Speaker
Stanislaw Osowski
(Warsaw University of Technology)
Description
The paper proposes an ensemble composed of CNN networks for the detection of anomalies in ECG waveforms. The approach is composed of two stages: transformation of ECG signals into images and association of the images with the appropriate class of anomaly using the ensemble of CNN classifiers. The experiments have been performed on the publicly available database Complex Physiologic Signals PhysioNet and directed to recognize three types of ECG signals. The results of numerical experiments are presented and discussed.
Authors
Dr
Maciej Golgowski
(Military University of Technology)
Stanislaw Osowski
(Warsaw University of Technology)
