Late potential recognition using Wigner-Ville distribution and neural network

Author

Rakotomamonjy, Alain ; Migeon, Bruno ; Marché, Pierre

Author_Institution

Lab. Vision et Robotique, Bourges, France

Volume

4

fYear

1996

fDate

31 Oct-3 Nov 1996

Firstpage

1369

Abstract

In this paper, we present a method for the recognition of simulated late potentials in ECG by using a Wigner-Ville transform (WVT) associated with a neural network (NN). We extract 64 ms of the ECG signal after the J point. This part of the signal is then processed by the WVT. The NN is trained with the energy value of the time-frequency transform obtained from 75 simulated ECG with late potentials and 25 simulated ECG without late potentials. The pattern recognition of the NN is then tested with 75 ECG, and we achieve in 94% of sensitivity and 88% of specificity

Keywords

Wigner distribution; electrocardiography; feature extraction; feedforward neural nets; medical signal processing; pattern classification; signal representation; time-frequency analysis; ECG; Wigner-Ville distribution; energy value; feedforward neural network; late potential recognition; pattern recognition; sensitivity; simulated late potentials; specificity; time-frequency transform; Electrocardiography; Electronic mail; Feedforward neural networks; Neural networks; Neurons; Pathology; Pattern recognition; Robot vision systems; Signal processing; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE

Conference_Location

Amsterdam

Print_ISBN

0-7803-3811-1

Type

conf

DOI

10.1109/IEMBS.1996.647458

Filename

647458