A Wavelet-Based ECG Delineation Method: Adaptation to an Experimental Electrograms with Manifested Global Ischemia

We present a novel wavelet-based ECG delineation method with robust classification of P wave and T wave. The work is aimed on an adaptation of the method to long-term experimental electrograms (EGs) measured on isolated rabbit heart and to evaluate the effect of global ischemia in experimental EGs o...

Full description

Saved in:
Bibliographic Details
Published in:Cardiovascular engineering and technology 2015-09, Vol.6 (3), p.364-375
Main Authors: Hejč, Jakub, Vítek, Martin, Ronzhina, Marina, Nováková, Marie, Kolářová, Jana
Format: Article
Language:English
Subjects:
Algorithms
Animals
Biomedical Engineering and Bioengineering
Biomedicine
Cardiology
Electrocardiography - methods
Engineering
Heart - physiopathology
Humans
Ischemia - physiopathology
Rabbits
Signal Processing, Computer-Assisted
Wavelet Analysis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We present a novel wavelet-based ECG delineation method with robust classification of P wave and T wave. The work is aimed on an adaptation of the method to long-term experimental electrograms (EGs) measured on isolated rabbit heart and to evaluate the effect of global ischemia in experimental EGs on delineation performance. The algorithm was tested on a set of 263 rabbit EGs with established reference points and on human signals using standard Common Standards for Quantitative Electrocardiography Standard Database (CSEDB). On CSEDB, standard deviation (SD) of measured errors satisfies given criterions in each point and the results are comparable to other published works. In rabbit signals, our QRS detector reached sensitivity of 99.87% and positive predictivity of 99.89% despite an overlay of spectral components of QRS complex, P wave and power line noise. The algorithm shows great performance in suppressing J-point elevation and reached low overall error in both, QRS onset ( SD  = 2.8 ms) and QRS offset ( SD  = 4.3 ms) delineation. T wave offset is detected with acceptable error ( SD  = 12.9 ms) and sensitivity nearly 99%. Variance of the errors during global ischemia remains relatively stable, however more failures in detection of T wave and P wave occur. Due to differences in spectral and timing characteristics parameters of rabbit based algorithm have to be highly adaptable and set more precisely than in human ECG signals to reach acceptable performance.
ISSN:1869-408X
1869-4098
DOI:10.1007/s13239-015-0224-z