{"title":"ECG data compression based on wave atom transform","authors":"Hongteng Xu, Guangtao Zhai","doi":"10.1109/MMSP.2011.6093793","DOIUrl":null,"url":null,"abstract":"In this paper, a new ECG signal compression algorithm based on wave atom transform is presented. According to an assumption that ECG is oscillatory signal, we decompose ECG signal by wave atoms and trimmed insignificant coefficients. The wave atom decomposition has been proved to have a significantly sparser solution than other existing transform methods when it comes to oscillatory signal. In our experiment, the convergence of the energy of wave atoms' coefficients is faster than that of wavelet indeed. The most significant advantage of our algorithm is that unlike many conventional methods, the performance of our algorithm is not dependent on QRS detection, which simplifies the architecture of compression system and is beneficial to telemedicine application. After wave atom transform, the data stream is divided and coded by a hybrid entropy coding strategy combining delta coding, run-length-coding and arithmetic coding. The experimental results on MIT-BIH arrhythmia database proved that our algorithm has high compression ratio (CR > 10) with percentage root mean square difference (PRD) under 1%.","PeriodicalId":214459,"journal":{"name":"2011 IEEE 13th International Workshop on Multimedia Signal Processing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 13th International Workshop on Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2011.6093793","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, a new ECG signal compression algorithm based on wave atom transform is presented. According to an assumption that ECG is oscillatory signal, we decompose ECG signal by wave atoms and trimmed insignificant coefficients. The wave atom decomposition has been proved to have a significantly sparser solution than other existing transform methods when it comes to oscillatory signal. In our experiment, the convergence of the energy of wave atoms' coefficients is faster than that of wavelet indeed. The most significant advantage of our algorithm is that unlike many conventional methods, the performance of our algorithm is not dependent on QRS detection, which simplifies the architecture of compression system and is beneficial to telemedicine application. After wave atom transform, the data stream is divided and coded by a hybrid entropy coding strategy combining delta coding, run-length-coding and arithmetic coding. The experimental results on MIT-BIH arrhythmia database proved that our algorithm has high compression ratio (CR > 10) with percentage root mean square difference (PRD) under 1%.