DETECTION OF WAVE V USING CONTINUOUS WAVELET TRANSFORM

AND INSTANSTANEOUS ENERGY FOR HEARING LOSS

MOHD RUSHAIDIN BIN MUHAMED

UNIVERSITI TEKNOLOGI MALAYSIA

DETECTION OF WAVE V USING CONTINUOUS WAVELET TRANSFORM

AND INSTANSTANEOUS ENERGY FOR HEARING LOSS

MOHD RUSHAIDIN BIN MUHAMED

A thesis submitted in fulfilment of the

requirements for the award of the degree of

Master of Engineering (Electrical)

Faculty of Electrical Engineering

Universiti Teknologi Malaysia

FEBRUARY 2011

iii

Praise to Allah the Almighty

Thanks to my beloved mother, father and lovely wife

For humanity, hope to be more submitted, pious and to the Creator do we return

iv

ACKNOWLEDGEMENT

Alhamdulillah, thanks to Allah, God the Almighty for giving me the strength and

time to complete this project.

In preparing this thesis, I was in contact with many people – researchers,

academicians, and practitioners. I would like take this opportunity to thank them.

Particular, I would like to express my gratitude to my thesis supervisor, Prof. Ir. Dr.

Sheikh Hussain Shaikh Salleh for his encouragement, guidance, critics, advice and

motivation in the process of preparing and completing this project. I also wish to express

my sincere appreciation to Prof. Dr. Dr. Daniel J. Strauss, Dr. Delb and Farah Corona

for their particular guidance. Without the continued support and interest of these

individuals, this thesis would not have been as complete as what you can see in front of

you.

In particular appreciation is due to En. Najeb Jamaludin, En. Zamri Mohd Zin,

En. Yusman Nawazir and others who have provide assistance at various occasions. Their

views were useful indeed in completing this project. In addition, there were Ear, Nose &

Throat (ENT) Specialists and Audiologists who have assisted me in providing

information in this research. Unfortunately, it is not possible to list all of them in this

limited space. The information they contributed have enriched my understanding and

thoughts.

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ABSTRACT

Hearing screening is an essential test to detect hearing ability of someone. A

good hearing ability is absolutely necessary for a normal speech development. In cases

with pronounced hearing loss even no speech ability will develop at all causing serious

communication problems and impaired intellectual and emotional development.

Auditory brainstem response is a well known method that has been used on detection of

hearing problem. An alternative method was also introduced in this thesis in detecting

the hearing loss problem. Evoked potentials are used because they can indicate problem

along nerve pathways that are too subtle to show up during neurologic examination or to

be noticed by the person. This description may not be visible on magnetic resonance

imaging test. This study proposes methods of identifying hearing loss based on

continuous wavelet transforms (CWT) and instantaneous energy (IE). Study showed that

the IE performed better than the CWT with the sensitivity of 0.88 and specificity of 0.81

compared to the CWT with the sensitivity of 0.63 and specificity of 0.83. Significance of

the results is 0.42.This experiments result can be used as a basis to improve methods of

detection hearing loss.

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ABSTRAK

Ujian pendengaran merupakan satu ujian yang penting bagi mengesan keupayaan

pendengaran seseorang. Keupayaan pendengaran yang baik sangat perlu untuk

pembangunan pertuturan yang normal. Dalam kes - kes kehilangan pendengaran,

keupayaan pertuturan juga tidak dapat dibangunkan yang mana menyebabkan masalah

komunikasi yang serius dan juga ketidakseimbangan pembangunan intelektual dan

emosi. Auditori refleks batang otak merupakan kaedah yang sering kali digunakan bagi

mengesan masalah pendengaran. Keupayaan rangsang digunakan kerana ia boleh

mengesan masalah sepanjang lorongan saraf yang terlalu halus untuk dilihat semasa

pemeriksaan neurologi atau dikesan oleh seseorang dengan mata kasar. Masalah

sepanjang lorongan saraf ini mungkin tidak dapat dilihat melalui pengimejan resonans

magnetik. Dalam kajian ini kaedah mengenalpasti gangguan pendengaran berdasarkan

transformasi gelombang selanjar (CWT) dan tenaga serta merta (IE) telah dicadangkan.

Penyelidikan menunjukkan bahawa IE lebih baik daripada CWT dengan tahap kepekaan

0.88 dan kespesifikan 0.81 berbanding CWT dengan tahap kepekaan 0.63 dan

kespesifikan 0.83. Keputusan ekperimen ini boleh digunakan sebagai asas untuk

meningkatkan kaedah pengesanan kehilangan pendengaran.

vii

TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF SYMBOLS xiii

LIST OF ABBREVIATIONS xv

LIST OF APPENDICES xvii

1 INTRODUCTION

1.1 Introduction 1

1.2 Problem statement 2

1.3 Objectives of the Research 3

1.4 Scope of Research 4

1.5 Contribution of the Thesis 5

1.6 Outline of Thesis 5

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2 LITERATURE REVIEW

2.1 Introduction 7

2.2 Hearing Loss 8

2.2.1 Types of Hearing Loss 9

2.2.2 Hearing Loss Factors 9

2.3 Hearing Screening 10

2.3.1 Hearing Screening Tools 10

2.4 Digital Signal Processing Technique 13

2.4.1 Fourier Transform 13

2.4.2 Averaging Technique 14

2.4.3 Instantaneous Energy 16

2.4.4 Wavelet Transform 17

2.5 Summary 19

3 HEARING SYSTEM

3.1 Introduction 21

3.2 Human Ear 22

3.2.1 Outer Ear 22

3.2.2 Middle Ear 22

3.2.3 Inner Ear 23

3.3 Auditory Nervous System 27

3.4 Human Brain 28

3.4.1 Brainstem 28

3.5 Evoked Potential 30

3.5.1 Electroencephalography 32

3.5.2 Auditory Brainstem Response 34

3.6 Summary 37

4 DATA COLLECTION

4.1 Introduction 38

4.2 ABR Recording 38

4.2.1 Subject and Environment Description 39

4.2.2 Electrodes 39

ix

4.2.3 Stimulus 43

4.2.4 Hardware 45

4.3 Data acquisition 48

4.4 Summary 49

5 DATA ANALYSIS

5.1 Introduction 50

5.2 Averaging Technique 50

5.3 Continuous Wavelet Technique 52

5.3.1 Preprocessing 54

5.3.2 Wave V Detection 55

5.4 Instantaneous Energy Technique 57

5.4.1 Preprocessing 58

5.4.2 Wave V Detection 58

5.5 Sensitivity and Specificity 59

5.6 Summary 61

6 RESULT AND DISCUSSION

6.1 Introduction 62

6.2 Averaging Technique 62

6.3 CWT Technique 69

6.4 IE Technique 75

6.5 Performance Analysis 80

6.6 Summary 82

7 CONCLUSIONS AND RECOMMENDATIONS

7.1 Conclusions 83

7.2 Recommendations 84

REFERENCES 87

Appendices 97-101

x

LIST OF TABLES

TABLE NO. TITLE PAGE

2.1 Hearing loss ranking and its corresponding decibel

ranges

8

2.2 Screening tools versus age level 12

4.1 Electrodes configurations 40

4.2 Electrodes configuration used by other researchers 41

4.3 Parameter setting that had been used by other

researchers

44

5.1 Mneumonic device for calculate sensitivity and

specificity

60

6 1 CWT experiment results on hearing loss persons. 73

6.2.1 CWT experiment results on normal persons 74

6.2.2 CWT experiment results on normal persons 75

6.3.1 IE experiment results on normal persons 78

6.3.2 IE experiment results on normal persons 79

6.4 IE experiment results on hearing loss persons 79

6.5 Sensitivity and specificity of CWT technique 81

6.6 Sensitivity and specificity of IE technique 81

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LIST OF FIGURES

FIGURE NO. TITLE PAGE

3.1 Anatomy of the human ear. From Wikipedia site 24

3.2 Details of ossicles. From webschoolsolutions site 25

3.3 Cochlea-cross sections. From Wikipedia site 25

3.4 Details of human ear anatomy. From Park Avenue

Acoustics site

26

3.5 Human brain structure .(Noback, The Human

Nervous System, 4th ed., McGraw-Hill, 1991)

29

3.6 Typical set of EEG signals (Adopted from Sanei

and Chambers, 2007)

33

3.7 Human auditory pathways. (Netter,2003) 34

3.8 Human auditory pathways and the correlation with

the ABR signal (Courtesy of Grass Telefactor, an

Astro-Med. Inc. Product Group, West Warwick,

RI.)

35

4.1 Electrodes that were used in the experiment 39

4.2 Types of recording (a) ipsilateral (b) contralateral 40

4.3 Electrodes positions on the scalp 42

4.4 Stimulus (a) click (b) tone burst (c) chirp 43

4.5 Trigger box 45

xii

4.6 gUSBamp biosignal amplifier 46

4.7 Programmable attenuator 47

4.8 Hardware configuration 47

4.9 Matlab model configuration 48

5.1 Signal segmentation 52

5.2 Time and frequency resolution cells for wavelet 54

5.3 Continuous wavelet of ABR signal 57

5.4 Color code of CWT contour 57

5.5 Instantaneous Energy of ABR signal 59

6.1 Power spectrum of raw signal 63

6.2 Comparison between raw signal and averaged

signal of 2000 sweeps

63

6.3 Power Spectrum; (a) 1000 (b) 800 (c) 625 (d) 500

sweeps

64

6.4 Power Spectrum; (a) 250 (b) 125 (c) 100 (d) 80 (e)

50 (f) 40 (g) 20 (h) 10 sweeps

65

6.5 The ABR averaged signal and its power spectrum 66

6.6 ABR waveform 68

6.7 ABR waveform of various sweeps 68

6.8 (a) Averaged signal (b) CWT of 1000 sweeps

averaged signal

70

6.9 (a) Averaged signal (b) CWT of 10 sweeps

averaged signal

71

6.10 Abnormal; (a) Averaged signal (b) CWT of 10

sweeps averaged signal

72

6.11 Normal: (a) Averaged signal (b) IE of 1000 sweeps

averaged signal

76

6.12 Abnormal: (a) Averaged signal (b) IE of 1000

sweeps averaged signal

77

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LIST OF SYMBOLS

dBnHL - Decibel normal hearing level

μV - microvolt

Ag-AgCl - Argentum-argentum cloride

k - kilo

� - Ohm

A1 - Mastoid left

A2 - Mastoid right

Cz - Vertex

Hz - Hertz

Fz - Forehead

dB - Decibel

μs - microsecond

dB SL - Decibel sensation level

dB peSPL - Decibel peak equivalent sound pressure level

ms - millisecond

s - second

- translation

� - wavelet transform

� - integral

� - Square root

xiii

t - time

- scale

� - summation

xv

LIST OF ABBREVIATIONS

ABR - Auditory brainstem response

AC - Alternating current

AEP - Auditory evoked potential

ASSR - Auditory steady state responses

BAEP - Brainstem auditory evoked potentials

CD - Compact disk

CNR - Contrast to noise ratio

CT - Computed tomography

CWT - Continuous wavelet transform

DPOAE - Distortion product otoacoustic emissions

DSP Digital signal processing

DWT - Discrete wavelet transform

ECG - Electrocardiography

EEG - Electroencephalography

EMG - Electromyography

EMI Electro-magnetic interferences

EOAE - Evoked otoacoustic emissions

EP - Evoked potentials

ERP - Event related potential

FFT - Fast Fourier transform

xv

gPAH - Guger programmable attenuator headphone buffer

gTec - Guger Technology

gUSBamp - Guger USB amplifier

g.Zcheck - Guger impedance check

ICU - Intensive care units

IE - Instantaneous energy

LED - Light emmiting diode

MRI - Magnetic resonance imaging

NICU - Neonatal intensive care units

OAE - Otoacoustic emissions

OAFCCD - Ontario association for families of children with

communication disorders

OR - Operating rooms

SEP - Somatosensory evoked potentials

TEOAE - Transient evoked otoacoustic emissions

USB - Universal serial bus

UTM - Universiti Teknologi Malaysia

VEP - Visual evoked potentials

WACFM - Weighted averaging based on criterion function

minimization

CHAPTER 1

INTRODUCTION

1.1 Introduction

Hearing screening is an essential test to detect hearing ability of someone. It

is one of the most important recommendations in modern pediatric audiology. A

good hearing ability is absolutely necessary for a normal speech development. In

cases with pronounced hearing loss even no speech ability will develop at all causing

serious communication problems and impaired intellectual and emotional

development. Many methods have been used as hearing screening tools. One of the

popular screening tools is auditory brainstem response (ABR) machine (Satoshi et

al., 2003; Bradley and Wilson, 2004). There are also some other hearing screening

tools such as transient evoked otoacoustic emissions (TEOAE), distortion product

otoacoustic emissions (DPOAE), pure tone audiometry, tympanometry and auditory

steady state responses (ASSR) (Satoshi et al., 2003; McWilliams, 2008; Swanepoel

et al., 2004).

Nowadays, hearing screening becomes important. There are needs to

implement hearing screening in every hospital. However, the time consuming

problem for the existing equipment have caused difficulties to implement hearing

2

screening. Recently, many researchers try to come out with new approach to improve

the hearing screening system.

1.2 Problem Statement

Several types of hearing screening programs have been established so far to

detect the hearing loss as early as possible (Helfand et al., 2001; Delb, 2002; Delb,

2003). The technical methods used in these programs include otoacoustic emissions

(OAE, sound responses that are emitted from the ear) and auditory evoked responses

or ABR (responses in the electroencephalography that are evoked by an auditory

stimulus).

There are two types of OAE screening techniques, TEOAE and DPOAE

(Helfand et al. 2001; Delb, 2003; Plinkert and Delb, 2001; Delb et al., 1999; Delb et

al., 2004). TEOAE are generated in response to clicks while DPOAE are a response

to tones. Both stimuli are presented via lightweight ear canal probes. A microphone

picks up the signal, and multiple responses are averaged to get a reproducible

waveform. This test can be carried out at the bedside and a pass or fail response is

recorded. TEOAE measurements are more commonly used for screening whereas

DPOAE are still a subject of research (Delb et al., 1999). The absence of TEOAE

indicates that the inner ear is not responding appropriately to sound. TEOAE can be

used for a hearing check but they do not allow for a quantification of the hearing loss

(Delb, 2003).

The ABR is an electrophysiological response in the electroencephalography

generated in the brainstem in response to auditory signals such as clicks or chirps.

The stimulus is delivered via earphones or an inserted ear probe, and scalp electrodes

are used to obtain the signals. Detection of wave V in the ABR measurements is the

3

most reliable objective diagnosis and quantification of hearing loss (Delb, 2003;

Wicke et al., 1978; Woodworth et al., 1983; Mason and Adams, 1984; Peters, 1986;

Shangkai and Loew, 1986). This method has a higher specificity as the TEOAE

measurement and it can also be used for the detection of the hearing threshold, i.e.,

the quantification of the hearing loss.

However, due to a poor signal-to-noise ratio, 2000 to 4000 sweeps have to be

averaged to obtain a meaningful, visually noticeable signal at a particular stimulation

level (the exact number depends on the number of artifacts produced). As such large-

scale averaged signals are used in the conventional visual analysis; they are also

commonly used in computational scheme, although, for a machine other data

representations might be more appropriate (Strauss et al., 2004). Using the currently

available devices, this takes approximately 2 to 4 minutes to get the result for one

stimulation level, e.g., (Meier et al., 2004) where it was not possible to obtain a

reliable response in less than even 4 to 5 minutes. This measurement time requires a

state of spontaneous sleep or strong sedation. Therefore, the needs to design a faster

screening tool become important.

1.3 Objectives of the Research

The main objective of this research is to use signal processing theory to

improve the detection of wave V with reduced number of sweeps. In order to

achieve the main objective, several sub-objectives are addressed in this thesis as

following:

(1) To apply averaging technique in detecting the wave V signal for

abnormalities of hearing impairment.

4

(2) To apply Fourier transforms to analyze the power spectrum on

different sweeps or clicks.

(3) To apply continuous wavelet transforms to detect abnormalities of

hearing impairment.

(4) To apply instantaneous energy to detect abnormalities of hearing

impairment.

1.4 Scope of Research

The scopes of research are limited to the following issues:

� The research is focus on real ABR signal. The simulated signal is not

included in this research. Real ABR signal is original ABR signal recorded

from patient, while simulated signal is generated by machine known as ABR

signal simulator. Analysis and features extraction based on simulated signal

are not reliable. Real signal are largely interfered by many factors such as

background noise, patients’ movements and age.

� The real ABR signals are collected at out-patient clinic at Pusat Kesihatan

Universiti Teknologi Malaysia (UTM) and Pusat Kejuruteraan Bioperubatan,

Fakulti Bioperubatan dan Sains Kesihatan, UTM.

� The patients’ ages are from eight to thirty years old.

5

� This research is limited to data analysis based on ipsilateral recording.

� This research focused on the averaging technique, continuous wavelet

transforms (CWT) and instantaneous energy (IE) to detect abnormalities of

hearing impairment and this research used Fourier transform to analyze the

power spectrum on different sweeps or clicks.

1.5 Contribution of the Thesis

In this research, there are two different techniques have been developed based

on signal analysis techniques which are IE and CWT used as marker in order to

detect wave V. The main contributions of this research is to see whether signal

processing theory can be an alternative approach to determine hearing impairment

compared to the traditional approach of averaging. The CWT and IE approach in this

thesis do provide a primary result to further the work in this area.

1.6 Outline of the Thesis

This thesis is organized into six chapters. The current chapter describes the

introduction of this research, the background and problems of this research as well as

the objectives, scopes and contributions of this research.

Chapter 2 describes literature review on hearing loss and hearing screening.

Various types of hearing loss are described; conductive hearing loss and

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sensorineural hearing loss. The hearing loss factors are also discussed in this chapter.

Various types of hearing screening tools and the digital signal processing techniques

used on analyzing auditory signals are discussed.

Chapter 3 describes an overview of human ear, auditory nervous system,

human brain and the evoked potential. The human ear from the outer to the inner ear

had been discussed. The discussion also covered sound propagation from the outer

ear to the brain. The evoked potential is also discussed in this chapter.

Chapter 4 describes the methodology of the research in detail. The features of

the subjects and environment are described in this chapter. This chapter covered the

discussion on the electrodes configurations that had been used in this study. The

stimulus, hardware as well as data acquisition are also discussed in this chapter.

Chapter 5 describes the analysis techniques of the research in detail. The most

popular method in ABR research, the averaging technique is discussed in this

chapter. The technique is used to extract the ABR wave signal from the recorded

brain signal. The wave V detection techniques that had been used in this research are

also discussed.

Chapter 6 delivers the results of the experiments carried out. Several

experiments were carried out, based on averaging, continuous wavelet transform and

instantaneous energy techniques to find out a way to establish fast detection of wave

V in order to test hearing problems.

Chapter 7, the final chapter, summaries the research findings and some

suggestions for future work which might be useful for further development and

improvement are written in this chapter.