Please use this identifier to cite or link to this item:
Title: An Exploration of Heart Sound Denoising Method Based on Dynamic Wavelet Shrinkage and Singular Spectrum Analysis
Authors: ZENG, TAO (曾韜)
Department: Department of Electrical and Computer Engineering
Faculty: Faculty of Science and Technology
Issue Date: 2014
Citation: ZENG, T. (2014). An Exploration of Heart Sound Denoising Method Based on Dynamic Wavelet Shrinkage and Singular Spectrum Analysis (Outstanding Academic Papers by Students (OAPS)). Retrieved from University of Macau, Outstanding Academic Papers by Students Repository.
Abstract: Intelligent computer-aided heart sound (HS) auscultation provides quantitative and qualitative HS interpretation for preemptive cardiovascular diseases (CVDs). However, the noises corruption in electronic stethoscope acquired HS signals will not only pollute the HS pathological characteristics but also deteriorate diagnosis accuracy dramatically. Therefore, HS denoising plays a pivotal role to get qualified HS signals for further analysis and interpretation. In this research, a scheme for HS denoising systems adapting dynamic threshold wavelet shrinkage (DTWS) method and singular spectrum analysis (SSA) are proposed. Massive pathological information contained in murmurs is vulnerable to be distorted by applying traditional wavelet shrinkage (TWS) methods. As an improvement of TWS methods, DTWS method further identifies the HS and murmurs information before denoising. Taking advantage of dynamic thresholds, DTWS methods could overcome the shortcomings of TWS method and reserve the foremost HS and murmurs information while eliminating noises utmostly. SSA can efficiently decompose the HS signals with noise into meaningful components representing the constituent of original signals. After reserving the effective eigenvalues, the principal components of HS are picked up and re-assembled as the final de-noised HS. Experiments using HS signals from eGeneral Medical benchmark database validate the high performance of the proposed denoising scheme adapting DTWS method and SSA in terms of signal-noise ratio (SNR) and root mean square error (RMSE). The results also demonstrated that the proposed denoising scheme not only eliminates the noise components from HS efficiently, but also retains the pathological details of the original HS signals.
Instructor: Prof. DONG, MING CHUI
Programme: Bachelor of Science in Electrical and Electronics Engineering
Appears in Collections:FST OAPS 2014

Files in This Item:
File Description SizeFormat 
OAPS_2014_FST_016.pdf2.41 MBAdobe PDFView/Open
OAPS_2014_FST_016_presentation.pptx2.99 MBMicrosoft Powerpoint XMLView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.