Title :
A hybrid neuro-fuzzy system for ECG classification of myocardial infarction
Author :
Bozzola, P. ; Bortolan, G. ; Combi, C. ; Pinciroli, F. ; Brohet, C.
Author_Institution :
Milano, Italy
Abstract :
We present an approach to the automated ECG classification based on a hybrid neuro-fuzzy model. The classification power of the connectionist paradigm has been coupled with the ability of the fuzzy set formalism to treat in a quantitative way natural language. This allows us to build up a system capable of both a good classification accuracy and to give meaningful explanations of the proposed diagnoses, in the form of symbolic IF-THEN rules.
Keywords :
adaptive signal processing; electrocardiography; feedforward neural nets; fuzzy set theory; medical signal processing; multilayer perceptrons; muscle; pattern classification; ECG classification; automated ECG classification; classification accuracy; classification power; connectionist paradigm; fuzzy set formalism; hybrid neuro-fuzzy system; multilayer perceptron model; myocardial infarction; natural language; symbolic IF-THEN rules; Adaptive systems; Cardiology; Databases; Electrocardiography; Fuzzy neural networks; Libraries; Multilayer perceptrons; Myocardium; Natural languages; Neural networks;
Conference_Titel :
Computers in Cardiology, 1996
Conference_Location :
Indianapolis, IN, USA
Print_ISBN :
0-7803-3710-7
DOI :
10.1109/CIC.1996.542518
