体力举重疲劳肌的肌电信号分析综述

T. Zawawi, A. Abdullah, R. Sudirman, N. Saad, N. Mahmood
{"title":"体力举重疲劳肌的肌电信号分析综述","authors":"T. Zawawi, A. Abdullah, R. Sudirman, N. Saad, N. Mahmood","doi":"10.1109/ICCED51276.2020.9415806","DOIUrl":null,"url":null,"abstract":"Electromyography (EMG) signal is decidedly complex time and frequency characteristics. The common technique of Fast-Fourier transform is applied in signal processing involving EMG signal. However, to provide time-frequency information for EMG signals, it has a limitation. This paper presents the systematic review of the concept of EMG signal and how the EMG signal can be analysed which focuses on signal processing using time-frequency distribution. Spectrogram is suggested to used compared to short-time Fourier transform (STFT) and wavelet because it is lower process complexity, high resolution and higher accuracy of EMG signal's interpretation. Besides that, from the spectrogram, some of the signal characteristics are identified able to provide clearer information of the analysed signal. Thus, this paper will help the researcher in order to get an overview of the concept of EMG signal. A further researcher can expand the information to get more advanced in this field based on this concept.","PeriodicalId":344981,"journal":{"name":"2020 6th International Conference on Computing Engineering and Design (ICCED)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review of Electromyography Signal Analysis of Fatigue Muscle for Manual Lifting\",\"authors\":\"T. Zawawi, A. Abdullah, R. Sudirman, N. Saad, N. Mahmood\",\"doi\":\"10.1109/ICCED51276.2020.9415806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electromyography (EMG) signal is decidedly complex time and frequency characteristics. The common technique of Fast-Fourier transform is applied in signal processing involving EMG signal. However, to provide time-frequency information for EMG signals, it has a limitation. This paper presents the systematic review of the concept of EMG signal and how the EMG signal can be analysed which focuses on signal processing using time-frequency distribution. Spectrogram is suggested to used compared to short-time Fourier transform (STFT) and wavelet because it is lower process complexity, high resolution and higher accuracy of EMG signal's interpretation. Besides that, from the spectrogram, some of the signal characteristics are identified able to provide clearer information of the analysed signal. Thus, this paper will help the researcher in order to get an overview of the concept of EMG signal. A further researcher can expand the information to get more advanced in this field based on this concept.\",\"PeriodicalId\":344981,\"journal\":{\"name\":\"2020 6th International Conference on Computing Engineering and Design (ICCED)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 6th International Conference on Computing Engineering and Design (ICCED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCED51276.2020.9415806\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 6th International Conference on Computing Engineering and Design (ICCED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCED51276.2020.9415806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

肌电信号具有复杂的时间和频率特征。将常用的快速傅立叶变换技术应用于肌电信号的信号处理。然而,在为肌电信号提供时频信息方面,存在一定的局限性。本文系统地介绍了肌电信号的概念和分析肌电信号的方法,重点介绍了利用时频分布对肌电信号进行处理的方法。与短时傅里叶变换(STFT)和小波变换相比,频谱图具有处理复杂度低、分辨率高、解释肌电信号精度高的优点。此外,从频谱图中可以识别出信号的一些特征,可以更清晰地提供被分析信号的信息。因此,本文将有助于研究者对肌电信号的概念有一个概述。进一步的研究人员可以在这个概念的基础上扩展信息,在这个领域取得更大的进步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Review of Electromyography Signal Analysis of Fatigue Muscle for Manual Lifting
Electromyography (EMG) signal is decidedly complex time and frequency characteristics. The common technique of Fast-Fourier transform is applied in signal processing involving EMG signal. However, to provide time-frequency information for EMG signals, it has a limitation. This paper presents the systematic review of the concept of EMG signal and how the EMG signal can be analysed which focuses on signal processing using time-frequency distribution. Spectrogram is suggested to used compared to short-time Fourier transform (STFT) and wavelet because it is lower process complexity, high resolution and higher accuracy of EMG signal's interpretation. Besides that, from the spectrogram, some of the signal characteristics are identified able to provide clearer information of the analysed signal. Thus, this paper will help the researcher in order to get an overview of the concept of EMG signal. A further researcher can expand the information to get more advanced in this field based on this concept.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Comparison Data Mining based on Optimization Algorithms in Receiving Electricity Subsidies Embracing Agile Development Principles in an Organization using The Legacy System: The Case of Bank XYZ in Indonesia Modelling and Optimization Containers Dwell-Time in Tanjung Perak Port Indonesia Consumer Acceptance in Grocery Shopping Mobile Applications Multi-Faces Recognition in Crowd Using Support Vector Machine on Histogram of Gradient
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1