JOURNAL ARTICLE

Empirical Mode Decomposition (EMD) Based Denoising Method for Heart Sound Signal and Its Performance Analysis

Amy Hamidah SalmanNur AhmadiRichard MengkoArmein Z. R. LangiTati L. R. Mengko

Year: 2016 Journal:   International Journal of Electrical and Computer Engineering (IJECE) Vol: 6 (5)Pages: 2197-2197   Publisher: Institute of Advanced Engineering and Science (IAES)

Abstract

<p>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.</p>

Keywords:
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

Metrics

17
Cited By
0.25
FWCI (Field Weighted Citation Impact)
22
Refs
0.70
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Phonocardiography and Auscultation Techniques
Health Sciences →  Medicine →  Pulmonary and Respiratory Medicine
ECG Monitoring and Analysis
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine

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