PSZ 19:16 (Pind. 1/07)
UNIVERSITI TEKNOLOGI MALAYSIA
PSZ 19:16 (Pind. 1/07)
DECLARATION OF THESIS / UNDERGRADUATE PROJECT PAPER AND COPYRIGHT
Author’s full name :
HANIS ZAFIRAH BINTI KOSNAN
Date of birth
:
31 MARCH 1990
Title
:
DIFFERENCES IN CORTI-CORTICOL FUNCTIONAL CONNECTIVITY AMONG
YOUNG CHILDREN DURING BASIC DRAWING TASK
Academic Session :
2013/2014
I declare that this thesis is classified as :
√
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(Contains confidential information under the Official Secret
Act 1972)*
RESTRICTED
(Contains restricted information as specified by the
organization where research was done)*
OPEN ACCESS
I agree that my thesis to be published as online open access
(full text)
I acknowledged that Universiti Teknologi Malaysia reserves the right as follows:
1. The thesis is the property of Universiti Teknologi Malaysia.
2. The Library of Universiti Teknologi Malaysia has the right to make copies for the purpose
of research only.
3. The Library has the right to make copies of the thesis for academic exchange.
Certified by :
SIGNATURE
SIGNATURE OF SUPERVISOR
900331016706
DR NORLAILI BINTI MAT SAFRI
(NEW IC NO. /PASSPORT NO.)
Date : 16 JUNE 2014
NOTES :
*
NAME OF SUPERVISOR
Date : 16 JUNE 2014
If the thesis is CONFIDENTAL or RESTRICTED, please attach with the letter from
the organization with period and reasons for confidentiality or restriction.
i
“I hereby declare that I have read this thesis and in my opinion this thesis is
sufficient in terms of scope and quality for the award of the degree of Bachelor of
Engineering (Electrical Medical-Electronics)”
Signature
: ……………………………………...
Name of Supervisor
: DR NORLAILI BINTI MAT SAFRI
Date
: JUNE 2014
ii
DIFFERENCES IN CORTI-CORTICOL FUNCTIONAL CONNECTIVITY
AMONG YOUNG CHILDREN DURING BASIC DRAWING TASK
HANIS ZAFIRAH BINTI KOSNAN
A thesis submitted in partial fulfillment of the requirement for the award of the
degree of Bachelor of Engineering (Electrical Medical-Electronics)
Faculty of Electrical Engineering
Universiti Teknologi Malaysia
JUNE 2014
i
I hereby declare that this thesis entitled “ Differences In Corti-Corticol Functional
Connectivity Among Young Children During Basic Drawing Task” is the result of my
own research except as cited in the references. The thesis has not been accepted for
any degree and is not concurrently submitted in candidature of any other degree.
Signature
: ………………………………………
Name
: HANIS ZAFIRAH BINTI KOSNAN
Date
: JUNE 2014
ii
Specially dedicated to my beloved parents: Kosnan Bin Bukhiran and Jamnah Binti
Mohamed Zin and wonderful siblings
iii
ACKNOWLEDGEMENT
Highest gratitude and thankfulness to ALMIGHTY ALLAH, the most
Gracious, Merciful and Compassionate, the creator of universe, for blessings,
strengths, patients and ideas during the project. I am also very thankful and present
salute to many individuals who helped me during the period of this project. I wish to
express my gratitude to my supervisor, Dr Norlaili Binti Mat Safri for her intellectual
guidance. Thanks a lot for giving me a professional training, advice and suggestion
to bring this report to its final form. I am very grateful to her for her constructive
comment that enriched this project.
A very most thankful to all of teachers and staff in Sekolah Agama UTM who
provided me an opportunity to work in a friendly environment. It was an honor and
pleasure to work with them. I would also like to acknowledge with much
appreciation to all of the subjects involved for their time during the period of the
experiment. In particular, my sincere thanks to Intan Shazreen Binti Hashim for her
advice and guidance during the project period.
Last but not least I would love to thank to all my family for their continuous
support and confidence in my effort. A very grateful to all members for all the hard
work, helping hand and encouragement until it successfully accomplished. The
experiences faced will be remembered till the end of time.
iv
ABSTRACT
Handwriting is an integral part of every child’s in the school experience.
Many researchers on handwriting among young children are widely done. There are
many different approaches to analyze the differentiation of young children with
handwriting. Partial Directed Method has become a famous method nowadays. In
this project, the Partial Directed Coherence method is chosen to get the real path
information pathway of brain activity. Twenty young children participated randomly.
The subject must trace three different unlined shapes on the WACOM digitizing
tablet. While doing a basic drawing task, brain signal was recorded using
electroencephalogram (EEG) machine to analyze the information pathway using
partial directed coherence (PDC) method in the Linux open source. The result
showed that subject drew with non preferred rule used left frontal region ( ) as their
source of functional coupling where emotional expression and mood regulation
executed during performance. Meanwhile, subject whom performed the drawing task
with preferred rule show that most information sources came from the frontal (
for motor planning, parietal (
occipital (
and
)
) for perception midline and route finding and
) for visual processing and pattern recognition. As a conclusion,
the corti-cortical connectivity using Partial Directed Coherence provides insight how
the brain functions during drawing task among young children.
v
ABSTRAK
Baru-baru ini, tulisan tangan adalah merupakan sebahagian pengalaman
daripada setiap kanak-kanak di sekolah. Pelbagai kajian mengenai tulisan tangan
dalam kalangan kanak-kanak telah dilakukan secara meluas. Terdapat banyak
pendekatan yang berbeza untuk menganalisis perbezaan tulisan tangan dalam
kalangan kanak-kanak. Kaedah arah koherensi separa telah menjadi kaedah yang
terkenal pada masa kini. Dalam projek ini, kaedah arah koherensi separa dipilih
untuk mendapatkan laluan sebenar maklumat aktiviti otak. Dua puluh kanak-kanak
telah mengambil bahagian secara rawak. Subjek mesti melukis tiga bentuk yang
berbeza pada buku pendigitan, WACOM. Ketika melakukan tugas asas lukisan,
isyarat otak telah direkod menggunakan elektroencephalogram(EEG) mesin untuk
menganalisis laluan maklumat sebenar menggunakan kaedah arah keherensi separa
(PDC) dalam sumber terbuka, Linux. Keputusan menunjukkan bahawa subjek
melukis dengan tidak menggunakan peraturan pilihan menggunakan kawasan frontal
( ) sebagai sumber informasi dimana pengungkapan emosi dan regulasi perasaan
semasa melakukan tugas. Sementara itu, subjek melukis dengan menggunakan
peraturan pilihan menunjukkan bahawa kebanyakan sumber maklumat daripada
frontal (
) untuk motor perancangan, parietal (
laluan dan occipital (
and
) untuk persepsi dan dapatan
) untuk pemprosesan visual dan pengenalan corak.
Kesimpulannya, penyambungan korti-kortikal menggunakan kaedah arah koherensi
separa memberi gambaran tentang bagaimana fungsi otak ketika melakukan tugas
asas lukisan dalam kalangan kanak-kanak.
vi
TABLE OF CONTENT
CHAPTER TITLE
1
2
PAGE
ACKNOWLEDGMENT
iii
ABSTRACT
iv
ABSTRAK
v
TABLE OF CONTENT
vi
LIST OF TABLE
ix
LIST OF FIGURES
x
LIST OF ABBREVIATIONS
xi
LIST OF APPENDICES
xii
INTRODUCTION
1.1 Background of the study
1
1.2 Problem statement
2
1.3 Project objective
3
1.4 Scope of Project
3
1.5 Thesis outline
3
LITERATURE REVIEW
2.1
Chapter Overview
5
2.2
Paper Review about handwriting
5
2.2.1 Handwriting difficulties in primary school children
6
2.2.2 The use of graphic rules help to identify children
6
at risk of handwriting difficulties
2.2.3 The development of graph motor skills in hand
function in the child
8
vii
2.3 Introduction of Brain
3
2.3.1 Parts and function of Brain
10
2.3.2 Measuring the EEG signals in brain
11
2.4 Concept of Coherence Analysis
13
2.5 Partial Directed Coherence (PDC)
15
2.5.1 Vector Autoregressive Coefficient (VAR) functions
15
2.5.2 Partial Directed Coherence function
16
2.5.3 GNU plot function
17
METHODOLOGY
3.1 Block Diagram of the Project
4
5
9
18
3.1.1 Subject
19
3.1.2 Instrument and data Analysis
19
3.1.3 Model Information Pathway
21
3.1.4 Experimental procedure
22
RESULT AND DISCUSSION
4.1 Chapter Overview
26
4.2 Drawing Task
26
4.3 Summary
37
CONCLUSION
5.1 Chapter Overview
38
5.2 Conclusion
38
5.3 Future recommendations
40
viii
6
PROJECT MANAGEMENT
6.1 Chapter Overview
41
6.2 Project schedule
42
6.3 Cost estimation
45
6.4 Recommendations
46
REFERENCES
47
APPENDIX A-B
50-80
ix
LIST OF TABLE
TABLE
TITLE
PAGE
NO.
1.1
Brain Region And Its Function
11
3.1
Subject Information
19
3.3
Checklist Of Drawing Task For Semi Circle
23
And Triangular Shape
4.1
Preferred direction and brain information for
28
first orientation drawing task
4.2
Preferred direction and brain information for
30
second orientation drawing task
4.3
Preferred direction and brain information for
32
triangular drawing task
4.4
Brain information pathway due to their
35
handness for the first orientation task
4.5
Brain information pathway due to their age for
36
all the drawing
6.1
Gannt Chart for a project during semester 1
43
6.2
Gannt Chart for a project during semester 2
44
6.3
Cost estimation of project
45
x
LIST OF FIGURES
FIGURE
TITLE
PAGE
NO.
2.1
First Nine Forms Of Development Test Of Visual
9
Motor Integration
2.2
Four Major Parts Of Brain
10
2.3
Point Marked On The Head By Length
12
2.4
Ordinary Coherence
13
2.5
Directed Coherence
14
2.6
Partial Coherence
14
3.1
Block Diagram Of The General Purpose
18
3.2
Procedural Taken Data
20
3.3
Signal Connection Between Channel
22
3.4
Three Different Unlined Shape For Drawing Task
22
3.5
Non preferred and preferred task
24
3.6
Arrangement 10-20 electrode system
25
4.1
Number of subjects due to their preferred direction
27
xi
LIST OF ABBREVIATIONS
EEG
Electroencephalogram
VAR
Vector Autoregressive Coefficient function
PDC
Partial Directed Coherence
xii
LIST OF APPENDICES
APPENDIX
TITLE
PAGE
A
PREFERRED TRACING DIRECTION AND
50
BRAIN INFORMATION PATHWAYS
DURING DRAWING TASK
B
CODING FOR THE INFORMATION
PATHWAY DURING DRAWING TASK
71
1
CHAPTER 1
INTRODUCTION
1.1
Background of the study
Handwriting is complex motor behaviors requiring the maturation and
integration of cognitive, visual perception and fine motor skills.
Eye-hand
coordination, auditory perception, visual perception, directionally, sequencing and
memory is also developing with maturation and experiences in the early year and
thought to be an underlying component required for handwriting. Graphomotor
skills comprise the conceptual and perceptual-motor abilities[1].
EEG machine can detect electrical activity of the brain. Many physicians and
neurologists indicate that EEG is collaborative tools in diagnosing brain function and
diseases. In fact, EEG waveform was thought to be a summation of action potential
of neurons [2]. Mostly EEG record for diagnosis, including localized cerebral brain
lesions and assist in diagnosing mental disorder or sleep pattern.
observation and analysis of brain responses to sensory stimuli.
It allows an
2
An investigation on the human brain activity is very common, nowadays.
However, it is challenging to measure causal influences between different brain
areas. Nowadays, there are many various techniques that detect the causal influences
in multivariate systems. The concept of Ganger causality is widely used especially
in analyzing information of brain activities.
Partial directed coherence (PDC) is the combination of Ganger causality and
coherence to process the numerous time series for determining the functional and
directional connectivity in the human brain. The concepts of PDC are widely used as
it provided the direct structural information flow in the brain. This PDC can measure
the relative strength of the direct structural interaction.
So, the directional
connectivity in the brain that is related to the employed strategy can be explored by
using PDC method.
1.2
Problem Statement
Handwriting is an integral part of every child’s school experience. Failure to
attain handwriting competency during the school age years often has far reaching
negative impact on both academic success and self esteem. Handwriting difficulty is
a significant problem for the educationalist and occupational therapist. Nowadays,
there is a growing interest on investigating handwriting difficulties using human
brain activity Although some aspects of handwriting in the kindergartner have been
investigated but the relationship between cognitive ability of understanding spatial
and temporal concepts and handwriting has not been explored. Therefore, this study
investigated the relationship between the cognitive understanding of spatial and
temporal and graphomotor production.
3
1.3
Objective
To investigate the functional connectivity in brain among young children
during basic drawing task using Partial Directed Coherence (PDC) method.
1.4
Scope Of Study
While doing a drawing task, brain signal was recorded using an EEG
machine (Neurofax µ EEG-9100J/K, Nihon Kohden). Cap with 19 electrodes was
applied to subject scalp with references linking to the ear lobe and the cap was
connected to the EEG machine for data acquisition. The EEG were analyzed based
on Partial Directed Coherence (PDC) method using C language in Linux Fedora 8.
PDC result were plotted using Tgif and gnuplot that includes 19x19 matrices. Subject
made drawings using WACOM tablet. WACOM tablet is a graphic tablet and the
computer output device that enables users to hand-draw image, similar to a person
draw image with a pen or pencil. This tablet is used to detect and record subject’s
drawing. WACOM used wireless electronic pen. The time and position of the pen
tip were recorded in laptop computer.
1.5
Thesis outline
This thesis is divided into five phases which is an introduction, literature
review, project methodology, result and discussion, conclusion and lastly project
management. The first phase shows the introduction that consists of the information
4
about handwriting, brain and the background of Electroencephalogram machine.
This phase also involved method and techniques to measure the direct structural
information flow in the brain.
The second phase consists of a literature review. This phase explains the
anatomy of the brain and brief explanation on partial directed method for data
analysis. The third phase is the methodology. This indicates the implementation
steps and flow of the project. All of the procedure and experiments were conducted
based on proposed methodology.
Next, the fourth phase is result and discussion. All of the results are taken
into account. This phase focuses more on observation and analysis. Furthermore,
this phase discusses the model information pathway of the brain. Lastly, the fifth
phase is conclusion. The conclusion summarized the result obtained. This phase
also includes some future recommendation for the future.
Project management
which is a requirement for this thesis is put under the last phase. It involve time
management and cost estimation when organizing and planning the project.
5
CHAPTER 2
LITERATURE REVIEW
2.1
Chapter Overview
This chapter provides a brief knowledge about the introduction of brain
includes part and function of the brain itself. Next, this chapter discusses the concept
of coherence analysis by analyzing the EEG signal in brain structures. Lastly, the
concept of Partial Directed Method for analyzing the collected data is presented.
2.2
Handwriting Difficulties
This chapter reviews the analysis about handwriting difficulties in primary
school children. Earlier findings suggest that the use of graphic rule help to identify
children at risk in handwriting difficulty. In fact, the development in graph motor
skill in hand function of the child provides a better way to identify the child's
problem in writing ability. It is proven by one of the research that carried out an
experiment that specialized in children with handwriting problem using visual-motor
integration.
6
2.2.1
Handwriting difficulties in primary school children
The contribution of perceptual-motor dysfunction and cognitive planning
may cause problems to the quality of handwriting in children [3]. The researcher
argued that visual motor integration was the best predictor for the children with
handwriting problem and fine-motor coordination was the best predictor for the
children without a handwriting problem.
They also argued that the speed of handwriting was not related to quality of
handwriting either in handwriting problem or without a handwriting problem.
Although most of the children with handwriting problem were very slow writers, but
there is no significant correlation between quality and speed of handwriting.
Volman also concludes that there are two different mechanisms underlie the
quality of handwriting ability.
Poor quality of handwriting ability seems
significantly related to deficiency of visual motor integration.
2.2.2 The use of graphic rules in identifying children at risk of handwriting
difficulties.
In reality, children copy geometric figures seem to follow a set of rule; where
to begin drawing and which direction to proceed [4].
The role of person's
preferences from his or her initiate drawing by certain location point [5]. As an
example, right handed children prefer to start upward rather than downward or left
rather than on the right.
7
There are four event sequences that take place before the children begin
copying the geometric figures. First, children evaluated the visual form. Then,
children will select the sequences of stroke.
Next, children need to take
consideration on correct reproduction. Lastly, the stroke selected feasibility have
least of error [5].
Children at risk of handwriting difficulties display varied graphmotor skills.
There is a possibility that drawing behavior can identify children, who at risk in
handwriting difficulties [6]. Copying a figure does not require memorization but it
always required translation process.
It's proven that children with handwriting
difficulties could not translate the visual information into motor actions [7]. In fact,
copy task required the children to consider the visual form (figure).
Children
drawing a task by sequences of movement with their motor capabilities.
Handwriting difficulties may relate to the strategy of implementation. It also may
influence the use of graphic rule [6]. Thus, it can be assumed that children who do
not have proficiency with their handwriting skills will use the graphic rules with nonrule governed fashion.
Some of the researcher had investigated the feasibility of using quantitative
measurement of children’s drawing to identifies children who at risk in handwriting
difficulties. Three different features are extracted. The extracted features are the
number of peaks in drawing a velocity profile, the mean drawing velocity and pen
pressure. The dynamic features such as mean velocity and pressure variability can
identify the performance characteristic of handwriting ability [8].
8
2.2.3
The development of graphomotor skills in hand function among children
Graphomotor skills comprise the conceptual and perceptual-motor abilities
necessary for drawing and writing [9].
Handwriting is the process of forming
figures, letter, or symbol on paper to form words and words to form sentences.
Handwriting is one of the activities that record experiences and also thoughts.
Drawing and handwriting are complex motor behavior in which psychomotor,
linguistic, and biomechanical process interact with maturation, development, and
learning process [10]. Eye-hand coordination, visual perception, auditory perception,
directionally sequencing, and memory also develop with maturation and experience
in early years and are thought to be underlying components required for handwriting.
Children with handwriting difficulties may avoid writing that significantly
reflect their knowledge. Handwriting difficulties are one of the most problems for
educationalists and occupational therapies.
The issues of handwriting development and by understanding the
developmental expectation for handwriting is the question of when young children
are ready to begin handwriting instruction. There may be some factor that must be
considered such as perceptual readiness, linguistic readiness, and the maturity of
control of pencil tools.
Figure 2.1 shows the first nine forms of the development test of Visual Motor
Integration (VMI).
Children are not ready to learn handwriting until they are
introduced this first nine forms of the VMI [11]. Several features of handwriting
development are consistent from both historical and cross-cultural perspectives.
Some of the characteristics of handwriting are likely to be common across cultures,
language and written script. Seems that these are the factor that operate in the
development of written script [12]. The size of writing diminishes, letter formation,
9
spacing, and horizontal alignment become more accurate, simplified and
standardized, thus the handwriting become abbreviated [13].
BOX11-1
The First Nine Forms of the
Developmental Test of Visual
Motor Integration in Order of
Increasing Difficulty
1. Vertical Line
2. Horizontal Line
3. Circle
4. Cross
5. Right Oblique Line
6. Square
7. Left Oblique Line
8. Oblique cross
9. Triangle
Beery KE (1989). The Development Test of VisualMotor Integration, 3rd rev. Cleveland, OH, Modern
Curriculum Press.
Figure 2.1 : First Nine Forms of the Developmental Test of Visual Motor Integration
2.3
Introduction of Brain
Brain is one of the largest organ of the body consist of 100 billion neurons
and 10-50 trillion neuroglia with a mass about 1300g. Four major parts are the brain
stem, diencephalon, cerebrum, and cerebellum as shown in Figure 2.2. All together
parts of the brain control every part of human daily life.
10
CEREBRUM
DIENCEPHALON
Thalamus
Hypothalamus
BRAIN STEM
CEREBELLUM
Pons
Medulla oblongata
Spinal Cord
Figure 2.2 : Four major parts of Brain[14]
2.3.1
Parts and Function of Brain
The four major parts of the brain are the brain stem, diencephalon, cerebrum,
and cerebellum. The brain stem is continuous with the spinal cord and consists of
the medulla oblongata, Pons and midbrain.
Above the brain stem is diencephalon
consists of the thalamus, hypothalamus and pineal gland. Supported the brainstem
and diencephalon and produce the bulk of the brain called the cerebrum.
The
surface of the cerebrum consists of thin layer gray matter called cerebral cortex,
internal region cerebral white matter. Cerebrum provides us with the ability to read,
speak, to make calculation, compose music, to remember the past and plan for the
future and also to create. Posterior to the brain stem is the cerebellum. When there
is rapid increases in brain size, the gray matter of the cerebral cortex large faster than
underlying white matter. Then cerebral cortex rolls and folds itself and fit the cranial
cavity. The fold called gyri. The deep grooves between the folds are called fissures.
The longitudinal fissure separates the cerebrum into right and left halves called
cerebral hemispheres. Each cerebral hemisphere has four lobes that are named after
the bones that cover them, frontal lobe, parietal lobe, temporal lobe and occipital
lobe. All the four lobe control our system. Table 1.1 shows the purpose of each lobe
[9].
11
Table 1.1: Brain region and its function
Brain region
Function of brain region
Frontal lobe

Involved in concentration

The conceptual thinking, create problem solving,
creative thought, control the emotion, deal with mental
power, initiative, judgment

Coordinated movements, muscle movements, smell
and physical reactions
Temporal lobe
Parietal lobe
Occipital
2.3.2

Personality and behavior

Auditory and visual memories

Some hearing

Control speech and language

Manage sensation

Respond to internal stimuli

Sensory comprehension

Some language and reading

Arithmetic processing

Brain visual processing
Measuring the EEG signals in brain
Electroencephalogram (EEG) machine measures the spontaneous activity on
the scalp of the human head. Spontaneous means the activity goes continuously in
the living individual. Electroencephalogram machine record the electric field in
human brain made by a German psychiatrist in 1924 in Jena [2]. EEG signal are
recorded based on International Standard 10-20 system. The amplitude, phase and
frequency of EEG signals depend on electrode placement. This system is located on
12
the surface of scalp of head and based on the frontal, parietal, temporal, and occipital
cranial areas. One of the most popular schemes is 10-20 electrode placement system
establish by the Internal Federation of EEG Societies. This system applied to head
which mapped four standard points: the nation (nose), the inion (external occipital
protuberance) and the left and right preauricular point (ears) . For example,
placed on the frontal area and lies on a circle with another lead. There are nineteen
electrodes plus one for grounding the subject. Electrode is placed (using flexible
tape measure) by measuring nasion-inion distance and the point marked on the head
by 10%, 20%, 20%, 20% and 10% of the length as shown in Figure 2.3. The
midpointis vertex,
electrode. EEG signal voltage amplitudes range from about 1
to 100µV peak to peak at low frequency, 0.5 to 100Hz at the cranial surface.
Figure 2.3: Point marked on the head by length[2]
13
2.4
Concept of Coherence Analysis
EEG Coherence is one of the methods that measure dependency two distinct
brains on the EEG activity. The first application of coherence analysis to human
EEG was not performed before 1961 due to the lack of mathematical algorithms,
computer power and computer software [15].
By increasing development of
computerized technique, the application of coherence in EEG signal due to human
brain started early 1970. Due to multivariate dynamic process, there are more than
two processes are usually observed.
The interaction of the process may be
directionally or in directionally among brain signal.
Thus, the synchronization of
the brain structure process can be analyzed using coherence. The process analyzed
by using this Coherence analysis. There are three types of Coherence analysis i.e
Ordinary Coherence, Directed Coherence, and Partial Directed Coherence [16].
Figure 2.4 shows the ordinary coherence, this coherence shows the direct pair
between two structures i.e: The structure A is directed to structure B, and structure B
directed to the structure A.
A
C
B
Figure 2.4: Ordinary Coherence
14
While, Figure 2.5 shows the directed coherence. This figure shows that the
coherence of the structure of A to the structure C via the structure of B, but it can
transfer directed from the structure A directly to structure C.
A
C
B
Figure 2.5: Directed Coherence
Figure 2.6 shows the partial coherence. The flow of the coherence of the
structure A to the structure C can through by partly by structure B.
A
C
B
Figure 2.6: Partial Coherence
15
2.5
Partial Directed Coherence (PDC)
Partial Directed Coherence ( PDC) is the latest concept in neural structure
determination. PDC is a frequency-domain representating the concept of Granger
causality.
Granger causality can illustrates in term of multivariate Vector
Autoregressive process (VAR).
The PDC defines the graphical interaction that
described the dependence structure of multivariate time series by undirected graph
[17].
PDC method based on spare multivariate autoregressive (Mar) model to have
been used to investigate the pattern of the real information flow in
electroencephalography (EEG) recording in Parkinson diseases when performing
visually-guided motor task [18]. In order to investigate the functional connectivity
changes in Parkinson diseases, they employed a Partial Directed Coherence method
that examines the multi-channel time series and allows simultaneous modeling all
channels with a multivariate autoregressive (mAR).
2.5.1 Vector Autoregressive Coefficient (VAR) functions
Interrelation between signals in neural activity is one of the most challenge in
neuroscience. Granger causality has been introduced which apply multivariate time
series analysis, a technique that can detect a direct relationship in neural signal [19].
In fact, Ganger causality is closely related to vector autoregressive (VAR).
X(t) =
(2.1)
16
Equation (1) shows the vector autoregressive coefficient model.
equation state that
(r) represent a n × n coefficient matrices of the model. It
describes how the present value of
component
This
depend linearly on past values of the
.Where p stands for model order, ε (t) is a vector of white noise value
usually zero.
2.5.2
Partial Directed Coherence function
A (ω) =
(2.2)
Based on equation (2), it is remark than when i=j, the PDC function
represents how much its own past couples in its present state. By referring to the
concept of PDC, the time domain of VAR coefficient converted to frequency domain
based on fourier transform. Then, Partial directed Coherences come with |
|
for VAR[p] process
(f) =
(2.3)
Once the PDC values were obtained based on equation (3), using Tgif software, 19 ×
19 matrix of PDCs are layout.
17
2.5.3
GNU plot function
GNU plot is a portable command-line driven graphing for LINUX, OS/2, MS
windows and many other platforms [20]. GNU created to help scientist or student
visualize the data interactively. GNU under active development since 1986. GNU
has many basic functions such as sine, cosine, bessel, gamma and etc. It also can be
plotted by a combination of many functions using C language.
18
CHAPTER 3
METHODOLOGY
3.1
Block Diagram of the Project
Figure 3.1 shows the general process of the project. There are three main
components of the block diagram which are subject, data analysis and model
information pathway.
The data analysis include the autoregressive coefficient
function, partial directed coherence function and gnuplot function.
The model
information pathway applied when the output result of 19 x 19 matrices are done.
Figure 3.1: Block Diagram of the general purpose of the project
19
3.1.1
Subject
Twenty young children from primary school between age 7 to 11 years old
willingly participated in this case study. Subjects were selected randomly. Table 3.1
shows that there were twenty young children participated randomly. Ten of them
were male and the other ten were female. Eighteen of them were right handed while
two female subjects were left handed.
Table 3.1 : Subject Information
Gender
Handedness
3.1.2
Male
10
Female
10
Right
18
Left
2
Instruments and Data Analysis
To detect and record subject drawing, portable digitizing tablet (WACOM)
was used with wireless electronic inking pen. The time and the position of the pen
tip were recorded in a laptop computer. For the recording of EEG data, the 19
electrode cap was applied to the subject scalp with references linking to the ear lobe.
The cap was then connected to the EEG machine for data acquisition. The recorded
waveforms were reflection of cortical activity.
After capturing the signal, the
20
acquisition and review function was used to compile the data. The data can be open
with Microsoft Excel for future analysis.
Figure 3.2 shows the procedure to capture EEG data while doing the drawing
task. The experiment took place in a quiet environment. The subject wore EEG cap
which was connected to the EEG machine.
The EEG machine captured the
waveform signal of brain while subject perform the basic drawing task using a
digitizing tablet. Firstly, the subjects were given the task and instruction . After that,
the subjects were asked to gaze the given shape for about 10 second. The time was
recorded on a digitizing tablet using laptop computer. The signal waveform that was
on display in EEG machine were recorded. Then the subject was asked to trace the
given shape for about 10 second. The time and position while doing the drawing
task were observed as the signal waveform was recorded.
START
GIVE TASK AND INSTRUCTION
SUBJECT GAZE
EEG RECORD
SUBJECT TRACE
EEG RECORD
STOP
Figure 3.2: Procedural Taken Data
The data provided in the EEG machine were in binary form, thus the data
need to be converted first to the ASCII form for later process. PDC was used to
analyzed the captured EEG signals. After that, Vector Autoregressive Coefficient
function, Fourier function and gnuplot for plotting the result output in 19x19 matrix
form were performed
21
3.1.3
Model Information Pathway
PDC with gnu plot function performed 19x19 matrix diagram of brain
activities.
The information pathway was plotted manually based on gnu plot
diagram. The way to choose the signal connection between channels is shown in
Figure 3.3.
Figure 3.3 shows the sample of the three signal connection with brain
activities. The way to select real connection signal occurs based on the position of
the red line. The horizontal red line that is perpendicular or greater that the first
point of vertical box was selected as having connection. The red line signal means
that there is a signal connection occurs either to their channels itself or to the other
channels. The output result was shown in the gnu plot diagram. Gnuplot diagram
have 361 box channels in 19x19 matrices.
The signal connection between the
channel does not occur
The signal between the channel
connection occur
The strong connection between the
channel occur
Figure 3.3 : Signal Connection between Channels
22
3.1.4
Experimental procedure
The experiment was done in a quiet environment. No interference by other
people as it can influence the EEG signal taken and the subject will lose focus. This
can lead in inconsistencies of data and was difficult to analyze. The subject wore an
EEG cap with electrode attach to the brain signal while doing the basic drawing task
using a digitizing tablet.
Figure 3.4 shows three different unlined shapes used in the research. The
subject must trace all the unlined shape on a digitizing tablet. Every shape was
printed out on A5 paper size. One shape must be drawn three times for accuracy and
subject was instructed trace the shape directly on top of the A5 printed image.
Subject was able to choose their own direction when tracing the shape.
Right
Left
Semicircle
Semicircle
Triangle
Figure 3.4 : Three different Unlined Shape for Drawing Task
Table 3.2 shows the observation by subject preferential while drawing basic
task. This observation was needed as the graphic rule planning, which includes
identifying the first point (starting point)
and deciding the sequences of
23
stroke(progression rule) always be one of the aspect of graphic behavior [6]. Subject
normally visualize the shape before doing the sequence planning and organizing to
complete the geometric shape.
Table 3.2 : Checklist of Drawing Task for Semi Circle and Triangular Shape
Left to Right
S1
S2
Right to Left
S3
S4
S1
S2
S3
S4
ROblique11
LOblique21
ROblique12
LOblique22
Roblique13
LOblique23
First Line
Line S1
S2
Second Line
S3
S4
S1
S2
Third Line
S3
S4
S1
S2
S3
S4
Figure 3.5 shows the preferred and non preferred graphic rules of right
semicircle, left semicircle and triangle. There are many different ways to draw when
both direction and order of movement are taken into account. Subject follow graphic
rule used a less order of movement. In other word, simple pattern is executed during
the drawing task. Children drawing a task by sequences of movement with their
motor capabilities [6].
24
Figure 3.5 : Non preferred and preferred task
Shape
Preferred
1
Non-Preferred
3
1
2
3
2
2
1
1
2
1
1
2
3
1
2
2
3
3
3
3
25
Figure 3.6 shows the electrode placement of the brain. . Letter F for frontal,
T for temporal, C for central, P for parietal, and O for occipital. Letter A for
reference linking. Known that
,
and
in the middle area of the brain. All of
the results of brain information pathway are based on Figure 3.6.
Figure 3.6 : Arrangement 10-20 electrode system.[21]
26
CHAPTER 4
RESULT AND DISCUSSION
4.1
Chapter Overview
This chapter discusses the result obtained from each subject. Based on the
analysis of brain signal by using PDC, the pattern of information pathways among
young children was described.
The preferred movement of each subject was
observed and analyzed.
4.2
Drawing task
Figure 4.1 shows the result of number of subjects based on their preferred
direction. Fourteen subjects (70%) used all preferred graphic rule while doing the
drawing task. Three subjects (15%) drew 2 out of 3 drawing tasks with the preferred
graphic rule. Two subjects (10%) drew 1 out of 3 drawing tasks with the preferred
graphic rule. Only one (5 %) subject drew all drawing tasks with non preferred rules
27
Statistics of Preferred Graphic Rule
All Preferred
2/3 Preferred
1/3 Preferred
All Non Preferred
5%
10%
15%
70%
Figure 4.1 : Number of subjects based on their preferred direction
Table 4.1 shows the preferred direction made by subject and their brain
information pathway during the first orientation drawing task. The result shows that
eighteen out of twenty subject drew the first orientation task with preferred
movement . During gaze, nine subjects used frontal area as information sources.
Five subjects used
, one subject used
and only one subject used
as
information sources, where motor planning and fine motor coordination executed
during the performance.Two subject used
for emotional expression and mood
regulation. Four subject used the parietal area as information source where two of the
subject used
and the another two subjects used
and route findings. Five subjects used occipital area,
pattern recognition executed during the performance.
for perception midline, praxis
where visual processing and
28
Table 4.1 : Preferred direction and brain information for first orientation
drawing task.
Gaze
Use
of
Lobe
Trace
Pattern
graphic
No of
Lobe
Pattern
No of
Subject
Subject
9/20
8/20
rule
P
R
S11
S17
E
F
4/20
E
6/20
R
R
E
S2
S2
D
5/20
4/20
S10
S12
N
O
2/20
2/20
N
P
R
S19
E
F
E
R
R
E
D
Note :S(X) Refer to number of subject of X in Appendix A
S19
29
During trace, four subjects used
and one subject used
as information
sources where motor planning and fine-motor coordination executed during the
performances while three subjects used
for mood attention and judgment.
Therefore, eight of them made traces using frontal area as information sources.
Three of the subjects used
and route findings.
and the other three used
area for perception, praxis
Four of the subjects used occipital area,
where visual
processing and pattern recognition executed during the performance.
Two subjects used non preferred movement for all three trials. During all
gaze trials, PDC shows that one of the subject used
emotional expression and the another one used
for mood regulation and
where verbal expression and mood
regulation during the performance and the information was distributed to other brain
region i.e : to temporal, parietal and occipital area. During trace trials, one subject
used
for emotional expression and mood regulation and the another used
where emotional attention executed during the performance. It can be concluded that
subject drew with
non preferred movement in emotional condition during the
performance.
Table 4.2 shows the second orientation of the basic drawing task, most of the
subject used preferred movement for all the three trials. The result shows that fifteen
out of twenty subject drew the second orientation task with preferred movement .
During gaze, there were seven subjects used parietal area as information sources.
Four subjects used
and another three used
where perception midline, praxis
and route findings executed during the performance. Three of the subjects used
and one subject used
for motor planning and fine motor coordination. Another
three subjects used
and one subject used
, the occipital area as information
sources where visual processing and pattern recognition executed during the
performance.
30
Table 4.2 : Preferred direction and the brain information pathway for second
orientation drawing task
Gaze
Use
of
Lobe
Trace
Pattern
graphic
No
of
Lobe
Pattern
Subject
No
of
Subject
rule
4/20
S13
6/20
S6
7/20
P
3/20
R
E
F
S10
S8
E
R
4/20
R
1/20
E
D
S12
S14
1/20
S1
4/20
S12
31
N
O
4/20
5/20
N
P
S19
R
S9
E
F
1/20
E
R
R
E
C20
D
Note :S(X) Refer to number of subject of X in Appendix A
During the trace trials, fifteen out of twenty subjects traced with preferred
movement. Six subject used frontal area where four subject used
used
as information sources for motor planning and fine motor coordination. One
of the subject used
occipital area
for logical attention and decision making .Four subjects used
as information sources where visual processing and pattern
recognition executed during the performance. One subject used
used
and one subject
and two subjects
as information sources for perception and praxis. One subject used
as
information sources for symbol recognition and some emotional understanding.
Only one subject used midline area,
as information source where sensorimotor
integration executed during the performance.
Five subjects used non preferred movement for all three trials. During gaze,
most of the information sources came from frontal area. One subject used
where
emotional expression and planning executed during performance. Three subjects
used
for emotional expression and mood regulation. Only one subject used
as
information sources for perception, route findings and praxis. For all the three trace
trials, all of the subjects used frontal area as information source before spreading to
other movement related regions. Subject drew with non preferred movement used
32
frontal area. Two subjects used
One subject used
for emotional expression and mood regulation.
for emotional attention and two subjects used
for motor
planning.
Table 4.3 shows the result of a triangular shape drawing task, where there are
various directions that could possibly occur for starting rule and progression rule.
All the direction was observed as shown in Table 4.3. Seventeen out of twenty
subjects used preferred movement and three out of twenty subjects used non
preferred movement for all three trials.
Table 4.3 : Preferred direction and the brain information pathway for triangular
drawing task
Gaze
Subject
Preference
Lobe
Trace
Pattern
No of
Subject
Lobe
Pattern
7/20
1
P
No of
Subject
6/20
3
2
S11
S9
R
E
F
2
3
7/20
7/20
E
R
1
R
E
D
S4
S4
3
1
3/20
1/20
2
S8
S14
33
2
3/20
3
1
S8
Note :S(X) Refer to number of subject of X in Appendix A
Gaze
Subject
Lobe
Trace
Pattern
Preference
1
of
Lobe
Pattern
Subject
N
O
No
of
Subject
3/20
2
No
3/20
N
3
P
R
S20
1
S20
2
E
F
3
E
R
R
1
2
E
D
3
Note :S(X) Refer to number of subject of X in Appendix A
The result shows that seventeen subject drew triangular task with preferred
movement. It shows that seven out of seventeen subjects gaze the triangular pattern
with source from frontal region. Three subjects used
for motor planning and one
subject used
for mood regulation and emotional expression. Another three
subjects used
for some emotional attention and judgment. A total of seven
34
subjects used parietal area where four subjects used
used
and the other three subjects
where perception midline, praxis and route findings executed during the
performance. Three subjects used
i.e the occipital area, where visual processing
and pattern recognition executed during the performance.
Seventeen out of twenty subjects traced the pattern with preferred
movement. Six subjects used frontal area as sources where four subjects used
motor planning and one subject used
working memory. One subject used
Another four subjects used
for logical attention, decision making and
for mood regulation and emotional expression
and another three subjects used
midline and only one subject used
integration. Two subjects used
for
for perception
as information sources for sensorimotor
and another one used
occipital area, as
information sources where visual processing and pattern recognition executed during
the performances.
Three out of twenty subjects drew the triangular task with non preferred
movement . During gaze trials, one subject used frontal area,
understanding. One subject used
and the another one used
for emotional
for motor planning.
The subject traced the triangular pattern with non preferred movement using frontal
area as information sources. One subject used
judgment and one subject used
for emotional attention and
for motor planning . Only one subject used
where emotional expression and mood regulation executed during performance.
Table 4.4 shows the different result of their brain information pathway during
first orientation drawing task due to handedness. It shows that there is not much
difference on the brain information pathway. In fact, human with the right handed in
their handwriting usually used
used
and human with left handed in their handwriting
[15]. The principal function of C, central area of the brain focuses on the
sensorimotor integration.
35
Table 4.4 : Brain information pathway due to their handness
Subject
Difference
Right Handed
Left Handed
Gaze
Gaze
Trace
Trace
Gaze
Gaze
Trace
Trace
Preference
Difference
1
Difference
2
Table 4.5 shows the brain information pathway during basic drawing task
based on subjects age. It shows that there is not much difference on the brain
information pathway. Thus, it is proven that the relationship between cognitive
ability of understanding spatial and temporal concepts and handwriting are not
affected by a factor of age.
36
Table 4.5 : Brain information pathway due to their age
Total
Year
No ID
Preferred
subject
Task
Non preferred
Pattern
Gaze
1
11
9
S1,T
12
10
8
S1,S2,
Task
Trace
Gaze
S2
T
20
S1,S2
,T
4
9
19
T
S1,S2
17
S1
S2,T
12
S1,S2,
T
2
7
7
S1,S2
T
5
S1,T
S2
Note :S1- First orientation task, S2- Second orientation task, T- Triangular task
No. ID Subject refer to Appendix A
Pattern
Trace
37
4.3
Summary
The information pathways model gives an information signal of the brain
activities while doing a drawing task. The study reveals that most of the subjects
used their motor planning while doing a drawing task.
38
CHAPTER 5
CONCLUSION
5.1
Chapter Overview
This chapter is about the conclusion and summarize of the work analysis. It
also provides some suggestion for future undertaking.
5.2
Conclusion
Handwriting is effective communications that express our thought and
experiences involving complex human activity. To copy a geometric shape, a child
need to analyze the shape, judge the spatial characteristics of shape, sequence of the
stroke line of shape and make an appropriate neuromuscular adjustment.
39
It was intention to investigate the connectivity in brain signal among young
children in relation to the employed strategy while performing basic drawing task.
So, these analyses successfully synthesize the functional connectivity in the brain,
thus the relationship between cognitive ability of understanding the spatial and
temporal concept and handwriting has been explored.
From the analysis of brain signal using PDC, the pattern of information
pathway among young children was described and the preferred movement of each
subject was observed and analyzed. The present result shows that when subject drew
with preferred movement, most information sources come from the frontal (
motor planning, parietal (
occipital (
&
) for
) for perception midline, praxis and route finding and
) for visual processing and pattern recognition . Subject drew with
non preferred rule used frontal region ( ) as their source of functional coupling
where emotional expression and mood regulation executed during performance.
Cortico-cortical connectivity using partial directed coherence may provide
insight on how the brain functions among young children during the basic drawing
task. In fact, partial directed coherence is the best tool that gives the real path of the
information pathway of the brain activity. In conclusion, subject drew with non
preferred rule executed their emotional expression and mood regulation during
performance. While subject drew with preferred rule executed their motor planning,
perception midline, route finding, visual processing and pattern recognition during
performance.
40
5.3
Future Recommendation
Upon the completion of this analysis, the partial directed coherence (PDC)
gives the real path of the information pathway which is manually plot by hand one by
one of each connection. The PDC result give 19 x 19 matrixes diagram and there is
possibility to cause an error such as the channel connection is out of sight as there are
391 boxes of channels in gnu plot diagram [16]. Hence, it is recommended to invent
a new approach to give the real path of information pathways model automatically
rather than manually as it saves time and energy.
41
CHAPTER 6
PROJECT MANAGEMENT
6.1
Chapter Overview
In this chapter, it discusses about the project management to achieve all
project goals by organizing, and controlling resource within a specified time period.
The project schedule had been tabulated on Gantt chart which it gives a clear
guideline in time management of this project. Next, the cost estimation is performed
to ensure a minimal project cost while keeping the project. In this process, the price
of the device is tabulated to compute the final cost.
42
6.2
Project Schedule
Table 6.1 shows the Gannt chart for a project in semester 1. Identify the topic
and research of the project was done in the first and second week. On the third week
until the end research, focuses on the literature review that provide a brief knowledge
and information that covered the whole project. Next, proposal preparation of the
project in week fourth and fifth. The proposal also included the Need, Approach,
Benefit per Cost and Competition (NABC). The submission of the proposal was
done in the sixth week. During sixth and seven week, research instrument used in
this project was discussed.
All of the instruments were available in Advanced
Electronic Lab. Preparation on the experiment was conducted in week seven and
eight. An implementation and testing an experiment were conducted in week nine to
eleven. One of the UTM students was selected as subject. The experiment was
conducted in Advanced Lab. The result was observed and analyzed. It is important,
especially for preliminary result.
Validation experiment was done in week eleven
and twelve. Next, presentation preparation was done in week twelve and thirteen.
Project presentation was done in week fifteen. During week fifteen and sixteen more
focused more on report writing. Report submission was done at the end of the week
which was week sixteen.
43
Table 6.1: The Gannt chart for a project during semester 1.
Week
Task
Identifying
topic and
research
Preparing
literature
review
Preparing the
proposal
Discuss
research
instrument
Preparing the
experiment
sources
Implement
and testing an
experiment
Validation an
experiment
Preparing for
presentation
Presenting
proposal
Report
Writing
Report
Submission
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
44
Table 6.2 shows the Gannt chart for this project in semester 2. In the first
and second week data collection through primary sources was done. The experiment
was conducted in SK Agama UTM. Twenty subjects participated randomly. All the
experimental procedure was completely done. Then, all the collected data were
analyzed in week three until week twelve. The result was observed and analyzed
based on the methodology. Next, report writing of the project in week sixth until
week thirteen.
All of the formats in writing report were considered.
Next,
presentation preparation in week fourteen. Project presentation was done in week
fifteen. Final draft report was revised in week sixteen. Submission of draft report
was done in the week seventeen and handed to the supervisor.
Table 6.2 : Gannt chart for project during semester 2
Week
Task
Collecting
data through
primary
sources
Analyzing
collected
data
Writing
report
Preparing
for
presentation
Presenting
the project
Revising
final report
Report draft
submission
1
2
3
4
5
6 7
8
9
10
11
12
13
14
15
16
17
45
6.3
Cost Estimation
Table 6.3 shows the cost involved for the whole project. For recording EEG
data, the electrode cap applied to the subject scalp and the brain signal was recorded
using Electroencephalogram (EEG machine). The recorded waveform reflects the
cortical activity. Electroencephalogram are cost expensive due to high quality. To
detect and record subject drawing , a portable digitizing tablet was used with a
wireless electronic pen. The time and position of the pen tip were recorded in laptop
computer. After capturing the signal, Linux Fedora 8 was used to compiled and
analyzed the data based on partial directed (PDC) method. This computer already
provided the coding of vector autoregressive, fourier and gnuplot. This LINUX
compiled the program using C language and Octave for signal processing. Tgif was
used to display 19x 19 matrices result of PDC. All of the software are already
provided in the computer (LINUX). Twenty subjects participated randomly. Each
subject get rewarded for their participant.
Table 6.3 : Cost estimation of project
No
Device
1
Electroencephalogram
(Neurofax
Unit
µ
Price
machine 1
RM 70000
EEG-9100J/K,
Nihon Kohden)
2
Portable
(WACOM
digitizing
tablet 1
RM 300
)
3
Computer (LINUX)
1
RM 5000
4
Gift/ Voucher for subject
20
RM 90
TOTAL
RM 75390
46
6.4
Recommendation
The Educationalist and occupational therapist can apply this PDC analysis to
understand handwriting problems among human better. In addition, they also can be
very familiar with the relationship between the cognitive understanding of spatial and
temporal locatives and graphomotor production.
47
REFERENCES
[1].
Alston, J. The handwriting of 7 to 9 years olds. British Journal of Special
Education, 1985. 12: 68-72
[2].
Joseph J. Carr and John M.Brown. Introduction to Medical Equipment
Technology. 4th. ed. New Jersay, USA: Prentice Hall. 2000
[3].
M.J.M., van Schendel, B.M., & Jongmans, M. J.. Handwriting difficulties in
primary school children: A search for underlying mechanism. American Journal of
Occupational Therapy, 2006. 60 : 451-460
[4].
R. G. J Meulenbroek, A. J. W. M Thomassen, J.J Schilings & D. A.
Rosenbaum. Synergies and sequencing in copying L-Shaped patterns. In : M. L.
Simner.
Handwriting and Drawing Research: Basic and applied issues .
Amsterdam, Netherlands : IOI Press. 41-55; 1996
[5].
Simner. M.L. The grammar of action and children printing. Development
Psychology, 1981. 17 : 866-871
[6].
P.I.Khalid,.
J.
Yunos, R Adnan, M.Harun, R.
Sudirman, and N.H.
Mahmood. The use of graphic rules in grade one to help identify children at risk of
handwriting difficulties. Research in Development Disabilities, 2010. 31: 16851693.
[7].
Gillespie, H.M.
Component handwriting skills among early elementary
children with average and below average printing ability.
Northwestern University; 2003
Ph.D.
Thesis,
48
[8].
Khalid, P.I, Yunos, J. & Adnan R. Extraction of dynamic features from hand
drawn data for the identification of children with handwriting difficult. Research in
Development Disabilities, 2010. 31: 256-262.
[9].
Jenny Ziviani & M.Wallen. The development of graphmotor skills in Hand
Function in the child., In A.Henderson and C.Pehoski. Foundation for remediation.
Philadelphia USA : Eds Elsevier. 217-236 ; 2006
[10].
Smits-Engelsman BCM, Van Galen GP. Dysgraphia in Children: Lasting
psychomotor deficiency or transient development delay. Journal of Experimental
Child Psychology, 1997. 67 :164-184.
[11].
Berry KE. The Development Test of Visual Motor Integration. 3rd. ed.
Cleveland, OH : Modern Curriculum Press. 1989
[12].
Yochman A, Parush S. Differences in Hebrew handwriting skills between
Israeli children in second and third grade. Physical and Occupational Therapy in
Pediatrics, 1998. 18(3/4) : 53-65.
[13].
Summers J. Joint laxity in the index finger and thumb and its relationship to
pensil grasps used by children. Australian Occupational Therapy Journal, 2001.
48(3) : 132-141.
[14]. Gerard J.Tortora, Bryan Derrickson. Essential of anatomy and physiology . 8th.
ed. River Street, Hoboken:John Wiley & Sons. 2010
[15].
Walker J.
E, Koozlowski, GP.
and Lawson, R. A Modular
Activation/Coherence Approach to Evaluating Clinical/ QEEG Correlation and for
Guiding Neurofeesback Training: Modular Insufficiences, Modular Excesses,
Disconnections, and Hyperconnections. Journal of Neurotherapy, 2007. 11(1) : 2544.
[16].
Nurul Aquillah Binti Mohd Shafie. Information pathway during mental
arithmetic. Graduate Report Project, Universiti Teknologi Malaysia, Skudai ; 2013
49
[17].
Brillinger D. Remarks concerning graphical model for time series and point
process. Revista de Econometrical, 1996. 16 : 1-23.
[18]. G Tropini and J Chiang. Partial directed coherence-based information flow
in Parkinson's disease patients performing a visually-guided motor task. Engineering
in Medicine and Biology Society, 2009. EMBC 2009. Annual International
Conference of the IEEE. September 2-6,2009. Minneapolis, Minnesota, USA : IEEE.
2009. 1873-1878.
[19].
L.A. Baccala, & K.Sameshima. Partial Directed Coherence: A New Concept
in Neural Structure Determination. Biological Cybernetics, 2001. 84 : 463-474.
[20].
Philipp K.Janert. Data Analysis with Open Source Tools . A hands-on guide
for programmers and data scientists. Sebastopol, CA : O'Reilly Media. 2010
[21].
M. Khazi, A. Kumar and M. J. Vidya. Analysis of EEG using 10:20 electrode
system. International Journal of Innovation Research in Science, Engineering and
Technology, 2012. 1(2): 185-191.
50
APPENDIX A
PREFERRED TRACING DIRECTION AND BRAIN INFORMATION
PATHWAYS DURING DRAWING TASK
LIST OF SUBJECT
1. Subject 1-adam_najmi (S1)
2. Subject 2-aina (S2)
3. Subject 3-annysya (S3)
4. Subject 4-amar (S4)
5. Subject 5-arif (S5)
6. Subject 6-arifah(S6)
7. Subject 7-daniel (S7)
8. Subject 8-fatin najiha (S8)
9. Subject 9-hairuddin (S9)
10. Subject 10-hasnida (S10)
11. Subject 11-harisin (S11)
12. Subject 12-hazim (S12)
13. Subject 13-haziq (S13)
14. Subject 14-ikmal (S14)
15. Subject 15-maya (S15)
16. Subject 16-nabila (S16)
17. Subject 17-shalahuddin (S17)
18. Subject 18-sofea (S18)
19. Subject 19-asyraf (S19)
20. Subject 20-erina (S20)
51
Table 1 : Preferred tracing direction and brain information pathways for subject 1
Subject
ID
Shape
Subject
Condition
S1
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
52
Table 2 : Preferred tracing direction and brain information pathways for subject 2
Subject
ID
Shape
S2
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
53
Table 3 : Preferred tracing direction and brain information pathways for subject 3
Subject
ID
Shape
S3
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
54
Table 4 : Preferred tracing direction and brain information pathways for subject 4
Subject
ID
Shape
S4
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
55
Table 5 : Preferred tracing direction and brain information pathways for subject 5
Subject
ID
Shape
S5
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
56
Table 6: Preferred tracing direction and brain information pathway for subject 6
Subject
ID
Shape
S6
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
57
Table 7 : Preferred tracing direction and brain information pathways for subject 7
Subject
ID
Shape
S7
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
2
Trace
3
First Trial
Second Trial
Third Trial
58
Table 8 : Preferred tracing direction and brain information pathways for subject 8
Subject
ID
Shape
S8
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
59
Table 9: Preferred tracing direction and brain information pathways for subject 9
Subject
ID
Shape
S9
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
60
Table 10: Preferred tracing direction and brain information pathways for subject 10
Subject
ID
Shape
S10
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
61
Table 11: Preferred tracing direction and brain information pathways for subject 11
Subject
ID
Shape
S11
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
62
Table 12: Preferred tracing direction and brain information pathways for subject 12
Subject
ID
Shape
S12
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
63
Table 13: Preferred tracing direction and brain information pathways for subject 13
Subject
ID
Shape
S13
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
2
3
Trace
1
First Trial
Second Trial
Third Trial
64
Table 14: Preferred tracing direction and brain information pathways for subject 14
Subject
ID
Subject
Condition
Shape
S14
Gaze
Trace
Gaze
Trace
Gaze
2
3
1
Trace
First Trial
Second Trial
Third Trial
65
Table 15: Preferred tracing direction and brain information pathways for subject 15
Subject
ID
Subject
Condition
Shape
S15
Gaze
Trace
Gaze
Trace
Gaze
3
1
Trace
2
First Trial
Second Trial
Third Trial
66
Table 16: Preferred tracing direction and brain information pathways for subject 16
Subject
ID
Shape
S16
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
67
Table 17: Preferred tracing direction and brain information pathways for subject 17
Subject
ID
Shape
S17
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
2
Trace
3
First Trial
Second Trial
Third Trial
68
Table 18: Preferred tracing direction and brain information pathways for subject 18
Subject
ID
Shape
S18
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
3
Trace
2
First Trial
Second Trial
Third Trial
69
Table 19: Preferred tracing direction and brain information pathways for subject 19
Subject
ID
Subject
Condition
Shape
S19
Gaze
Trace
Gaze
Trace
Gaze
2
3
Trace
1
First Trial
Second Trial
Third Trial
70
Table 20: Preferred tracing direction and brain information pathways for subject 20
Subject
ID
Shape
S20
Subject
Condition
Gaze
Trace
Gaze
Trace
Gaze
1
2
Trace
3
First Trial
Second Trial
Third Trial
71
APPENDIX B
CODING FOR THE INFORMATION PATHWAY DURING DRAWING TASK
B1: VECTOR AUTOREGRESSIVE COEFFICIENT FUNCTION
B2: PARTIAL DIRECTED COHERENCE FUNCTION
B3: GNUPLOT FUNCTION
72
D1: VECTOR AUTOREGRESSIVE COEFFICIENT FUNCTION
/*##################################################################
Function for Vector AutoRegressive
ARcoeff(int argc, char *argv[ ])
No return value
##################################################################*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include"CSD.h"
void Manual(int argc);
int i, j, k, ch, MAT, start, end, m;
double **data, *datapi;
char fin[20], string[256];
FILE *FIN, *FINOctave;
main(int argc, char *argv[ ]){
/*################START ---- Give EEGs Data Memory
Space################*/
data = (double **)calloc(WANTEDDATA*bilpi,sizeof(double *));
if(data == NULL){
puts("data ¤Î¥á¥â¥ê¤¬³ÎÊݤǤ¤Þ¤»¤ó¡£");
exit(1);
}
for(MAT=0;MAT<(WANTEDDATA*bilpi);MAT++){
*(data + MAT) = (double *)calloc(MATRIX+1,sizeof(double));
if(*(data + MAT) == NULL){
puts("data ¤Î¥á¥â¥ê¤¬³ÎÊݤǤ¤Þ¤»¤ó¡£");
exit(1);
}
}
datapi = (double *)calloc(bilpi,sizeof(double));
if(data == NULL){
50
puts("(ARcoeff) Cannot allocate memory for datapi");
exit(1);
}
/*################END ---- Give EEGs Data Memory
Space################*/
Manual(argc);
system("rm *.pi");
sprintf(fin,"%s.csv",argv[1]);
/* Check file existance */
if((FIN=fopen(fin,"r"))==NULL){
fprintf(stderr,"(ARcoeff) Cannot find %s. \n",fin);
exit(1);
}
73
for(j=0;j<2;j++){
fgets(string,256,FIN);
}
for(j=0;j<WANTEDDATA;j++){
for(i=EEG_START;i<=MATRIX;i++){
fscanf(FIN,"%lf",&data[j][i]);
}
}
fclose(FIN);
start = 0;
end = WANTEDDATA;
for(ch=EEG_START;ch<=EEG_END;ch++){
m=EEG_START;
while(m<=EEG_END){
FINOctave = fopen("pi","w");
if(FINOctave==NULL){
puts("(ARcoeff) Cannot create file=pi\n");
exit(1);
}
k=bilpi-1;
fprintf(FINOctave,"A=[");
for(j=start;j<end;j++){
while(k!=-1){
fprintf(FINOctave,"%lf ", data[j+k][m]);
k--;
51
}
if(j!=(bilpi-1)){
fprintf(FINOctave,";");
}
else{
fprintf(FINOctave,"];");
j= end;
}
k=bilpi-1;
}
k=bilpi;
fprintf(FINOctave,"B=[");
for(j=start;j<bilpi;j++){
fprintf(FINOctave,"%lf",data[j+k][ch]);
if(j!=(bilpi-1)){
fprintf(FINOctave,";");
}
else{
fprintf(FINOctave,"];");
}
}
fprintf(FINOctave,"Atrans=A';");
fprintf(FINOctave,"C=Atrans*A;");
fprintf(FINOctave,"Ains=inv(C);");
74
fprintf(FINOctave,"D=Atrans*B;");
fprintf(FINOctave,"pivalue=Ains*D;");
fprintf(FINOctave,"save pi_value pivalue;");
fprintf(FINOctave,"save inputA A;");
fprintf(FINOctave,"save inputB B;");
fclose(FINOctave);
system("octave -q pi");
/*############### Read pi value and save ############*/
FINOctave = fopen("pi_value","r");
/* Check file existance*/
if(FINOctave == NULL){
puts("(ARcoeff) Cannot read filename=pi_value\n");
exit(1);
}
52
/*Baca isi file*/
for(j=0;j<5;j++){
fgets(string,256,FINOctave);
}
for(j=0;j<bilpi;j++){
fscanf(FINOctave, "%lf",&datapi[j]);
}
fclose(FINOctave);
sprintf(fin,"%s.pi",argv[1]);
/* Check for memory space*/
if((FIN=fopen(fin,"a+"))==NULL){
puts("(ARcoeff) Cannot create filename=%s.pi\n");
exit(1);
}
fprintf(FIN,"%d %d ", ch, m);
for(j=0;j<bilpi;j++){
fprintf(FIN,"%lf ", datapi[j]);
}
fprintf(FIN,"\n");
fclose(FIN);
m++;
}
}
system("mv *.pi PI/");
exit(1);
}
void Manual(int argc){
if(argc != 2){
printf("To run programme type \n");
printf(" ./ARcoeff <filename(*.csv)>\n\n");
exit(1);
}
}
75
D2: PARTIAL DIRECTED COHERENCE FUNCTION
/*##################################################################
Function for FFT for PDC
fourier transform(int argc, char *argv[ ])
No return value
##################################################################*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include"CSD.h"
int MAT, i, j, m;
double sumcos, cosre, ficos, sumsine, sinim, fisin, denom;
double **data, **pdenom, **pdc, **areal, **aimag;
double *CH1,*CH2;
char fin[100], fout[100];
FILE *FIN, *FOUT;
main(int argc, char *argv[]){
/*################Memory Allocation and Initialization################*/
CH1 = (double *)calloc(DOUBLECH,sizeof(double));
if(CH1 == NULL){
puts("CH1 can't allocated");
exit(1);
}
CH2 = (double *)calloc(DOUBLECH,sizeof(double));
if(CH2 == NULL){
puts("CH2 can't allocated");
exit(1);
}
data = (double **)calloc(DOUBLECH +1,sizeof(double *));
if(data == NULL){
puts("data can't allocated");
exit(1);
}
for(MAT=0;MAT<(DOUBLECH+1);MAT++){
*(data + MAT) = (double *)calloc(bilpi,sizeof(double));
54
if(*(data + MAT) == NULL){
puts("data can't allocated");
exit(1);
}
}
pdc = (double **)calloc(DOUBLECH+1,sizeof(double *));
if(pdc == NULL){
puts("pdc can't allocated");
exit(1);
}
for(MAT=0;MAT<(DOUBLECH+1);MAT++){
*(pdc + MAT) = (double *)calloc(FREQ,sizeof(double));
76
if(*(pdc + MAT) == NULL){
puts("pdc can't allocated");
exit(1);
}
}
areal = (double **)calloc(DOUBLECH+1,sizeof(double *));
if(areal == NULL){
puts("areal can't allocated");
exit(1);
}
for(MAT=0;MAT<(DOUBLECH+1);MAT++){
*(areal + MAT) = (double *)calloc(FREQ,sizeof(double));
if(*(areal + MAT) == NULL){
puts("areal can't allocated");
exit(1);
}
}
aimag = (double **)calloc(DOUBLECH+1,sizeof(double *));
if(aimag == NULL){
puts("aimag can't allocated");
exit(1);
}
for(MAT=0;MAT<(DOUBLECH+1);MAT++){
*(aimag + MAT) = (double *)calloc(FREQ,sizeof(double));
if(*(aimag + MAT) == NULL){
puts("aimag can't allocated");
exit(1);
}
}
pdenom = (double **)calloc(DOUBLECH+1,sizeof(double *));
if(pdenom == NULL){
puts("pdenom can't allocated");
exit(1);
}
for(MAT=0;MAT<(DOUBLECH+1);MAT++){
*(pdenom + MAT) = (double *)calloc(FREQ,sizeof(double));
if(*(pdenom + MAT) == NULL){
puts("pdenom can't allocated");
exit(1);
}
}
/*################Give EEGs Data Memory Space################*/
if (argc!=2){
printf("To execute: ==> ./fourier filename(*.pi) \n");
exit(1);
}
sprintf(fin,"%s.pi",argv[1]);
/* Read input file */
if((FIN=fopen(fin,"r"))==NULL){
77
fprintf(stderr,"(Fourier) cannot open file %s\n",fin);
exit(1);
}
for(i=1;i<=DOUBLECH;i++){
fscanf(FIN,"%lf %lf ",&CH1[i], &CH2[i]);
for(j=1;j<=bilpi;j++){
fscanf(FIN,"%lf",&data[i][j]);
}
}
fclose(FIN);
/*################Fourier Transform: cosine series################*/
for(m=1;m<=DOUBLECH;m++){
for(j=1;j<=FREQ;j++){
sumcos = 0.0;
56
for(i=1;i<=bilpi;i++){
cosre = cos(PAI2 * i * j / bilpi);
ficos = data[m][i] * cosre;
sumcos += ficos;
}
if(CH1[m]==CH2[m]){
areal[m][j]= 1 - sumcos;
}
else
areal[m][j] = -1 * sumcos;
}
}
/*################ Fourier Transform: sine series ################*/
for(m=1;m<=DOUBLECH;m++){
for(j=1;j<=FREQ;j++){
sumsine = 0.0;
for(i=1;i<=bilpi;i++){
sinim = sin(PAI2 * i * j / bilpi);
fisin = data[m][i] * sinim;
sumsine += fisin;
}
aimag[m][j] = sumsine;
}
}
/*################ PDC denominator calculation ################*/
for(i=1;i<=EEG_END;i++){
for(j=1;j<=FREQ;j++){
m=i;
denom = 0.0;
while(m<=DOUBLECH){
denom += (areal[m][j] * areal[m][j]) + (aimag[m][j] * aimag[m][j]);
m = m+EEG_END;
}
pdenom[i][j] = denom;
}
78
}
/*################ PDC calculation ################*/
for(i=1;i<=EEG_END;i++){
for(j=1;j<=FREQ;j++){
57
m=i;
while(m<=DOUBLECH){
pdc[m][j] = ((areal[m][j] * areal[m][j]) + (aimag[m][j] *
aimag[m][j]))/(pdenom[i][j]);
m = m+EEG_END;
}
}
}
/*################ save to file the PDC value ################*/
for(m=1;m<=DOUBLECH;m++){
sprintf(fout,"%s_%.lf_%.lf.pdc",argv[1],CH1[m],CH2[m]);
FOUT = fopen(fout, "w");
for(j=1;j<=FREQ;j++){
fprintf( FOUT,"%d %lf\n",j, pdc[m][j]);
}
fclose(FOUT);
}
}
79
D3: GNUPLOT FUNCTION
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <string.h>
#define N 2000
FILE *fpGpFile, *FIN;
int j, k;
float
axisx[]={0,0.07,0.14,0.21,0.28,0.35,0.42,0.49,0.56,0.63,0.7,0.77,0.84,0.91,0.98,1.05,
1.12,1.19,1.26};
float axisy[]={-1.8,-1.7,-1.6,-1.5,-1.4,-1.3 ,-1.2,-1.1,-1.0,-0.9,-0.8,-0.7,-0.6,-0.5,-0.4,0.3,-0.2,-0.1,0.0};
int titlech[]={1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19};
int titlech2[]={1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19};
char fin[100], fout[100];
main(int argc,char *argv[])
{
if(argc!=2){
printf ("To run type ./gnupower <filename>\n");
}
else {
sprintf(fin,"%s",argv[1]);
sprintf(fout,"%s.gp", fin);
/*setting for gnu*/
fpGpFile=fopen(fout,"w"); /*1.change title refer to nashi, vistim and subjectname*/
fprintf(fpGpFile,"set term tgif\n");
fprintf(fpGpFile,"set parametric\n");
fprintf(fpGpFile,"set xtic\n");
fprintf(fpGpFile,"set ytic\n");
fprintf(fpGpFile,"unset key\n");
fprintf(fpGpFile,"set output '%s.obj'\n", fin);/*2.change outputname and folder*/
fprintf(fpGpFile,"set yrange[0:1]\n");
fprintf(fpGpFile,"set xrange[0:3]\n");
fprintf(fpGpFile,"set size square 0.06,0.15\n");
fprintf(fpGpFile,"set pointsize 0.0000001\n");
fprintf(fpGpFile,"set rmargin 0\n");
fprintf(fpGpFile,"set lmargin 0\n");
59
fprintf(fpGpFile,"set tmargin 0\n");
fprintf(fpGpFile,"set bmargin 0\n");
fprintf(fpGpFile,"set multiplot\n");
fprintf(fpGpFile,"pause 1\n");
/*all channel*/
for (k=0;k<19;++k){
for (j=0;j<19;++j)
{
fprintf(fpGpFile,"set origin %.2f,%.1f\n",axisx[j],axisy[k]);
80
fprintf(fpGpFile,"plot'%s_%i_%i.pdc'using1:2with
lines\n",fin,titlech[j],titlech2[k]);/*3.change the input name and folder*/
fprintf(fpGpFile,"pause 1\n");
}
}
fprintf(fpGpFile,"unset multiplot\n");
fclose(fpGpFile);
}
system ("gnuplot lihting_control6.gp");
}