jn.00222.2005. View
5.
Donoghue J, Sanes J, Hatsopoulos N, Gaal G . Neural discharge and local field potential oscillations in primate motor cortex during voluntary movements. J Neurophysiol. 1998; 79(1):159-73. DOI: 10.1152/jn.1998.79.1.159. View