SVD- based method for ECG denoising

Author

Ouali, M.A. ; Chafaa, K.

Author_Institution

Electron. Dept., Univ. Hadj Lakhdar, Batna, Algeria

fYear

2013

fDate

20-22 Jan. 2013

Firstpage

1

Lastpage

4

Abstract

In this paper an efficient filtering procedure based on the Singular Value Decomposition (SVD) has been proposed. SVD, a high resolution spectrum estimation tools, is used to decompose the ECG data matrix into orthogonal subspaces. Due to the energy-preserving orthogonal transformation in the SVD, these subspaces correspond to the signal and noise components contained in the ECG data. Projection of the data onto the desired subspace eliminates the noise and the unwanted signal components.

Keywords

electrocardiography; filtering theory; medical signal processing; signal denoising; singular value decomposition; ECG data matrix decomposition; ECG denoising; SVD-based method; electrocardiography; energy-preserving orthogonal transformation; filtering procedure; noise component; orthogonal subspace; signal component; singular value decomposition; spectrum estimation tool; Electrocardiography; Matrix decomposition; Noise reduction; Signal to noise ratio; Singular value decomposition; Vectors; Den o ising; EeG signal; Singular value decemposition; prejection operator;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Applications Technology (ICCAT), 2013 International Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4673-5284-0

Type

conf

DOI

10.1109/ICCAT.2013.6522051

Filename

6522051