计算机科学
振幅
信号(编程语言)
噪音(视频)
平滑的
均方根
肌电图
人工智能
语音识别
航程(航空)
模式识别(心理学)
计算机视觉
电气工程
工程类
物理
医学
量子力学
精神科
航空航天工程
图像(数学)
程序设计语言
作者
Edward A. Clancy,Evelyn Morin,Gelareh Hajian,Roberto Merletti
标识
DOI:10.1016/j.jelekin.2023.102807
摘要
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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