4.1 Article

Electromyography in the Horse: A Useful Technology?

Journal

JOURNAL OF EQUINE VETERINARY SCIENCE
Volume 60, Issue -, Pages 43-+

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jevs.2017.02.005

Keywords

Electromyography; Equine; Indwelling EMG; Surface EMG; Equine muscle

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Equine performance research to date has focussed on cardiorespiratory and biomechanical assessment of the horse neglecting the role of muscles. This review considers electromyography (EMG) in the horse, with a specific focus on the role of surface EMG (sEMG) as a tool to analyze muscle activity in the sports horse. Three themes have been evaluated in the horse using EMG: muscle recruitment, muscle activity during exercise, and fatigue. Results support kinematic research and add to the knowledge base on how the horse moves. Surface EMG is a relatively noninvasive technology requiring clipping which can be used effectively in the ridden horse. Understanding equine locomotion and how muscles respond during different exercises could inform and evaluate training practices used in the sports horse. However, issues exist for example individual variation, accuracy of sensor placement, and preventing noise within the EMG signal. Therefore, key concepts in research design, data acquisition, and processing are explored to inform future studies and to enable reasoned judgments on the validity and reliability of sEMG as a tool to investigate muscle recruitment and activity and subsequently assess performance in the horse. The high level of intersubject variance observed in between-subjects' designs combined with differences seen between individuals may preclude reliable comparison of muscle performance between groups of horses. Therefore, within-subject designs are advised for future sEMG studies. A standardized approach to data collection and analysis conforming to guidance from the human Surface EMG for Non-Invasive Assessment of Muscle database is recommended including consideration of the inherent challenges that present in EMG research. (C) 2017 Elsevier Inc. All rights reserved.

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