The Use of Wavelet Analysis to Denoising of Electrocardiography Signal - Publication - Bridge of Knowledge

Search

The Use of Wavelet Analysis to Denoising of Electrocardiography Signal

Abstract

The electrocardiography examination, due to its accessibility and simplicity, has an important role in diagnostics of the heart ailments. It enables quick detection of various heart defects, undetectable by other kinds of diagnostic tools, so it is very popular. Nevertheless, the measured signal is exposed to a different disturbances. Among them, the electromagnetic interferences, drift of reference electrode and high frequency noises occurring during the measure, should be included. The frequencies spectrum of the noise overlap the spectrum of the electrocardiography signal, which makes impossible to use a classical filters. In the human’s diagnosis, a high quality of the signal is of a great importance. Therefore, in this paper, an optimal wavelet denoising algorithm for electrocardiography signal is presented. The simulation shows that the use of wavelet analysis during the filtration process allows to remove effectively the noise from the electrocardiography signal, without losing an important information and also improves the quality of the signal. To obtain an unambiguous evaluation of wavelet denoising algorithms the signal-to-noiseratio (SNR), mean square error (MSE), and correlation coefficient were used simultaneously. What is more, a fit coefficient, determining the relation between original and denoised signal, were developed.

Cite as

Full text

full text is not available in portal

Keywords

Details

Category:
Conference activity
Type:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Title of issue:
XV International PHD Workshop OWD 2013 strony 456 - 461
Language:
English
Publication year:
2013
Bibliographic description:
Gradolewski D., Redlarski G.: The Use of Wavelet Analysis to Denoising of Electrocardiography Signal// XV International PHD Workshop OWD 2013/ ed. Grzegorz Kłapyta : , 2013, s.456-461
Verified by:
Gdańsk University of Technology

seen 157 times

Recommended for you

Meta Tags