Denoising of electrocardiogram measurement system based on statistical signal processing

D. Sueaseenak
{"title":"Denoising of electrocardiogram measurement system based on statistical signal processing","authors":"D. Sueaseenak","doi":"10.1109/GCCE.2016.7800349","DOIUrl":null,"url":null,"abstract":"Electrocardiogram(ECG) signal is the most important of medical information used to diagnosis and indicates the condition of the heart in humans. In a design and construction of single-lead electrocardiogram measurement system using discrete component incorporated with data acquisition(DAQ) was a problem from the noise or external interference. The modern technology in signals processing used to perform a noise canceling in electrocardiography. In this paper, we propose the simulation study of modern signal processing technique to separate the single channel of ECG signals from noise and others interference. The ECG signal was performed a denoising using ICA. A useful ICA algorithm called FAS-TICA is a highperformance algorithm to divide multiple linear combinations of ECG and noise to statistically independent elements. Our experimental results indicate the robustness of ICA after applied ECG is higher than before applied ICA, since the correlation coefficient and SNR is improved with minimum error.","PeriodicalId":416104,"journal":{"name":"2016 IEEE 5th Global Conference on Consumer Electronics","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 5th Global Conference on Consumer Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2016.7800349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Electrocardiogram(ECG) signal is the most important of medical information used to diagnosis and indicates the condition of the heart in humans. In a design and construction of single-lead electrocardiogram measurement system using discrete component incorporated with data acquisition(DAQ) was a problem from the noise or external interference. The modern technology in signals processing used to perform a noise canceling in electrocardiography. In this paper, we propose the simulation study of modern signal processing technique to separate the single channel of ECG signals from noise and others interference. The ECG signal was performed a denoising using ICA. A useful ICA algorithm called FAS-TICA is a highperformance algorithm to divide multiple linear combinations of ECG and noise to statistically independent elements. Our experimental results indicate the robustness of ICA after applied ECG is higher than before applied ICA, since the correlation coefficient and SNR is improved with minimum error.
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
基于统计信号处理的心电图测量系统去噪
心电图信号是用于诊断和指示人体心脏状况的最重要的医学信息。在设计和构建单导联离散元件结合数据采集(DAQ)的心电图测量系统时,存在噪声或外界干扰的问题。在心电图中用于消除噪声的现代信号处理技术。本文提出了将单通道心电信号从噪声和其他干扰中分离出来的现代信号处理技术的仿真研究。采用ICA对心电信号进行去噪处理。一种有用的独立分量分析算法称为FAS-TICA,它是一种将ECG和噪声的多个线性组合划分为统计独立元素的高性能算法。实验结果表明,在误差最小的情况下,提高了相关系数和信噪比,因此,应用心电信号后的ICA鲁棒性优于应用前的ICA。
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
High power factor boost PFC controller with feedforward adaptive on-time control Comprehensive deformed map generation for wristwatch-type wearable devices based on landmark-based partitioning Analysis of fill-in-blank problem solution results in Java programming course Accuracy improvement in human detection using HOG features on train-mounted camera New intelligent glass curtain with IT2FLC for conversion efficiency enhancement of PV system
×
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:481959085
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