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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
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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.
v
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.
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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
xi
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
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.