Empirical modal decomposition applied to cardiac signals analysis

O. Beya; B. Jalil; E. Fauvet; O. Laligant

doi:10.1117/12.840667

4 February 2010 Empirical modal decomposition applied to cardiac signals analysis

O. Beya, B. Jalil, E. Fauvet, O. Laligant

Proceedings Volume 7535, Wavelet Applications in Industrial Processing VII; 75350B (2010) https://doi.org/10.1117/12.840667
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

In this article, we present the method of empirical modal decomposition (EMD) applied to the electrocardiograms and phonocardiograms signals analysis and denoising. The objective of this work is to detect automatically cardiac anomalies of a patient. As these anomalies are localized in time, therefore the localization of all the events should be preserved precisely. The methods based on the Fourier Transform (TFD) lose the localization property [13] and in the case of Wavelet Transform (WT) which makes possible to overcome the problem of localization, but the interpretation remains still difficult to characterize the signal precisely. In this work we propose to apply the EMD (Empirical Modal Decomposition) which have very significant properties on pseudo periodic signals. The second section describes the algorithm of EMD. In the third part we present the result obtained on Phonocardiograms (PCG) and on Electrocardiograms (ECG) test signals. The analysis and the interpretation of these signals are given in this same section. Finally, we introduce an adaptation of the EMD algorithm which seems to be very efficient for denoising.

Citation Download Citation

O. Beya, B. Jalil, E. Fauvet, and O. Laligant "Empirical modal decomposition applied to cardiac signals analysis", Proc. SPIE 7535, Wavelet Applications in Industrial Processing VII, 75350B (4 February 2010); https://doi.org/10.1117/12.840667

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available