{"title":"Performance analysis of FIR and IIR filters for ECG signal denoising based on SNR","authors":"Nilotpal Das, M. Chakraborty","doi":"10.1109/ICRCICN.2017.8234487","DOIUrl":null,"url":null,"abstract":"Filtering of ECG signal is an essential step in ECG signal processing and analysis. Since ECG is a low amplitude biosignal, it is easily corrupted by external noises, and by the presence of other biosignals. The aim of filtering is to remove unwanted noise while preserving important characteristics of the signal. Various filtering techniques are available thus choosing the right filter for ECG denoising is a problem. This study aims to solve that problem by quantifying and comparing performance of various FIR and IIR filters, based on their SNR values, in both diagnostic and monitoring mode. For this purpose, ECG signals are collected from MIT-BIH Physionet Database. This study identifies the order at which filters perform best, thus order optimization for each filter design has been done. Readers will be able to understand the variation of filter performance with filter order and choose the best filter for ECG signal denoising.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCICN.2017.8234487","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
Filtering of ECG signal is an essential step in ECG signal processing and analysis. Since ECG is a low amplitude biosignal, it is easily corrupted by external noises, and by the presence of other biosignals. The aim of filtering is to remove unwanted noise while preserving important characteristics of the signal. Various filtering techniques are available thus choosing the right filter for ECG denoising is a problem. This study aims to solve that problem by quantifying and comparing performance of various FIR and IIR filters, based on their SNR values, in both diagnostic and monitoring mode. For this purpose, ECG signals are collected from MIT-BIH Physionet Database. This study identifies the order at which filters perform best, thus order optimization for each filter design has been done. Readers will be able to understand the variation of filter performance with filter order and choose the best filter for ECG signal denoising.
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