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      A wavelet based time frequency analysis of electromyograms to group steps of runners into clusters that contain similar muscle activation patterns

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          Abstract

          Purpose

          To wavelet transform the electromyograms of the vastii muscles and generate wavelet intensity patterns (WIP) of runners. Test the hypotheses: 1) The WIP of the vastus medialis (VM) and vastus lateralis (VL) of one step are more similar than the WIPs of these two muscles, offset by one step. 2) The WIPs within one muscle differ by having maximal intensities in specific frequency bands and these intensities are not always occurring at the same time after heel strike. 3) The WIPs that were recorded form one muscle for all steps while running can be grouped into clusters with similar WIPs. It is expected that clusters might have distinctly different, cluster specific mean WIPs.

          Methods

          The EMG of the vastii muscles from at least 1000 steps from twelve runners were recorded using a bipolar current amplifier and yielded WIPs. Based on the weights obtained after a principal component analysis the dissimilarities (1-correlation) between the WIPs were computed. The dissimilarities were submitted to a hierarchical cluster analysis to search for groups of steps with similar WIPs. The clusters formed by random surrogate WIPs were used to determine whether the groups were likely to be created in a non-random manner.

          Results

          The steps were grouped in clusters showing similar WIPs. The grouping was based on the frequency bands and their timing showing that they represented defining parts of the WIPs. The correlations between the WIPs of the vastii muscles that were recorded during the same step were higher than the correlations of WPIs that were recorded during consecutive steps, indicating the non-randomness of the WIPs.

          Conclusions

          The spectral power of EMGs while running varies during the stance phase in time and frequency, therefore a time averaged power spectrum cannot reflect the timing of events that occur while running. It seems likely that there might be a set of predefined patterns that are used upon demand to stabilize the movement.

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          Most cited references28

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          The extraction of neural strategies from the surface EMG.

          This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, the review critically evaluates only some of the applications. The focus is on the relations between global features of the surface EMG and the underlying physiological processes. Because direct measurements of motor unit activation are not available and many factors can influence the signal, these relations are frequently misinterpreted. These errors are compounded by the counterintuitive effects that some system parameters can have on the EMG signal. The phenomenon of crosstalk is used as an example of these problems. The review describes the limitations of techniques used to infer the level of muscle activation, the type of motor unit recruited, the upper limit of motor unit recruitment, the average discharge rate, and the degree of synchronization between motor units. Although the global surface EMG is a useful measure of muscle activation and assessment, there are limits to the information that can be extracted from this signal.
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            Training adaptations in the behavior of human motor units.

            The purpose of this brief review is to examine the neural adaptations associated with training, by focusing on the behavior of single motor units. The review synthesizes current understanding on motor unit recruitment and rate coding during voluntary contractions, briefly describes the techniques used to record motor unit activity, and then evaluates the adaptations that have been observed in motor unit activity during maximal and submaximal contractions. Relatively few studies have directly compared motor unit behavior before and after training. Although some studies suggest that the voluntary activation of muscle can increase slightly with strength training, it is not known how the discharge of motor units changes to produce this increase in activation. The evidence indicates that the increase is not attributable to changes in motor unit synchronization. It has been demonstrated, however, that training can increase both the rate of torque development and the discharge rate of motor units. Furthermore, both strength training and practice of a force-matching task can evoke adaptations in the discharge characteristics of motor units. Because the variability in discharge rate has a significant influence on the fluctuations in force during submaximal contractions, the changes produced with training can influence motor performance during activities of daily living. Little is known, however, about the relative contributions of the descending drive, afferent feedback, spinal circuitry, and motor neuron properties to the observed adaptations in motor unit activity.
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              Common synaptic input to motor neurons, motor unit synchronization, and force control.

              In considering the role of common synaptic input to motor neurons in force control, we hypothesize that the effective neural drive to muscle replicates the common input and is, thus, the main determinant of force production. Such a perspective argues against a significant role for motor unit synchronization in force control.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: Writing – original draft
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Project administrationRole: Writing – review & editing
                Role: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                18 April 2018
                2018
                : 13
                : 4
                : e0195125
                Affiliations
                [001]Faculty of Kinesiology, Human Performance Laboratory, University of Calgary, Calgary, Alberta, Canada
                University of Illinois at Urbana-Champaign, UNITED STATES
                Author notes

                Competing Interests: BMN is the chief scientific officer of the sponsoring company Biomechanigg Sport & Health Research Inc (BSHR). BSHR is sponsoring the research and is simply interested in the outcome of the study. The company BSHR does not benefit from the results of the study, regardless of the outcome and had no involvement in the study design, data collection, data analysis or interpretation, the writing of the manuscript or the decision to submit the manuscript for publication. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0002-5779-6244
                Article
                PONE-D-17-39200
                10.1371/journal.pone.0195125
                5906018
                29668731
                083d7798-4eb9-499e-8a63-849d75d166b8
                © 2018 von Tscharner et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 November 2017
                : 16 March 2018
                Page count
                Figures: 7, Tables: 1, Pages: 19
                Funding
                This project was supported by Biomechanigg Sport & Health Research Inc. Calgary. The funder provided support in the form of salaries for authors [MM, BMN], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. MU was a visiting student from Friedrich Alexander University Erlangen-Nuremberg, Germany, supervised by VVT and was supported by the German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes).
                Categories
                Research Article
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Electrophysiological Techniques
                Muscle Electrophysiology
                Electromyography
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Membrane Potential
                Action Potentials
                Medicine and Health Sciences
                Physiology
                Electrophysiology
                Membrane Potential
                Action Potentials
                Biology and Life Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Action Potentials
                Medicine and Health Sciences
                Physiology
                Electrophysiology
                Neurophysiology
                Action Potentials
                Biology and Life Sciences
                Neuroscience
                Neurophysiology
                Action Potentials
                Engineering and Technology
                Signal Processing
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Mathematical Functions
                Wavelet Transforms
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Fatigue
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Fatigue
                Engineering and Technology
                Signal Processing
                Signal Amplification
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Muscle Analysis
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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