辅导的表面肌电(sEMG)振幅估计:最佳实践

IF 2 4区 医学 Q3 NEUROSCIENCES
Edward A. Clancy , Evelyn L. Morin , Gelareh Hajian , Roberto Merletti
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引用次数: 1

摘要

本教程旨在为新手(包括临床医生、工程师和非工程师)提供从自主收缩的双极表面肌电信号中提取肌电图振幅的见解、说明和“最佳实践”。还简要讨论了从高密度sEMG(HDsEMG)阵列中提取sEMG振幅和从电引发的收缩中提取特征。本教程试图以一种简单明了的方式介绍其主要概念,该领域的新手不具备该领域的广泛技术背景(如果有的话)。表面肌电振幅,也被称为表面肌电包络[通常被实现为均方根(RMS)表面肌电或平均整流值(ARV)表面肌电],量化表面肌电信号的电压变化,并与肌肉的整体神经兴奋和外周参数密切相关。本教程简要回顾了自主表面肌电信号和表面肌电记录的生理起源,包括电极配置、表面肌电信号转导、电子调节和模数转换器的转换。本系列以前的教程中已详细介绍了这些主题。然后,对计算sEMG振幅的最先进方法进行了深入描述,包括信号预处理、绝对值与平方律检测、适当的sEMG幅度平滑滤波器的选择和测量噪声的衰减方面的指导。本教程提供了sEMG振幅估计最佳实践的详细列表。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tutorial. Surface electromyogram (sEMG) amplitude estimation: Best practices

This tutorial intends to provide insight, instructions and “best practices” for those who are novices—including clinicians, engineers and non-engineers—in extracting electromyogram (EMG) amplitude from the bipolar surface EMG (sEMG) signal of voluntary contractions. A brief discussion of sEMG amplitude extraction from high density sEMG (HDsEMG) arrays and feature extraction from electrically elicited contractions is also provided.

This tutorial attempts to present its main concepts in a straightforward manner that is accessible to novices in the field not possessing a wide range of technical background (if any) in this area. Surface EMG amplitude, also referred to as the sEMG envelope [often implemented as root mean square (RMS) sEMG or average rectified value (ARV) sEMG], quantifies the voltage variation of the sEMG signal and is grossly related to the overall neural excitation of the muscle and to peripheral parameters.

The tutorial briefly reviews the physiological origin of the voluntary sEMG signal and sEMG recording, including electrode configurations, sEMG signal transduction, electronic conditioning and conversion by an analog-to-digital converter. These topics have been covered in greater detail in prior tutorials in this series. In depth descriptions of state-of-the-art methods for computing sEMG amplitude are then provided, including guidance on signal pre-conditioning, absolute value vs. square-law detection, selection of appropriate sEMG amplitude smoothing filters and attenuation of measurement noise. The tutorial provides a detailed list of best practices for sEMG amplitude estimation.

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来源期刊
CiteScore
4.70
自引率
8.00%
发文量
70
审稿时长
74 days
期刊介绍: Journal of Electromyography & Kinesiology is the primary source for outstanding original articles on the study of human movement from muscle contraction via its motor units and sensory system to integrated motion through mechanical and electrical detection techniques. As the official publication of the International Society of Electrophysiology and Kinesiology, the journal is dedicated to publishing the best work in all areas of electromyography and kinesiology, including: control of movement, muscle fatigue, muscle and nerve properties, joint biomechanics and electrical stimulation. Applications in rehabilitation, sports & exercise, motion analysis, ergonomics, alternative & complimentary medicine, measures of human performance and technical articles on electromyographic signal processing are welcome.
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