Methodology of ECG Interpretation in the AVA Program

H. V. Pipberger; C. D. McManus; H. A. Pipberger

doi:10.1055/s-0038-1634797

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1990; 29(04): 337-340
DOI: 10.1055/s-0038-1634797

ECG Interpretation Systems

Schattauer GmbH

Methodology of ECG Interpretation in the AVA Program

Authors

H. V. Pipberger

¹Veterans Affairs Medical Center, Washington DC, and Department of Computer Medicine, George Washington University, Washington DC, U.S.A
C. D. McManus

¹Veterans Affairs Medical Center, Washington DC, and Department of Computer Medicine, George Washington University, Washington DC, U.S.A
H. A. Pipberger

¹Veterans Affairs Medical Center, Washington DC, and Department of Computer Medicine, George Washington University, Washington DC, U.S.A

Abstract

The AVA program combines a thirty-year history with an approach that remains innovative; namely: multivariate statistical analysis on orthogonal ECG leads. Its diagnostic reference base includes only diagnoses independently verified by non-ECG criteria. The diagnostic module assesses probabilities of nine alternative disease categories, based on QRS-T parameters; or four other categories in case of conduction defects. Probabilities of left or right atrial overload are also computed. The program also recognizes wall injury, T-wave abnormalities, electrolyte disturbances, myocardial ischemia, and makes differential diagnoses between strain and digitalis effects. An arrhythmia classification module can generate any of 40 rhythm statements. Signal recognition is based on the spatial velocity function. The program has been translated to a microcomputer version.

Key-Words

Electrocardiography - Signal Analysis - Computer-Assisted Diagnosis

Full Text

References

REFERENCES
1 Stallmann FW, Pipberger HP. Automatic recognition of electrocardiographic waves by digital computer. Circulation Res 1961; 09: 1138-43.
2 Batschlet E. Statistical Methods for the Analysis of Problems in Animal Orientation and Certain Biological Rhythms . The American Institute of Biological Sciences; Washington DC: 1965
3 Cornfield J, Dunn RA, Batchlor CD, Pipberger HV. Multigroup diagnosis of electrocardiograms. Comp Biomed Res 1973; 06: 97-120.
4 Pipberger HV, Simonson E, Lopez EA, Araoye MA, Pipberger HA. The electrocardiogram in epidemiological investigations. A new classification system. Circulation 1982; 65: 1456-64.
5 Willems JL, Pipberger HV. Arrhythmia detection by digital computer. Comp Biomed Res 1972; 05: 263-78.
6 Pipberger HV, Bialek SM, Perloff JK, Schnaper HW. Correlation of clinical information in the standard 12-lead ECG and in a corrected orthogonal 3-lead ECG. Am Heart J 1961; 61: 34-43.
7 Pipberger HV, McCaughan D, Littmann D. et al. Clinical application of a second generation electrocardiographic computer program. Am J Cardiol 1975; 35: 597-608.
8 Bailey JJ, Horton M, Iscoitz SB. The importance of reproducibility testing of computer programs for electrocardiographic interpretation: Application to the automated vectorcardiographic analysis program (AVA 3.4). Comp Biomed Res 1976; 09: 307-16.