Tutorial. Frequency analysis of the surface EMG signal: Best practices

IF 2 4区 医学 Q3 NEUROSCIENCES
Silvia Muceli , Roberto Merletti
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引用次数: 0

Abstract

This tutorial is aimed primarily to non-engineers (clinical researchers, clinicians, neurophysiology technicians, ergonomists, movement and sport scientists, physical therapists) or beginners using, or planning to use, surface electromyography (sEMG) as a monitoring and assessment tool for muscle and neuromuscular evaluations in the prevention and rehabilitation fields.
Its first purpose is to explain, with minimal mathematics, basic concepts related to: (a) time and frequency domain description of a signal, (b) Fourier transform, (c) amplitude, phase, and power spectrum of a signal, (d) sampling of a signal, (e) filtering of sEMG signals, (f) cross-spectrum and coherence between two signals, (g) signal stationarity and criteria for epoch selection, (h) myoelectric manifestations of muscle fatigue and (i) fatigue indices. These concepts are consolidated knowledge and are addressed and discussed with examples taken from the literature.
教程。表面肌电信号的频率分析:最佳实践。
本教程主要面向在预防和康复领域使用或计划使用表面肌电图 (sEMG) 作为肌肉和神经肌肉评估的监测和评估工具的非工程人员(临床研究人员、临床医生、神经生理学技术人员、人体工程学专家、运动和体育科学家、物理治疗师)或初学者。其首要目的是用最少的数学知识解释与以下方面有关的基本概念:(a) 信号的时域和频域描述,(b) 傅立叶变换,(c) 信号的振幅、相位和功率谱,(d) 信号的采样,(e) sEMG 信号的滤波,(f) 两个信号之间的交叉谱和相干性,(g) 信号的静止性和时间选择标准,(h) 肌肉疲劳的肌电表现和 (i) 疲劳指数。这些概念都是综合知识,并通过文献中的实例加以阐述和讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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