{"title":"一种基于HOSVD的多路心电压缩方法","authors":"Yuliyan Velchev","doi":"10.1109/TELECOM50385.2020.9299549","DOIUrl":null,"url":null,"abstract":"A novel approach for multichannel electrocardiogram compression is presented in this paper. It is based on tensor decomposition for inter-beat and inter-lead redundancy minimization as a first stage. The intra-beat correlation is exploited using ID wavelet compression of the result obtained from the first stage. Finally, the resulting tensors and matrices are serialized and entropy encoded. The achieved compression ratio is as high as 17 with acceptable restoration error.","PeriodicalId":300010,"journal":{"name":"2020 28th National Conference with International Participation (TELECOM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Approach for Multichannel ECG Compression Using HOSVD\",\"authors\":\"Yuliyan Velchev\",\"doi\":\"10.1109/TELECOM50385.2020.9299549\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel approach for multichannel electrocardiogram compression is presented in this paper. It is based on tensor decomposition for inter-beat and inter-lead redundancy minimization as a first stage. The intra-beat correlation is exploited using ID wavelet compression of the result obtained from the first stage. Finally, the resulting tensors and matrices are serialized and entropy encoded. The achieved compression ratio is as high as 17 with acceptable restoration error.\",\"PeriodicalId\":300010,\"journal\":{\"name\":\"2020 28th National Conference with International Participation (TELECOM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 28th National Conference with International Participation (TELECOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TELECOM50385.2020.9299549\",\"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 28th National Conference with International Participation (TELECOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TELECOM50385.2020.9299549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Approach for Multichannel ECG Compression Using HOSVD
A novel approach for multichannel electrocardiogram compression is presented in this paper. It is based on tensor decomposition for inter-beat and inter-lead redundancy minimization as a first stage. The intra-beat correlation is exploited using ID wavelet compression of the result obtained from the first stage. Finally, the resulting tensors and matrices are serialized and entropy encoded. The achieved compression ratio is as high as 17 with acceptable restoration error.
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