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      Long term consistency and location specificity of equine gluteus medius muscle activity during locomotion on the treadmill

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          Abstract

          Background

          The equine m. gluteus medius (GM) is the largest muscle of the horse, its main movement function is the extension of the hip joint. The objective of the present study was to measure equine GM activity in three adjacent locations on GM during walk and trot on a treadmill, in order to document potential differences. Fourteen Haflinger mares were measured using surface electromyography and kinematic markers to identify the motion cycles on three occasions over 16 weeks. The electrodes were placed on left and right gluteus medius muscle over the middle of its widest part and 5 cm lateral and medial of it. For data processing, electrical activity was normalised to its maximum value and timing was normalised to the motion cycle. A Gaussian distribution approach was used to determine up to 10 modes of focussed activity, and results were analysed separately for stance and swing phase of the ipsilateral hindlimb.

          Results

          Fair reliability was found for mean mode values (Cronbach’s alpha = 0.66) and good reliability was found for mean mode locations (Cronbach’s alpha = 0.71) over the three data collection days. The magnitude of muscle activity identified as mean mode value was much larger at trot than at walk, and mean mode value was significantly different between stance phases of walk and trot for all electrode positions ( p < 0.01). The pattern of muscle activity identified as mean mode location was significantly different for walk and trot at all electrode positions, both during stance and swing phases ( p < 0.001). This indicates the different timing pattern between the gaits. Results of the three electrode positions on the same muscle during each gait were not significantly different when comparing the same measurement.

          Conclusions

          The middle of the equine GM does not show any indication of functional differentiation during walk and trot on a treadmill; this might be due to lack of segmentation as such, or due to lack of need for segmented use for these very basic main tasks of the muscle. The reliability of the sEMG measurements over several weeks was fair to good, an indication for the robustness of the methodology.

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          Most cited references40

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          How muscle fiber lengths and velocities affect muscle force generation as humans walk and run at different speeds.

          The lengths and velocities of muscle fibers have a dramatic effect on muscle force generation. It is unknown, however, whether the lengths and velocities of lower limb muscle fibers substantially affect the ability of muscles to generate force during walking and running. We examined this issue by developing simulations of muscle-tendon dynamics to calculate the lengths and velocities of muscle fibers from electromyographic recordings of 11 lower limb muscles and kinematic measurements of the hip, knee and ankle made as five subjects walked at speeds of 1.0-1.75 m s(-1) and ran at speeds of 2.0-5.0 m s(-1). We analyzed the simulated fiber lengths, fiber velocities and forces to evaluate the influence of force-length and force-velocity properties on force generation at different walking and running speeds. The simulations revealed that force generation ability (i.e. the force generated per unit of activation) of eight of the 11 muscles was significantly affected by walking or running speed. Soleus force generation ability decreased with increasing walking speed, but the transition from walking to running increased the force generation ability by reducing fiber velocities. Our results demonstrate the influence of soleus muscle architecture on the walk-to-run transition and the effects of muscle-tendon compliance on the plantarflexors' ability to generate ankle moment and power. The study presents data that permit lower limb muscles to be studied in unprecedented detail by relating muscle fiber dynamics and force generation to the mechanical demands of walking and running.
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            Stance and swing phase costs in human walking.

            Leg swing in human walking has historically been viewed as a passive motion with little metabolic cost. Recent estimates of leg swing costs are equivocal, covering a range from 10 to 33 per cent of the net cost of walking. There has also been a debate as to whether the periods of double-limb support during the stance phase dominate the cost of walking. Part of this uncertainty is because of our inability to measure metabolic energy consumption in individual muscles during locomotion. Therefore, the purpose of this study was to investigate the metabolic cost of walking using a modelling approach that allowed instantaneous energy consumption rates in individual muscles to be estimated over the full gait cycle. At a typical walking speed and stride rate, leg swing represented 29 per cent of the total muscular cost. During the stance phase, the double-limb and single-limb support periods accounted for 27 and 44 per cent of the total cost, respectively. Performing step-to-step transitions, which encompasses more than just the double-support periods, represented 37 per cent of the total cost of walking. Increasing stride rate at a constant speed led to greater double-limb support costs, lower swing phase costs and no change in single-limb support costs. Together, these results provide unique insight as to how metabolic energy is expended over the human gait cycle.
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              Reliability of EMG measurements for trunk muscles during maximal and sub-maximal voluntary isometric contractions in healthy controls and CLBP patients.

              The purpose of this study was to compare the reliability of trunk muscle activity measured by means of surface electromyography (EMG) during maximal and sub-maximal voluntary isometric contractions (MVC/sub-MVC) over repeated trials within-day and between-days in healthy controls and patients with chronic low back pain (CLBP). Eleven volunteers (six controls and five CLBP patients) were assessed twice with a 1-week interval. Surface EMG signals were recorded bilaterally from six trunk muscles. Intra-class correlation coefficients (ICC) and standard error of measurement as a percentage of the grand mean (%SEM) were calculated. MVC and sub-MVC showed excellent within-day reliability in both healthy controls and CLBP patients (ICC mean 0.91; range 0.75-0.98; %SEM mean 4%; range 1-12%). Sub-MVC for both groups between-days showed excellent reliability (ICC mean 0.88; range 0.78-0.97; %SEM mean 7%; range 3-11%). The between-days MVC for both groups showed trends towards lower levels of reliability (ICC mean 0.70; range 0.19-0.99; %SEM mean 17%; range 4-36%) when compared to sub-MVC. Findings of the study provide evidence that sub-MVC are preferable for amplitude normalisation when assessing EMG signals of trunk muscles between-days.
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                Author and article information

                Contributors
                rebeka.zsoldos@boku.ac.at
                anna.voegele@uni-bonn.de
                kruegerb.cs@gmail.com
                weber@uni-bonn.de
                theresia.licka@vetmeduni.ac.at
                Journal
                BMC Vet Res
                BMC Vet. Res
                BMC Veterinary Research
                BioMed Central (London )
                1746-6148
                6 April 2018
                6 April 2018
                2018
                : 14
                : 126
                Affiliations
                [1 ]ISNI 0000 0001 2298 5320, GRID grid.5173.0, Department of Sustainable Agricultural Systems, Section Livestock Sciences, , University of Natural Resources and Life Sciences Vienna, ; Vienna, Austria
                [2 ]ISNI 0000 0001 2240 3300, GRID grid.10388.32, Multimedia, Simulation and Virtual Reality Group, Institute of Computer Science II, , University of Bonn, ; Bonn, Germany
                [3 ]Gokhale Method Institute, Stanford, CA USA
                [4 ]ISNI 0000 0000 9686 6466, GRID grid.6583.8, Department for Companion Animals and Horses, , University of Veterinary Medicine Vienna, ; Vienna, Austria
                [5 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Royal (Dick) School of Veterinary Studies, , The University of Edinburgh, ; Edinburgh, Scotland UK
                Article
                1443
                10.1186/s12917-018-1443-y
                5889605
                29625573
                8c690869-0e17-4a0b-8311-a2a2043c02fe
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 2 May 2016
                : 26 March 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002428, Austrian Science Fund;
                Award ID: I1532-B23
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: KR 4309/2-1
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Veterinary medicine
                surface electromyography,horse,gluteus medius,walk,trot,locomotion,scar,gaussian distribution

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