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      A Longitudinal Electromyography Study of Complex Movements in Poststroke Therapy. 2: Changes in Coordinated Muscle Activation

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          Abstract

          Fine motor control is achieved through the coordinated activation of groups of muscles, or “muscle synergies.” Muscle synergies change after stroke as a consequence of the motor deficit. We investigated the pattern and longitudinal changes in upper limb muscle synergies during therapy in a largely unconstrained movement in patients with a broad spectrum of poststroke residual voluntary motor capacity. Electromyography (EMG) was recorded using wireless telemetry from 6 muscles acting on the more-affected upper body in 24 stroke patients at early and late therapy during formal Wii-based Movement Therapy (WMT) sessions, and in a subset of 13 patients at 6-month follow-up. Patients were classified with low, moderate, or high motor-function. The Wii-baseball swing was analyzed using a non-negative matrix factorization (NMF) algorithm to extract muscle synergies from EMG recordings based on the temporal activation of each synergy and the contribution of each muscle to a synergy. Motor-function was clinically assessed immediately pre- and post-therapy and at 6-month follow-up using the Wolf Motor Function Test, upper limb motor Fugl-Meyer Assessment, and Motor Activity Log Quality of Movement scale. Clinical assessments and game performance demonstrated improved motor-function for all patients at post-therapy ( p < 0.01), and these improvements were sustained at 6-month follow-up ( p > 0.05). NMF analysis revealed fewer muscle synergies (mean ± SE) for patients with low motor-function (3.38 ± 0.2) than those with high motor-function (4.00 ± 0.3) at early therapy ( p = 0.036) with an association trend between the number of synergies and the level of motor-function. By late therapy, there was no significant change between groups, although there was a pattern of increase for those with low motor-function over time. The variability accounted for demonstrated differences with motor-function level ( p < 0.05) but not time. Cluster analysis of the pooled synergies highlighted the therapy-induced change in muscle activation. Muscle synergies could be identified for all patients during therapy activities. These results show less complexity and more co-activation in the muscle activation for patients with low motor-function as a higher number of muscle synergies reflects greater movement complexity and task-related phasic muscle activation. The increased number of synergies and changes within synergies by late-therapy suggests improved motor control and movement quality with more distinct phases of movement.

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          Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke.

          Evidence suggests that the nervous system controls motor tasks using a low-dimensional modular organization of muscle activation. However, it is not clear if such an organization applies to coordination of human walking, nor how nervous system injury may alter the organization of motor modules and their biomechanical outputs. We first tested the hypothesis that muscle activation patterns during walking are produced through the variable activation of a small set of motor modules. In 20 healthy control subjects, EMG signals from eight leg muscles were measured across a range of walking speeds. Four motor modules identified through nonnegative matrix factorization were sufficient to account for variability of muscle activation from step to step and across speeds. Next, consistent with the clinical notion of abnormal limb flexion-extension synergies post-stroke, we tested the hypothesis that subjects with post-stroke hemiparesis would have altered motor modules, leading to impaired walking performance. In post-stroke subjects (n = 55), a less complex coordination pattern was shown. Fewer modules were needed to account for muscle activation during walking at preferred speed compared with controls. Fewer modules resulted from merging of the modules observed in healthy controls, suggesting reduced independence of neural control signals. The number of modules was correlated to preferred walking speed, speed modulation, step length asymmetry, and propulsive asymmetry. Our results suggest a common modular organization of muscle coordination underlying walking in both healthy and post-stroke subjects. Identification of motor modules may lead to new insight into impaired locomotor coordination and the underlying neural systems.
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            Algorithms and applications for approximate nonnegative matrix factorization

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              Filtering the surface EMG signal: Movement artifact and baseline noise contamination.

              The surface electromyographic (sEMG) signal that originates in the muscle is inevitably contaminated by various noise signals or artifacts that originate at the skin-electrode interface, in the electronics that amplifies the signals, and in external sources. Modern technology is substantially immune to some of these noises, but not to the baseline noise and the movement artifact noise. These noise sources have frequency spectra that contaminate the low-frequency part of the sEMG frequency spectrum. There are many factors which must be taken into consideration when determining the appropriate filter specifications to remove these artifacts; they include the muscle tested and type of contraction, the sensor configuration, and specific noise source. The band-pass determination is always a compromise between (a) reducing noise and artifact contamination, and (b) preserving the desired information from the sEMG signal. This study was designed to investigate the effects of mechanical perturbations and noise that are typically encountered during sEMG recordings in clinical and related applications. The analysis established the relationship between the attenuation rates of the movement artifact and the sEMG signal as a function of the filter band pass. When this relationship is combined with other considerations related to the informational content of the signal, the signal distortion of filters, and the kinds of artifacts evaluated in this study, a Butterworth filter with a corner frequency of 20 Hz and a slope of 12 dB/oct is recommended for general use. The results of this study are relevant to biomechanical and clinical applications where the measurements of body dynamics and kinematics may include artifact sources. Copyright 2010 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                URI : http://frontiersin.org/people/u/424546
                URI : http://frontiersin.org/people/u/446898
                URI : http://frontiersin.org/people/u/451910
                URI : http://frontiersin.org/people/u/329961
                URI : http://frontiersin.org/people/u/114809
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                20 July 2017
                2017
                : 8
                : 277
                Affiliations
                [1] 1Neuroscience Research Australia , Sydney, NSW, Australia
                [2] 2School of Medical Science, University of New South Wales , Sydney, NSW, Australia
                Author notes

                Edited by: Cliff Klein, Guangdong Provincial Work Injury Rehabilitation Center, China

                Reviewed by: Winston D. Byblow, University of Auckland, New Zealand; Sahil Bajaj, University of Arizona, United States

                *Correspondence: Penelope A. McNulty, p.mcnulty@ 123456neura.edu.au

                Specialty section: This article was submitted to Stroke, a section of the journal Frontiers in Neurology

                Article
                10.3389/fneur.2017.00277
                5517410
                28775705
                bf71ad82-8af2-425a-9c99-e0b570b4322c
                Copyright © 2017 Hesam-Shariati, Trinh, Thompson-Butel, Shiner and McNulty.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 20 March 2017
                : 29 May 2017
                Page count
                Figures: 6, Tables: 0, Equations: 3, References: 71, Pages: 12, Words: 8041
                Categories
                Neuroscience
                Original Research

                Neurology
                muscle synergy,non-negative matrix factorization,upper limb,rehabilitation,chronic stroke

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