Further improvement of classical criteria for differentiation of wide-QRS tachycardia in SVT and VT using artificial neural network techniques

Author

Dassen, Willem R M ; Mulleneers, Rob G A ; Den Dulk, Karel ; Karthaus, Vincent L J ; Talmon, Jan L. ; Wellens, Hein J J

Author_Institution

Limburg Univ., Maastricht, Netherlands

fYear

1993

fDate

5-8 Sep 1993

Firstpage

337

Lastpage

340

Abstract

A number of criteria for differentiation of wide-QRS tachycardias have been published. Recently criteria were published based on a sequential analysis of four parameters (P. Brugada et al., Circulation, vol. 83, no. 5, p. 1649-59, 1991). Based on the same ECGs as used to derive these rules, an artificial neural network was trained, and tested using a separate test set. With the help of a model, based on this network, the parameters used in the criteria mentioned above could be improved. These improvements were validated using an automatic learning system based on inductive methods

Keywords

electrocardiography; medical signal processing; ECG analysis; automatic learning system; classical criteria improvement; inductive methods; medical signal analysis; parameters; sequential analysis; supraventricular tachycardia; ventricular tachycardia; wide-QRS tachycardia differentiation; Artificial neural networks; Biomedical informatics; Cardiology; Electrocardiography; Gold; Intelligent networks; Morphology; Neural networks; Sequential analysis; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computers in Cardiology 1993, Proceedings.

Conference_Location

London

Print_ISBN

0-8186-5470-8

Type

conf

DOI

10.1109/CIC.1993.378435

Filename

378435