Cardiogram Analysis and Classification Using Signal Analysis Techniques.

Abstract

The study pertains to the development of automated techniques for classification of vectorcardiograms and electrocardiograms using signal analysis techniques. A data preprocessor is developed to produce an average heartbeat from a record containing multiple heartbeats corrupted by severe baseline shifts. Several techniques for generating an ECG/VCG transformation are studied. Individual transformations are found to be quite accurate, if phase shifts among the leads are taken into account. However, patient variability appears to preclude use of a standardized transformation. The structure of the data base required to accurately test the classification algorithms is discussed and specific recommendations are made. The effect of using both two- and three-dimensional coordinate systems and a normalizing transformation for feature generation was studied; classification accuracy remained essentially unchanged.

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1974
Accession Number
ADA024865

Entities

People

  • Adnan Akant
  • Donald E. Gustafson
  • Timothy L. Johnson

Organizations

  • Charles Stark Draper Laboratory

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Aerospace Medicine
  • Algorithms
  • Classification
  • Coordinate Systems
  • Databases
  • Demographic Cohorts
  • Electrocardiography
  • Health Services
  • Phase Shift
  • Three Dimensional

Fields of Study

  • Engineering

Readers

  • Cardiovascular Physiology
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design