SIGNIFICANT POINT EXTRACTION ALGORITHM FOR ECG DATA REDUCTION AND PATTERN RECOGNITION.

J. Weinrib, H. Lee, N. Thakor

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

Abstract

The authors present a new technique to derive from an ECG waveform the significant points, or the points where the curvature of the waveform is significant. They employ these in ECG data reduction and pattern recognition programs. The significant points are derived by first producing a chain-code from the pattern, and from that the local and then the global curvature. When only the significant points are used to reconstruct the signal, it results in a data-reduction of the order of 10:1. At the same time these significant points are used in a pattern recognition program to extract the QRS complex, and the ectopic beats.

Original languageEnglish (US)
Title of host publicationComputers in Cardiology
EditorsKenneth L. Ripley
PublisherIEEE
Pages97-100
Number of pages4
ISBN (Print)0818605472
StatePublished - Dec 1 1984

Publication series

NameComputers in Cardiology
ISSN (Print)0276-6574

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ASJC Scopus subject areas

  • Computer Science Applications
  • Cardiology and Cardiovascular Medicine

Cite this

Weinrib, J., Lee, H., & Thakor, N. (1984). SIGNIFICANT POINT EXTRACTION ALGORITHM FOR ECG DATA REDUCTION AND PATTERN RECOGNITION. In K. L. Ripley (Ed.), Computers in Cardiology (pp. 97-100). (Computers in Cardiology). IEEE.