Paper Info
Title
Automatic real-time ECG coding methodology guaranteeing signal interpretation quality.
Abstract
This paper introduces a new methodology for compressing ECG signals in an automatic way guaranteeing signal interpretation quality. The approach is based on noise estimation in the ECG signal that is used as a compression threshold in the coding stage. The Set Partitioning in Hierarchical Trees algorithm is used to code the signal in the wavelet domain. Forty different ECG records from two different ECG databases commonly used in ECG compression have been considered to validate the approach. Three cardiologists have participated in the clinical trial using mean opinion score tests in order to rate the signals quality. Results showed that the approach not only achieves very good ECG reconstruction quality but also enhances the visual quality of the ECG signal.
Year
DOI
Venue
2008
10.1109/TBME.2008.2001263
IEEE Trans. Biomed. Engineering
Keywords
Field
DocType
clinical evaluation,electrocardiography,noise estimation,wavelet transforms,medical signal processing,encoding,image reconstruction,automatic real-time ecg coding methodology,wavelet domain,set partitioning in hierarchical trees (spiht),hierarchical trees algorithm,ecg coding,set partitioning,set partitioning in hierarchical trees,clinical trial,data compression,communications technology,fourier transforms,real time,mean opinion score
Iterative reconstruction,Computer vision,Pattern recognition,Set partitioning in hierarchical trees,Computer science,Coding (social sciences),Mean opinion score,Artificial intelligence,Data compression,Encoding (memory),Wavelet,Wavelet transform
Journal
Volume
Issue
ISSN
55
11
1558-2531
Citations 
PageRank 
References 
13
0.87
8
Authors
2
Name
Order
Citations
PageRank
Alvaro Alesanco112713.33
José García225045.30