{"title":"基于初等时域特征的SVM与KNN分类器肌电信号分类的比较分析","authors":"Yogesh Paul, Vibha Goyal, R. Jaswal","doi":"10.1109/ISPCC.2017.8269670","DOIUrl":null,"url":null,"abstract":"The extraction of the feature is a significant method to extract the useful information which is hidden in the signal acquired form the types of different. These signals may be speech, EEG, EMG, ECG, EOG etc. Here, within this paper, we carry on further with EMG signal to discuss the comparative analysis in between linear SVM and KNN classifier using time domain features. For the purpose of successful classification of EMG signal, careful selection of feature is required. Within this paper, seven elementary time domain features are realized as they are frequently used for the same.","PeriodicalId":142166,"journal":{"name":"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"Comparative analysis between SVM & KNN classifier for EMG signal classification on elementary time domain features\",\"authors\":\"Yogesh Paul, Vibha Goyal, R. Jaswal\",\"doi\":\"10.1109/ISPCC.2017.8269670\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The extraction of the feature is a significant method to extract the useful information which is hidden in the signal acquired form the types of different. These signals may be speech, EEG, EMG, ECG, EOG etc. Here, within this paper, we carry on further with EMG signal to discuss the comparative analysis in between linear SVM and KNN classifier using time domain features. For the purpose of successful classification of EMG signal, careful selection of feature is required. Within this paper, seven elementary time domain features are realized as they are frequently used for the same.\",\"PeriodicalId\":142166,\"journal\":{\"name\":\"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPCC.2017.8269670\",\"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 4th International Conference on Signal Processing, Computing and Control (ISPCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPCC.2017.8269670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative analysis between SVM & KNN classifier for EMG signal classification on elementary time domain features
The extraction of the feature is a significant method to extract the useful information which is hidden in the signal acquired form the types of different. These signals may be speech, EEG, EMG, ECG, EOG etc. Here, within this paper, we carry on further with EMG signal to discuss the comparative analysis in between linear SVM and KNN classifier using time domain features. For the purpose of successful classification of EMG signal, careful selection of feature is required. Within this paper, seven elementary time domain features are realized as they are frequently used for the same.