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肌电图实验设计共识(CEDE)项目:肌电图在肌肉力量估计中的应用。

Consensus for experimental design in electromyography (CEDE) project: Application of EMG to estimate muscle force.

机构信息

School of Biomedical Sciences, The University of Queensland, Brisbane, Australia.

School of Biomedical Sciences, The University of Queensland, Brisbane, Australia; Université Côte d'Azur, LAMHESS, Nice, France.

出版信息

J Electromyogr Kinesiol. 2024 Dec;79:102910. doi: 10.1016/j.jelekin.2024.102910. Epub 2024 Jun 14.

Abstract

Skeletal muscles power movement. Deriving the forces produced by individual muscles has applications across various fields including biomechanics, robotics, and rehabilitation. Since direct in vivo measurement of muscle force in humans is invasive and challenging, its estimation through non-invasive methods such as electromyography (EMG) holds considerable appeal. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, summarizes recommendations on the use of EMG to estimate muscle force. The matrix encompasses the use of bipolar surface EMG, high density surface EMG, and intra-muscular EMG (1) to identify the onset of muscle force during isometric contractions, (2) to identify the offset of muscle force during isometric contractions, (3) to identify force fluctuations during isometric contractions, (4) to estimate force during dynamic contractions, and (5) in combination with musculoskeletal models to estimate force during dynamic contractions. For each application, recommendations on the appropriateness of using EMG to estimate force and justification for each recommendation are provided. The achieved consensus makes clear that there are limited scenarios in which EMG can be used to accurately estimate muscle forces. In most cases, it remains important to consider the activation as well as the muscle state and other biomechanical and physiological factors- such as in the context of a formal mechanical model. This matrix is intended to encourage interdisciplinary discussions regarding the integration of EMG with other experimental techniques and to promote advances in the application of EMG towards developing muscle models and musculoskeletal simulations that can accurately predict muscle forces in healthy and clinical populations.

摘要

骨骼肌为运动提供动力。从单个肌肉产生的力中推导出的应用在包括生物力学、机器人技术和康复等各个领域都具有吸引力。由于在人体中直接进行肌肉力量的体内测量具有侵入性和挑战性,因此通过肌电图(EMG)等非侵入性方法进行估计具有很大的吸引力。该矩阵是由肌电图实验设计共识(CEDE)项目制定的,总结了使用肌电图估计肌肉力量的建议。该矩阵包括使用双极表面肌电图、高密度表面肌电图和肌内肌电图(1)来确定等长收缩期间肌肉力量的起始,(2)确定等长收缩期间肌肉力量的结束,(3)确定等长收缩期间的力量波动,(4)估计动态收缩期间的力量,以及(5)与骨骼肌肉模型结合估计动态收缩期间的力量。对于每种应用,都提供了关于使用 EMG 来估计力的适当性的建议以及对每项建议的理由。所达成的共识清楚地表明,在有限的情况下,EMG 可以用于准确估计肌肉力量。在大多数情况下,考虑肌肉的激活以及状态和其他生物力学和生理因素仍然很重要-例如在正式的机械模型的背景下。该矩阵旨在鼓励就 EMG 与其他实验技术的整合进行跨学科讨论,并促进肌电图在开发能够准确预测健康和临床人群中肌肉力量的肌肉模型和骨骼肌肉模拟中的应用的进展。

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