1.
T
TO
OP
P 1
10
0 M
MO
OS
ST
T C
CI
IT
TE
ED
D
A
AR
RT
TI
IC
CL
LE
ES
S I
IN
N J
JA
AN
NU
UA
AR
RY
Y
2
20
02
23
3
H
He
ea
al
lt
th
h I
In
nf
fo
or
rm
ma
at
ti
ic
cs
s -
- A
An
n I
In
nt
te
er
rn
na
at
ti
io
on
na
al
l
J
Jo
ou
ur
rn
na
al
l (
(H
HI
II
IJ
J)
)
https://airccse.org/journal/hiij/index.html

2.
A SYSTEMATIC LITERATURE REVIEW OF CLOUD
COMPUTING IN EHEALTH
Yan Hu and Guohua Bai
Department of Creative Technologies, Blekinge Institute of Technology, Sweden
ABSTRACT
Cloud computing in eHealthis an emerging area for only few years. There needs to identify the
state of the art and pinpoint challenges and possible directions for researchers and applications
developers. Based on this need, we have conducted a systematic review of cloud computing in
eHealth. We searched ACM Digital Library, IEEE Xplore, Inspec, ISI Web of Science and
Springer as well as relevant open-access journals for relevant articles. A total of 237 studies were
first searched, of which 44 papers met the Include Criteria. The studies identified three types of
studied areas about cloud computing in eHealth, namely (1) cloud-based eHealth framework
design (n=13);(2) applications of cloud computing (n=17); and (3) security or privacy control
mechanisms of healthcare data in the cloud (n=14). Most of the studies in the review were about
designs and concept-proof. Only very few studies have evaluated their research in the real world,
which may indicate that the application of cloud computing in eHealth is still very immature.
However, our presented review could pinpoint that a hybrid cloud platform with mixed access
control and security protection mechanisms will be a main research area for developing citizen
centred home-based healthcare applications.
KEYWORDS
Systematic review, eHealth, cloud computing, home-based healthcare
For More Details: http://airccse.org/journal/hiij/papers/3414hiij02.pdf
Volume Link: https://airccse.org/journal/hiij/Current2014.html

3.
REFERENCES
[1] “WHO | E-Health,” WHO. [Online]. Available: http://www.who.int/trade/glossary/story021/en/.
[Accessed: 09-Feb-2014].
[2] P. Mell and T. Grance, “The NIST definition of cloud computing,” Natl. Inst. Stand. Technol., vol. 53,
no. 6, p. 50, 2009.
[3] W. Afzal, R. Torkar, and R. Feldt, “A systematic review of search-based testing for non-functional
system properties,” Inf. Softw. Technol., vol. 51, no. 6, pp. 957–976, Jun. 2009.
[4] A. Jovell and M. Navarro-Rubio, “Evaluation of scientific evidence,” Med. Clínica, vol. 105, no. 19, p.
740, 1995.
[5] S. Keele, “Guidelines for performing Systematic Literature Reviews in Software Engineering,” EBSE
Technical Report EBSE-2007-01, 2007.
[6] C. O. Rolim, F. L. Koch, C. B. Westphall, J. Werner, A. Fracalossi, and G. S. Salvador, “A Cloud
Computing Solution for Patient’s Data Collection in Health Care Institutions,” in 2010 Second International
Conference on eHealth, Telemedicine, and Social Medicine (ETELEMED), 10-16 Feb. 2010, 2010, pp. 95–
9.
[7] E. Hendrick, B. Schooley, and C. Gao, “CloudHealth: Developing a reliable cloud platform for
healthcare applications,” in 2013 IEEE 10th Consumer Communications and Networking Conference,
CCNC 2013, January 11, 2013 - January 14, 2013, 2013, pp. 887–891.
[8] O. Gul, M. Al-Qutayri, C. Y. Yeun, and Q. H. Vu, “Framework of a national level electronic health
record system,” in 2012 International Conference on Cloud Computing Technologies, Applications and
Management (ICCCTAM), 2012, pp. 60–65.
[9] M. R. Patra, R. K. Das, and R. P. Padhy, “CRHIS: Cloud Based Rural Healthcare Information System,”
in Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance, New
York, NY, USA, 2012, pp. 402–405.
[10] R. Smith, J. Xu, S. Hima, and O. Johnson, “Gateway to the Cloud - Case Study: A Privacy-Aware
Environment for Electronic Health Records Research,” in 2013 IEEE 7th International Symposium on
Service Oriented System Engineering (SOSE), 2013, pp. 292–297.
[11] N. Regola and N. V. Chawla, “Storing and Using Health Data in a Virtual Private Cloud,” J. Med.
Internet Res., vol. 15, no. 3, p. e63, Mar. 2013. [12] G. Martinovic and B. Zoric, “E-health Framework
Based on Autonomic Cloud Computing,” in 2012 Second International Conference on Cloud and Green
Computing (CGC), 2012, pp. 214–218.
[13] B. Coats and S. Acharya, “Achieving electronic health record access from the cloud,” in
HumanComputer Interaction: Applications and Services. 15th International Conference, HCI International
2013, 21-26 July 2013, 2013, vol. pt. II, pp. 26–35.
[14] E. Ekonomou, L. Fan, W. Buchanan, and C. Thuemmler, “An integrated cloud-based healthcare
infrastructure,” in 2011 3rd IEEE International Conference on Cloud Computing Technology and Science,
CloudCom 2011, November 29, 2011 - December 1, 2011, 2011, pp. 532–536.
[15] F. Amato, A. Mazzeo, V. Moscato, and A. Picariello, “A Framework for Semantic Interoperability over
the Cloud,” in 2013 Workshops of 27th International Conference on Advanced Information Networking and
Applications (WAINA), 25-28 March 2013, 2013, pp. 1259–64.
[16] A. S. Radwan, A. A. Abdel-Hamid, and Y. Hanafy, “Cloud-based service for secure electronic medical
record exchange,” in 2012 22nd International Conference on Computer Theory and Applications, ICCTA
2012, October 13, 2012 - October 15, 2012, 2012, pp. 94–103.
[17] S. Alshehri, S. P. Radziszowski, and R. K. Raj, “Secure access for healthcare data in the cloud using
ciphertext-policy attribute-based encryption,” in 2012 IEEE International Conference on Data Engineering
Workshops (ICDEW 2012), 1-5 April 2012, 2012, pp. 143–6.
[18] F. Rahman, S. I. Ahamed, Ji-Jiang Yang, and Qing Wang, “PriGen: a Generic Framework to Preserve
Privacy of Healthcare Data in the Cloud,” in Inclusive Society: Health and Wellbeing in the Community,
and Care at Home. 11th International Conference on Smart Homes and Health Telematics, ICOST 2013,
19-21 June 2013, 2013, pp. 77–85.
[19] Y. Hu, F. Lu, I. Khan, and G. Bai, “A cloud computing solution for sharing healthcare information,” in
Internet Technology And Secured Transactions, 2012 International Conferece For, 2012, pp. 465– 470.
[20] Shilin Lu, R. Ranjan, and P. Strazdins, “Reporting an Experience on Design and Implementation of
eHealth Systems on Azure Cloud,” in Internet and Distributed Computing Systems. 6th International
Conference, IDCS 2013, 28-30 Oct. 2013, 2013, pp. 145–59.

4.
[21] A. Benharref and M. A. Serhani, “Novel Cloud and SOA-based Framework for E-health Monitoring
Using Wireless Biosensors,” IEEE J. Biomed. Health Inform., vol. 18, no. 1, pp. 46–55, Jan. 2014.
[22] R. Wooten, R. Klink, F. Sinek, Y. Bai, and M. Sharma, “Design and implementation of a secure
healthcare social cloud system,” in 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid
Computing, CCGrid 2012, May 13, 2012 - May 16, 2012, 2012, pp. 805–810.
[23] S. Mohammed, D. Servos, and J. Fiaidhi, “Developing a Secure Distributed OSGi Cloud Computing
Infrastructure for Sharing Health Records,” in Autonomous and Intelligent Systems. Second International
Conference, AIS 2011, 22-24 June 2011, 2011, pp. 241–52.
[24] G. S. Bhange and S. R. Hiray, “Dental Patient Records Maintenance on Cloud Computing Using Data
Protection Model,” in Proceedings of the CUBE International Information Technology Conference, New
York, NY, USA, 2012, pp. 526–531.
[25] A. Bahga and V. K. Madisetti, “A Cloud-based Approach for Interoperable Electronic Health Records
(EHRs),” IEEE J. Biomed. Health Inform., vol. 17, no. 5, pp. 894–906, Sep. 2013.
[26] L. Fan, W. Buchanan, C. Thummler, O. Lo, A. Khedim, O. Uthmani, A. Lawson, and D. Bell,
“DACAR Platform for eHealth Services Cloud,” in 2011 IEEE International Conference on Cloud
Computing (CLOUD), 2011, pp. 219–226.
[27] J. Vilaplana, F. Solsona, F. Abella, R. Filgueira, and J. Rius, “The cloud paradigm applied to eHealth,”
BMC Med. Inform. Decis. Mak., vol. 13, no. 1, p. 35, Mar. 2013.
[28] P. Van Gorp and M. Comuzzi, “Lifelong Personal Health Data and Application Software via Virtual
Machines in the Cloud,” IEEE J. Biomed. Health Inform., vol. 18, no. 1, pp. 36–45, Jan. 2014.
[29] Ruoyu Wu, Gail-Joon Ahn, and Hongxin Hu, “Secure sharing of electronic health records in clouds,”
in 2012 8th International Conference on Collaborative Computing: Networking, Applications and
Worksharing (CollaborateCom 2012), 14-17 Oct. 2012, 2012, pp. 711–18.
[30] S. Basu, A. H. Karp, Jun Li, J. Pruyne, J. Rolia, S. Singhal, J. Suermondt, and R. Swaminathan,
“Fusion: Managing Healthcare Records at Cloud Scale,” Computer, vol. 45, no. 11, pp. 42–9, Nov. 2012.
[31] M. Rodriguez-Martinez, H. Valdivia, J. Rivera, J. Seguel, and M. Greer, “MedBook: A cloud-based
healthcare billing and record management system,” in 2012 IEEE 5th International Conference on Cloud
Computing, CLOUD 2012, June 24, 2012 - June 29, 2012, 2012, pp. 899–905.
[32] Ruoyu Wu, Gail-Joon Ahn, and Hongxin Hu, “Towards HIPAA-Compliant Healthcare Systems in
Cloud Computing,” Int. J. Comput. Models Algorithms Med., vol. 3, no. 2, pp. 1–22, Apr. 2012.
[33] O. Gul, M. Al-Qutayri, Q. H. Vu, and C. Y. Yeun, “Data integration of electronic health records using
Artificial Neural Networks,” in 7th International Conference for Internet Technology and Secured
Transactions, ICITST 2012, December 10, 2012 - December 12, 2012, 2012, pp. 313–317.
[34] Yu-Yi Chen, Jun-Chao Lu, and Jinn-Ke Jan, “A Secure EHR System Based on Hybrid Clouds,” J.
Med. Syst., vol. 36, no. 5, pp. 3375–84, Oct. 2012.
[35] B. E. Dixon, L. Simonaitis, H. S. Goldberg, M. D. Paterno, M. Schaeffer, T. Hongsermeier, A. Wright,
and B. Middleton, “A pilot study of distributed knowledge management and clinical decision support in the
cloud,” Artif. Intell. Med., vol. 59, no. 1, pp. 45–53, Sep. 2013.
[36] Chia-Hui Liu, Fong-Qi Lin, Dai-Lun Chiang, Tzer-Long Chen, Chin-Sheng Chen, Han-Yu Lin,
YuFang Chung, and Tzer-Shyong Chen, “Secure PHR Access Control Scheme for Healthcare Application
Clouds,” in 2013 42nd International Conference on Parallel Processing (ICPP), 1-4 Oct. 2013, 2013, pp.
1067–76.
[37] M. FakhrulAlamOnik, K. Anam, S. Sabir Salman - Al - Musawi, and N. Rashid, “A Secured Cloud
based Health Care Data Management System,” Int. J. Comput. Appl., vol. 49, no. 12, pp. 24–30, Jul. 2012.
[38] M. Barua, X. Liang, R. Lu, and X. Shen, “ESPAC: Enabling Security and Patient-centric Access
Control for eHealth in cloud computing,” Int. J. Secur. Netw., vol. 6, no. 2, pp. 67–76, Jan. 2011.
[39] S. Narayan, M. Gagné, and R. Safavi-Naini, “Privacy preserving EHR system using attribute-based
infrastructure,” in Proceedings of the 2010 ACM workshop on Cloud computing security workshop, New
York, NY, USA, 2010, pp. 47–52.
[40] F. Aljumah, R. H. M. Leung, M. Pourzandi, and M. Debbabi, “Emergency mobile access to personal
health records stored on an untrusted cloud,” in 2nd International Conference on Health Information
Science, HIS 2013, March 25, 2013 - March 27, 2013, 2013, vol. 7798 LNCS, pp. 30–41.
[41] Jie Huang, M. Sharaf, and Chin-Tser Huang, “A Hierarchical Framework for Secure and Scalable EHR
Sharing and Access Control in Multi-cloud,” in 2012 41st International Conference on Parallel Processing
Workshops (ICPPW 2012), 10-13 Sept. 2012, 2012, pp. 279–87.

5.
[42] A. Lounis, A. Hadjidj, A. Bouabdallah, and Y. Challal, “Secure and scalable cloud-based architecture
for e-Health wireless sensor networks,” in 2012 21st International Conference on Computer
Communications and Networks, ICCCN 2012, July 30, 2012 - August 2, 2012, 2012, p. IEEE; IEEE
Communication Society; U.S. National Science Foundation (NSF); City Mayor of Munich.
[43] Yue Tong, Jinyuan Sun, S. S. M. Chow, and Pan Li, “Towards auditable cloud-assisted access of
encrypted health data,” in 2013 IEEE Conference on Communications and Network Security (CNS), 14-16
Oct. 2013, 2013, pp. 514–19.
[44] L. Chen and D. B. Hoang, “Novel data protection model in healthcare cloud,” in 13th IEEE
International Workshop on FTDCS 2011, the 8th International Conference on ATC 2011, the 8th
International Conference on UIC 2011 and the 13th IEEE International Conference on HPCC 2011,
September 2, 2011 - September 4, 2011, 2011, pp. 550–555.
[45] M. Sharma, Y. Bai, S. Chung, and L. Dai, “Using Risk in Access Control for Cloud-Assisted eHealth,”
in 2012 IEEE 14th International Conference on High Performance Computing and Communication 2012
IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), 2012, pp. 1047–
1052. [46] H. Löhr, A.-R. Sadeghi, and M. Winandy, “Securing the e-health cloud,” in Proceedings of the
1st ACM International Health Informatics Symposium, New York, NY, USA, 2010, pp. 220–229.
[47] Zhiwei Yu, C. Thomborson, Chaokun Wang, Jianmin Wang, and Rui Li, “A cloud-based watermarking
method for health data security,” in 2012 International Conference on High Performance Computing &
Simulation (HPCS 2012), 2-6 July 2012, 2012, pp. 642–7.
[48] A. Alabdulatif, I. Khalil, and V. Mai, “Protection of electronic health records (EHRs) in cloud,” in
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
(EMBC), 3-7 July 2013, 2013, pp. 4191–4.
[49] T. Ermakova and B. Fabian, “Secret sharing for health data in multi-provider clouds,” in 2013 IEEE
15th Conference on Business Informatics (CBI), 15-18 July 2013, 2013, pp. 93–100.
[50] “What is Open Data? — Open Data Handbook.” [Online]. Available:
http://opendatahandbook.org/en/what-is-open-data/. [Accessed: 04-May-2014

6.
PARKINSON'S DISEASE MOTOR SYMPTOMS IN MACHINE
LEARNING: A REVIEW
Claas Ahlrichs and Michael Lawo
Mathematics and Computer Science, University of Bremen, PO Box 330 440, 28334 ,Bremen, Germany
ABSTRACT
This paper reviews related work and state-of-the-art publications for recognizing motor symptoms of
Parkinson's Disease (PD). It presents research efforts that were undertaken to inform on how well
traditional machine learning algorithms can handle this task. In particular, four PD related motor
symptoms are highlighted (i.e. tremor, bradykinesia, freezing of gait and dyskinesia) and their details
summarized. Thus the primary objective of this research is to provide a literary foundation for
development and improvement of algorithms for detecting PD related motor symptoms.
KEYWORDS
Parkinson's Disease, Machine Learning, Artificial Intelligence, Review, State-of-the-Art
For More Details: http://airccse.org/journal/hiij/papers/2413hiij01.pdf
Volume Link: https://airccse.org/journal/hiij/Current2013.html

7.
REFERENCES
[1] A. Asuncion, D.J.N.: UCI machine learning repository (2007), http://www.ics.uci.edu/~mlearn/
[2] Ackermann, M.R., Lammersen, C., Märtens, M., Raupach, C., Sohler, C., Swierkot, K.: Streamkm++: A
clustering algorithms for data streams. In: Blelloch, G.E., Halperin, D. (eds.) ALENEX. pp. 173– 187.
SIAM (2010)
[3] Andlin-Sobocki, P., Jnsson, B., Wittchen, H.U., Olesen, J.: Cost of disorders of the brain in Europe.
European Journal of Neurology 12 Suppl 1 (Jun 2005), http://dx.doi.org/10.1111/j.1468-
1331.2005.01202.x
[4] Armstrong, R.A.: Visual signs and symptoms of parkinson's disease. Clinical and Experimental
Optometry 91(2), 129– 138 (2008), http://dx.doi.org/10.1111/j.1444-0938.2007.00211.x
[5] Arvind, R., Karthik, B., Sriraam, N., Kannan, J.K.: Automated detection of pd resting tremor using psd
with recurrent neural network classier. In: Advances in Recent Technologies in Communication and
Computing (ARTCom), 2010 International Conference on. pp. 414 – 417 (oct 2010)
[6] Asgari, M., Shafran, I.: Predicting severity of parkinson's disease from speech. In: Engineering in
Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. pp. 5201 –
5204 (31 2010-sept 4 2010)
[7] B and, A.P.L., Poignet, P., Geny, C.: Pathological tremor and voluntary motion modeling and online
estimation for active compensation. Neural Systems and Rehabilitation Engineering, IEEE Transactions on
19(2), 177 – 185 (april 2011)
[8] Bakar, Z.A., Tahir, N.M., Yassin, I.M.: Classification of parkinson's disease based on multilayer
perceptrons neural network. In: Signal Processing and Its Applications (CSPA), 2010 6th International
Colloquium on. pp. 1 – 4 (may 2010)
[9] Bakstein, E., Warwick, K., Burgess, J., Stavdahl, O., Aziz, T.: Features for detection of parkinson's
disease tremor from local field potentials of the subthalamic nucleus. In: Cybernetic Intelligent Systems
(CIS), 2010 IEEE 9th International Conference on. pp. 1 – 6 (sept 2010)
[10] Bächlin, M., Plotnik, M., Roggen, D., Maidan, I., Hausdor, J.M., Giladi, N., Troster, G.: Wearable
assistant for parkinson's disease patients with the freezing of gait symptom. Information Technology in
Biomedicine, IEEE Transactions on 14(2), 436 – 446 (march 2010)
[11] Bächlin, M., Roggen, D., Troster, G., Plotnik, M., Inbar, N., Meidan, I., Herman, T., Brozgol, M.,
Shaviv, E., Giladi, N., Hausdor, J.M.: Potentials of enhanced context awareness in wearable assistants for
parkinson's disease patients with the freezing of gait syndrome. In: Wearable Computers, 2009. ISWC '09.
International Symposium on. pp. 123 – 130 (sept 2009)
[12] Brewer, B.R., Pradhan, S., Carvell, G., Delitto, A.: Application of modied regression techniques to a
quantitative assessment for the motor signs of parkinson's disease. Neural Systems and Rehabilitation
Engineering, IEEE Transactions on 17(6), 568 – 575 (dec 2009)
[13] Burg, J.P.: Maximum Entropy Spectral Analysis. Ph.D. thesis, Stanford University (1975)
[14] Cancela, J., Pansera, M., Arredondo, M.T., Estrada, J.J., Pastorino, M., Pastor-Sanz, L., Villalar, J.L.:
A comprehensive motor symptom monitoring and management system: The bradykinesia case. In:
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE.
pp. 1008 – 1011 (31 2010-sept 4 2010)
[15] Cole, B.T., Roy, S.H., De Luca, C.J., Nawab, S.H.: Dynamic neural network detection of tremor and
dyskinesia from wearable sensor data. In: Engineering in Medicine and Biology Society (EMBC), 2010
Annual International Conference of the IEEE. pp. 6062 – 6065 (31 2010-sept 4 2010)
[16] Cole, B.T., Roy, S.H., Nawab, S.H.: Detecting freezing-of-gait during unscripted and unconstrained
activity. In: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference
of the IEEE. pp. 5649 – 5652 (30 2011-sept 3 2011) 11
[17] Cunningham, L., Mason, S., Nugent, C., Moore, G., Finlay, D., Craig, D.: Homebased monitoring and
assessment of parkinson's disease. Information Technology in Biomedicine, IEEE Transactions on 15(1), 47
– 53 (jan 2011)

8.
AUTHORS
Claas Ahlrichs is a PhD. candidate at Universitaet Bremen, where he studied computer
science with a focus on artificial intelligence and wearable computing. He graduated with
his thesis “Development and Evaluation of an Abstract User Interface for Performing
Maintenance Scenarios with Wearable Computers” in 2011. Since 2008, Ahlrichs is
involved at the Center for Computing and Communication Technologies (TZI)
Technologies in the field of wearable computing. Furthermore, he has been involved in
several regional and international research projects (ITASSIT, HELP, REMPARK) related
to health care, human computer interaction and wearable computing. Currently, he works as a software
developer at neusta mobile solutions GmbH in Bremen
Prof. Dr. Michael Lawo is since 2004 at TZI (www.tzi.de) of the Universitaet Bremen, and since 2009 one
of the two Managing Directors of neusta mobile solutions GmbH. He is professor for applied computer
science at Universitaet Bremen, member of the steering board of Logdynamics
(www.logdynamics.de) and involved in numerous projects of logistics, wearable
computing and artificial intelligence. He had been the CEO of a group of SME in the IT
domain since 1999 with a focus on the development and marketing of virtual reality
simulators for surgeons; from 1996 to 2000 he was CEO of an IT consulting firm and
from 1991 to 1995 top manager information systems with the Bremer Vulkan group.
Michael Lawo was consultant before joining the nuclear research centre in Karlsruhe
from 1987 to 1991 as head of the industrial robotics department. He is a 1975 graduate of structural
engineering of Ruhr Universität Bochum, received his PhD from Universität Essen in 1981 and became
professor in structural optimisation there in 1992. In 2000 he was appointed as professor of honour of the
Harbin/China College of Administration & Management. He is author, co-author and co-publisher of eight
books and more than 150 scientific papers on numerical methods and computer applications also in
logistics, healthcare, optimization, IT-security, sensorial materials and wearable computing

9.
PROGRESS AND CHALLENGES IN THE IMPLEMENTATION
OF ELECTRONIC MEDICAL RECORDS IN SAUDI ARABIA: A
SYSTEMATIC REVIEW
Rihab Hasanain1
, Kirsten Vallmuur2
and Michele Clark3
1
School of Public Health and Social Work, Queensland University of Technology,
Brisbane, Australia
2
School of Psychology and Counselling, Queensland University of Technology, Brisbane,
Australia
3
School of Clinical Sciences, Queensland University of Technology, Brisbane, Australia
ABSTRACT
Electronic Medical Record (Emr) Systems Are Being Implemented Increasingly Worldwide.
Saudi Arabia Is One Of Developing Countries That Commenced Implementing Such Systems
In 1988. Whilst Emr Uptake Has Been Low In Saudi Arabia Until Now, A Number Of
Hospitals Have Implemented Emr Systems Successfully. This Paper Analyses Available
Studies (N=28) In The Literature Regarding Emr Implantation In Saudi Arabia To Identify The
Progress Of Emr Implementation To Date And To Identify The Facilitators And Barriers To
Implementation.
Keywords
Electronic Medical Records; Health Information Systems; Saudi Arabia.
For More Details: https://airccse.org/journal/hiij/papers/3214hiij01.pdf
Volume Link: https://airccse.org/journal/hiij/Current2014.html

10.
REFERENCES
[1] Cesnik B, Kidd MR. History of health informatics: a global perspective. Studies in health technology
and informatics. [Historical Article]. 2010;151:3-8.
[2] Al Jarullah A, El-Masri S. Proposal of an architecture for the national integration of Electronic Health
Records: a semi-centralized approach. Stud Health Technol Inform. 2012;180.
[3] Granlien MF, Hertzum M, Gudmundsen J. The gap between actual and mandated use of an electronic
medication record three years after deployment. Studies in health technology and informatics.
2008;136:419-24.
[4] Alsahafi Y. STUDIES OF EHR IMPLEMENTATION AND OPERATION IN DIFFERENT
COUNTRIES WITH PARTICULAR REFERENCE TO SAUDI ARABIA: Massey University; 2012.
[5] Aldajani M. Electronic Patient Record Security Policy in Saudi Arabia National Health Services: De
Montfort University 2012.
[6] ALTUWAIJRI M. Electronic-health in Saudi Arabia. Just around the corner? Saudi Med J.
2008;29(2):171-8.
[7] Davidson P. Health Information System: Auerbach Publications, New York; 2000.
[8] McLean V. Electronic Health Records Overview. National Institutes of Health National Center for
Research Resources, Citeseer. 2006.
[9] ISO/TC. Electronic Health Record Definition, Scope, and Context. ISO/TC 215 Technical Report; 2003
[28/2/2010]; Available from:
http://secure.cihi.ca/cihiweb/en/downloads/infostand_ihisd_isowg1_mtg_denoct_contextdraft.pdf.
[10] Alkraiji A, Jackson T, Murray I. Barriers to the widespread adoption of health data standards: an
exploratory qualitative study in tertiary healthcare organizations in saudi arabia. J Med Syst. 2013
Apr;37(2):9895.
[11] Alanazy S. Factors associated with implementation of electronic health records in Saudi Arabia: D.,
UNIVERSITY OF MEDICINE AND DENTISTRY OF NEW JERSEY, New Jersey, USA.; 2006.
[12] MOH. A Review of Health Situation, Ministry Of Health,. 2006 [19/3/2010]; Available from:
http://www.moh.gov.sa/statistics/stats2007/Book Seha02.pdf.
[13] Khudair AA. Electronic health records: Saudi physicians' perspective. 5th IET International Seminar
on Appropriate Healthcare Technologies for Developing Countries (AHT 2008)2008. p. 7-.
[14] ALTUWAIJRI M. Health Information Technology Strategic Planning Alignment in Saudi Hospitals: A
Historical Perspective. Journal of Health Informatics in Developing Countries 2011;5(2).
[15] WHO/CCS. Cooperation Strategy for WHO and Saudi Arabia 2006–2011, World Health Organization.
2006 [19/4/2010]; Available from: http://www.who.int/countryfocus/cooperation_strategy/ccs_sau_en.pdf.
[16] Khalifa M. Barriers to Health Information Systems and Electronic Medical Records Implementation. A
Field Study of Saudi Arabian Hospitals. Procedia Computer Science. 2013;21:335–42.
[17] Altuwaijri M. Supporting the Saudi e-health initiative: the Master of Health Informatics programme at
KSAU-HS. EMHJ. 2010;16(1). Health Informatics- An International Journal (HIIJ) Vol.3, No.2, May 2014
13
[18] Albishi H. Health Information Management in the Kingdom of Saudi Arabia. 2011 [10/11/2013]; Saudi
Association for Health Informatics]. Available from:
http://www.sahi.org.sa/article_details.php?article_id=9.
[19] SAHI. The Saudi Association for Health Informatics (SAHI). 2014 [23/01/2014]; Available from:
http://www.imia-medinfo.org/new2/node/108.
[20] Altwaijir M, Aldosari B. Health Informatics Master Program at King Saud bin Abdulaziz University
for Health Sciences, Riyadh, Saudi Arabia. Yearb Med Inform. 2008;145(9).
[21] Househ M, ALTUWAIJRI M, Aldosari B. Establishing an Electronic Health Center of Research
Excellence (E-CoRE) within the Kingdom of Saudi Arabia. Journal of Health Informatics in Developing
Countries. 2010;4(1).
[22] Altuwaijri MM, Sughayr AM, Hassan MA, Alazwari FM. The effect of integrating short messaging
services` reminders with electronic medical records on non-attendance rates. Saudi medical journal. 2012
Feb;33(2):193-6.
[23] El-Mahalli AA, El-Khafif SH, Al-Qahtani MF. Successes and challenges in the implementation and
application of telemedicine in the eastern province of Saudi Arabia. Perspect Health Inf Manag. [Research
Support, Non-U.S. Gov't]. 2012;9:1-27.

11.
[24] Nour El Din MM. Physicians' use of and attitudes toward electronic medical record system
implemented at a teaching hospital in saudi arabia. J Egypt Public Health Assoc. 2007;82(5-6):347- 64.
[25] Almalki M, Fitzgerald G, Clark M. Health care system in Saudi Arabia: an overview. East Mediterr
Health J. [Research Support, Non-U.S. Gov't Review]. 2011 Oct;17(10):784-93.
[26] Middleton B, Bloomrosen M, Dente MA, Hashmat B, Koppel R, Overhage JM, et al. Enhancing
patient safety and quality of care by improving the usability of electronic health record systems:
recommendations from AMIA. J Am Med Inform Assoc. [Guideline]. 2013 Jun;20(e1):e2-8.
[27] Unertl KM, Johnson KB, Lorenzi NM. Health information exchange technology on the front lines of
healthcare: workflow factors and patterns of use. J Am Med Inform Assoc. [Multicenter Study, Research
Support, N.I.H., Extramural,Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, P.H.S.].
2012 May-Jun;19(3):392-400.
Authors
Rihab Hasanain is a PhD candidate in Health Services Management, School of Public Health and
Social Work at Queensland University of Technology. Her topic of research is focusing on EMRs
implementation in public hospitals in Saudi Arabia.
Dr. Kirsten Vallmuur is the associate supervisor. She is the Senior Research Fellow with the Centre for
Accident Research and Road Safety - Queensland. She has expertise in the analysis and understanding
of large morbidity and mortality coded data sets, injury surveillance systems, trauma data linkage,
health classifications and injury classifications. She is a member of the World Health Organisation
ICD-11 Revision Topic Advisory Group for Injury and External causes, and is the chair of the research
committee for the Australasian Mortality Data Interest Group.
Professor Michele Clark is an allied health professional and has worked as a both a clinician and senior
researcher. Prof Clark is a former recipient of a NHMRC Post-doctoral fellowship and has an extensive
research background in prehospital and emergency care utilization patterns, aged care and policy
implementation. She was the Inaugural Director of the Australian Centre for Prehospital Research,
which was a collaborative centre of the Qld Ambulance Service and the University of Queensland.
Career highlights include working at the United Nations in New York for International Year of Older
Persons and being a former Assistant Commissioner (Allied Health) on the Health Quality and
Complaints Commission.

12.
MEDICAL IMAGES AUTHENTICATION THROUGH
WATERMARKING PRESERVING ROI
Sonika C. Rathi1
and Vandana S. Inamdar2
1Department of Computer Engineering, College of Engineering Pune, Shivajinagar, Pune University,
Maharashtra, India
2Department of Computer Engineering, College of Engineering Pune, Shivajinagar, Pune University,
Maharashtra, India
ABSTRACT
Telemedicine is a well-known application where enormous amount of medical data need to be
securely transferred over the public network and manipulate effectively. Medical image
watermarking is an appropriate method used for enhancing security and authentication of
medical data, which is crucial and used for further diagnosis and reference. This project focuses
on the study of medical image watermarking methods for protecting and authenticating medical
data. Additionally, it covers algorithm for application of water marking technique on Region of
Non Interest (RONI) of the medical image preserving Region of Interest (ROI). The medical
images can be transferred securely by embedding watermarks in RONI allowing verification of
the legitimate changes at the receiving end without affecting ROI. Segmentation plays an
important role in medical image processing for separating the ROI from medical image. The
proposed system separate the ROI from medical image by GUI based approach, which works
for all types of medical images. The experimental results show the satisfactory performance of
the system to authenticate the medical images preserving ROI.
KEYWORDS
ROI & RONI, Segmentation, Authentication, security, medical confidentiality
For More Details: https://airccse.org/journal/hiij/Current2014.html
Volume Link: https://airccse.org/journal/hiij/Current.html

13.
REFERENCES
[1] Giakoumaki, Sotiris Pavlopoulos, and Dimitris Koutsouris, (Oct. 2006) “Multiple Image Watermarking
Applied to Health Information Management”, IEEE Trans. on information technology in biomedicine, vol.
10, no. 4
[2] Imen Fourati Kallel, Mohamed Kallel, Mohamed Salim BOUHLEL, (2006 ) “A Secure fragile
Watermarking Algorithm for medical Image Authentication in the DCT Domain”, IEEE
[3] M.S.Bouhlel, (Mars 2002) “Conception d'une banque d'images medicales sur INTERNET”, 3eme
Rencontres Institutionnelles: Rhones Alpes/ Tunisie (RIRAT'02). Tozeur, Tunisie, 21-22
[4] Preeti Aggarwal, Renu Vig, Sonali Bhadoria, and C.G.Dethe , (September 2011) “Role of Segmentation
in Medical Imaging: A Comparative Study”, International Journal of Computer Applications (0975 – 8887),
Volume 29– No.1
[5] Pradeep Singh; Sukhwinder Singh, Gurjinder Kaur, (2008) “A Study of Gaps in CBMIR using Different
Methods and Prospective, Proceedings of world academy of science, engineering and technology”, volume
36 , ISSN 2070-3740, pp. 492-496.
[6] Zhen Ma, Joao Manuel, R. S. Tavares, R. M. Natal Jorge, (2009) “A review on the current segmentation
algorithms for medical images”, 1st International Conference on Imaging Theory and Applications
(IMAGAPP), Lisboa, Portugal, INSTICC Press, pp. 135-140.
[7] Nisar Ahmed Memon, Anwar Majid Mirza, and S.A.M. Gilani, (2006) “Segmentation of Lungs from CT
Scan Images for Early Diagnosis of Lung Cancer”, World Academy of Science, Engineering and
Technology 20.
[8] Hossein Badakhshannoory and Parvaneh Saeedi, (September 2011) “A Model-Based Validation Scheme
for Organ Segmentation in CT Scan Volumes”, IEEE Trans. on biomedical information, vol. 58, no. 9,
[9] R. Susomboon, D. Raicu, and J. Furst, (2007) “A hybrid approach for liver segmentation”, in Proc. 3-D
Segment. Clin.-MICCAI Grand Challenge
[10] K. Seo, L. C. Ludeman, S. Park, and J. Park, (2005) “Efficient liver segmentation based on the spine”,
Adv. Inf. Syst., vol. 3261, pp. 400–409
[11] A. H. Forouzan, R. A. Zoroofi, M. Hori, and Y. Sato, (2009) “Liver segmentation by intensity analysis
and anatomical information in multislice CT images”, in Proc. Liver Segment. Intensity Anal Anatomical
Inf. Multi-Slice CT Images, vol. 4, pp. 287–297
[12] T. F. Cootes, C. J. Taylor, and D. H. Cooper, (2001) “Statistical models of appearance for medical
image analysis and computer vision,” Proc. SPIE, vol. 4322, pp. 236–248
[13] S. Pan and B. M. Dawant, (2001) “Automatic 3D segmentation of the liver from abdominal CT images:
A level-set approach,” Proc. SPIE, vol. 4322, pp. 128–138
[14] D. T. Lin, C. C. Lei, and S. W. Hung, (Jan 2006) “Computer-aided kidney segmentation on abdominal
CT images”, IEEE Trans. Inf. Technol. Biomed.,vol. 10, no. 1, pp. 59–65
[15] H. Badakhshannoory and P. Saeedi, (2010) “Liver segmentation based on de-formable registration and
multilayer segmentation,” in Proc. IEEE Int. Conf. Image Process., pp. 2549– 2552
[16] Samuel G. Armato III, Maryellen L. Giger and Catherine J. Moran, (1999) “Computerized Detection of
Pulmonary Nodules on CT Scans”, RadioGraphics, vol. 19, pp. 1303-1311
[17] Julian Kerr, (May 2000) “The TRACE method for Segmentation of Lungs from Chest CT images by
Deterministic Edge Linking”, University of New South Wales, Department of Artificial Intelligence,
Australia
[18] Shiying Hu, Eric A.Huffman, and Joseph M. Reinhardt, (June 2001) “Automatic Lung Segementation
for Accurate Quantitiation of Volumetric X-Ray CT images”, IEEE Transactions on Medical Imaging, vol.
20, No. 6
[19] Ayman El-Baz, Aly A. Farag, Robert Falk, and Renato La Rocc, (Jan 2002) ” Detection, Visualization,
and Identification of Lung Abnormalities in Chest Spiral CT Scans: Phase 1”, International Conference on
Biomedical Engineering, Cairo, Egypt
[20] Riccardo Boscolo, Mathew S. Brown, Michael F. McNitt-Gray, (2002) “Medical Image Segmentation
with Knowledge-guided Robust Active Contours”, Radiographics, vol. 22, pp. 437-448
[21] Binsheng Zhao, Gordon Gamsu, Michelle S. Ginsberg, (2003) “Automatic detection of small lung
nodules on CT utilizing a local density maximum algorithm”, Journal of Applied Clinical Medical Physics,
vol. 4, No. 3

14.
[22] A. Wakatani, (Jan 2002) “Digital Watermarking for ROI Medical Images by Using Compressed
Signature Image", Proceedings of the 35th International Conference on System Sciences,
[23] Yusuk Lim, Changsheng Xu, and David Dagan Feng, “Web based Image Authentication Using
Invisible Fragile Watermark”, Pan-Sydney Area Workshop on Visual Information Processing (VIP2001),
Sydney, Australia
[24] C.R. Rodriguez, F. Uribe Claudia, T. Blas Gershom De J, (2007) “Data Hiding Scheme for Medical
Images”, IEEE 17th International Conference on Electronics, communications and computers
[25] Hemin Golpira and Habibollah Danyali, (2009)“Reversible Blind Watermarking for Medical Images
Based on Wavelet Histogram Shifting”, IEEE
[26] Nisar Ahmed Memon, S.A.M. Gilani, and Shams Qayoom, (2009) “Multiple Watermarking of Medical
Images for Content Authentication and Recovery”, IEEE
AUTHORS
Ms. Sonika Rathi is pursuing her M. Tech in computer Engineering from College of
Engineering Pune, Maharashtra. She is graduated from Swami Ramanand Tirth
Marathwada University, Nanded in 2009. Her research interest are watermarking, data
mining and medical informatics.
Mrs. Vandana Shridhar Inamdar is Assistant Professor, at Department of Computer
Engineering & IT, College of Engineering Pune, Maharashtra. She is having more than
20 years experience in teaching along with 2 years industry experience. She has
registered for Ph.d in Pune university. Her Topic of research is- “Biometric
watermarking for digital media”. She has completed her M.E. Electronics from Pune
University, 1997. she is graduated from Shivaji University, 1989.

15.
RANKING THE MICRO LEVEL CRITICAL FACTORS OF ELECTRONIC
MEDICAL RECORDS ADOPTION USING TOPSIS METHOD
Hossein Ahmadi1
, Maryam Salahshour Rad2
, Mehrbakhsh Nilashi3,*
, Othman Ibrahim4
,
Alireza Almaee5
1,2,3,4
Faculty of Computing, Universiti Technologi Malaysia, Johor, Malaysia 5Department of
Management, Rasht Payame Noor University, Rasht, Iran
ABSTRACT
In many countries, the health care sector is entering into a time of unprecedented change.
Electronic Medical Record (EMR) has been introduced into healthcare organizations in order to
incorporate better use of technology, to aid decision making, and to facilitate the search for
medical solution. This needs those professionals in healthcare organizations to be in the process of
changing from the use of paper to maintain medical records into computerized medical
recordkeeping opportunities. However, the adoption of these electronic medical records systems
has been slow throughout the healthcare field. The critical users are physicians which play an
important role to success of health information technology including Electronic Medical Record
systems. As a result user adoption is necessary in order to understand the benefits of an EMR.
Therefore, in the current paper, a model of ranking factors of micro-level in EMRs adoption was
developed. Surveys distributed to physicians as this study’s respondent in two private hospitals in
Malaysia. The findings indicate that physicians have a high perception means for the technology
and showed that EMR would increase physician’s performance regarding to decision making.
They have been and continue to be positively motivated to adopt and use the system. The relevant
factors according to micro-level perspective prioritized and ranked by using the Technique for
Order of Preference by Similarity to Ideal Solution (TOPSIS). The aim of ranking and using this
approach is to investigate which factors are more important in EMRs adoption from the micro-
level perspectives. The results of performing TOPSIS is as a novelty which assist health
information systems (HIS) success and also healthcare organizations to motivate their users in
accepting of new technology.
KEYWORDS
EMRs, Adoption, TOPSIS, Micro-Level Adoption Factors
For More Details: https://airccse.org/journal/hiij/papers/2413hiij02.pdf
Volume Link: https://airccse.org/journal/hiij/Current2013.html

16.
REFERENCES
[1] Baron, R. J. (2007)."Quality improvement with an electronic health record: achievable, but not
automatic." Annals of Internal Medicine 147(8): 549-552.
[2] Bolger-Harris, H., et al. (2008). "Using computer based templates for chronic disease management."
Australian family physician 37(4): 285.
[3] Booth, N., Robinson, P., & Kohannejad, J. (2004). Identification of high-quality consultation practice
in primary care: the effects of computer use on doctor-patient rapport. Informatics in primary care, 12(2),
75-83.
[4] Cauldwell, M. R., Beattie, C. E., Cox, B. M., Denby, W. J., Ede-Golightly, J. A., & Linton, F. L.
(2007). The impact of electronic patient records on workflow in general practice. Health informatics
journal, 13(2), 155-160.
[5] Chee, H. L., &Barraclough, S. (2007). Health care in Malaysia: the dynamics of provision, financing
and access: Routledge.
[6] Christensen, T. and A. Grimsmo (2008). "Expectations for the next generation of electronic patient
records in primary care: a triangulated study." Informatics in primary care 16(1): 21-28.
[7] Christian G. D. (2002). Electronic Medical Records Mark a Landmark Shift in Record Keeping.
[8] de Jong, J. D., Groenewegen, P. P., Spreeuwenberg, P., Westert, G. P., & de Bakker, D. H. (2009). Do
decision support systems influence variation in prescription? BMC health services research, 9(1), 20.
[9] DeLone, W. H. and E. R. McLean (1992). "Information systems success: the quest for the dependent
variable." Information Systems Research 3(1): 60-95.
[10] Dennison, J., Eisen, S., Towers, M., & Clark, C. I. (2006). An effective electronic surgical referral
system. Annals of the Royal College of Surgeons of England, 88(6), 554.
[11] Frank, O. R., Litt, J. C., & Beilby, J. J. (2004). Opportunistic electronic reminders: improving
performance of preventive care in general practice. Australian family physician, 33(1-2), 87-90.
[12] Hamilton, W. T., Round, A. P., Sharp, D., & Peters, T. J. (2003). The quality of record keeping in
primary care: a comparison of computerised, paper and hybrid systems. The British Journal of General
Practice, 53(497), 929.
[13] Hippisley-Cox, J., Pringle, M., Cater, R., Wynn, A., Hammersley, V., Coupland, C., . . . Johnson, C.
(2003). The electronic patient record in primary care—regression or progression? A cross sectional study.
Bmj, 326(7404), 1439-1443.
[14] Hollingworth, W., Devine, E. B., Hansen, R. N., Lawless, N. M., Comstock, B. A., Wilson-Norton,
J. L., . . . Sullivan, S. D. (2007). The Impact of e-Prescribing on Prescriber and Staff Time in Ambulatory
Care Clinics: A Time–Motion Study. Journal of the American Medical Informatics Association, 14(6),
722-730.
[15] Hwang, C.L., Yoon, K., ‘‘Multiple Attributes Decision Making Methods and Applications’’,
Springer, BerlinHeidelberg, 1981.
[16] Keshavjee, K., Troyan, S., Holbrook, A., & VanderMolen, D. (2001). Measuring the success of
electronic medical record implementation using electronic and survey data. Paper presented at the
Proceedings of the AMIA Symposium.
[17] Kinn, J. W., O’Toole, M. F., Rowley, S. M., Marek, J. C., Bufalino, V. J., & Brown, A. S. (2001).
Effectiveness of the electronic medical record in cholesterol management in patients with coronary artery
disease (Virtual Lipid Clinic). The American journal of cardiology, 88(2), 163-165.
[18] Lau, F., Hagens, S., & Muttitt, S. (2006). A proposed benefits evaluation framework for health
information systems in Canada. Healthcare quarterly (Toronto, Ont.), 10(1), 112-116, 118.
[19] Lau, F., Price, M., & Keshavjee, K. (2011). From benefits evaluation to clinical adoption: making
sense of health information system success in Canada. Healthc Q, 14(1), 39-45.
[20] Lau, F., Price, M., Boyd, J., Partridge, C., Bell, H., &Raworth, R. (2012). Impact of electronic
medical record on physician practice in office settings: a systematic review. BMC medical informatics
and decision makin.12(1), 10.
[21] Linder, J. A., Ma, J., Bates, D. W., Middleton, B., & Stafford, R. S. (2007). Electronic health record
use and the quality of ambulatory care in the United States. Archives of Internal Medicine, 167(13), 1400-
1405.

17.
[22] Ludwick, D. and J. Doucette (2009). "Primary care physicians' experience with electronic medical
records: barriers to implementation in a fee-for-service environment." International Journal of
Telemedicine and Applications 2009: 2.
[23] Margalit, R. S., Roter, D., Dunevant, M. A., Larson, S., & Reis, S. (2006). Electronic medical record
use and physician–patient communication: an observational study of Israeli primary care encounters.
Patient education and counseling, 61(1), 134-141.
[24] Martens, J. D., van der Weijden, T., Severens, J. L., de Clercq, P. A., De Bruijn, D., Kester, A. D., &
Winkens, R. A. (2007). The effect of computer reminders on GPs’ prescribing behaviour: a
clusterrandomised trial. International Journal of Medical Informatics, 76, S403-S41

18.
A FRAMEWORK FOR A SMART SOCIALBLOOD DONATION SYSTEM
BASEDON MOBILE CLOUD COMPUTING
Almetwally M. Mostafa
College of Computer and Information Sciences, King Saud University, Riyadh, KSA
&Faculty of Engineering, Alazhar University, Cairo, Egypt
Ahmed E. Youssef
College of Computer and Information Sciences, King Saud University, Riyadh, KSA &
Faculty of Engineering, Helwan University, Cairo, Egypt
GamalAlshorbagy
College of Computer and Information Sciences, King Saud University, Riyadh, KSA
ABSTRACT
Blood Donation and Blood Transfusion Services (BTS) are crucial for saving people’s lives.
Recently, worldwide efforts have been undertaken to utilize social media and smartphone
applications to make the blood donation process more convenient, offer additional services,
and create communities around blood donation centers. Blood banks suffer frequent shortage
of blood;hence, advertisements are frequently seen on social networks urging healthy
individuals to donate blood for patients who urgently require blood transfusion. The blood
donation processusuallyconsumesa lot of time and effort from both donors and medical staff
since there is no concrete information system that allows donorsand blood donation centers
communicate efficiently and coordinate with each other tominimize time and effort required
for blood donation process. Moreover, most blood banks work in isolation and are not
integrated with other blood donation centers and health organizations which affect the blood
donation and blood transfusion services’ quality. This work aims at developing a Blood
Donation System (BDS) based on the cutting-edge information technologies of cloud
computing and mobile computing. The proposedsystem facilitates communication between
blood donorsand blood donation centers and integrates the blood information dispersed
among different blood donation centers and health organizations acrossa
country.Stakeholders will be able to use the BDS as an application installed on their
smartphones to help them complete the blood donation process with minimal effort and time.
Thisapplication helps people receive notifications on urgent blood donation calls, know their
eligibility to give blood, search for the nearest blood center, and reserve a convenient
appointment using temporal and/or spatial information. It also helps establish a blood
donation community through social networks such as Facebook and Twitter.
KEYWORDS
Blood donation systems; Cloud computing; Mobile computing; Ontology.
For More Details: https://airccse.org/journal/hiij/papers/3414hiij01.pdf
Volume Link: https://airccse.org/journal/hiij/Current2014.html

19.
REFERENCES
[1] Abdullah K. Al-Faris and others, Attitude to Blood Donation among Male Students at King Saud
University, journal of Applied Hematology 2013
[2] AK Al-Faris and others, Attitude to blood donation in Saudi Arabia, Asian journal of transfusion
science
[3] WHO Global Observatory for eHealth (2011) New horizons for health through mobile technologies.
Geneva: World Health Organization. Available:
http://www.who.int/goe/publications/ehealth_series_vol3/en/
[4] www.thelocal.se/36550/20111005
[5] Ramesh Singh, Preeti Bhargava, and SamtaKain, “Smart Phones to the Rescue: The Virtual Blood
Bank Project”, IEEE CS and IEEE ComSoc 1536-1268/07/$25.00 © 2007 IEEE Pervasive Computing
Magazine.
[6] IMA Launches SMS-Bases Blood Bank Service”, Available at:
http://beta.thehindu.com/news/cities/Thiruvananthapuram/article318809.ece
[7] A. H. M. Saiful Islam, Nova Ahmed, KamrulHasan, and Md. Jubayer, mHealth: Blood Donation
Service in Bangladesh, 2013 International Conference on Informatics, Electronics & Vision (ICIEV).
[8] http://www.microsoft.com/en-us/news/Press/2013/May13/05-04AppsForAsiaPR.aspx
[9] The Blood Alliance services hospitals in Northeast Florida March 29, 2013
https://play.google.com/store/apps/details?id=com.idon8&hl=en
[10] The Irish Blood Transfusion Service http://www.giveblood.ie/
[11] Blood transfusion guideline. Utrecht (The Netherlands): Dutch Institute for Healthcare Improvement
CBO; 2011. p. 60-107 Health Informatics-An International Journal (HIIJ) Vol.3, No.4, November 2014
[12] Marcus Foth, Christine Satchell, Jan Seeburger, and Rebekah Russell-Bennett. Social and mobile
interaction design to increase the loyalty rates of young blood donors. In Proceedings of the 6th
International Conference on Communities and Technologies (C&T '13). ACM, New York, NY, USA, 64-
73.
[13] Masser, B.M., White, K.M., Hyde, M.K., Terry, D.J.: The Psychology of Blood Donation: Current
Research and Future Directions. Transfusion Medicine Reviews 22, 215—233 (2008)
[14] Brionesa , R.L., Kucha , B., Fisher Liua, B., Jinb, Y.: Keeping up with the digital age: How the
American Red Cross uses social media to build relationships. Public Relations Review 37 (2011) 37- 43
[15] Niroshinie Fernando, Seng W. Loke, &WennyRahayu, (2013). “Mobile Cloud Computing: A
survey”, Future Generation Computer Systems, Vol. 29, pp84-106, Elsevier.
[16] Ahmed Youssef. Towards Pervasive Computing Environments with Cloud Services. International
Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC), 4(3):1-9, 2013.
[17] S. Perez, Mobile cloud computing: $9.5 billion by 2014, http://exoplanet.eu/catalog.php, 2010.
[18] http://www.socialblood.org

20.
AN ELEMENTARY NOTE ON SKIN HYDRATION MEASUREMENT
USING MEMRISTIVE EFFECT
T. D. Dongale
School of Nanoscience and Technology, Shivaji University Kolhapur
ABSTRACT
The Memristor was predicted by Prof. L. Chua in 1971 and first prototype was reported by team of HP
researcher. The memristor follows interesting relation in the view of magnetic flux and charge. There
are tremendous applications areas emerged out in the framework of memristor in last few years. The
applications in the Memory Technology, Neuromorphic Hardware solution, Soft Computing are name
of few. The memristor was hidden at many instances in biomedical fields, but recently reported
literature revels that memristor is universal part of medical diagnosis. In the bird eye view of this
scenario, this paper deals with elementary note on the skin hydration measurement using memristor.
KEYWORDS
Forth Circuit Element; Memristor; Hydration Measurement
For More Details: https://airccse.org/journal/hiij/papers/2113hiij02.pdf
Volume Link: https://airccse.org/journal/hiij/Current2013.html

21.
REFERENCES
[1] Chua, L. O. Memristor - the missing circuit element, IEEE Trans. Circuit Theory, 18, 1971, pp.507–
519.
[2] Strukov, D. B., Snider, G. S., Stewart, D. R. & Williams, R. S. Nature, 453, 2008, pp.80–83
[3] Gorm K. Johnsen, An introduction to the memristor – a valuable circuit element in bioelectricity and
bioimpedance, J Electr Bioimp, vol. 3, 2012, pp. 20 –28.
[4] Yogesh N Joglekar and Stephen J Wolf, "The elusive memristor: properties of basic electrical
circuits", European Journal of Physics, vol. 30, 2009, pp. 661–675.
[5] L. Chua and S.M. Kang, “Memristive Device and Systems,” Proceedings of IEEE, Vol. 64, no. 2,
1976, pp. 209-223.
[6] Z. Biolek, D. Biolek, V. Biolková, "Spice Model of Memristor with Nonlinear Dopant Drift", Radio
engineering, vol. 18, no. 2, 2009, pp. 210-214.
[7] Robinson E. Pino, Kristy A. Campbell, Compact Method for Modeling and Simulation of Memristor
Devices, Proceeding of international Symposium on Nanoscale Architecture, 2010, pp.1-4. Health
Informatics - An International Journal (HIIJ) Vol.2, No.1, February 2013 20
[8] Dongale, T. D. An Overview of Fourth Fundamental Circuit Element-‘The Memristor’, Supporting
Docs. "NanoHUB. org." Available at: https://nanohub.org/resources/16590 [9] Cole KS. Rectification and
inductance in the squid giant axion, J Gen Physiol. 25; 1941; pp.29-51
[10] Cole KS, Membranes, ions, and impulses. University of California Press; Berkeley, 1972.
[11] Mauro A, Anomalous impedance, a phenomenological property of time-variant resistance – an
analytic review, Biophys J. 1961; 1; pp.353-72.
[12] Johnsen GK, Lütken CA, Martinsen ØG, Grimnes S. Memristive model of electro-osmosis in skin.
Phys Rev E, 83, 031916, 2011.
[13] Tiny organisms remember the way to food, Available at:
http://www.newscientist.com/article/dn11394-tiny-organisms-remember-the-way-to-food.html,
Retrieved: 28 December, 2012.
[14] Licht TS, Stern M, Shwachman H. Measurement of the electrical conductivity of sweat. Clin Chem.
1957;3; pp.37–48.
[15] Tronstad C, Johnsen GK, Grimnes S, Martinsen ØG. A study on electrode gels for skin conductance
measurements. Physiol Meas. 2010;31;pp.1395-1410.
[16] Martinsen, Ø. G., Grimnes, S., Lütken, C. A., & Johnsen, G. K. (2010, May). Memristance in human
skin. In Journal of Physics: Conference Series (Vol. 224, No. 1, p. 012071). IOP Publishing.
[17] S.P. Kosta, Y.P. Kosta, Mukta Bhatele, Y.M. Dubey, Avinash Gaur, Shakti Kosta, Jyoti Gupta, Amit
Patel and Bhavin Patel, Human blood liquid memristor, Int. J. Medical Engineering and Informatics, Vol.
3, No. 1, 2011
AUTHORS
Mr. T. D. Dongale was born in 1989, India. He did his Bachelors and Masters in
Electronics specialized in Embedded Systems. He is Assistant Professor in School
of Nanoscience and Technology, SUK, Kolhapur. He also qualified the State
Eligibility Test for Lectureship (SET) and National Eligibility Test for Lectureship
with Junior Research Fellowship (NET-JRF) during his secon d year of Masters
itself. He has been awarded ‘Merit Scholarship’ of the Shivaji University, Kolhapur
for securing the first rank in his graduation and post graduation studies. Moreover
he is also a recipient of the ‘Eklavya Scholarship’ for supporting his Masters
studies. He has to his credit 15 research papers published in reputed international
journals and author of three book ‘The Treatise on sensor interfacing’ (Germany, Lap- Lambert, 2012)’,
‘Annals of Scholarly Research in Electronic’, (Germany, Lap- Lambert, 2012)’, ‘ZigBee and RFID Based
System Design’, (Germany, Lap- Lambert, 2012)’. His current research interests are Fuzzy Logic,
Artificial Neural Network, Feedback Control System, Power Electronics and Memristor.

22.
SURVEY OF OPEN SOURCE HEALTH INFORMATION SYSTEMS
Bilan Jones, Xiaohong Yuan, Emmanuel Nuakoh, and Khadija Ibrahim
Department of Computer Science, North Carolina A&T State University, Greensboro, NC
ABSTRACT
Due to the Health Information Technology for Economic and Clinical Health Act (HITECH), the US
medical industry has been given a directive to transition to electronic health records. Electronic Health
Records will enhance efficiency and quality of patient care. In this paper, open-source health
information systems are surveyed.These systems include electronic medical records, electronic health
records and personal health record systems. Their functionality, implementation technologies used, and
security features are discussed.
KEYWORDS
Electronic Health Records, Health information systems, Electronic medical records, Personal health
records
For More Details: https://airccse.org/journal/hiij/papers/3114hiij02.pdf
Volume Link: https://airccse.org/journal/hiij/Current2014.html

23.
REFERENCES
[1] Obama, Barack. George Mason University, Fairfax. 08 Jan 2009. Speech
[2] Wan, Yina, “Application of HER in Health Care,”Multimedia and Information Technology (MMIT),
2010 Second International Conference on, vol. 1, no., pp.60,63, 24-25 April 2010
[3] Thakkar, Minal, and Diane C. Davis. "Risks, barriers, and benefits of EHR systems: a comparative
study based on size of hospital." Perspectives in Health Information Management/AHIMA, American
Health Information Management Association 3 (2006).
[4] Wager, Karen A., Frances W. Lee, and John P. Glaser. "Types of Health Care Information." Health
Care Information Systems: A Practical Approach for Health Care Management. United States:
JosseyBass, 2009. 5. Print.
[5] "Introduction to ClearHealth." Osnews,[online] June 2005, http://www.osnews.com/story/10740
(Accessed: 11 August 2013).
[6] Cleland-Huang, J.; Czauderna, A.; Gibiec, M.; Emenecker, J., "A machine learning approach for
tracing regulatory codes to product specific requirements," Software Engineering, 2010 ACM/IEEE 32nd
International Conference on , vol.1, no., pp.155,164, 2-8 May 2010
[7] "Caisis Cancer Data Management System : FAQ." Caisis, [online] 2013,
http://www.caisis.org/faq.html# (Accessed: 22 April. 2013).
[8] Fearn, Paul A., Kevin Regan, Frank Sculli, Jason Fajardo, Brandon Smith, and Paul Alli. "Lessons
Learned from Caisis: An Open Source, Web-Based System for Integrating Clinical Practice and
Research." (2007): Print.
[9] Eric Helms and Laurie Williams. 2011. “Evaluating access control of open source electronic health
record systems”. In Proceedings of the 3rd Workshop on Software Engineering in Health Care (SEHC
'11). ACM, New York, NY, USA, 63-70.
[10] “About OpenMRS”,.OpenMRS,[online] 2004, http://www.openmrs.org/about (Accessed: 4 June
2013).
[11] Dukes, L.; Xiaohong Yuan; Akowuah, F., "A case study on web application security testing with
tools and manual testing," Southeastcon, 2013 Proceedings of IEEE , vol., no., pp.1,6, 4-7 April 2013
[12] "Usage Statistics Module,." OpenMRS Community Wiki, [online] 2013,
https://wiki.openmrs.org/display/docs/Usage+Statistics+Module (Accessed: 22 June 2012).
[13] United States Department of Veteran Affairs .”VistA Monograph”.United States Department of
Veteran Affairs, 25 Nov. 2013. Web. 30 Nov. 2013.
[14] Herbsleb, James, Claudia MüllerBirn, and W. Ben Towne. "The VistA Ecosystem: Current Status
and Future Directions." Pittsburgh, PA: Institute for Software Research (2010).
[15] Rattan, Jennifer. "OSCAR." The Architecture of Open Source Applications, Volume II. 2012.
OSCAR. Web. 5 Oct. 2013. .
[16] "About OSCAR.," Oscar Canada Users Society, [online] 2013,
http://oscarcanada.org/aboutoscar/brief-overview/index_html#security (Accessed: 15 March 2013).
[17] Austin, A., Smith, B., and Williams, L., “Towards Improved Security Criteria for Certification of
Electronic Health Record Systems”, 2nd Workshop on Software Engineering in Healthcare at the
International Conference on Software Engineering (ICSE) 2010, Cape Town, South Africa, electronic
proceedings. Health Informatics- An International Journal (HIIJ) Vol.3, No.1, February 2014 31
[18] Lake, Jerissa. “Authentication Vulnerabilities in OpenEMR”, The 2013 symposium on Computing at
Minority Institutions, Association of Computer and Information Science/Engineering Departments at
Minority Institutions, April 2013, Virginia Beach, VA, Unpublished conference paper, 2013.
[19] "Encryption and Decryption of Documents.," OpenEMR Wiki, [online] 2013,
http://www.openemr.org/wiki/index.php/Encryption_and_Decryption_of_Documents (Accessed: July &
Aug. 2013).
[20] “Open Source Solutions.,” Tolven, [online] 2013, http://home.tolven.org/ (Accessed: 10 September
2013).

24.
DEVELOPMENT OF A RESPIRATION RATE METER –A LOW-COST DESIGN
APPROACH
Souvik Das
Department of Biomedical Engineering JIS College of Engineering, West Bengal, India
ABSTRACT
Measurement of physiological parameters like respiration rate is crucial in field of medicine.
Respiration rate can indicate the state of rhythmic behaviour of heart and proper gaseous exchange in
blood. As per Medical research, respiratory rate is regarded as the marker of pulmonary dysfunction.
Respiration rate meters are used in measuring CO2 in expired air and in apnea detectors. It is also used
in daily physiological tests like stress-o-meter for assessing ones level of stress that he/she can perceive
in life after monitoring respiration rate, pulse rate and heart rate. This paper shed lights on the
development of a lowcost respiration rate meter using infrared sensing and associated digital electronic
circuitry. The proposed device is able to measure respiration rate in the range of 0-999
respirations/minute.
KEYWORDS
Respiration Rate Meter, Biomedical Device, Physiological Stress, Medical Electronics, Apnea Detector,
Digital Circuits
For More Details: https://airccse.org/journal/hiij/papers/2213hiij02.pdf
Volume Link: https://airccse.org/journal/hiij/Current2013.html

25.
REFERENCES
[1] K.S. Tan, R. Saatchi, H. Elphick, and D. Burke: Real-Time Vision Based Respiration Monitoring
System, 7th International Symposium on Communication Systems Networks and Digital Signal
Processing (2010), p. 770-774.
[2] J. Zhang, and D.Y.T. Goh: A Novel Respiratory Rate Estimation Method for Sound-Based
Wearable Monitoring Systems, 33rd Annual International Conference of the IEEE EMBS (2011), p.
3213- 3216.
[3] S Kesten, R Maleki-Yazdi, BR Sanders, JA Wells, SL McKillop, KR Chapman and AS Rebuck:
Respiratory rate during acute asthma, Chest, Vol. 97(1) (1990), p. 58-62.
[4] D. Wu, L. Wang, , Y.T. Zhang, B.Y. Huang, B. Wang, S.J. Lin, and X.W. Xu: A Wearable
Respiration Monitoring System Based on Digital Respiratory Inductive Plethysmography, 31st Annual
International Conference of the IEEE EMBS (2009), p. 4844-4847.
[5] X. Zhu et al.: Real-time Monitoring of Respiration Rhythm and Pulse Rate During Sleep, IEEE
Trans. Biomed. Eng., Vol. 53 (2006).
[6] FQ AL-Khalidi, R. Saatchi, D. Burke and H. Elphick: Facial Tracking Method for Noncontact
Respiration Rate Monitoring, 7th International Symposium on Communication Systems Networks and
Digital Signal Processing (2010), p. 751-754.
[7] B. Mazzanti et al.: Validation of an ECG-derived respiration monitoring method, Computers in
Cardiology, Vol.30 (2003), pp.613-616.
[8] D.C. White: The History and Development of Low Flow Breathing Systems. IEE Seminar, Low
Flow Anaesthesia Breathing Systems - Technology, Safety and Economics (1999), p.1.
[9] S.C. Nijhawan, V.K. Sharma and R.S. Khandpur: A Beat-to-Beat Heart Rate Meter, IEEE
transactions on biomedical engineering, Vol. BME-28 (1981), p. 42-44.
[10] M.L. Fichtenbaum: Counter inverts period to measure low frequency, Electronics, Vol. 49 (1976),
pp. 100.
[11] R.C. Wang and T.W. Calvert: A Model to Predict Respiration from VCG Measurements,
Proceedings of IEEE Conference on Decision and Control and 11th Symposium on Adaptive Processes
(1972), p. 14-18.
[12] R. Ellis et al.: Comparative review of techniques for recording respiratory events at rest and
during deglutition, Dysphagia, Vol. 12 (1997), p. 24–38.
[13] S. Iamratanakull, J. McNamesl and B. Goldstein: Estimation of Respiration from Physiologic
Pressure Signals, Proceedings of the 25th Annual International Conference of the IEEE EMBS (2003),
p. 2734-2737.
[14] S. Brady, L.E. Dunne, R. Tynan, D. Diamond, B. Smyth, G.M.P. O’Hare: Garment-Based
Monitoring of Respiration Rate Using a Foam Pressure Sensor, Proceedings, Ninth IEEE International
Symposium on Wearable Computers (2005), p. 214-215.
[15] V. Vasu, N. Fox, T. Brabetz, M. Wren, C. Heneghan and S. Sezer: Detection of Cardiac Activity
using a 5.8 GHz Radio Frequency Sensor, 31st Annual International Conference of the IEEE EMBS
(2009), p. 4682-4686.
[16] J.H. Choi, and D.K. Kim: A Remote Compact Sensor for the Real-Time Monitoring of Human
Heartbeat and Respiration Rate, IEEE transactions on biomedical circuits and systems, Vol. 3 (2009),
p. 181-187.

26.
[17] H. Miwa and K. Sakai: Development of heart rate and respiration rate measurement system using
body-sound, Proceedings of the 9th International Conference on Information Technology and
Applications in Biomedicine (2009), p. 1-4.
[18] L Scalise, P Marchionni and I Ercoli: Optical Method for Measurement of Respiration Rate,
Proceedings, IEEE International Workshop on Medical Measurements and Applications (2010), p. 19-
22.
[19] S.D. Min, J.K. Kim, H.S. Shin, Y.H. Yun, C.K. Lee, and M. Lee: Noncontact Respiration Rate
Measurement System Using an Ultrasonic Proximity Sensor, IEEE sensors journal, Vol. 10 (2010), p.
1732-1739.
[20] S. Ansari, A. Belle, K. Najarian and K. Ward: Impedance Plethysmography on the Arms:
Respiration Monitoring, IEEE International Conference on Bioinformatics and Biomedicine
Workshops (2010), p. 471-72.
[21] A.E. Santo and C. Carbajal: Respiration Rate Extraction from ECG Signal via Discrete Wavelet
Transform, Circuits and Systems for Medical and Environmental Applications Workshop (2010), p. 1-
4.
[22] T. Hoffmann, B. Eilebrecht, and S. Leonhardt: Respiratory Monitoring System on the Basis of
Capacitive Textile Force Sensors, IEEE sensors journal, Vol. 11(2011), p. 1112-1119.
[23] M. Otsu, R. Nakamura, and A. Kajiwara: Remote Respiration Monitoring Sensor Using Stepped-
FM, IEEE Sensors Applications Symposium (2011), p. 155-158.
[24] K.V. Madhav, M.R. Ram, E.H. Krishna, N.R. Komalla, K.A. Reddy: Estimation of Respiration
Rate from ECG, BP and PPG signals using Empirical Mode Decomposition, IEEE Instrumentation and
Measurement Technology Conference (2011), pp. 1-4.
[25] L. Scalise, I. Ercoli, P. Marchionni and E.P. Tomasini: Measurement of Respiration Rate in
Preterm Infants by Laser Doppler Vibrometry, IEEE International Workshop on Medical
Measurements and Applications Proceedings (2011), p. 657-661.
Authors
Mr. Souvik Das did his M.E. in Biomedical Engineering from Jadavpur University,
West Bengal and B.Tech in Electronics & Instrumentation Engineering from University
of Kalyani, West Bengal. His research interests include medical device development,
sensor development, patient care monitoring and biomechanics. He has 6 years of
teaching and 1 year research experience. He has published 10 research papers in
National and International Journals, conferences and seminars. He has also participated
and presented research papers in various National and International Conferences/ seminars/ symposiums
etc. He is member of IAENG, IACSIT, ISDWT and ISCOC

27.
MHEALTH APPLICATIONS DEVELOPED BY THE MINISTRY
OF HEALTH FOR PUBLIC USERS INKSA: A PERSUASIVE
SYSTEMS DESIGN EVALUATION
Asmaa Shati
Department of Information Systems, IMSIU University, Riyadh, KSA Department of
Information Systems, KKU University, Abha, KSA
ABSTRACT
mHealth applications have shown promise in supporting the delivery of health services in
peoples’ daily life. Recently, the Ministry of Health in the Kingdom of Saudi Arabia (MOH)
has launched several mHealth applications to develop work mechanisms. Our study aimed to
identify and understand the design of mHealth apps by classifying their persuasive features
using the Persuasive Systems Design (PSD) model and expert evaluation method. This paper
presents the distinct persuasive features applied in recent applications launched by MOH for
public users called “Sehha & Mawid” Apps. The results revealed the extensive use of
persuasive features; particularly features related to credibility support, dialogue support and
primary task support respectively. The implementation and design of social support features
were found to be poor; this could be due to the nature of the apps or lack of knowledge from
the developers’ perspectives. The findings suggest some features that may improve the
persuasion for the evaluated apps.
KEYWORDS
Persuasion, mHealth apps, The persuasive systems design model (PSD), MOH, Persuasive features.
For More Details: https://aircconline.com/hiij/V9N1/9120hiij01.pdf
Volume Link: https://airccse.org/journal/hiij/Current2020.html

28.
REFERENCES
[1] M. Alhammad and S. Gulliver, "ONLINE PERSUASION FOR E-COMMERCE WEBSITES", In
Proceedings of the 28th International BCS Human Computer Interaction Conference on HCI 2014-
Sand, Sea and Sky-Holiday HCI. BCS. pp. 264-269.
[2] C. Aranda-Jan, N. Mohutsiwa-Dibe and S. Loukanova, "Systematic review on what works, what
does not work and why of implementation of mobile health (mHealth) projects in Africa", BMC Public
Health, vol. 14, no. 1, 2014.
[3] P. Briñol and R. Petty, "Persuasion: Insights from the self-validation hypothesis", Advances in
experimental social psychology, vol. 41, pp. 69-118, 2009.
[4] S. Consolvo, P. Klasnja, W. McDonald, D. Avrahami, J.Froehlich, L. LeGrand, ... & J. Landay,
“Flowers or a robot army?: encouraging awareness & activity with personal, mobile displays,” In
Proceedings of the 10th international conference on Ubiquitous computing, 2008, pp. 54-63.
[5] B. Fogg, “A behavior model for persuasive design” , In Proceedings of the 4th international
Conference on Persuasive Technology, 2009, p. 40.
[6] X. Gu, X. Yang, H. Li, Jain and C. Liang, "Understanding the Role of Mobile Internet-Based Health
Services on Patient Satisfaction and Word- of-Mouth", International Journal of Environmental Research
and Public Health, vol. 15, no. 9, p. 1972, 2018.
[7] P. Klasnja and W. Pratt, "Healthcare in the pocket: Mapping the space of mobile-phone health
interventions", Journal of Biomedical Informatics, vol. 45, no. 1, pp. 184-198, 2012.
[8] S. Langrial, T. Lehto, H. Oinas-Kukkonen, M. Harjumaa, & P. Karppinen, “Native Mobile
Applications for Personal Well-Being: A Persuasive Systems Design Evaluation”, In PACIS, 2012, p.
93.
[9] D. Lockton, D. Harrison and N. Stanton, "The Design with Intent Method: A design tool for
influencing user behaviour", Applied Ergonomics, vol. 41, no. 3, pp. 382-392, 2010.
[10] H. Oinas-Kukkonen, "Persuasive Systems Design: Key Issues, Process Model, and System
Features", Communications of the Association for Information Systems, vol. 24, 2009.
[11] T. Räisänen, T. Lehto and H. Oinas-Kukkonen, "Practical Findings from Applying the PSD
Model for Evaluating Software Design Specifications", Persuasive Technology, pp. 185-192, 2010.
Available: 10.1007/978-3-642-13226-1_19 [Accessed 8 November 2019].
[12] WHO Global Observatory for eHealth (2011) New horizons for health through mobile
technologies. Geneva: World Health Organization. available:
http://www.who.int/goe/publications/ehealth_series_vol3/en/
[13] A. M.Mostafa, A. E.Youssef and G. Alshorbag, "A Framework for a Smart Social Blood
Donation System Based on Mobile Cloud Computing", Health Informatics - An International Journal,
vol. 3, no. 4, pp. 1-10, 2014. Available: 10.5121/hiij.2014.3401 [Accessed 3 December 2019].
[14] R. Hasanain, K. Vallmuur and M. Clark, "Progress and Challenges in the Implementation of
Electronic Medical Records in Saudi Arabia: A Systematic Review", Health Informatics - An
International Journal, vol. 3, no. 2, pp. 1-14, 2014. Available: 10.5121/hiij.2014.3201 [Accessed 3
December 2019]
AUTHOR
Asmaa Shati is a student of MSc (Information Systems) in University of IMSIU. She is working as a
Teaching Assistant, Department of Information Systems, University of KKU, KSA. Her research of
interest includes Human Computer Interaction, System Analysis and Design, Persuasion Technology and
Mobile Computing