{"title":"一种基于层次分类器的心电生物特征识别新方法","authors":"Yue Zhang, Youqun Shi","doi":"10.1109/ICSESS.2015.7339096","DOIUrl":null,"url":null,"abstract":"In this paper, a new method for ECG biometric recognition using a hierarchical scheme classifier is presented. The integral process of the method is introduced, including preprocessing, feature extraction and classification. To achieve a better performance of proposed method, cross-validation is applied to determine the parameters in the classifier. As a result, proposed method offers considerably high recognition rates when tested on MIT-BIH NSRDB. The total heartbeat recognition rate is 97.98%, and window recognition rate and subject recognition rate are both 100%.","PeriodicalId":335871,"journal":{"name":"2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A new method for ECG biometric recognition using a hierarchical scheme classifier\",\"authors\":\"Yue Zhang, Youqun Shi\",\"doi\":\"10.1109/ICSESS.2015.7339096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new method for ECG biometric recognition using a hierarchical scheme classifier is presented. The integral process of the method is introduced, including preprocessing, feature extraction and classification. To achieve a better performance of proposed method, cross-validation is applied to determine the parameters in the classifier. As a result, proposed method offers considerably high recognition rates when tested on MIT-BIH NSRDB. The total heartbeat recognition rate is 97.98%, and window recognition rate and subject recognition rate are both 100%.\",\"PeriodicalId\":335871,\"journal\":{\"name\":\"2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSESS.2015.7339096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 6th IEEE International Conference on Software Engineering and Service Science (ICSESS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2015.7339096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new method for ECG biometric recognition using a hierarchical scheme classifier
In this paper, a new method for ECG biometric recognition using a hierarchical scheme classifier is presented. The integral process of the method is introduced, including preprocessing, feature extraction and classification. To achieve a better performance of proposed method, cross-validation is applied to determine the parameters in the classifier. As a result, proposed method offers considerably high recognition rates when tested on MIT-BIH NSRDB. The total heartbeat recognition rate is 97.98%, and window recognition rate and subject recognition rate are both 100%.
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