Estimation of noise in ECG signals using wavelets

Author

Stolojescu, Cristina

Author_Institution

Dept. of Commun., Politeh. Univ. of Timisoara, Timisoara

fYear

2008

fDate

22-24 May 2008

Firstpage

113

Lastpage

118

Abstract

ECG signal and generally biomedical signals change their statistical properties over time. The most powerful tool for analyzing non-stationary signals is the wavelet transform. We developed and evaluated a noise perturbing ECG detection system based on the multi-resolution analysis. We considered four types of ECG signal, without additional noise and corrupted by three types of noise and we realized the signals classification using wavelet filtering and statistical analyses. The ECG data is taken from the standard MIT-BIH Arrhythmia database, while the signals of noise belong to MIT-BIH Noise Stress Test Database.

Keywords

electrocardiography; filtering theory; medical signal detection; medical signal processing; noise; signal classification; signal resolution; statistical analysis; wavelet transforms; ECG detection system; ECG signal noise estimation; MIT-BIH arrhythmia database; MIT-BIH noise stress test database; biomedical signal processing; multiresolution analysis; signal classification; statistical analyses; wavelet filtering; wavelet transform; Databases; Electrocardiography; Filtering; Pattern classification; Signal analysis; Statistical analysis; Stress; Testing; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Optimization of Electrical and Electronic Equipment, 2008. OPTIM 2008. 11th International Conference on

Conference_Location

Brasov

Print_ISBN

978-1-4244-1544-1

Electronic_ISBN

978-1-4244-1545-8

Type

conf

DOI

10.1109/OPTIM.2008.4602509

Filename

4602509