Intelligent classification of electrocardiogram (ECG) signal using extended Kalman Filter (EKF) based neuro fuzzy system.

Abstract:

:This study presents the development of a hybrid system consisting of an ensemble of Extended Kalman Filter (EKF) based Multi Layer Perceptron Network (MLPN) and a one-pass learning Fuzzy Inference System using Look-up Table Scheme for the recognition of electrocardiogram (ECG) signals. This system can distinguish various types of abnormal ECG signals such as Ventricular Premature Cycle (VPC), T wave inversion (TINV), ST segment depression (STDP), and Supraventricular Tachycardia (SVT) from normal sinus rhythm (NSR) ECG signal.

authors

Meau YP,Ibrahim F,Narainasamy SA,Omar R

doi

10.1016/j.cmpb.2006.03.003

subject

Has Abstract

pub_date

2006-05-01 00:00:00

pages

157-68

issue

2

eissn

0169-2607

issn

1872-7565

pii

S0169-2607(06)00065-4

journal_volume

82

pub_type

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