Paper Info
Title
Real-time CHF detection from ECG signals using a novel discretization method.
Abstract
This study proposes a new method, equal frequency in amplitude and equal width in time (EFiA-EWiT) discretization, to discriminate between congestive heart failure (CHF) and normal sinus rhythm (NSR) patterns in ECG signals. The ECG unit pattern concept was introduced to represent the standard RR interval, and our method extracted certain features from the unit patterns to classify by a primitive classifier. The proposed method was tested on two classification experiments by using ECG records in Physiobank databases and the results were compared to those from several previous studies. In the first experiment, an off-line classification was performed with unit patterns selected from long ECG segments. The method was also used to detect CHF by real-time ECG waveform analysis. In addition to demonstrating the success of the proposed method, the results showed that some unit patterns in a long ECG segment from a heart patient were more suggestive of disease than the others. These results indicate that the proposed approach merits additional research.
Year
DOI
Venue
2013
10.1016/j.compbiomed.2013.07.015
Comp. in Bio. and Med.
Keywords
DocType
Volume
ecg record,Congestive heart failure,long ecg segment,Electrocardiography,classification experiment,proposed approach merit,ecg signal,novel discretization method,real-time chf detection,ecg unit pattern concept,Time series classification,Real-time detection,real-time ecg waveform analysis,EFiA-EWiT discretization,new method,unit pattern
Journal
43
Issue
ISSN
Citations 
10
1879-0534
4
PageRank 
References 
Authors
0.62
18
1
Name
Order
Citations
PageRank
Umut Orhan1608.66