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ABSTRACT

Phonocardiographic signals contain bioacoustic informationreflecting the operation of the heart. Normally there are two heart sounds,

systole and diastole. If a third heart sound is present it could be a sign of

heart failure whereas a murmur indicates defective valves or an orifice in

the septal wall. The primary aim of this thesis is to find the heart diseases

from their heart sounds. In order to improve the automatic diagnosis

capabilities of auscultations, signal processing algorithms are developed.

Acoustic heart signals are generated by the mechanical processes of the

cardiac cycle, carry significant information about the underlying

functioning of the cardiovascular system. We describe a computational

analysis framework for identifying distinct morphologies of heart sounds

and classifying them into physiological states. The analysis framework is

based on hierarchical clustering, compact data representation in the

feature space of cluster distances and a classification algorithm. A novel

method of histogram matching algorithm based on structural and

perceptual features such as Zero-Crossing Rate (ZCR), Mel-Frequency

Cepstral Coefficient (MFCC), Fast Fourier transform (FFT), power

spectrum analysis are discussed. And based on this algorithm the heart

sounds are classified using matlab toolbox. The proposed framework

could be a potential solution for automatic analysis of heart sound that

may be implemented in real time for classification of heart sounds.

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TABLE OF CONTENTS

CHAPTER CONTENTS PAGE

NO NO

ABSTRACT iLIST OF FIGURE iv

LIST OF TABLES v

ACRONYMS vi

1. 1.1.INTRODUCTION 1

1.1.1.CARDIOVASCULAR ANATOMY AND

PHYSIOLOGY 1

1.1.2.THE HEART VALVES 3

1.1.3.PHONOCARDIOGRAPHY 4

1.1.4.ORIGIN OF HEART SOUND 6

1.1.5.VALVULAR HEART DISEASES 7

1.2.PROBLEM STATEMENT 11

1.3.PROPOSED SOLUTIONS 121.4.IMPLEMENTATION 13

1.5.OBJECTIVES 15

1.6.ORGANISATION OF THE REPORT 15

2. 2.1.LITERATURE REVIEW 16

3 3.1METHODOLOGY 27

3.2SEGMENTATION 28

3.3FEATURE EXTRACTION AND THEIR CHARACTERISTICS 29

3.3.1MEL-FREQ CEPSTRAL COEFFICIENTS (MFCC) 33

3.3.2POWER SPECTRAL DENSITY 35

3.3.3FAST FOURIER TRANSFORM (FFT) 36

3.3.4ZERO-CROSSING RATE 38

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3.4SUPPORT VECTOR MACHINE CLASSIFIER 39

3.4.1DATA PREPROCESSING 40

3.4.2SCALING 40

3.4.3RBF KERNEL 40

4 4.1MATLAB SIMULATOR 42

4.2SIGNAL PROCESSING TOOLBOX 42

4.3SEGMENTATION IN MATLAB 43

4.4FEATURE EXTRACTION OF PCG SIGNALS 44

4.4.1ZERO CROSSING RATE 45

4.4.2HISTOGRAM MODELING 45

4.4.3CEPSTRAL ANALYSIS 46

4.4.4FFT-BASED TIME-FREQUENCY ANALYSIS 47

4.4.5DISCRETE FOURIER TRANSFORM 48

4.4.6SPECTRAL ANALYSIS 484.5K-MEANS CLUSTERING 50

4.6CLASSIFICATION OF UNKNOWN MODULATED

SIGNAL 51

5 5.1 RESULTS 87

5.2CONCLUSION 98

REFERENCES 100

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LISTOFFIGURES

FIGURE TITLE PAGE

NO NO

1.1 Anatomy of the heart (left figure) and the blood flowpathways through left and right side of the heart 2

1.2 Illustration of the mitral valve and its associated chordaetendineae and papillary muscles and the heart valves

and the fibrous rings surrounding each valve. 4

1.3 Implementation process of heart sound classification 143.1 Design model of heart sound classification 28

3.2 Flow chart of Mel-Freq Cepstral Coefficients 35

3.3 Representation of s1,s2,s3,s4 using fast fourier transform. 37

3.4 Representation of Heart Sound In terms of ZCR 39

4.1 Segmentation of input signal 444.2 Histogram of Normal and Arotic-regugration heart sound

Using (MFCC) 46

4.3 Example of waveforms and MFCC spectrograms of S1. 47

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LIST OF TABLE

3.1 Feature Extraction And Their Characteristics 30

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ACRONYMS

PCG - Phonocardiograph

MRI - Magnetic resonance imaging

TFR - Time-Frequency Representation

S1 - First heart second

S2 - Second heart second

S3 - Third heart sound

S4 - Fourth heart sound

A2 - aortic component

P2 - pulmonary component

FHR - Fetal heart rate

KNN - k-nearest neighbor

MLP - Multilayer perceptron

SVM - Support vector machines

STFT - Short-term Fourier transforms

DWT - Discrete wavelet transformNAR-PSD - Normalized autoregressive power

spectral density

HSAS - HeartSound Authentication System

MSE - Mean Square Error

DSK - Digital signal processor starter kit

DSPPCG - Digital signal processorbasedphonocardiogram

PCPCG PC - Based phonocardiogram

CWT - Continuous WaveletTransform

ECG - Electrocardiogram

RPROP - Resilient Back propagation

SDOF - Single degree-of freedom

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CSCW - Cardiac sound characteristic

waveform

THV - Threshold value

ZCR - zero crossing rate

MFCC - mel frequency cepstral coefficient

FFT - fast fourier transform

DCT - dicrete cosine transform

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