An improved lossy and lossless combined ECG data compression using ASCII character encoding

Dharmendra Gurve, B. Saini, I. Saini
{"title":"An improved lossy and lossless combined ECG data compression using ASCII character encoding","authors":"Dharmendra Gurve, B. Saini, I. Saini","doi":"10.1504/IJMEI.2016.079363","DOIUrl":null,"url":null,"abstract":"Electrocardiogram (ECG) compression can significantly reduce the storage and transmission burden in telemedicine applications. In this paper, an improved ECG data compression method using ASCII character encoding is proposed. A QRS detection algorithm firstly applied to separate QRS and non-QRS region. Then, the QRS regions of ECG signal are compressed using lossless method and non-QRS regions are compressed using lossy method, which improves the compression ratio and minimise the reconstruction error between original and reconstructed ECG signal. All tested ECG records are selected from the PTB database. Statistical results show that the compression performance of the proposed method is better than both lossless and lossy ECG data compression technique. The average compression ratio (CR) and percent root mean square difference (PRD) obtained using proposed ECG data compression method are 27.40 and 4.753 respectively, which is better than other existing ECG data compression method.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Medical Eng. Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJMEI.2016.079363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Electrocardiogram (ECG) compression can significantly reduce the storage and transmission burden in telemedicine applications. In this paper, an improved ECG data compression method using ASCII character encoding is proposed. A QRS detection algorithm firstly applied to separate QRS and non-QRS region. Then, the QRS regions of ECG signal are compressed using lossless method and non-QRS regions are compressed using lossy method, which improves the compression ratio and minimise the reconstruction error between original and reconstructed ECG signal. All tested ECG records are selected from the PTB database. Statistical results show that the compression performance of the proposed method is better than both lossless and lossy ECG data compression technique. The average compression ratio (CR) and percent root mean square difference (PRD) obtained using proposed ECG data compression method are 27.40 and 4.753 respectively, which is better than other existing ECG data compression method.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种改进的有损和无损合并心电数据压缩,采用ASCII字符编码
在远程医疗应用中,心电图压缩可以显著降低存储和传输负担。本文提出了一种改进的心电数据压缩方法,采用ASCII字符编码。首先将QRS检测算法应用于QRS区域与非QRS区域的分离。然后,对心电信号的QRS区域进行无损压缩,对非QRS区域进行有损压缩,提高了压缩比,使原始心电信号与重构心电信号之间的重构误差最小化。所有测试的心电图记录都是从PTB数据库中选择的。统计结果表明,该方法的压缩性能优于无损和有损心电数据压缩技术。所提出的心电数据压缩方法得到的平均压缩比(CR)和百分均方根差(PRD)分别为27.40和4.753,优于现有的心电数据压缩方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Computational fluid dynamics analysis of carotid artery with different plaque shapes Pilot study of THz metamaterial-based biosensor for pharmacogenetic screening Access control to the electronic health records: a case study of an Algerian health organisation The impact of income level on childhood asthma in the USA: a secondary analysis study during 2011-2012 A low-complexity volumetric model with dynamic inter-connections to represent human liver in surgical simulators
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1