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      Adaptations in equine axial movement and muscle activity occur during induced fore- and hindlimb lameness: A kinematic and electromyographic evaluation during in-hand trot.

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          Abstract

          The inter-relationship between equine thoracolumbar motion and muscle activation during normal locomotion and lameness is poorly understood.

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          Most cited references48

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          Vector field statistical analysis of kinematic and force trajectories.

          Todd Pataky, Mark Robinson, Jos Vanrenterghem (2013)
          When investigating the dynamics of three-dimensional multi-body biomechanical systems it is often difficult to derive spatiotemporally directed predictions regarding experimentally induced effects. A paradigm of 'non-directed' hypothesis testing has emerged in the literature as a result. Non-directed analyses typically consist of ad hoc scalar extraction, an approach which substantially simplifies the original, highly multivariate datasets (many time points, many vector components). This paper describes a commensurately multivariate method as an alternative to scalar extraction. The method, called 'statistical parametric mapping' (SPM), uses random field theory to objectively identify field regions which co-vary significantly with the experimental design. We compared SPM to scalar extraction by re-analyzing three publicly available datasets: 3D knee kinematics, a ten-muscle force system, and 3D ground reaction forces. Scalar extraction was found to bias the analyses of all three datasets by failing to consider sufficient portions of the dataset, and/or by failing to consider covariance amongst vector components. SPM overcame both problems by conducting hypothesis testing at the (massively multivariate) vector trajectory level, with random field corrections simultaneously accounting for temporal correlation and vector covariance. While SPM has been widely demonstrated to be effective for analyzing 3D scalar fields, the current results are the first to demonstrate its effectiveness for 1D vector field analysis. It was concluded that SPM offers a generalized, statistically comprehensive solution to scalar extraction's over-simplification of vector trajectories, thereby making it useful for objectively guiding analyses of complex biomechanical systems.
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            Sampling, noise-reduction and amplitude estimation issues in surface electromyography.

            E.A. Clancy, E.L. Morin, R. Merletti (2002)
            This paper reviews data acquisition and signal processing issues relative to producing an amplitude estimate of surface EMG. The paper covers two principle areas. First, methods for reducing noise, artefact and interference in recorded EMG are described. Wherever possible noise should be reduced at the source via appropriate skin preparation, and the use of well designed active electrodes and signal recording instrumentation. Despite these efforts, some noise will always accompany the desired signal, thus signal processing techniques for noise reduction (e.g. band-pass filtering, adaptive noise cancellation filters and filters based on the wavelet transform) are discussed. Second, methods for estimating the amplitude of the EMG are reviewed. Most advanced, high-fidelity methods consist of six sequential stages: noise rejection/filtering, whitening, multiple-channel combination, amplitude demodulation, smoothing and relinearization. Theoretical and experimental research related to each of the above topics is reviewed and the current recommended practices are described.
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              Speed dependence of averaged EMG profiles in walking.

              A.L. Hof, H Elzinga, W Grimmius … (2002)
              Electromyogram (EMG) profiles strongly depend on walking speed and, in pathological gait, patients do not usually walk at normal speeds. EMG data was collected from 14 muscles in two groups of healthy young subjects who walked at five different speeds ranging from 0.75 to 1.75 ms(-1). We found that average EMG profiles varied in a predictable way with speed. The average EMG profile for each muscle at any speed could be estimated in a simple way from two functions, one constant and one proportionally increasing with walking speed. By taking into account the similarity among profiles within functional groups, the number of basic functions could be reduced further. Any average EMG profile among the 14 leg muscles studied at all speeds in the measured range could be predicted from six constant and ten speed-dependent basic patterns. These results can be interpreted in terms of a central pattern generator for human walking. Copyright 2002 Elsevier Science B.V.
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                Author and article information

                Journal
                Journal ID (iso-abbrev): Equine Vet J
                Title: Equine veterinary journal
                Publisher: Wiley
                ISSN (Electronic): 2042-3306
                ISSN (Print): 0425-1644
                Publication date (Electronic): Dec 14 2022
                Affiliations
                [1 ] Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
                [2 ] Research Centre for Applied Sport, Physical Activity and Performance, University of Central Lancashire, Preston, UK.
                [3 ] Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, Michigan, USA.
                [4 ] Delsys/Altec Inc., Natick, Massachusetts, USA.
                [5 ] Allied Health Research Unit, University of Central Lancashire, Preston, UK.
                Article
                DOI: 10.1111/evj.13906
                PubMed ID: 36516302
                SO-VID: 7ebff050-af20-4a4c-91ff-8ec3d619f33a
                History

                Keywords: horse,longissimus dorsi,sEMG,thoracolumbar,trot,gait analysis
                Data availability:
                Keywords: horse, longissimus dorsi, sEMG, thoracolumbar, trot, gait analysis

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