多数据库心电信号处理

Taissir Fekih Romdhane, R. Ouni, Mohamed Atri
{"title":"多数据库心电信号处理","authors":"Taissir Fekih Romdhane, R. Ouni, Mohamed Atri","doi":"10.1109/ATSIP49331.2020.9231880","DOIUrl":null,"url":null,"abstract":"An Electrocardiogram (ECG) records the electrical activity of the heart to locate the abnormalities. ECG signal processing is an emerging tool for the cardiologists in medical diagnosis for effective treatments. Many researches focus on how to improve preprocessing and processing algorithms in order to classify ECG signals with low cost and high accuracy. These algorithms consist of removing all types of noise that contaminate the ECG recording as well as extracting the most important features. In this paper, we present a useful Matlab GUI to analyze and classify ECG signal using efficient preprocessing and processing techniques. These techniques allow acquiring ECG recorders from various universal cardiac databases, filtering them using Butterworth low pass filter and IIR notch filter and extracting the most important cardiac features based on discrete wavelet transform db6.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multidatabase ECG signal processing\",\"authors\":\"Taissir Fekih Romdhane, R. Ouni, Mohamed Atri\",\"doi\":\"10.1109/ATSIP49331.2020.9231880\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An Electrocardiogram (ECG) records the electrical activity of the heart to locate the abnormalities. ECG signal processing is an emerging tool for the cardiologists in medical diagnosis for effective treatments. Many researches focus on how to improve preprocessing and processing algorithms in order to classify ECG signals with low cost and high accuracy. These algorithms consist of removing all types of noise that contaminate the ECG recording as well as extracting the most important features. In this paper, we present a useful Matlab GUI to analyze and classify ECG signal using efficient preprocessing and processing techniques. These techniques allow acquiring ECG recorders from various universal cardiac databases, filtering them using Butterworth low pass filter and IIR notch filter and extracting the most important cardiac features based on discrete wavelet transform db6.\",\"PeriodicalId\":384018,\"journal\":{\"name\":\"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ATSIP49331.2020.9231880\",\"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 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATSIP49331.2020.9231880","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

心电图(ECG)记录心脏的电活动来定位异常。心电信号处理是心内科医生在医学诊断和有效治疗方面的新兴工具。如何改进预处理和处理算法,以实现低成本、高精度的心电信号分类,是众多研究的重点。这些算法包括去除污染心电图记录的所有类型的噪声以及提取最重要的特征。在本文中,我们提出了一个有用的Matlab图形用户界面,利用有效的预处理和处理技术对心电信号进行分析和分类。这些技术允许从各种通用心脏数据库中获取心电图,使用巴特沃斯低通滤波器和IIR陷波滤波器进行滤波,并基于离散小波变换db6提取最重要的心脏特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multidatabase ECG signal processing
An Electrocardiogram (ECG) records the electrical activity of the heart to locate the abnormalities. ECG signal processing is an emerging tool for the cardiologists in medical diagnosis for effective treatments. Many researches focus on how to improve preprocessing and processing algorithms in order to classify ECG signals with low cost and high accuracy. These algorithms consist of removing all types of noise that contaminate the ECG recording as well as extracting the most important features. In this paper, we present a useful Matlab GUI to analyze and classify ECG signal using efficient preprocessing and processing techniques. These techniques allow acquiring ECG recorders from various universal cardiac databases, filtering them using Butterworth low pass filter and IIR notch filter and extracting the most important cardiac features based on discrete wavelet transform db6.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信