An HCI Principles based Framework to Support Deaf Community

(IJEACS) International Journal of Engineering and Applied Computer Science
Volume: 02, Issue: 02, February 2017
DOI: 10.24032/IJEACS/0202/02
ISBN: 978-0-9957075-3-5 www.ijeacs.com 47
An HCI Principles based Framework
to Support Deaf Community
Fazal Qudus Khan
Department of Information Technology
FCIT, King Abdulaziz University
Jeddah
Saudi Arabia
Asif Irshad Khan
Department of Computer Science
FCIT , King Abdulaziz University
Jeddah
Saudi Arabia
Mohammed Basheri
Department of Information Technology
FCIT, King Abdulaziz University
Jeddah
Saudi Arabia
Abstract— Sign language is a communication language
preferred and used by a deaf person to converse with the
common people in the community. Even with the
existence of the sign language, there exist a
communication gap between the normal and the
disable/deaf person. Some solutions such as sensor gloves
already are in place to address this problem area of
communication, but they are limited and are not covering
all parts of the language as required by the deaf person
for the ordinary person to understand what is said and
wanted? Due to the lack of credibility of the existing
solutions for sign language translation, we have proposed
a system that aims to assist the deaf people in
communicating with the common people of the society
and helping, in turn, the disabled people to understand
the healthy (normal people) easily. Knowing the needs of
the users will help us in focusing on the Human
Computer Interaction technologies for deaf people to
make it further more a user-friendly and a better
alternative to the existing technologies that are in place.
The Human Computer Interface (HCI) concept of
usability, empirical measurement and simplicity are the
key consideration in the development of our system. The
proposed Kinect System removes the need for physical
contact to operate by using Microsoft Kinect for Windows
SDK beta. The result shows that the It has a strong,
positive and emotional impact on persons with physical
disabilities and their families and friends by giving them
the ability to communicate in an easy manner and non-
repetitive gestures.
Keywords- Human Computer Interaction, Design,
Human Factors, Deaf, Sign Language Synthesis, Kinect
Devic.
I. INTRODUCTION
It has been noticed that deaf person face many
difficulties when they try to communicate with their
community by sign language especially in public
places like hospitals, hotels, and markets. That is
what usually forces them to accompany individuals to
help them to get their needs. For this reason, this
research focuses on suggesting an HCI based solution
using technology that may give them a chance to
depend on themselves and get out from their solitude.
This research work target for people with disabilities
(deaf people). Al-Amal Institute that deals with such
cases were contacted to test the proposed system and
study the impact of the application on deaf people. A
system which is based on HCI Framework is
proposed to help the deaf community people to
understand and use it easily. This system would
provide:
- Easy-to-use user interfaces activated by hand
motions.
- An economical IT solution for deaf and dumb
people rather than accompanying individuals to help
them get their needs.
- An efficient IT solution rather than other IT
technologies and solutions such as the sensor gloves
that are used in translating sign language. KTDP
system can work in any public place at any time as
well as it can recognize the motion of the head, arms,
hands, and fingers.[9]
The proposed solution for the previous problem is
developing a system consists of Kinect device as
shown in figure 1, PC, and a database. Kinect is
Microsoft‟s motion sensor add-on for the Xbox 360
gaming console. The device provides a natural user
interface (NUI) that allows users to interact
intuitively and without any intermediary device, such
as a controller in the middle [1,3].
The database contains a set of images that
represent a dictionary for the sign language; each
image is stored with a particular meaning. By
programming the Kinect device, it will be responsible
for capturing and detecting the motion of the deaf
then sending the captured scene or image to the PC.
The PC then will compare between the captured
image and the images in the database using the
appropriate matching algorithm. After matching the
images, the PC will show the text of the captured
image. Subsequently, this system is considered as a

Fazal Qudus Khan et al. (IJEACS) International Journal of Engineering and Applied Computer Science
DOI: 10.24032/IJEACS/0202/02
mediator between healthy people and those of special
needs. As mentioned previously, we called this
system Kinect Technology for Deaf People (KTDP).
Figure 1. Shows how the system works.
This paper is organized as follows: section I
introduction of the paper, sections II discusses the
related work, section III the proposed Framework,
section IV result of implementation and testing of the
framework, and lastly section V the conclusion and
future work.
II. RELATED WORK
Michelangelo in one of his famous brainy quote
said “If people only knew how hard I work to gain
my mastery, it would not seem so wonderful at all”
from this saying we realize that hard work makes us
prepared to face adverse situations. Hard work helps
any student to become extraordinary. It's the key to
success. Hence, we believed that we need to keep
working patiently and hardly till the goal of our
project is achieved. To us, we need to "see a little
further into the sea" that we had to search efficiently,
read deeply a lot of scientific websites and books of
different fields and topics to get the best information
and reference required for the project to keep going
on.
Yasir Niaz Khan and Syed Atif Mehdi in their
article describe the use of a device known as the
Sensor gloves. This device is made of cloth attached
with sensors.While they suggest that the utilization of
a device called ““the data glove” is a better choice
over the utilization of a traditional camera, the reason
being that the user has the flexibility of free
movement which is dependent on the length of wire
connecting the glove to the computer. However,
when the camera is used, the user should stay in
position in front of the camera. The gloves
performance is not affected by any disturbing factor
i.e. electromagnetic fields, the light or any other
disturbances.[8]
In total seven (7) sensor glove of 5DT Company
were used in their system out of which five (5)
sensors are used for the fingers and thumb. While
among the two sensors left, the sixth sensor is used to
measure the tilt motion of the hand and the seventh or
the last sensor is used for the rotation motion of the
hand. While the flexure of the fingers is measured by
the Optic fibers which are placed on the gloves.[8]
The project under discussion uses only postures
because of the reason that the glove can only capture
the shape of the hand and not the skeleton/shape or
motion of any other part of the body. Among the
Signs, there are two letters for which the signs are
ignored and those are for letters "j" and "z" because
they involve moving gestures. Only Two special
signs i.e. Space between words ( ) and Full stop (.)
were added to the input set. There was no compulsion
in doing so but they have been added as to perform
Basic English sentence writing functionality.[8]
Among the problems mentioned by the authors of the
article, One of the problems was that some letters
were left out of the domain of the project as they
involved dynamic gestures and may not be
recognized using this glove. The use of two sensor
gloves was not tested out and another problem was
that some gestures require the use of both hands
which was not discussed in the project.[8]
The article "Multiperspective Thermal IR and
Video Arrays for 3D Body Tracking and Driver
Activity Analysis" by Shinko Y. Cheng, Sangho
Park, Mohan M. Trivedi focused on the body part
movement for driver alertness. They develop the
system to determine the used multi-perspective (i.e.
four camera views) multimodal (i.e., thermal infrared
and color) video-based system for robust and real-
time 3D tracking of important body parts and to track
some other things like head and hand motions during
the driving. So their focus was on tracking in a noisy
environment to avoid accidents while adopting the
said system for the sign language is not a cost
effective solution, as many sensors and furthermore,
a lot of image processing is involved, which makes
the system more complicated and less efficient.[11]
A. Comparing methods to find information First
approach; using the internet
Strength
 The availability of internet all the time (24
hours a day, 7 days a week). [2]
 Cheap resource.
 A resource that has a huge amount of rich
and useful information.
 The existence of search engines helps us a
lot.
 Getting latest and up-to-date of information.

DOI: 10.24032/IJEACS/0202/02
Weakness
 We face some difficulties to find the
information that we need especially when
we are looking for a small point.[3]
 There is much wrong information on the
internet so we cannot trust everything we
read on the internet.
 We must verify the reliability of information
source before using them.
B. Second approach: using the interviews
Strength
 Making interviews help us to get
information from experts.
 The ability to get more details in specific
knowledge area or field.
Weakness
 Facing difficulties to make appointments
with some responsible people.[3]
 Hiding some correct information could
happen during the meeting from some
people.[3]
III. THE PROPOSED FRAMEWORK
Figure 2 HCI Principles based Framework for the proposed
system.
The proposed system as shown in figure 2 is
based on the HCI Principles theories exist relating
different design and user consideration. The user
requirements consideration of the system is based on
how the user communicate with the Kinect device
and how it is interpreted? Here we consider Several
elements that influence the way the model is
developed, tested and maintained. At the Deaf users'
side: their understanding of the sign language, as they
will give input to the system. At the Normal Person
users' side: their understanding of the Arabic
language, who will see the interpretation of the
gestures.
Design considerations:
This system is developed for the especially needed
person, a user-friendly application is proposed that
should help the users to form the correct productive
rational interpretation on the screen of the given
gesture by the deaf person. Common design methods
that are considered in our design include the
following factors:
 Simplicity in Gestures interpretation:
Frequently and commonly used gestures by the deaf
person are to be focused so that the interpreted
function should be easily readable and
understandable by a normal person. commonly used
simple gestures by the deaf person will be considered
for interpretation rather than asking the deaf person
to memorize a new gesture for the system
requirement, So that the system should be easy to
understand and simple to use and transparent enough
for the user to concentrate on the actual meaning or
message of the sign that is used.
 Familiarity with the sign language:
As this framework is built upon concrete requirement
determination, it is very important to use this fact in
designing a system. Relying on sign language the
deaf people are familiar, this system is designed in
such a way so that the familiarity factor within our
system must be addressed and prioritized.
 Availability of options:
Since recognition is always better than remembering
of the options available, Our system is efficient
enough in terms of the user friendly interface and the
options that we are providing, that it always suggest
help in the form of animations and visual elements to
ease the user to recall the functionality of the system.
 Flexibility:
The user will be able to use any hand, in the same
sequence that the sign language use and the system
will be flexible enough to handle it, at any time.
 System Feedback:
The Kinect device reads the movement of the
gestures continuously and gives feedback through the
system, through the action/hands movement of the
deaf user. We understand that the prompt feedback
helps to assess the correctness of the sequence of
actions and that is the reason this feature is of high
priority to us in our proposed framework.

DOI: 10.24032/IJEACS/0202/02
3.1 SYSTEM DETAILS
A. Managing the database
Description: This system is mainly depending on its
database in which it is impossible to accomplish the
main functionality of the system without it. After
creating the database, the administrator must be able
to add, delete, and manage the elements of the
database.
Priority: this function has a very high priority due to
its role in the system.
Requirements:
1- Database to store the data.
2- Enough storage capacity.
3- Administrator to manage the database.
B. Making gestures
Description: special needs person has to stand in
front of the Kinect device and make some motions or
gestures that can be translated to text according to
sign language rules.
Priority: this function has a high priority because it is
considered as an essential pillar of our system as
well.
Requirements:
1- Special needs person to make the motions.
2- Kinect device to detect the motion.
3- A program to translate the motion into text.
C. Reading gesture translation
Description: after detecting a motion by Kinect
device, the appropriate text will appear on the screen
to show the meaning of that motion to normal people.
Priority: this function has a moderate priority because
the system can work and accomplish its main
functionality without the existence of the normal
people to read.
Requirements:
1- Kinect device to detect the motions.
2- A program to translate the motion into text.
3- PC screen to show the translated text.
4- Normal people to read the translated text.
As shown in Figure 3, the use case diagram of the
system, there are three main actors / stakeholders of
the system, the Deaf person can make a gesture
which is translated by the system into a plain English
text and the normal person (with whom the disable
person wish to communicate) can see the message on
the screen. The developer of the system can add more
gestures in future to enhance the system. Currently,
only few gestures with basic needs are programmed.
Figure 3. Shows high view of the main system requirements.
3.2 NON-FUNCTIONAL REQUIREMENTS
The non-functional requirements are not
fundamental like functional requirements. They
represent the qualities of our system. The KTDP
system requires the following non-functional
requirements to be filled in:
- Modifiability: the admin need to add more gestures,
so modifiability is required as to enhance the system
in future. We will make admin rights for the code to
be modified.
- Usability: the system is useful if it can help the Deaf
community, For usability, the device need to be
installed with the modifications that we do in the
using the Kinect SDK.
- Response time: a quick response time is required,
this can be achieved if the device is in range.
A. Data requirements
After making several meetings with instructors and
doctors that have a good experience in our project
fields, and after looking in similar projects and
literature searches, our team concludes what data
should be stored in the database. The database should
include the following data:
- The Sign Language gesture's data.
- The Meanings of each gesture's data.
- The Administrator's data to add and delete gestures
and its meaning.

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3.3 DESIGN AND METHODOLOGY OF
GESTURES RECOGNITION
A. Methodology of Gestures Recognition
Gesture recognition in our system as shown in
figure 4, can be explained in three steps; getting
joints positions, comparing the position of some
joints with the other joints positions, and generating a
value for each gesture depending on the comparison
step. [4]
Using the skeleton tracking feature that the
Kinect device provide, we can track up to 20 joints in
the user body who stands in front of the Kinect. In
our system, we are interested in 14 joints which are in
upper half of the body. [9]
By tracking these joints, we can get the position
of each one as X, Y, and Z coordinates. After that,
the system will go through 25 conditions ( IF
statements ) that we built in the code to compare the
positions of right hand, left hand, right elbow, and
left elbow with each other and with the rest of the 14
joints. Each condition will result in one bit ( 1 or 0 )
and add it to a variable, let us call it "value_word".
[7, 10]
Finally, the value_word variable will be a bit
pattern consists of 25 ones and zeros, and this pattern
could not be repeated for more than one gesture as
each gesture differs at least in one joint position from
others. This value is converted from binary to
decimal before being saved in the database. By this
way, the system can recognize up to 2 different
gestures. Each gesture represented by one unique
value. The following figure(figure 8.1.1) shows how
the system compares joints positions then generates a
value for the gesture. [7, 10]
For adding a new gesture to system purpose, we
only need to store the generated value in the database
as primary key with its title and id. On the other
hand, recognizing the gestures and showing their
meanings after they being added can be done by
comparing the values generated while the deaf user is
making gestures with the stored values in the
database. If one value produced by deaf user gesture
matches one stored value, then the title will appear on
the screen.
3.4 ANALYSIS DONE FOR THE REQUIREMENT
There are many useful ways to collect data from
different sources. One of them is making interviews
and meetings with experienced persons who could
give us valued information about our project.
Besides, questionnaires could also be necessary to get
feedbacks and opinions from large samples of
different classes of the society. As well, searching
and browsing the internet is a very important
technique that makes us able to find huge amounts of
both practical and theoretical information that is
useful for our project. This way of collecting
information could be much better in saving efforts,
time, and money than going to libraries and searching
for specific books.[2]
Figure 4. Gesture recognition
A. Questionnaire Analysis
a survey was conducted online, and the results were
analyzed. In the following section, we list the
requirements confirmation based on the questionnaire
results.
Results of main questions:
As can be seen in figure 5, the statics of questionnaire
showed good result that prove the importance of our
project i.e. 94% of normal people don't understand
the sign language. Also, 89% of them think that deaf
people live in isolation of the society. Based on the
previous percentages, we have verified on the
importance and the benefits of our system for the
society.
Figure 5. Statics of the questionnaire
as can be seen in figure 6, shows that the most of the
respondents i.e. about 72% of people see it 's hard to
communicate with deaf people and 89% of them
prefer to use the technology in translating the sign
language so that it could be a moderator between
them and deaf people.

DOI: 10.24032/IJEACS/0202/02
Figure 6. Statics of the questionnaire
B. Interview Analysis
Results of main questions:
The following is a list of the most important points
that we conclude from the conversation with him:
 Deaf people live in isolation everywhere
they go in their community.
 The Arabic Sign Language has not unified
completely yet.
 The most of the sign language gestures can
be made by only one hand.
 Deaf people can read and understand simple
words. On the other hand, they cannot read
or write long, complex sentences and
paragraphs.
 Al-Amal Institute will help us anytime we
need help even if we need a sign language
translator to work with us.
3.4 MODELING OF THE SYSTEM
The static model (class modelling) of the proposed
system is shown in figure 7.
Figure 7. Shows class diagram of the system
Figure 8. Shows sequence diagram of the system
The sequence diagram is necessary to show the
sequence of steps that occurs while using the system.
In the generic sequence diagram illustrated in figure
8, first, the registration and login process take place
to confirm whether the user is a normal user or an
admin. The Administrator can add gestures and its
subsequent meaning in the system. While once the
normal user is logged into the system after that
different gestures that are performed by the disabled
person are translated and delivered to the screen
where the normal user can see them in plain English
text.
While the HCI based User Interface is shown in
figure 9.
Figure 9. HCI based User Interface

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IV. IMPLEMENTATION AND TESTING RESULTS
After implementing the system, the following are
the interfaces that the user will interact with:
The main interface
When the user runs the program, the following
interface as can be seen in figure 10, appears
Figure 10. Main interface
It contains 7 buttons. As default, 5 buttons of
them are enabled and the other two are disabled. The
buttons are :
- About button: This button moves the users to
another window which show information about the
authors who builds the system. This button is enabled
for all users as default. If the users press this button
the following window will appear
- Login button: This button is used by admins to
login to the system as admin user. This button is
enabled for all users as default. After clicking on this
button another window will appear that asks the user
to enter the username and password to authorize the
admins. After clicking the Login button the following
window as shown in figure 11, appears
Figure 11. Admin Log-In interface
If the user is successfully authorized, the system will
move the user to the main interface again but all
buttons will be enabled as can be seen in figure 12
below.
Figure 12. Main interface admin user
- Start button : This button is used to start
recognizing the gestures made by the deaf user. This
button is enabled for all users as default. After
clicking on this button, another window will appear
that contains Title ID, Title, and Word value fields
that will show the id of the gesture, the text meaning
of the gesture, and the value generated by that gesture
respectively. Also, the window contains two squares.
The left one used to show the skeleton of the user and
the other one shows the complete sentence of group
of gestures. After clicking the Start button the
following window figure 13, appears [5,6]
Figure 13. Data information interface
- Learn Motion button: This button moves the user to
the system dictionary which has the gestures titles
and their photos. This dictionary helps the users to
learn how to make gestures. In the dictionary
window, the user can search for a certain gesture by
its title. This button is enabled for all users as default.
After clicking on this button, another window will
appear that contains a list of gestures and their values
as well as an area for showing the photos of the
gestures. After clicking the Learn Motion button the
following window figure 14, appears

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Figure 14. Dictionary interface
- Data button: This button is enabled only for admins
after logging in the system. This button moves the
admin to the window that makes him able to add,
update and delete gestures. After clicking on this
button, another window will appear that contains
buttons, text fields, gestures list, area for skeleton
view, and area for normal camera view. After
clicking the Start button, the following window
appears (Figure 15).
The Clear button clears the texts fields. Add, Update,
Delete buttons are used to add, update, and delete
system's gestures. Start button starts the skeleton
view. Close button closes the window. Find Value
button shows the value of a gesture. Select Image is
used to choose an image for a gesture to be added to
the dictionary. The rest two button are Take Photo,
and Capture.
The first one shows the standard camera view, and
the second one used to capture a photo using the
camera. When the admin wants to add a new gesture,
he should go through some steps respectively.
Figure 15. Data information(Admin interface)
First he should press the Start button. Then he should
fill the text fields. After that, he has to select an
image for the gesture. Finally, he can add the gesture
to the database by clicking on Add button.
- User Data button: This button is enabled only for
admins after logging in the system. This button
moves the admin to the window that makes him able
to add, update and delete admin users. After clicking
on this button, another window will appear that
contains a list of admin users and their information,
some buttons, and some text field to enter admin
data. After clicking the User Data button the
following window figure 16, appears.
Figure 16. Admin information interface
- Exit button: This button is used to close the system.
TESTING THE SYSTEM
In testing the recognition of the system, we selected
Ten (10) gestures randomly to be tested by some
people and us.
Figure 17. Gesture recognition testing(1)
The gestures are shown below Figure 17 till figure
26, with their skeleton views:

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Figure 19. recognition testing(3)
Three other persons have tested this system. Each
gesture of the ten gestures has been repeated five
times by each. Appendix shows This system has
been tested by 3 other persons. Each gesture of the 10
gestures has been repeated 5 times by each person.

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V. CONCLUSIONS AND FUTURE WORK
The aim of this research study is to support and
help deaf persons in communicating with their
community by using a KTDP system. The system
translates the body gestures made by deaf users into
text.
The system has a manual for the gestures that can
be recognized. Also, the system gives the admin the
ability to add new gestures easily.
The HCI concept of usability, empirical measurement
and simplicity are the key consideration in the
development of our system. In future, the research
will focus to include finger recognition to make it
able to translate the whole official sign language
gestures.
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[8] Mehdi, Syed Atif, and Yasir Niaz Khan. "Sign language
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AUTHOR'S PROFILE
Fazal Qudus Khan, M.Sc, is working as a faculty member in the
department of Information Technology, FCIT, King Abdulaziz
University, Jeddah, Saudi Arabia. He has over eleven years of
experience (Two years Industrial experience with more than nine
years in academia and research). Mr. Khan is currently a Ph.D.
candidate at the University of Kuala Lumpur, Malaysia. He has
received M.Sc. in Computer and Network Engineering from
Sheffield Hallam University, Sheffield, UK & Bachelor degrees in
Information Technology from NWFP Agricultural University,
Peshawar, KPK Pakistan. He has published several research
articles in leading journals and conferences; his current research
interest includes Software Engineering with a focus on Component
Based and Software Product Line Engineering. He can be reached
at fqkhan@kau.edu.sa.
Asif Irshad Khan, Ph.D., is working as a faculty member in the
department of Computer Science, FCIT, King Abdulaziz
University, Jeddah, Saudi Arabia. He has thirteen years of
experience as a professional academician and researcher. Dr.
Khan received Ph.D. in Computer Science and Engineering from
Singhania University, Rajasthan, India, and Master & Bachelor
degrees in Computer Science from the Aligarh Muslim University
(A.M.U), Aligarh, India. He has published several research
articles in leading journals and conferences. He is a member of the
editorial boards of international journals, and his current research
interest includes Software Engineering with a focus on Component
Based and Software Product Line Engineering. He can be reached
at aikhan@kau.edu.sa.
Mohammed Basheri, Ph.D., is an Assistant Professor and the
Chairman of Information Technology Department at the Faculty of
Computing and Information Technology in King Abdulaziz
University, Saudi Arabia. He has fifteen years of experience as a
professional academic. Dr. Basheri received PhD in Computer
Science from the School of Engineering and Computer Science at
Durham University, UK. He received Master of Information
Technology from Griffith University, Australia and Bachelor in
Computer Education from King Abdulaziz University, Saudi
Arabia. His current research interest is in HCI and E-learning. He
can be reached at mbasheri@kau.edu.sa.

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Appendix: The following are the tests summaries
Fig. The first test

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Fig. The second test

DOI: 10.24032/IJEACS/0202/02
Fig. The third test
© 2017 by the author(s); licensee Empirical Research Press Ltd. United Kingdom. This is an open access article
distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license.
(http://creativecommons.org/licenses/by/4.0/).

An HCI Principles based Framework to Support Deaf Community

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