Publication detail

Optimization of the Wavelet Wiener Filtering for ECG Signals

SMITAL, L. VÍTEK, M. KOZUMPLÍK, J.

Original Title

Optimization of the Wavelet Wiener Filtering for ECG Signals

Type

conference paper

Language

English

Original Abstract

This paper deals with the methods of ECG signals denoising via wavelet Wiener filtering. We have studied the influence of the input parameters setting on filtered signals in a consideration of achieved signal to noise ratio (SNR). The Wiener filtering is used in the shift invariant dyadic discrete time wavelet domain for suppression of a parasite electromyographic (EMG) signal. To improve the filtering performance we used the adaptive adjustment of the method parameters, according to the level of the input noise. We are able to increase the average SNR of the whole tested database almost about 10 dB. The proposed algorithm provides better results, than a classic wavelet Wiener filtering method. The algorithm was tested on signals from the standard multilead CSE database.

Keywords

Wiener filtering, Wavelet transform, ECG signal, Parameters optimization, EMG noise, Noise estimation, standard CSE database.

Authors

SMITAL, L.; VÍTEK, M.; KOZUMPLÍK, J.

RIV year

2011

Released

26. 10. 2011

Publisher

ACM New York, NY, USA

Location

Barcelona, Spain

ISBN

978-1-4503-0913-4

Book

ACM digital library: 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies

Pages from

1

Pages to

5

Pages count

5

BibTex

@inproceedings{BUT73846,
  author="Lukáš {Smital} and Martin {Vítek} and Jiří {Kozumplík}",
  title="Optimization of the Wavelet Wiener Filtering for ECG Signals",
  booktitle="ACM digital library: 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies",
  year="2011",
  pages="1--5",
  publisher="ACM New York, NY, USA",
  address="Barcelona, Spain",
  isbn="978-1-4503-0913-4"
}