{"title":"基于连续小波的肌电信号分析技术","authors":"Abdelali Belkhou, A. Jbari, Larbi Belarbi","doi":"10.1109/EITECH.2017.8255232","DOIUrl":null,"url":null,"abstract":"Electromyography is a technique for the study of muscular activity in which placed sensors provide electrical signals. These signals require electronic and computer processing to improve the quality of information requested for the diagnosis of neuromuscular disorders. The aim of this study is to present a continuous wavelet based technique for the analysis of the electromyography signals with first giving an overview of the functioning of the neuromuscular system. A comparison between healthy, neuropathy and myopathy signals using the continuous wavelets transform using the MATLAB software was done. This technique is efficient to compare and interpret these different categories of EMG signals.","PeriodicalId":447139,"journal":{"name":"2017 International Conference on Electrical and Information Technologies (ICEIT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A continuous wavelet based technique for the analysis of electromyography signals\",\"authors\":\"Abdelali Belkhou, A. Jbari, Larbi Belarbi\",\"doi\":\"10.1109/EITECH.2017.8255232\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electromyography is a technique for the study of muscular activity in which placed sensors provide electrical signals. These signals require electronic and computer processing to improve the quality of information requested for the diagnosis of neuromuscular disorders. The aim of this study is to present a continuous wavelet based technique for the analysis of the electromyography signals with first giving an overview of the functioning of the neuromuscular system. A comparison between healthy, neuropathy and myopathy signals using the continuous wavelets transform using the MATLAB software was done. This technique is efficient to compare and interpret these different categories of EMG signals.\",\"PeriodicalId\":447139,\"journal\":{\"name\":\"2017 International Conference on Electrical and Information Technologies (ICEIT)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Electrical and Information Technologies (ICEIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EITECH.2017.8255232\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Electrical and Information Technologies (ICEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EITECH.2017.8255232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A continuous wavelet based technique for the analysis of electromyography signals
Electromyography is a technique for the study of muscular activity in which placed sensors provide electrical signals. These signals require electronic and computer processing to improve the quality of information requested for the diagnosis of neuromuscular disorders. The aim of this study is to present a continuous wavelet based technique for the analysis of the electromyography signals with first giving an overview of the functioning of the neuromuscular system. A comparison between healthy, neuropathy and myopathy signals using the continuous wavelets transform using the MATLAB software was done. This technique is efficient to compare and interpret these different categories of EMG signals.