Title :
Neural network for automatic anomalous QRS complex detection
Author :
Casaleggio, A. ; Morando, M. ; Ridella, S.
Author_Institution :
Istituto per i Circuiti Elettronici, Consiglio Nazionale delle Ricerche, Genova, Italy
Abstract :
An application of the back-propagation (BP) neural network (NN) for the discrimination between normal and pathological electrocardiogram (ECG) complexes is presented. The BP is used as a part of an unsupervised method: the network output has not been used to discriminate normal and pathological complexes, but only to extract the prototype complex of the analyzed ECG. An attempt is made to automatically individualize a pathological QRS morphology on those ECGs where anomalous premature ventricular contraction (PVC) beats were less than 15%. Results show a sensitivity of 0.991 and a specificity of 0.985
Keywords :
computerised signal processing; electrocardiography; medical diagnostic computing; neural nets; anomalous premature ventricular contraction; automatic anomalous QRS complex detection; back-propagation neural network; normal electrocardiogram complexes; pathological electrocardiogram complexes; prototype complex extraction; unsupervised method; Algorithm design and analysis; Circuits; Data mining; Electrocardiography; Iterative algorithms; Morphology; Neural networks; Pathology; Performance analysis; Prototypes;
Conference_Titel :
Computers in Cardiology 1990, Proceedings.
Conference_Location :
Chicago, IL
Print_ISBN :
0-8186-2225-3
DOI :
10.1109/CIC.1990.144278
