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The New Approach for ECG Signal Quality Index Estimation on the Base of Robust Statistic

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

In this article a new method for automatic determination of the quality indicator of electrocardiographic signal (ECG) is presented. The proposed method allows to determine the time intervals in which the ECG signal is of such quality that it is possible to detect the R-waves of the electrocardiogram. The developed method is based on analysis of the median standard deviation (MAD). The method is divided into three stages: determination of variability of MAD, finding of the time intervals in which the signal is in saturation and the decision stage, on the basis of which the masking signal is created. The performance of the proposed method has been tested with using the ECG recordings taken from the MIT-BIH Noise Stress Test database and the telehealth database. The obtained results show the usefulness in location of artifacts in the ECG signal. The proposed algorithm can be useful especially in acquisition of electrophysiological signals for mobile devices for telemedicine purposes.

Original languageEnglish
Title of host publicationInformation Technology in Biomedicine, 2019
EditorsEwa Pietka, Pawel Badura, Jacek Kawa, Wojciech Wieclawek
PublisherSpringer Verlag
Pages481-494
Number of pages14
ISBN (Print)9783030237615
DOIs
Publication statusPublished - 2019
Event7th International Conference on Information Technology in Biomedicine, ITIB 2019 - Kamień Śląski, Poland
Duration: 18 Jun 201920 Jun 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1011
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference7th International Conference on Information Technology in Biomedicine, ITIB 2019
Country/TerritoryPoland
CityKamień Śląski
Period18/06/1920/06/19

Keywords

  • Artifacts masking
  • Electrocardiogram
  • MAD
  • Signal quality index

ASJC Scopus subject areas

  • Control and Systems Engineering
  • General Computer Science

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