Complexity Measure Revisited: A New Algorithm for Classifying Cardiac Arrhythmias

Abstract

This paper deals to the suitability of Complexity Measure of ECG signals for the classification of cardiac arrhythmia's. Applying this algorithm to data from the MIT- BIH database a very poor performance, especially for SR signals, and an overall error rate of 2O% is obtained. In this study a novel measure, named SPDR, Sample Percentage in the Dynamic Range, to be used in combination with the Complexity Measure algorithm, is proposed. Using this novel proposal the result of the classification is improved decreasing the overall error rate until to 9%. The algorithm has been implemented in a computer using LabView and C++ software.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412130

Entities

People

  • Il Romero
  • L. Serrano
  • U. Ayesta

Organizations

  • Public University of Navarre

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Algorithms
  • Cardiac Arrhythmias
  • Cardiovascular System
  • Classification
  • Databases
  • Detection
  • Dynamic Range
  • Electrocardiography
  • Engineering
  • Frequency
  • Health Services
  • Heart Rate
  • Learning Machines
  • Time Domain

Fields of Study

  • Computer science

Readers

  • Approximation Theory.
  • Psychometric Testing or Psychological Assessment.
  • Wave Propagation and Nonlinear Chaotic Dynamics.