{"title":"基于小波和分形插值的心电数据压缩","authors":"W. Lee, Y. Yoon","doi":"10.1109/IEMBS.1996.647468","DOIUrl":null,"url":null,"abstract":"This paper represents the data compression for ECG signals using the wavelet and adaptive fractal interpolation method. The method represents any range of ECG signal by fractal interpolation parameters after wavelet transform. The suggested algorithm was evaluate using MIT/BIH database. A high compression ratio (CR) is achieved with a relatively low percent rms difference (PRD).","PeriodicalId":20427,"journal":{"name":"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1996-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"ECG data compression using wavelet and fractal interpolation\",\"authors\":\"W. Lee, Y. Yoon\",\"doi\":\"10.1109/IEMBS.1996.647468\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper represents the data compression for ECG signals using the wavelet and adaptive fractal interpolation method. The method represents any range of ECG signal by fractal interpolation parameters after wavelet transform. The suggested algorithm was evaluate using MIT/BIH database. A high compression ratio (CR) is achieved with a relatively low percent rms difference (PRD).\",\"PeriodicalId\":20427,\"journal\":{\"name\":\"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMBS.1996.647468\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1996.647468","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ECG data compression using wavelet and fractal interpolation
This paper represents the data compression for ECG signals using the wavelet and adaptive fractal interpolation method. The method represents any range of ECG signal by fractal interpolation parameters after wavelet transform. The suggested algorithm was evaluate using MIT/BIH database. A high compression ratio (CR) is achieved with a relatively low percent rms difference (PRD).
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