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The Analyses and Researches of Heart Sound Signal on the Basis of Matlab

Author: YangYanNi
Tutor: YanBiGe
School: Shaanxi Normal University
Course: Acoustics
Keywords: Heart sound signals Wavelet Transform STFT Autoregressive model
CLC: R318.04
Type: Master's thesis
Year: 2007
Downloads: 483
Quote: 4
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Showed an increasing trend with modern social and material living standards improve, cardiovascular disease, its cause mortality among the first of the various diseases, as the biggest threat to human health. The heart sounds is a reflection of the condition of the mechanical movement of the heart and cardiovascular system, which includes the role of the various parts of the heart itself, and between physiological and pathological information. Analysis of heart sounds with modern digital signal processing technology has significant value in basic research and clinical diagnosis of cardiovascular disease. Heart sound research field of the study of the physiology and pathology of the first heart sound and second heart sounds; non-invasive detection of artificial heart valves; analysis of heart sounds weak ingredients (third heart sound and fourth heart sounds); analysis of heart murmur frequency variation; positioning extract from a cardiac cycle of heart sounds ingredients; conduction mechanism modeling of the heart sounds. The basis for discussions on the heart sound signal analysis method, pre-processing and ingredients positioning, extract the characteristic frequency of the second heart sound different pathological cases, provide a reference for the clinical diagnosis of heart disease. According to the valvular theory, the second heart sound (S 2 ) from ventricular diastolic ventricular wall vibration, the aortic valve (Aortic valve) and pulmonary valve (Pulmonary valve) off and atrioventricular valve open flow from the atrium into the ventricle, comprising a plurality of frequency components is an important part of the heart sounds. In this paper, the short-time Fourier transform and AR model power spectrum analysis and extraction of the second heart sound data of 20 cases of heart sounds (including normal 10 cases, 10 cases of abnormal) two main characteristic frequency, combined with the physiological characteristics of the experimental results of the second heart sound were analyzed and discussed. The experimental results show that: (1) the second heart sound (S 2 ) containing aortic lobe (A 2 ) and pulmonary valve (P 2 ) two main ingredients; (2) (A 2 ) of abnormal heart sounds (S 2 ) aortic and pulmonary valve (P 2 ) frequency than normal heart sounds increased; (3) the second heart sound also contains low-frequency, low-amplitude, longer duration ingredients. Mainly in the following aspects: 1. Heart sound data collected from the hardware to the very serious interference, the heart sound signal can not be normal analytical processing, these disturbances include the 50Hz frequency interference, the interference of breath sounds and white noise. According to the different signal and noise wavelet coefficients after wavelet transform with the scale changes, the paper proposes denoising using wavelet multi-resolution analysis of heart sound signals. Through comparative analysis, to find the best wavelet denoising parameters, ie coif5 Wavelet heart sound signal layer decomposition de-noising by soft thresholding and fixed threshold. 2. Analysis of heart sounds, time-varying characteristics of heart sound signals, using the following method and compare their advantages and disadvantages in the analysis of heart sound signals, different analytical methods in order to be selected depending on the purpose. (1) heart sounds, heart murmurs frequency components is an important feature of the heart sounds, therefore, the use of modern power spectrum AR model analysis method of heart sounds on a cycle energy analysis, divided into high, medium and low frequency in the frequency component of the heart sounds bands. (2) heart sounds is a time-varying signal its time - frequency characteristics that best reflect the characteristics 2205Hz sampling frequency of 128-point Hamming window short-time Fourier transform of heart sound signals, the results of the analysis can be used two-dimensional and the three-dimensional two ways to display the results intuitive. (3) Another method is to time-frequency analysis of the heart sound analysis, The dyadic wavelet sub-band filter characteristics, the heart sound is decomposed into three bands of high, medium and low frequencies, the use of the signal waveform of each band reconstruction Figure examine each band of the time - amplitude characteristics of each ingredient and its trends, and characteristics of the heart sounds made fully reflected. 3. Using wavelet multiresolution analysis method and normalized the Shannon energy extraction second heart sound. Multiresolution analysis by wavelet after decomposition of the heart sound signals, different frequency bands are reconstructed, and then each band is the same length of time segment, computing for each segment the Shannon normalized energy, and then, combined heart sound characteristic determination S < sub> 2 of the location. 4. Eigenvalue extraction of the second heart sound signal. AR model and the short-time Fourier transform to detect the two main characteristics of the frequency of the second heart sound, comparative study of the different points of the normal heart sounds and heart sounds valvular heart disease, and provide a reference for the clinical diagnosis of heart disease. This article provides a basic analysis methods clinical studies of the heart sound signal, laid the foundation for the heart sounds for assisted diagnosis of heart disease.

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CLC: > Medicine, health > Basic Medical > Medical science in general > Biomedical Engineering > General issues > Biological information, biological control
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