A simple real-time QRS detection algorithm utilizing curve-length concept with combined adaptive threshold for electrocardiogram signal classification

Jacek Lewandowski, Hisbel E. Arochena, Raouf N.G. Naguib, Kuo Ming Chao

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

15 Citations (Scopus)

Abstract

QRS detection is a standard procedure in electrocardiogram (ECG) signal classification and analysis. Although there is a large number of methods published, some featuring high accuracy, the problem remains open. This is especially true with respect to high accuracy QRS detection in noisy ECGs such as long-term Holter monitoring during normal daily activity. In this paper a robust real-time QRS detector for noisy applications is proposed. It exploits a modified curve-length concept with combined adaptive threshold derived by basic mean, standard deviation and average peak-to-peak interval. The method was tested using the MIT-BIH arrhythmia database with an observed detection accuracy of 99.70%, sensitivity of 99.86%, positive prediction of 99.84%, and an average failed detection of 0.30%. The proposed approach compares favourably with published results for other QRS detectors, and proves superior to those having constant and manually entered threshold parameters.

Original languageEnglish
Title of host publicationIEEE TENCON 2012
Subtitle of host publicationSustainable Development Through Humanitarian Technology
PublisherIEEE
ISBN (Print)9781467348225
DOIs
Publication statusPublished - 2012
Event2012 IEEE Region 10 Conference: Sustainable Development Through Humanitarian Technology, TENCON 2012 - Cebu, Philippines
Duration: 19 Nov 201222 Nov 2012

Conference

Conference2012 IEEE Region 10 Conference: Sustainable Development Through Humanitarian Technology, TENCON 2012
CountryPhilippines
CityCebu
Period19/11/1222/11/12

Keywords

  • Electrocardiography
  • Noise
  • Transforms
  • Detection algorithms
  • Standards
  • Databases
  • Accuracy

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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