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CHAPTER I

INTRODUCTION

1.1 The problems

Auditory Brainstem Response (ABR) (Hall, 1992) is one of the auditory evoked

potentials obtained from the brain electrical activity through stimulation by an acoustic

stimulation. It represents the neural activity from several anatomical structures within the

peripheral and central auditory nervous system. ABR is composed of several voltage

deflections occurring within the first 15 ms after stimulus onset (Katz, 2002) and consist

of 5 to 7 peaks or waves that labeled using Roman numerals (Hood, 1998).

ABR test offer several advantages such as assisting in identifying neurological

abnormalities in the eight cranial nerve and auditory pathways of brainstem. Besides,

ABR is also useful to estimate the hearing sensitivity of patients who cannot give valid or

reliable hearing threshold using behavioral methods (Hood, 1998).

Despite its advantages, the ABR has one obvious limitation. The ABR is a time

consuming procedure because several number of ABR signals need to be averaged and

collected in order to eliminate noise from other related activities. The process is called

signal averaging function to improve the ABR signal to noise ratio (SNR) thus improve

the likehood of ABR detection.

One of the possible solutions to reduce ABR acquisition time is by using high

stimulus repetition rate. High stimulus rate cause time between presentations of stimuli

equals to limit of ABR conventional averaging responses about 20 ms. However at rates

faster than limit, conventional averaging ABR response will overlap and interfere to one

another and causing distorted and useless final averaged (Eysholdt & Schreiner, 1982).

Hence, Maximum Length Sequences (MLS) paradigm was introduced in order to

increase the stimulus repetition rate that cannot be achieved using conventional

averaging. MLS is a pseudorandom binary sequence that allow for each subsequent

stimulus to be presented before the response of previous stimulus has completed. It works

by process of deconvolution where response recorded using MLS stimulation can be

extracted from the multiply overlapped combination of responses that will be generated

by the stimulus sequence.

Previous studies showed that high stimulus repetition rate through MLS generally

can improve the ABR testing time compared to the conventional stimulus rate. However,

by increasing the stimulus rate neural fatigue may cause poorer signal to noise ratio

(SNR). High stimulus repetition rate with poorer SNR may lead to difficulty for

Audiologist to detect ABR waveform with poor morphology. Thus, presenting the

stimulus very quickly does not turn out to be that efficient as the clinician need to present

more stimulus to get better SNR (Lasky R.E., Shi Y., & Hecox K.E., 1992; Marsh R.R.,

1992; Bell S.L., Allen R., & Lutman M.E., 2000).

However most of the literatures used an ideal SNR as a baseline instead of

minimal SNR to conclude that the high stimulus repetition rates through MLS paradigm

is not a beneficial tool to improve ABR testing time. In reality, Audiologist detects the

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ABR waves based on its visibility rather than looking at the SNR value. Therefore there

is a possibility that MLS can improve the ABR testing time by looking to other

perspective such as Audiologist detection instead of looking at SNR.

1.2 Contributions of the study to the body of knowledge

This study contributed to the body of knowledge in audiology field specifically in

auditory electrophysiology part involving ABR test using MLS technique. Currently,

there is no study was conducted concerning from linear and non linear MLS with

subjective detection.

This study is the first report on the following areas:

1. In measuring the improvement of MLS testing time in infants.

2. Improvement in testing time provided by new non linear algorithm for infant.

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CHAPTER II

LITERATURE REVIEW

2.1 Description of Auditory Brainstem Response

Auditory Brainstem Response (ABR) is an evoked responses occur within the

first 15 ms after stimulus acoustical or electrical stimulation consist of a series of 5 to 7

peaks or waves that represent neural activity at several anatomical sites (Hood,1998). The

ABR response is recorded by the placement of the electrode that is attached on specific

part of the head. ABR wave’s series are labeled based on the Roman numeral from I till

VII. In general, wave I represent the neural activity of distal or peripheral portion of

auditory nerve (Hood, 1998; Hall, 1992).Wave II is generated by the neural activity from

the proximal eight nerves as it enters the brainstem (Hood, 1998). However due to the

factor of age, wave II maybe absent in recording children as shorter eight nerve length

(Hall, 1992). Meanwhile, wave III is contributed by the neurons in the cochlear nucleus

and possibly other fibers that entering the cochlear nucleus (Hood, 1998). For wave IV,

studies suggest that the third-order neurons likely involved the superior olivary complex.

Other contributions of wave IV are the fibers at the area of cochlear nucleus and the

nucleus of the lateral lemniscus (Hood, 1998). Wave V representing the neural activity in

the lateral lemniscus and/or inferior colliculus (Hood, 1998).

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2.2 Stimulus factor

Both latency and amplitude of the early evoked potentials can be affected by

manipulating the stimulus. Thus, it is necessary to obtain the best possible response and

correctly interpret test result by using an optimal stimulus parameter.

2.2.1 Type of stimulus

There are various types of stimulus used in ABR recording. ABR is best elicited

by stimulus with brief onset due to its high dependency to the neural synchrony.

Therefore, clicks are favored as a stimulus because it nature of abrupt onset and

broadband spectrum that can elicit good neural synchrony at broader region of

frequencies in basilar membrane (BM) and make it produce a robust response when

measuring from the scalp (Katz, 2002). The neural synchrony occur in BM is based on

the cochlear onset neuron in auditory nerve. Onset chopper (Oc) neurons have very

specialized membrane properties and precise temporal processing. Hence, Oc neurons

exhibit a wide dynamic range and robust firing to broadband stimuli and it suggested that

they may have a role involved in signal processing in noise and in the detection of

spectral cues related to sound localization (Mulders et al., 2007).

Tone burst is another type of stimulus with brief onset that has specific frequency

where it activates the restricted part of the basilar membrane in the cochlea by using

certain stimulus envelope. However, due to its fast rise and fall time it has high tendency

to have ‘spectral splatter’ effect especially in low frequency tone burst that causing of

unwanted contribution from high frequency region of the BM (Hall, 1992).

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2.2.2 Stimulus polarity

Polarity is referred to the direction or movement of transducer diaphragm in

relation to the pressure wave generating at tympanic membrane. Condensation,

rarefaction and alternating are three categories of stimulus polarity. Condensation

polarity occurs when movement of transducer’s diaphragm is towards the tympanic

membrane producing positive direction of sound wave, whereas movement of transducer

away from tympanic membrane is called rarefaction polarity (negative direction).

Alternating polarity is switching mode between both two polarities (Hall, 1992).

Garga et al. (1991) reported that polarity will affect latencies for stimulus

conditions response dominated by low frequency energy whereas at the high frequency

energy there are no such affect were observed. These finding are completely consistent

with behavior of individual hair cells and neurons within the auditory pathway true for

normal hearing. According to Fowler et al. (2002), rarefaction clicks are expected to

produce shorter latencies and greater amplitude for ABR compared to condensation. In

contrast, Stockard et al. (1979) noted that 15% to 30% of normal subjects may show the

opposite polarity pattern where shorter latency values for condensation than for

rarefaction clicks (Hall, 1992).

Even though there are arguments whether to use rarefaction or condensation

stimuli. Study showed wave V amplitude tends to be larger in response to condensation

stimuli but there is no significant latency difference in wave V latency to rarefaction or

condensation stimuli in normal hearing individuals (Hood, 1998). This study used

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condensation stimuli. It is based on presence or absence of wave V with subjective

detection to identify the time.

2.2.3 Stimulus intensity

The site of ABR generation along the basilar membrane is related to intensity. In

general principle, ABR latency decreases and amplitude increases with greater stimulus

intensity. There are two reasons behind it. Firstly, it is due to progressively faster rising

generator potential within the cochlea causing similarly faster development of excitatory

postsynaptic potentials (EPSPs). Besides, shorter travel time from the oval window to

basal end occur if use high stimulus level resulting shorter latency of ABR waveform

(Hall, 1992). This was supported by Picton et al. (1981) where high stimulus level

between 75 dBnHL to 95 dBnHL may activate the basal part and then moves

progressively toward apex for lower intensity level when decrease from 70 to 80 dBnHL

(Hall, 1992). Only wave V is clearly visible whereas the earlier component tends to

become indistinguishable at 35 dBnHL (Hood, 1998).

2.2.4 Stimulus rate

Stimulus rate is defined as number of stimulus presented in one seconds. Rate

need to be presented more than the duration of ABR which are more than 15 milliseconds

(Hall, 1992). In general principle, stimulus repetition rates up to approximately 20 clicks

per seconds have little effect on the ABR. However, above that rate the latency will

increase and amplitude decreases (Burkard et al., 2007; Hood, 1998).

Each wave component has different effect of ABR amplitude toward stimulus

rate. Wave V amplitude show less decrement with increase of rate from relatively slow

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rate (8 to 33/sec) to rapid rate (80 to 90/sec) than the earlier component. At higher rate,

amplitude for wave V typically less than about 10% to 30% from the amplitude of slower

rate while wave I amplitude is less about 50% (Hall, 1992). Thus, less testing time

achieved when using higher stimulus rate that permit large collection of data for clinical

threshold estimation. Besides, by increasing repetition rate it will cause latencies shift due

to adaptation of neuron which does not have enough time to recover (Don et al., 1977;

Pratt & Sohmer, 1976).

Stimulus rate may have different effect based on age. Prolongation of ABR

latency is more prominent for younger children (under age of 18 months) than adult

(Stockard et al., 1977). Consequently, the infant ABR is characterized by delayed

interwave intervals. For instance, an interwave interval for normal newborn in average is

about 5 ms compared to 4 ms in adult. In anatomy and physiology of central nervous

system (CNS), delayed interwave latencies is due to incomplete nerve fiber

myelinization, reduced axon diameter and immature synaptic functioning which cause

prolonged neural transmission in younger subjects (Hall, 1992).

Whilst high rate may affect the quality of ABR waveforms, it is reported that high

stimulus rate is useful to determine site of lesion testing (Hall, 1992) as well as the ability

to reduce ABR acquisition time (Eysholdt & Schreiner, 1982). However, high stimulus

rate cause time between presentations of stimuli equals to limit of ABR conventional

averaging responses about 20 ms. Thus, at rates faster than limit, responses will overlap

and interfere to one another and causing distorted and useless final averaging.

Interactions between responses also take place if high stimulus rate is applied to second-

order or third-order neuron (Burkard et al., 2007).

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In conventional ABR the presentation of click stimulus can only take place when

response to the previous stimulus is over (Eysholdt & Schreiner, 1982). If stimulus is

being presented before the response of previous stimulus is obtained, those ABR waves

will be overlapped to each other causing ABR signal will be deteriorated. This could be

problematic for audiologist to interpret ABR waveforms. Although there is some

possibility reduction of ABR amplitude and increase wave latencies, those effect does not

hinder the ability for audiologist to detect wave V ABR.

2.3 Maximum Length Sequences (MLS)

Maximum Length Sequences (MLS) is pseudorandom binary sequences first

introduced to check feasibility of obtaining response and speculated that it will lead to

improvement of recording technique with reduce time taken to find average (Eysholdt &

Schreiner, 1982). It works by process of deconvolution where response recorded using

MLS stimulation can be extracted from the multiply overlapped combination of

responses that will be generated by the stimulus sequence. MLS can overcome several

problem occur when high stimulus rate was used.

Firstly, MLS has special mathematical properties which intervals between stimuli

vary in quasi-random fashion where ABR responses that overlap can be compensated

causing faster stimulus rate can be used. Hence, waveform obtained at lower rate from

conventional averaging can be extracted from MLS stimulation at high rates.

Secondly, MLS stimulation with proper decoding software can cause response

interactions of stimulus similar to the conventional response. Besides, MLS stimulation

also reveals nonlinear temporal interaction between responses of human auditory system

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(Shi & Hecox, 1991). A nonlinear interaction occurs between responses when the time

between presentations of stimuli is small and stimulus rate permitted by MLS technique

only. The properties of the nonlinear components differ from those of the conventional

component and there is preliminary evidence that they may provide a measure that is

more sensitive to pathology than the conventional component (Burkard et al., 2007).

Previous studies showed that high stimulus repetition rate through MLS generally

can improve the ABR testing time compared to the conventional stimulus rate via

different technique to identify ABR wave (Eysholdt & Schreiner, 1982; Leung et al.,

1998; Thornton & Slaven, 1993). The fixed number of sweeps technique use for MLS in

ABR wave detection theoretically can decreased test time by a factor of 8 in linear MLS

stimulation (Eysholdt & Schreiner, 1982). Same goes to the technique that used MLS

with SNR. The speed of test relative to the conventional rate of 33.3 cps, calculated using

the formula c2.k2. (r/r0) (Thornton & Slaven, 1993). This is the speed which the test can be

carried out when averaging to the same SNR and takes into account the reduction in wave

V amplitude seen with increasing rate and decreasing stimulus level. At linear MLS of

300 cps the relative speed of test is greater than all stimulus repetition rates level in

conventional ABR and MLS. As the rate increases and the level decreases, the relative

speed of test also decreases, until by 1000 cps testing to the same SNR takes longer than

the conventional case at all stimulus levels. Thus, the effective test time using MLS with

SNR is between 200 cps till 300 cps (Leung et. al., 1998).

According to Hall (1992) there is also statistical and clinically significant

relationship between rates of transient stimuli with behavioral auditory threshold. From a

stimulus rate of 5 cps to 80cps, threshold is enhanced by 5 dBpeSPL. This is due to large

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temporal summation of acoustic energy. However by increasing the stimulus repetition

rates up to 1000 cps, the ABR waves cause longer wave latencies and ABR waveform

amplitude reduced due to incomplete recovery of auditory system from previous and

continuous stimulation (Eysholdt & Schreiner, 1982; Burkard et al., 1991; Burkard et al.,

2007). However, changes are not the same for each wave component. Even though

amplitude for wave V has typically decreased about 10% to 30% relative from the

amplitude of slower rate; it is acceptable to use high repetition rates because of clear

wave V ABR morphology remains there.

Besides, MLS also feasible to test infant ear binaurally. According to Hood

(1998) study done to compare between standard ABR and MLS ABR at several

intensities for normal infant showed less than 5 minutes total test time needed for click

stimuli on both ears with the MLS technique.

Researchers also have been exploring the possible MLS applications in various

areas. In the study of ABR, it has been noticed that reliable ABR were produced

remarkably comparable to conventional ones in morphology (Burkard et al., 1991).

During recording ABR of premature infants by MLS, Weber & Roush (1993) found that

the clarity of ABR could be well-defined under a rate as high as 900 cps and the quality

of MLS ABR even better than conventional ABR especially in large noise environment.

It is suggested that MLS could be applied in newborn hearing screening. This suggestion

was verified by Jiang et al. (1999). Besides, they also employed MLS in asphyxiated

neonates and found that central auditory impairment of these neonates was more

detectable with MLS paradigm (Jiang et al., 2001)

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2.3.1 MLS limitations

Despite the advantages of MLS to reduce the ABR test time; there were

arguments that MLS ABR is intrinsically noisier than conventional ABR with equal

number of stimuli (Marsh, 1990; Burkard, 1991; Picton et al., 1992). Marsh (1992)

reported that for each MLS condition compared to conventional ABR, wave V amplitude

decreased more than the noise level supporting the argument of a reduced signal to noise

ratio (SNR). Thus, with a poor signal to noise ratio none of the MLS conditions was as

efficient as the conventional method. Besides, issues regarding low SNR obviously affect

ability to identify presence and reliability of response in ABR testing (Lasky, Perlman &

Hecox, 1992). Despite this, the quality of MLS ABR waveforms was reported to be better

than conventional ABR based on audiologist report even with poor SNR (Weber &

Roush, 1995). Three judges evaluated the quality of ABR responses and among fifty

newborns, 32% had more clearly defined ABR responses obtained with MLS compared

to conventional ABR.

Burkard (1991) noted that more number of MLS pulses must be presented in

order to achieve same SNR as the conventional response recorded at slower rate. The

number of additional pulse must be presented equal to amplitude of MLS response and

amplitude of conventional response (Lasky, Shi & Hecox, 1992).

There are several factors need to consider on how MLS allows greater rate than

100 cps might reduce the time required to obtain constant SNR response with application

of more number of MLS pulses. Firstly, the increased rate must more than offset the

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decrease in response amplitude. Thus, amplitude of the wave V must be reduced less than

a factor of 1.414 for each doubling in rate. This is assuming that SNR increases in

proportion to the square root of the number of sweeps. Secondly, there is a 3 dB loss in

SNR with use of cross correlation procedure. Basically, the cross correlation procedure

results in a summation of noise over almost twice as many events as the number of

stimulus presentations. Hence, this result in a loss of 3 dB in SNR and roughly twice as

many stimuli are necessary to recover this loss in SNR. Other than that, at very

sufficiently high rates the noise epochs are not truly independent. If these noise epochs

are partially correlated, SNR will not recover in proportion to the square root of the

number of sweeps but at some lesser value (Burkard et al., 2007). Lastly, although that is

not measurable in the ABR, it is unlikely that the ABR for each stimulus in the train is

identical. This is because the interstimulus interval is not constant in train. It is likely that

the ABR reaches an adapted state after a few stimuli. Based on Don et al. (1978) when

clicks are presented in trains the ABR adapts following 3 to 5 clicks and no further

changes in the ABR are noted for responses to additional clicks in the train. It maybe the

reason of MLS ABR looks like conventional ABR. However, it probably there is still

some recovery in the response if it is not deterministic which means presentation of each

stimulus is not similar.

Even though improvement in SNR depends on the response being the same for

each stimulus presentations, the nondeterministic nature of the ABR due to temporal jitter

in MLS stimulus presentation will also reduce the rate of SNR improvement across the

number of stimulus presentations. To date, no one has included all of those factors in

determining whether the MLS procedure allows collecting ABR more efficiently.

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2.4 Waveform detection

Waveform detection is referring to the time taken to determine whether an ABR

waveform was present or absent whereas waveform analysis is referring to the time taken

to both detect and analysis the ABR waveform. There are two methods that can be used

for ABR detection which are objective and audiologist detection (Ahmad et al., 2008).

2.4.1 Audiologist detection

Audiologist detection is a technique where the presence of ABR waveform is

made by clinician upon visual inspection of the recorded waveforms under favourable

conditions (Arnold, 1985; Don, Elberling & Waring, 1984). The criteria of visual

judgment includes clear ABR component in the waveform as well as waveform

repeatability. By using audiologist detection, human operator has full authority over the

waveform interpretation. Thus, all relevant considerations must be taken into account

before making any diagnosis for each case. Nevertheless, at least two problems occur

with audiologist detection. Firstly, tester will take a longer time to observe and visualize

many waveforms for each patient when performing this technique (Hall, 1992) as well as

the possibility of error rises when too many waveforms must be interpreted within a short

period of time. Secondly, there is the possibility of mis-labelling and errors during the

waveform interpretation, especially with persons who have less experience at interpreting

an ABR waveform (Ahmad et al., 2008).Based on Elberling & Don (2007), the methods

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used for audiologist detection can be divided into four categories which are response

judgment made by one observer, response replication, response tracking, and response

judgment by multiple observers.

2.4.1.1 Response judgment made by one observer

In this technique, human operator use his or her experience to interpret whether or

not there is an ABR based on the peaks and latency in the waveform, It usually applies to

condition where the ABR waves can be seen clearly at high intensity (more than 70

dBnHL) (Ahmad et al, 2008). This technique is considers fast because it only require

single run. However, large amount of noise sometimes produce peaks within the usual

latency of a normal ABR waveform which can contribute to the tendency for a false

positive result (Ahmad et al, 2008).

2.4.1.2 Response judgment by multiple observers

In this technique, more than one observer will interpret the ABR response which

aims to reduce the errors made when a single observer is used. The validity for this

technique is based on the assumption that all observers are independent (Ahmad et al,

2008). However, it is not always true; in some cases where both observers have similar

training procedure for ABR waveform interpretation there is a possibility that both of

them could make a false positive interpretation or a similar judgment even if both

observers are independent (Ahmad et al, 2008). The reliability made by Kappa test also

showed that there was considerable disagreement between judges in their decisions in

determining the presence of ABR. Thus, subjective detection by clinician may introduce

bias and inaccurate ABR interpretation (Arnold, 1985).

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2.4.1.3 Response replication

In this technique, two ABR averages are recorded and overlayed on each other.

The degree of overlap between the two traces is observed and compared. If there is

consistent overlap between those two traces particularly of peaks occurring at expected

latencies and amplitudes, it is more likely that an ABR is present in the waveforms. The

principle in this technique is that the ABR will replicate and the random noise will

fluctuate over time. However, it might be a problem if the noise in two averaged differs

in large amount causing poorer replication and difficult interpretation. Besides, this

approach takes time because it requires extra test runs to acquire for each original and

repeated waveform. (Ahmad et al, 2008).

2.4.1.4 Response tracking

In response tracking, the waveforms are observed as a function of the stimulus

intensity usually done either by one or multiple observers. This technique allow observer

to review the response based on the expected changes in the waveforms, such as a

decrease in amplitude and an increase in the latency, while he or she decreases the

stimulus intensity. For instance, clinician may start testing at where the ABR peaks are

often clearly observed (80dBnHL), and then reduce the intensity and track the expected

changes in the Wave V of each new waveform. When no peak was obtained at certain

intensity testing can be stopped. Clinician need to repeat the waveforms at any intensity

to ensure his or her judgment is true. By using high intensity waveforms it can be

template for the low intensity waveforms by observing the changes in amplitude and

latency. However, problems with this technique include the effects of noise on the

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expected changes in the ABR waveform, and the time required to complete the multiple

recording runs (Ahmad et al, 2008).

2.5 Conclusion

Although MLS have limitation which is intrinsically noisier than conventional

ABR. It can be solved out by using more number of MLS pulses presented in one

seconds in order to achieve same SNR as the conventional response recorded at slower

rate. In previous study, there are many techniques can be applied for MLS ABR to reduce

the test time in detection of ABR wave whether by fixed number of sweeps or SNR.

However, all of those study only concern regarding the conventional ABR and linear

MLS. Therefore, this current study investigated different technique which is comparing

the ability of linear and nonlinear MLS with combination of audiologist detection with

the aim to decrease testing time in infant hearing screening.

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2.6 General objective

The purpose of this study is to investigate the improvement of ABR testing time

between high stimulus repetition rates and slow stimulus repetition rates with

combination of audiologist detection (waveform analysis).

2.6.1 Specific objectives

i. To compare the time for detection of ABR waveform between standard

click and linear MLS with audiologist detection.

ii. To compare the time for detection of ABR waveform between linear MLS

and non linear MLS with audiologist detection.

iii. To compare the time for detection of ABR waveform between standard

click and non linear MLS with audiologist detection.

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Chapter III

METHODOLOGY

3.1 Study design

Quasi-experimental design was used for this research. This study design involves

selecting groups which variable is tested without any random pre selection process. For

example, there is no randomization in term of pre-determined effects of gender, age and

hearing thresholds on subject performance. After the selection, experiment was preceded

in a similar ways to any other experiment where variable being compared between

different groups (Shuttleworth M., 2008). In this study, the time to detect ABR waveform

using different stimulus repetition rate applied to the same subject will be investigated.

The data collected in this study were obtained from the same subject who are exposed to

different stimulation or often called as repeated measures analysis. It is useful because

individual differences can be eliminated since the data was collected from the same

subject under repeated conditions. Besides, sample is not divided between conditions

such as gender, age and study population. Hence, inferential testing become more

powerful (Choudhury A., 2009).

3.2 Equipment/Software

Compaq Presario V3000

Matrix Laboratory (MATLAB) software

Statistical Package for Social Sciences (SPSS) Version 16.0 software.

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3.3 Study place

International Islamic University Malaysia (IIUM), Kuantan, Pahang Campus.

3.4 Study population

3.4.1 Population

Subject of this study was sampled from newborn population involved in Newborn

Hearing Screening at Southern East of Queensland, Australia. This study was cleared by

Matter Health Services Human Research Ethics Committee (Clearance number: 770_mc)

and clear by ethics committee of School of Health and Rehabilitation Sciences University

of Queensland (Protocol number: A517/..kr). Besides, Kulliyyah of Medicine (KOM)

Ethics Committee from International Islamic University Malaysia (IIUM) also approved

the ethics application for this study

3.4.2 Subject selection criteria

In previous study, there are 144 subjects were involved. From the overall data, not

all of data contain good and clear ABR waveform. Thus, 20 out of 144 subjects were

selected based on criteria that had been met. The criteria of data being selected were

based on clear ABR wave as well as waves are not contaminated by muscle artifact and

electroencephalogram (EEG). These criteria were set in order to prevent from faulty

result and test validity and reliability.

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3.4.3 Subject description

20 subjects were newborns data that pass Neonatal Hearing Screening at Southern

East of Queensland, Australia. From that, there are 15 males and 5 females involved in

this recent offline data analysis.

3.5 Sampling technique

No sampling was done since the data was already collected from previous

Dzulkarnain A.A., (2008). However the data collected from this study was sampled using

convenience sampling technique. In conventional sampling technique the researcher

recruited their subject based on their availability. During the data collection, researcher

recruited the subject by approaching their primary care giver whether they are interested

to be a part of the research subject’s on top of their compulsory Newborn Hearing

Screening using AABR. The actual AABR test procedure was summarized in Appendix

1.1

3.6 Procedures

1 Ahmad et al. (2008). The method to improve maximum length sequences auditory brainstem response analysis and

detection time. Audio Neurotol, 13,

20

Since data has been collected from previous study, the aim of this study is to use

the same data for different offline analysis. It was conducted using custom code written

using Matrix Laboratory (MATLAB). The data is in the forms of binary M-files contains

of ABR waveform recorded at 35 dBnHL at six different stimulus repetition rates

(standard clicks: 33 & 90 clicks per second (cps), linear and nonlinear MLS: 180, 250,

500 and 833 cps). This MLS repetition rates were used because those rates represent

slightly higher rate, middle higher rate and extreme rate. However, this study used an

arbitrary rates rather than following previous literature repetition rates in order to see if

slight change to the typical rate numbers will give some effects. This further supported by

good result obtained previously (Ahmad Aidil, 2008). Therefore, the following

procedures were applied:

1. 20 data of subjects that had met the criteria were selected.

2. Then, case study was conducted in order to determine the best parameter to use in

term of type of averaging, type of artifact rejection, filter setting and comparison

setting. Hence, all criteria were finalized before the actual data analysis was

conducted. The result of case study used mean averaging, 15 μv for artifact

rejection, filter setting (low frequency cut filter 100Hz and high frequency cut

filter 5kHz) and comparison setting by elapsed time subplots.(See Appendix II)

3. MATLAB software is opened. Then, ABRpublish is entered. Once the browse

button appeared, Materdatafile folder was selected to search for subject number

that fulfills the criteria. Parameter settings from the case study were set first. Next,

data subjects of ABR wave were plotted from zero seconds to the last seconds of

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each recording for standard click (click 33cps and click 90cps) linear and

nonlinear MLS at different stimulus repetition rates (180cps, 250cps, 500cps and

833cps). After that, the time for ABR wave’s detection was determined by the

researcher. Those times to detection and ABR waves were given to an audiologist

to confirm the earliest time that an ABR can be detected for each stimulus

repetition rates.

3.7 Waveform detection criteria

There are widespread of technique in identifying ABR. In this study, a response

replication technique was used. In this technique, the area of overlapping between traces

and the degree of replication between traces are used as the criterion to detect the

presence of ABR waveforms. Firstly, the time detection of wave V is made by the

researcher. After that, all the data were saved and confirmed by an audiologist. Thus, for

the final data analysis, we used the time or data that was obtained from an audiologist.

The audiologist who confirmed the time to detection for ABR wave has more than 7

years experience in clinical and auditory electrophysiology field especially in ABR

3.7 Conclusion

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In overall, by using waveform detection criteria researcher need to figure out the

testing time between three groups of stimulus repetitions rates which are in standard click

(33cps and 90cps) as well as linear and non linear MLS (180cps, 250cps, 500cps and

833cps).

3.8 Data analysis

3.8.1 Variables

The main dependent variable in this study is the time to detection and the

independent variables are the ABR with various stimulus rate. The stimulus rate include

standard clicks is 33 and 90 clicks per seconds and both linear and non linear MLS at

180, 250, 500 and 833 clicks per seconds. The independent variables are something that

can be changed by experimenter in order to do the actual experiment. The independent

variable for this study is the type of stimulus and stimulus rate. The dependent variable is

the outcome of independent variables when it changes. In this study the dependent

variable is time taken to detect ABR waveform using subjective detection. Table 3.1

shows the summary of dependent and independent variables in this study.

Table 3.1 Summary of dependent and independent variables

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________________________________________________________________________Dependent variable Independent variable Types________________________________________________________________________Time taken to detect 1. Type of stimulus/algorithm Standard click, linear and ABR waveform nonlinear MLS

2. Types of stimulus repetition #Click 33 cps and 90 cps rates #Linear and nonlinear MLS

180cps#Linear and nonlinear MLS 250cps#Linear and nonlinear MLS 500cps#Linear and nonlinear MLS 833cps

________________________________________________________________________

3.8.2 Statistical analysis

All data in this study was analyzed using Statistical Package for Social Sciences

(SPSS) Version 16.0. In particular, Friedman test and Wilcoxon signed rank test (if

significant pair was found) was used as the statistical analysis for this study. This test is

used in order to compare median of the time taken for an Audiologist to detect the

presence of ABR waves at various different stimulus repetition rate (as stated in table

3.1). All tests were conducted at 95% confidence level.

24

CHAPTER IV

RESULT

4.1 Data analysis

For this analysis, parametric test (Repeated measure Anova) cannot be used since

the assumptions are not met. It is because sphericity and normality assumptions are not

met as well as convergence of equal variances. Hence, data was analyzed using

nonparametric tests (Friedman test) at 95% confidence level (as mentioned in section

3.8).

4.1.1 Friedman Test

For each of those three objectives, Friedman test and Wilcoxon Signed Rank test

(if significant different occur) was used to investigate the median testing time difference

between different stimulus repetition rates (standard click: 33cps and 90cps, linear and

novel non linear MLS: 180cps, 250cps, 500cps and 833cps) in combination with

subjective detection.

4.2 Objective 1: Comparison of ABR time detection of wave V between standard

click and linear MLS

Friedman test was carried out to compare the difference of median testing time

between standard click 33cps, 90 cps, linear MLS 180cps, 250cps, 500cps and 833cps.

There were no significant differences between different pairs of standard click rate and

25

standard MLS rate since p > 0.05 from the Friedman test . Table 4.1 shows the summary

of median, interquartile range (IQR) and results of Friedman test to compare the median

time to detection differences between standard click and linear MLS.

Table 4.1: Time between different stimulus rates in

standard click and linear MLS

Stimulus rate Median ± IQR Χ2 (df) p value

Click 90cps 3.00(2)

10.502 (5) 0.062

Click 33cps 4.00(2)

Mls 250cps 3.50(2)

Mls 180cps 3.00(2)

Mls 500cps 4.00(6)

Mls 833cps 4.00(10)

In general, result from table 4.1 shows there was no significant different in

median detection of time for ABR waveform recorded using standard click (33cps and

90cps) and linear MLS (180cps, 250cps, 500cps and 833cps) using subjective detection.

Figure 4.1 shows the median ± IQR at different stimulus repetition rates.

Figure 4.1: Median ± IQR at different stimulus repetition rates between

click and linear MLS

26

Median, interquartile range (IQR) at different stimulus repetition rates

(click & linear MLS)

012345

clic

k90

cps

clic

k33

cps

Line

ar25

0cps

Line

ar18

0cps

Line

ar50

0cps

Line

ar83

3cps

Different stimulus repetition rates (click & linear MLS) (click/s)

Med

ian

tim

e d

etec

tio

n (

s)

024681012

Inte

rqu

arti

le

ran

ge

(IQ

R)

Median time

IQR

4.3 Objective 2: Comparison of ABR time detection of wave V between standard

MLS and novel non linear MLS

Friedman test was carried out to compare the median difference in time to

detection between standard MLS and novel non linear (180cps, 250cps, 500cps, 833cps).

Table 4.2 showed the summary of median, interquartile range (IQR) and the results of

friedman test to compare the median differences between time detection of standard MLS

and novel non linear MLS. The results showed there was statistically significant

differences in time to detection at least one pair of standard MLS and novel non linear

MLS (p < 0.05 from the Friedman test). Bonferroni adjustment was calculated in order to

avoid Type 1 error (0.05/28=0.002). Thus, the new significance level is 0.002. Post hoc

test was done (Wilcoxon Signed-Rank test) (see table 4.2 and table 4.3). From 28 pairs,

only 1 pair showed median testing time difference which is the pair between MLS 180cps

27

and nonlinear MLS of 833cps (p < 0.002). In general, result for Objective 2 shows there

was no significant difference in median time to detection between linear MLS and

nonlinear MLS at the same rate or different rate with the exception for linear MLS of

180cps and nonlinear MLS of 833cps. Figure 4.2 shows the summary of median time

detection between linear and nonlinear MLS. Figures 4.3 shows the example of one data

of subject to detect ABR waveform time based on morphology of ABR and response

replication criteria according to linear and nonlinear MLS at different stimulus rates

180cps, 250cps, 500cps and 833cps.

Figure 4.2 Median ± IQR at different stimulus repetition rates of linear and nonlinear MLS

Table 4.2: Comparing time between different stimulus rates in

linear MLS and non linear MLS

Stimulus rate Median ± IQR χ2 (df) p value

Median ± IQR at different stimulus repetition rates(Linear and nonlinear MLS)

3 (2)3.5(2)

4(6) 4(10)4.5 (5)5(7)

3(6)

4(8)

0123456

180cps 250cps 500cps 833cps

Stimulus repetition rates ofLinear and nonlinear MLS (click/s)

Med

ian

tim

e

det

ecti

on

(s)

Linear MLS

Nonlinear MLS

28

Mls 250cps 3.50(2)

14.707 (7) 0.040

Mls 180cps 3.00(2)

Mls 500cps 4.00(6)

Mls 833cps 4.00(10)

Nonlinear 250cps 5.00(7)




Wilcoxon Signed Rank Test was conducted to check for significant different pair

Table 4.3: Different pair for stimulus repetition rates of

linear MLS and nonlinear MLS

Stimulus pair Z p value

Linear MLS 180cps and linear MLS 833cps

-3.218 0.001


-1.893 0.058


-0.381 0.703


-0.101 0.919


-2.398 0.016


-0.153 0.878


Nonlinear MLS 500cps and nonlinear MLS 833cps

-1.180 0.238

29

Linear MLS 250cps and nonlinear MLS 250cps

-2.103 0.035


-0.175 0.861


-1.012 0.312


-2.773 0.006


-2.750 0.006


-1.480 0.139


-1.006 0.314


-1.335 0.182


-1.401 0.161


-0.586 0.558


-1.147 0.252


-0.400 0.689


-0.468 0.640


-0.432 0.666


-1.041 0.298


-0.432 0.665


-0.901 0.368


-1.998 0.046


-0.502 0.615


-1.068 0.286


-0.827 0.408

Figure 4.3 Example of linear and nonlinear MLS based on ABR time detection

of different stimulus repetition rates

30

Time detection of linear MLS 250cps Time detection of nonlinear MLS 250cps

31

Time detection of linear MLS 833cps Time detection of nonlinear MLS 833cps

Time detection of linear MLS180cpsTime detection of nonlinear MLS180cps

32

Time detection of linear 500cpsTime detection of nonlinear MLS 500cps

33

4.4 Objective 3: Comparison of wave ABR time detection between standard click

and non linear MLS

Friedman test was carried out to compare the median time to detection between

standard click (33cps and 90cps) and novel non linear MLS (180cps, 250cps, 500cps,

833cps). Table 4.4 shows the summary of median, interquartile range (IQR) and

Friedman test results to compare the median time to detection differences between

standard clicks and novel non linear MLS. Table 4.4 shows there was significant

differences in median detection time between the standard click and novel non linear

MLS rate p < 0.05 from the Friedman test. Bonferroni adjustment was calculated in

order to avoid Type 1 error (0.05/15=0.003). Thus, the new significance level is 0.003.

Post hoc test was done (Wilcoxon Signed-Rank test) (see table 4.5). From 15 pairs, there

was no pair with significant difference below 0.003. Hence, pair with the lowest p value

was selected which is the pair of click 90 cps with nonlinear MLS of 250cps (Z = -2.906,

p = 0.004). Figure 4.4, table 4.4 and table 4.5 summarized objective 3 as below.

34

Figure 4.4: Median ± IQR at different stimulus repetition rates between

click and nonlinear MLS

Median, interquartile range (IQR) at different stimulus repetition rates (click & nonlinear MLS)

0123456

clic

k90

cps

clic

k33

cps

Non

linea

r25

0cps

Non

linea

r18

0cps

Non

linea

r50

0cps

Non

linea

r83

3cps

Different stimulus repetition rates (click & nonlinear MLS) (click/s)

Med

ian

tim

e d

etec

tio

n (

s)

0246810

Inte

rqu

arti

le

ran

ge

(IQ

R)

Median time

IQR

Table 4.4: Comparing time between different stimulus rates in

standard clicks and novel non linear MLS

Stimulus rate Median ± IQR χ2 (df) p value

Click 90cps 3.00(2)

11.233 (5) 0.047

Click 33cps 4.00(2)

Nonlinear MLS 250cps

5.00(7)


4.50(5)


3.00(6)


4.00(8)

35

Wilcoxon Signed Rank test was done in order to find the significant different pair

Table 4.6: Different pair for stimulus repetition rates of

standard click and nonlinear MLS


Click 90cps and nonlinear MLS 250cps

-2.906 0.004


-1.579 0.114


-1.206 0.228


-1.854 0.064


-2.688 0.008


-1.211 0.226


-0.501 0.616


-2.245 0.025

Click 90cps and click 33cps

-0.894 0.372


-0.901 0.368


-1.998 0.046

Nonlinear 250cps and nonlinear MLS 833cps

-0.502 0.615


-0.827 0.408


-1.068 0.286


-1.180 0.238

In general, result for Objective 3 shows there are no different between click and

nonlinear MLS at all stimulus repetition rates except for non linear MLS at 250cps with

click 90cps.

36

4.5 Conclusion

Result for Objective 1, 2, 3 shows three general finding which are:-

1. No difference in median time detection of ABR wave V between standard

click and standard MLS.

2. No difference in median time detection of ABR wave V between linear

MLS and nonlinear MLS at same stimulus repetition rates

3. No difference in median time detection of ABR wave V between standard

click and nonlinear MLS except for MLS of 250cps with click 90cps.

37

CHAPTER V

DISCUSSION

5.1 Introduction

The aim of this study is to compare the time for ABR waveform detection

between various combinations of ABR recorded under different stimulus repetition rates

with subjective detection (waveform analysis). The results in general show three general

findings; (i) there was no significant difference in time to detection between standard

click at 33 cps and standard MLS at all stimulus repetition rate (ii) there was no

significant difference in time to detection between standard MLS and nonlinear MLS at

similar stimulus repetition rate and (iii) there was no significant difference in time to

detection between standard click at 33 cps and nonlinear MLS at all stimulus repetition

rate except for MLS at 250 cps and click 90 cps. The discussion will cover three aspects

of the result which outlined as follow:

1. Audiologist can detect neither click nor linear MLS at same time.

2. Effect of non linear MLS to Audiologist detection by comparing time to detection

of linear MLS and non linear MLS.

3. Effect of non linear MLS to Audiologist detection by comparing time to detection

of non linear MLS and click.

38

5.2 Audiologist can detect neither click nor linear MLS at same time

The result in the present study show there was no significant difference in time to

detection between the standard click of 33 cps and 90 cps with linear MLS of 250cps,

180cps, 500cps and 833cps using subjective detection. This present study is not

consistent with the previous report which mentioned the total test time is considerably

reduced time when using the linear MLS technique compared to the conventional

averaging (Leung et al., 1998; Eysholdt & Schreiner, 1982; Burkard et al., 2007).

The inconsistency between our study and from previous results might be due to

several reasons. Firstly, part of the difference stems from the difference criteria of ABR

wave V detection technique used in previous study with the recent study. Previous study

claimed it can improve testing time due to the criteria of detection is made by using fixed

number of sweep (Eysholdt & Schreiner, 1982) and based on conventional ABR SNR

(Leung et al., 1998). The time to detection is reduced using ideal SNR by a factor of 1.2

(Thorton & Slaven, 1993), factor of 1.6 (Leung et al., 1998) and by a factor of 1.01

(Burkard et al., 1991). In addition, the test time also improved by a factor of 18.1 by

using time to detection of fixing 2000 sweeps criterion (Eysholdt & Schreiner, 1982). No

such improvement is observed when subjective detection was used which indicates that

our single observer can visualize and confidently detect an ABR peaks within 3 seconds

(the fastest) for all stimulus parameters. This 3 seconds is translates to only

approximately 99 sweeps for click at 33 cps, 270 sweeps for 90 cps, 480 sweeps for 160

cps MLS, 750 sweeps for 250 cps, 1500 sweeps for 500 cps and 2508 for 836 cps. In

short, the observer can detect an ABR peaks regardless of their SNR and stimulus used.

39

The same detection time using audiologist detection between both MLS ABR and

conventional ABR is not consistent with the fact that high stimulus rate abnormalities in

MLS become detectable due to brainstem response cannot process properly more

stressful stimuli compare to low stimulus rate. Higher stimulus rate provide a much

stronger physiological or temporal challenge to auditory neurons that lead to neural

fatigue (Jiang et al., 2005; Hall, 1992). Through neurophysiology, incomplete recovery

occurs when response changes with increasing rate or adaptation. More incomplete

recovery of the auditory system before the next stimulus result of the shorter

interstimulus interval. That statement supported the argument that higher MLS technique

gives a poor ABR response. However in the present study the use of high stimulus

repetition rate does not translate to poor ABR detection time Even we did not ask the

audiologist about the quality of ABR waveforms which indirectly indicates that an

audiologist can at least detect the less better morphology (e.g. MLS ABR) as long as the

ABR waves are presence according to their subjective criteria.

The second factor that might cause difference between the presence study and

previous study is the small sample size which is 20 subjects and this small sample size

might not be able to detect the difference of testing time between standard MLS and

standard click. Based on the descriptive data the difference between all pair can be as

small as 1 second. Thus to achieve statistical significant we need at least 33 subjects

number (Mora M., 2011). Therefore by increasing the sample size it will increase the

probability to get a statistically significant result.

There are possible factor contributing to the poor ABR MLS morphology. Firstly,

wave V amplitude deteriorates with the increasing presentation of stimulus rate in MLS.

40

There is potential contamination of peak amplitude estimates by residual noise because

some residual noise in the average is likely calculated into the ABR waveform averaging.

Thus, it will lead to reduction measured peak-to-trough amplitudes of the ABR (Burkard

et al., 1993).

Even though some problem might effect the ABR MLS waveform responses,

audiologist still can detect the ABR waveform as same time as the conventional ABR.

Thus, the different between both stimuli in ABR detection time is almost equal when

apply subjective detection technique.

5.3 Effect of non linear MLS to Audiologist detection by comparing time to

detection of linear MLS and non linear MLS

Our study found that there was no significant different of time to detection of the

same rates between ABR recorded using MLS linear algorithm with MLS non linear

algorithm. This is inconsistent with a study conducted by Ahmad Aidil et al. (2010, 2011)

where the author found MLS ABR non linear time to detection is significantly faster than

linear MLS ABR. The reason of this discrepancy might be due to the effect of different

waveform analysis (as mentioned in section 5.2), small sample size (as mentioned in

section 5.2), and the more linear system of newborn auditory system.

As mentioned in section 5.2 an audiologist can detect an ABR peaks as early as 3

seconds and as minimal as only 99 number sweeps regardless of the algorithm used. By

using a subjective detection and not considering any other factors (such as SNR and the

quality of ABR wave), audiologist can detect either click or non linear MLS ABR as

41

early as 3 seconds. Based on our data, an audiologist must detect an MLS non linear

ABR waves as early as 1 to 2 seconds (if we are expecting the non linear MLS to works

better than linear MLS) since the conventional ABR or linear MLS ABR can be detected

within 3 seconds only. A detection of less than 1 second or seconds to two seconds might

be inappropriate as in normal practice an audiologist will wait until certain number of

averaging or time before they can decide whether an ABR is present or not (Hall, 2007).

Another possible solution to this is to consider plotting the ABR waves in less than one

second interval which is not allowed in our equipment for the time being. .

Furthermore, newborn auditory system is less sensitive to rate effects at high rate

compare to the mature auditory system in neurophysiology or in other term there has

more linear auditory system. This is supported by the evidence that the delay maturation

in newborn auditory system will not affect the testing time for both standard MLS and

non linear MLS reconstruction (Lasky et al., 1992). However this is not consistent with

the finding by Ahmad Aidil et al. (2010, 2011) where the nonlinear MLS give faster

testing time than linear MLS. This difference occurs might be due to the newborn

auditory system is not completely linear system thus it might gain both benefit by using

linear algorithm and non linear algorithm in combination of difference waveform

detection analysis as stated earlier.

5.4 Effect of non linear MLS to Audiologist detection by comparing time to

detection of non linear MLS and click

42

The present study shows, 14 pairs of click (33cps and 90cps) and nonlinear MLS

(180cps, 250cps, 500cps, 833cps) no significant difference in ABR waveform detection

time by audiologist detection. There is only one pair with significant different in ABR

testing time between standard clicks 90cps and novel nonlinear MLS 250cps with

subjective detection. Hence, there is disagreement with Ahmad Aidil et al. (2008) where

in their study MLS non linear (all rates) was significantly faster than click at 33 cps as

well as nonlinear MLS at 833 cps significantly faster than click at 90 cps. This

inconsistencies in previous study might be due to number of subject sample are less in

this study. Previous study by Ahmad Aidil et al. (2010) there are 492 ABR waveforms

from 144 subjects were tested. Therefore less number of subject has resulted not all pairs

of click-non linear MLS ABR to have significant different.

Besides, another reason is Audiologist can detect ABR waves regardless of the

used of click or non linear MLS (as mentioned in section 5.2). Other than that, prior study

applied different technique which is automated detection rather than recent study using

subjective detection method. Regardless the stimulus and rate use, audiologist can detect

both click and non linear MLS almost the same time except between click 90cps and

nonlinear MLS 250cps.

Moreover, there is evidence where newborn with delay maturation in auditory

system will not affect the testing time for both standard MLS and non linear MLS

reconstruction (as mentioned in section 5.3).

43

5.5 Conclusion

In conclusion, standard click and linear MLS shows no different in time detection

for ABR waves with subjective detection. Besides, there is no significant difference of

time to detect ABR waves using non linear MLS and linear MLS with subjective

detection. In addition, there is also no significant difference time to detect ABR waves on

non linear MLS over click ABR at 33 cps and 90 cps.

44

CHAPTER VI

CONCLUSION

6.1 Conclusion and clinical application

In general, standard click and linear MLS are not significantly different in term of

ABR waveform time detection using subjective detection. Besides, there is no significant

difference of time to detect ABR waves using non linear MLS and linear MLS for same

stimulus rates with subjective detection. Other than that, there is also no significant

difference time to detect ABR waves on non linear MLS over click ABR at 33cps and

90cps. In overall, either click or MLS both can give similar result in testing time with

subjective detection therefore both stimulus can be used for UNHS and other clinical

applications

6.2 Limitation of the study

As this study done only at certain population, result obtained cannot represent the

actual population. Therefore the findings in this study cannot be generalized beyond the

subjects and parameter used

45

6.3 Recommendations for future study

It is recommended that future studies use a large number of subjects to analyze.

Based on the descriptive data the difference between all pair can be as small as one

second. Thus to achieve statistical significant we need at least 33 subjects number. This

will ensure that the finding represents the determined population and results obtained can

be implemented into clinical settings.

Besides, further study can be done by comparing the discrepancy of testing time

between automated and subjective detection for both click and MLS reconstruction.

Thus, the result will be valuable to know which waveform detection technique is more

feasible.

In addition, further research comparing ABR waveform of similar time interval

between conventional ABR and MLS technique should be carried out. It is to investigate

the quality of ABR wave between conventional and MLS technique.

Additional research also can be done by considering artifact rejection criteria if

improvement in testing time is to be achieved. It is due to ability of myogenic potentials

such as muscle activity can be counted in the ABR waveform averaging if artifact

rejection is not applied.

Last but not least intra and inter observer reliability can be conducted in order to

check for test retest reliability whether there are some changes before and after the ABR

waveform detection time.

46

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51

APPENDIX 1: AABR TEST PROCEDURE

AABR test procedure2

Each subject was assessed by the researcher using the PC-based AABR device,

after he or she had been assessed by the staff of the ‘Healthy Hearing: Newborn Hearing

Screening’ program using their AABR device. The staff of the ‘Healthy Hearing:

Newborn Hearing Screening’ program performed their AABR assessment on each

newborn by:

1. Preparing three sites on each newborn’s scalp and shoulder using alcohol wipes

and a skin-preparation solution. These sites were vertex (Cz), the nape of the

neck and one shoulder.

2. Placing their surface electrodes (jelly tab® from Natus) on these sites and

connected these electrodes to their AABR device. The impedance of these

electrodes was kept below 5 kOhms.

3. Positioning their earphones (flexicoupler® from Natus) from their AABR

device over the newborn’s ears

4. Initiating the test sequence on their AABR device, the ALGO 3® (from Natus)

5. Waiting for their AABR test to finish.

The researcher then completed his AABR assessment on each newborn by:

6. Leaving the electrodes from the above testing on the newborn

2

52

7. Disconnecting the hospital AABR device from these electrodes and connected

PC-based AEP device to these electrodes

8. Removing the hospital’s earphones and inserted the PC-based AABR device’s

insert earphones into one of the newborn’s ears only (whatever ear was most

accessible at the time of testing)

9. Entering the newborn’s research number into the PC-based AEP device

10. Initiating the test sequence on his PC-based AEP device

11. Waiting for the PC-based AEP device to finish its test run (this took

approximately eight minutes per newborn)

12. Disconnecting the newborn from the PC-based AEP device and returning the

newborn to the care of his or her parents/caregivers

13. Recording the newborn’s date of birth, date of test, gender, and relevant medical

history including any risk factors for hearing loss.

53

APPENDIX 2: AABR STIMULUS AND RECORDING PARAMETERS

AABR stimulus and recording parameters

Tables 1.1 and 1.2 shows the stimulus and recording parameters, respectively, used in the

previous study by Ahmad et al. (2008):

Table 1.1: The stimulus parameters used in previous study

Stimulus Parameter

PC-based AEP System

Intensity level 35 dBnHL

Transducer EAR-3A insert phones

Test ear Right or left (based on which ever ear was most accessible at the time of the testing)

Type Two stimulus types were used separately:

An acoustic click driven by a 0.1 ms electrical click in a conventional presentation sequence.

An acoustic click driven by a 0.1 ms electrical click in a MLS of order six, consisting of 32 clicks and 31 silences.

Polarity Condensating

Rate Two stimulus rates were used separately for the conventional stimulus: 33 and 90 cps.

Four maximum stimulus rates were used separately for the MLS stimulus: 180, 250, 500, and 833 cps.

MISI The MISI for the 4 MLS stimuli listed above were 5.56, 4, 2, and 1.2 ms respectively

54

Table 1.2: The recording parameters used in previous study

Recording Parameter

PC-based AEP System

MLS reconstruction technique

Two MLS reconstruction techniques were used:

linear, bipolar and linear, unipolar

Gain 30000 (A/D converter voltage of ±5 V with a 32-bit resolution)

Electrode montages

Vertical

Analysis window

0 to 15 ms for all stimuli except the conventional stimuli at 90 cps, which had an analysis window of 0 to 11.13 ms.

Sampling frequency

32 890 Hz

Low frequency cut filter

100 Hz

High frequency cut filter

5000 Hz (filtered off line to 3000 Hz)

Number of averages

2560 for each conventional stimulus

5120 for the 180 cps s maximum stimulus repetition rate (the MLS stimulus was presented 160 times), 7680 for the 250 cps rate (the MLS stimulus was presented 240 times), 8960 for the 500 cps rate (the MLS was presented 280 times), and 10240 for the 833 cps rate (the MLS stimulus was presented 320 times)

Masking Nil

Artifact rejection threshold

15 µV

Note: The vertical electrode montage required the non-inverting electrode to be placed on the vertex, the inverting electrode to be placed on the back of the neck, and the ground electrode to be placed on either shoulder.

55

APPENDIX 3: DATA COLLECTION RESULTS FOR ABR WAVEFORM DETECTION TIME USING MATLAB SOFTWARE

Gender Click 90cps

Click 33cps

MLS 250cps

MLS 180cps

MLS 500cps

MLS 833cps

1 Boy 3 4 3 3 3 5 3 1 1 3

2 Boy 3 2 3 10 4 4 4 3 3 4

3 Girl 2 3 13 7 1 20 4 10 10 1

4 Girl 3 5 5 9 5 10 20 1 15 15

5 Girl 6 4 17 21 6 5 9 10 12 7

6 Boy 2 5 3 15 3 4 8 1 2 10

7 Boy 6 2 3 5 3 26 7 10 6 5

8 Boy 1 4 4 4 10 5 8 5 21 21

9 Boy 12 2 5 12 3 3 10 8 1 4

10 Boy 4 1 3 3 1 1 2 2 2 2

11 Boy 3 4 9 4 2 1 3 3 2 2

12 Girl 5 3 4 3 2 3 2 1 2 2

13 Boy 1 4 2 2 2 1 4 4 3 9

14 Boy 3 4 3 1 4 10 2 4 5 5

15 Boy 1 3 3 3 3 3 2 2 4 4

16 Boy 2 2 6 10 5 3 2 1 17 21

17 Boy 4 7 11 13 2 6 9 9 5 14

18 Boy 1 3 5 5 1 1 5 3 4 3

19 Boy 2 5 1 4 3 7 2 5 12 2

20 Girl 3 4 5 5 2 5 6 5 3 3

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