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}
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.