Open AccessEmpirical Mode Decomposition (EMD) Based Denoising Method for Heart Sound Signal and Its Performance Analysis
Author(s) -
Amy Hamidah Salman,
Nur Ahmadi,
Richard Mengko,
Armein Z. R. Langi,
Tati L. R. Mengko
Publication year - 2016
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v6i5.pp2197-2204
Subject(s) - hilbert–huang transform , noise reduction , mean squared error , noise (video) , root mean square , white noise , computer science , signal (programming language) , wavelet , mathematics , speech recognition , signal to noise ratio (imaging) , algorithm , pattern recognition (psychology) , statistics , artificial intelligence , image (mathematics) , engineering , electrical engineering , programming language
In this paper, a denoising method for heart sound signal based on empirical mode decomposition (EMD) is proposed. To evaluate the performance of the proposed method, extensive simulations are performed using synthetic normal and abnormal heart sound data corrupted with white, colored, exponential and alpha-stable noise under different SNR input values. The performance is evaluated in terms of signal-to-noise ratio (SNR), root mean square error (RMSE), and percent root mean square difference (PRD), and compared with wavelet transform (WT) and total variation (TV) denoising methods. The simulation results show that the proposed method outperforms two other methods in removing three types of noises.