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Internet of Medical Things (IOMT): Applications, Benefits and Future Challenges in Healthcare Domain

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Internet of Medical Things (IOMT) is playing vital role in healthcare industry to increase the accuracy, reliability and productivity of electronic devices. Researchers are contributing towards a digitized healthcare system by interconnecting the available medical resources and healthcare services. As IOT converge various domains but our focus is related to research contribution of IOT in healthcare domain. This paper presents the peoples contribution of IOT in healthcare domain, application and future challenges of IOT in term of medical services in healthcare. We do hope that this work will be useful for researchers and practitioners in the field, helping them to understand the huge potential of IoT in medical domain and identification of major challenges in IOMT. This work will also help the researchers to understand applications of IOT in healthcare domain. This contribution will help the researchers to understand the previous contribution of IOT in healthcare industry.
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Internet of Medical Things (IOMT): Applications, Benefits
and Future Challenges In Healthcare Domain
Gulraiz J. Joyia1, Rao M. Liaqat2, Aftab Farooq3, Saad Rehman4
1, 2, 3,4National University of Sciences and Technology, Islamabad, Pakistan
Email: ingrgulraiz@gmail.com; muzammilliaqat@gmail.com; aftabfarooq2012@gmail.com; saadrehman@ce.nust.edu.pk
AbstractInternet of Medical things (IOMT) is playing vital role
in healthcare industry to increase the accuracy, reliability and
productivity of electronic devices. Researchers are contributing
towards a digitized healthcare system by interconnecting the
available medical resources and healthcare services. As IOT
converge various domains but our focus is related to research
contribution of IOT in healthcare domain. This paper presents the
peoples contribution of IOT in healthcare domain, application and
future challenges of IOT in term of medical services in healthcare.
We do hope that this work will be useful for researchers and
practitioners in the field, helping them to understand the huge
potential of IoT in medical domain and identification of major
challenges in IOMT. This work will also help the researchers to
understand applications of IOT in healthcare domain. This
contribution will help the researchers to understand the previous
contribution of IOT in healthcare industry.
Keywords- iot; IOMT; healthcare; challenges
I. INTRODUCTION
All manuscripts must be in English. Internet of things
is not a new concept but it is hot topic in the world. This is
not astonishing that around the world, 18.2 billion devices
are connected using internet of things (iot) [1]. This includes
all categories of iot in the world. Basically iot is the
internetworking of electronic devices to enable exchange of
data between devices for specific domain applications. This
concept of internetworking in internet of things (iot) makes
human life much easier than before. According to WHO,
Pakistan is facing health problems and our life expectancy in
2015 for males is 64.5 and for females it is 67.3 years [2].
This has gained our attention on iot and more over iot is most
promising solution for health care industry because it helps
patients to manage their own disease and receive help in
most emergency case via mobile [3].
It is anticipated that the demand for personal
healthcare applications will increase sharply. In the
traditional medical mode, the quality and scale of medical
service can't meet the needs of patients [4]. It is of great
significance to establish a set of family oriented remote
medical surveillance system based on mobile Internet.
Generally, the provision of healthcare facilities through
mobile devices is called m- health, which is used to analyze,
capture, transmit and store health statistics from multiple
resources, including sensors and other biomedical acquisition
systems. M-health offers an elegant solution to a problem
commonly faced in the medical field: how to access the right
information when and where needed in highly dynamic and
distributed healthcare organizations [5]. These health
applications can guide different type of spectators such as
guardians of patients, patients itself, doctors, nurses and
healthy peoples too. These m health provide better medical
services, efficiency , more effectiveness of health plan and
services so this reduce the cost of health maintenance.
Fig [1] Communication of IOT
Above Figure shows how iot does communicate with
other network devices. Doctors, patients and rest of the
networking system is connected to each other. All record is
digital and save in the databases which is accessible by the
doctors and clinical staff as well.
By this m health service we can reach easily the
standard of medical services and quality of medication as per
patient needs [4]. The iot based system is responsible for the
full care of the patient and these systems are flexible to the
patients conditions and there parameters can be set as per
patient illness. With this approach we will be able sure about
present and future health states of patient.
In this research paper, we will be discussing mainly
the applications, benefits and future challenges of internet of
things (IoT) based on the work done by different researchers
in the field of iot. The main aim of this paper is to provide an
overall idea of what Internet of Things is, the different form
of applications it has adopt, and how it is providing a
solution for the problems faced by the global health care
industry [6].
II. LITERATURE REVIEW
Shu-yuan Ge et. al. introduced a design which is
basically integration of 11073 IEEE Service/DIM and CoAP
to apply on devices of healthcare so they can be used in iot
settings. They also showed the comparison of performance
of Both HTTP and 11073 DIM by help of CoAP. They also
evaluated performance with CoAP and HTTP with respect to
packets abundance in single transaction, packets loss rate and
syntax by using JSON and XML. Finally they concluded that
CoAP is able to transmit few packets as compare to HTTP.
In terms of consumption of resources they said that XML is
not better than JSON [7].
Georges Matar et. al. proposed a technique to monitor
patient posture by using patient body weight that exerts
pressure on specially designed mattress, he used the
measured pressure for monitoring patient posture. He also
ensures his work by the help of Cohen’s Coefficient, the
value of the coefficient is .866 which means high accuracy of
detection. He also revealed that purpose of this work was to
reduce storage requirement and cost on computation [8].
Chao-Hsi Huang et. al. explained the designed MNS
(medical nursing system), his system is based on iot
architecture and used 2G-3G, WSN, RFID, sensor, ZigBee,
Wi-fi and Bluetooth for data transferring. His system also
enables supply of drugs with accuracy [9].
Yuan jie fan et. al. in his research he used SOA
techniques, iot technology, optimization technique,
resource allocation and ontology for diagnosis to design a
rehabilitation system. He also presented a methodology
for designing of rehabilitation system by using Iot
Technology. In the paper two key features are mentioned
which include construction of the rehabilitation and
easiness of sharing of the domain information [10].
Willian D. de Mattos et. al. represented the linkage of
m-health domain with m2m (machine to machine) and 5G
technologies. According to him new technologies will
open gate ways to solutions of m-health [5].
Iuliana Chiuchisan et. al. in the literature for Parkinsons’s
infection test, presented an intelligent system. He mentioned
monitoring system for home and support system for
decision making which not only support also assist the
physicians in medical treatment, prescriptions, diagnosis,
rehabilitation and patient progress [11].
Robert S .H. Istepanian et. al. in his research he
introduces a unique concept of iot in medical health.
According to him his concept is very helpful by mean of
functionalities of iot and medical health for upcoming
applications of 4G health, which will base on IPV6
connection[12].
Dr. Salah S. Al-Majeed et. al. in the research he proposed
to develop a device which is basically a medical sensing
device, low cost and iot based device to monitor patients
physiological conditions. The main focus of his research is
communication of messages and synchronization. Time
minimizing algorithm is applied to keep separation between
consecutive messages and measure the queue size for
individual health care nods, to avoid conjunction [13].
Hyun Jung La et. al. due to the increasing scope of iot, he
come up with a concept to maintain the data of the iot
application. He adopted semantic approach to deal with
challenges in his research and he presented a cloud based
proposal which provide core set of functionalities to help
individual diagnosis on network[14].
Beibei Dong et. al. researcher mentioned the problems in
detection of a patient in health monitoring system. In this
paper he provide solution to noise in signals and low rate of
accuracy in detection [4].
Diego Gachet Páez et. al. in this research author provided
key solution for initiation of services which will base on
internet of things and data engineering concepts [15].
K.B. Sundhara Kumar et. al. author provides a system
that monitor autism patient automatically, using sensors for
an individual patient. This system not only monitors but also
keeps track of sensors readings collected from brain signals
of pretentious individual[16].
K.Divya Krishna et. al. proposed an algorithm CAD for
detection of abnormality in kidney ultrasonic image files on
FPGA. Research is dependent on two stages; first stage is
LUT look up table technique and second is SVM- support
vector machine. Mentioned algorithm is implemented over
FPGA based kintex 7 [17].
Boyi Xu et. al. author proposed a new framework for
medical healthcare monitoring, which is based on cloud
computing and specially this framework is designed for
implementation of healthcare monitoring. This framework is
implemented in different modules which are also discussed
in the paper [18].
Allavi Chavan et. al. researcher key objective in this
research is to design android application in healthcare area
by using the concept of internet of things and cloud
computing. Paper also focuses on waves of ECGmonitoring
using an android application platform [19].
Harshal Arbat et. al. researcher worked to design a new
tool due to increasing trend in internet of things and its
demand. In the domain of m-health researcher focus on keep
track of patient health by reading heart rate value , this heart
rate value is obtained by a band called smart health band. On
this obtained value specific message will be transmitted to
his family or friend [20].
Lei Yu et. al. Researcher presented a scheme and
architecture of smart hospital, which is based on iot to have a
better hospital system. This hospital system will help to
manage information of old hospital system [21].
Avik Ghose et. al. author has designed a monitoring
system for aged patients. His research present a method of
end to end medical healthcare system to monitor the patient.
System basically use internet of things technique (iot), which
is back end platform [22].
K. M. Chaman Kumar et. al. research presented a new
technique to monitor such patients which are diseased OSA
(obstructive sleep apnea) and also help full for diseases
similar to this. [23]
Rashmi Singh et. al. presented a model for electronic
health care unit by using internet of things based on India
statistics of health. According to the research it is easy to
implement such research with the help of RFID tech and
experienced healthcare system, as he mentioned Mycin.
Indian medical units can be digitized easily by this presented
model [24].
Chetanya Puri et. al. researcher is aimed to present a new
dimension in the domain of cardio signals, so to make this
happen researcher presented a new technique for cardiac
patient, as this will intimate early about any warning.
Researcher named this technique iCarMa. This also include
the severity of cardiac patient and its timely detection and
diagnosis [25].
Ihor Vasyltsov et. al. author basically has focus on
gaining entropy from heart rate on the basis of biomedical
signals. Some mathematical models are presented to obtain
entropy. More over these results of entropy will be used for
security of health-care system and useful for device
certification [26].
Vivek Chandel et. al. has found a way to consistently
monitor the patient health by means of IMUs (inertial
measurement units). So to use this they presented a accurate
and improved algorithm for sensing the events of patient,
similar to counting of steps, length of stride, immobility and
fall etc [27].
Michael Fischer et. al. the idea is very simple, train a bot
using information in the book. Bot will help
nonprofessionals to know about the disease, even this bot
can be integrated with different sensors on mobile phone to
provide more flexible service by using iot (internet of things)
[28].
Mrs. Anjali S. Yeole et. al. done a survey on enabled iot
devices and there practices in healthcare domain for medical
dispense, children ,operation theaters, serious patients
monitoring, toddler and chronic care [29].
Sultan Alasmari et. al. has discusses the patient
healthcare information is the most critical information that
should be kept in safe hands. Iot has bought a tremendous
change in the domain of medical. Author specifically
discusses the challenges and survey the security and privacy
with context to iot. According to him the use of cloud for iot
has introduced the non-compliance and risk factor in medical
environment. He proposed a solution to this problem is the
people from multiple disciplines, should be included in the
research to evaluate the issue and find the facts of the
problem to resolve it [33].
Ghulam Muhammad et. al. discusses the importance of
integration of cloud computing with iot in healthcare
domain. He raised some issues in medical domain with
context of iot those should be resolved to improve the
domain in healthcare. He has proposed a system for
monitoring the audio pathology for people monitoring by the
help of cloud computing. Ease of use and interoperability are
the problems which are addressed and resolved in his
framework. According to him the scalability of dynamic
nature can be achieved by integration of different voice
models. Finally he also suggested a new framework can be
proposed to tackle the huge data using cloud technology
[34].
S. M. Riazul Islam et. al. in the paper author discusses
technologies, industrial focus, application and framework of
iot. The major focus of the paper was taxonomies attack,
models, requirements of security, iot privacy and security
features. He also discussed how iot is playing a role in
different fields of medical domain. Author proposed
intelligent model to decrease risk of security and discusses
the advancement of technology in the domain of iot with
context of medical things and also proposed e-health with iot
policies for the sake of different stackholders. Author
finishes his research by commenting that his work will be
beneficial for engineers, researches and policymakers in the
field of iot [35].
Darshan K R et. al. has discussed that if serious disorders
are predicted in the early stage then it will be very beneficial
for the patient. He said iot is providing the remote healthcare
systems to facilitate the society. In this literature the author
discuss the uses, challenges and reviews of all previous work
done related to iot in medical or healthcare domain and a
methodology presented is also discussed in this paper. In his
research he also aimed to increase the quality and efficiency
in the field of healthcare [36].
Dapheny et. al. he depicted the framework or
infrastructure plays an important role in the field of iot. He
reviewed different models that enable optimum and
progressive decision making reviewed in context of iot.
Many opportunities and challenges associated with this were
also discussed. According to author smart living is a good
option to provide smart healthcare to the peoples [37].
Kuo-hui yeh et. al. the advancement in the
communication brings new era of iot which is based on
networks. In the literature he proposed a new iot based
system which works on body sensor network, to reach
robustness and efficiency in public iot network. Author also
kept security parameter in mind to secure the proposed
system. He mentioned to guarantee the proposed system and
scheme it is more suitable to apply the scheme to the
common mobile object [38].
III. APPLICATIONS OF IOT IN HEALTHCARE
Table I Shows number of applications researched in
the field of iot from year 2012 up to 2016. There are five
columns each represents some attribute, serial number,
application, author name, published year and reference of the
paper from where we researched. All the applications we
researched are from the medical healthcare systems. Most of
the applications are from the research papers which are
published in 2016. So, our researched applications are up to
date.
TABLE I. APPLICATIONS OF IOT
Sr. #
Applications In Medical Domain
Application
Author et. al.
year
Reference
1
Medical Nursing
System
Chao-Hsi
Huang
201
4
[9]
2
Smart
Rehabilitation
System
YuanJieFan
2014
[10]
3
Iot based Kidney
abnormality
detection system
using ultrasound
imaging
K.Divya
Krishna
2016
[17]
4
Application for
patient posture
recognition using
supervised learning
Georges
M
Atar
2016
[8]
5
Monitoring patient
physiological
conditions
Dr. Salah S.
Al-Majeed
2015
[13]
6
Decision making
and home based
medical health
monitoring system
for neurological
disabled patients
Iuliana
Chiuchisan
2014
[11]
7
Autistic patient
monitoring medical
health care system
using iot
K.B.Sundhar
aKumar
2016
[16]
8
Smart medical
nursing healthcare
system for patients
Karan
Motwani
2016
[6]
9
Remotely ECG
monitoring system
based on cloud
Pallavi
Chavan
2016
[19]
10
Secured and smart
medical healthcare
system
Duddela
Dileep
Kumar
2016
[30]
11
Iot based smart
medical health
band
Harshal
Arbat
2016
[20]
12
Iot based smart
Hospital
Lei Yu
2012
[21]
13
Monitoring of OSA
(obstructive sleep
apnea) diseased
patient
K.M.
Chaman
Kumar
2016
[23]
14
Mobile electronic
medical health care
system based on iot
Rashmi
Singh
2016
[24]
15
Inexpensive
cardiac arrhythmia
management
(ICarMa) system
Chetanya
Puri
2016
[25]
16
Iot based medical
healthcare
monitoring system.
Vivek
Chandel
2016
[27]
17
Medical Bot
Michael
Fischer
2016
[28]
18
Ubiquitous medical
Healthcare
Monitor System
(UbiHeld) for
Chronic diseased
Patient
Avik
Ghose
2013
[22]
1. Searched number of applications in the field of iot in medical domain
We have selected these applications on the basis of
contribution of different researchers in the field of IoT from
different resources. On the basis of selection and rejection
criteria we have selected papers from different authentic
repositories like ACM, IEEE and Elsevier etc. We have
included those applications which were most recent in the
field of IoT with context of healthcare. The purpose was to
list applications of IoT in medical healthcare domain.
A. Depiction of yearly contribution in context of Multiple
databases
Bar Graph I depicts that different colors are assigned to
each year and on x-axis there are names of data base that is
used for applications research. It is very visible that most of
the papers are from year 2016 shown in sky blue color. On y-
axis there are number of the paper with respect to the
researched data bases for applications onlyMaintaining the
Integrity of the Specifications only.
2. Depicting yea rly contribution in context of IOMT
This graphical view depicts the number of researches we
took in our research. Our main focus was to select the most
recent research papers related to IoT in the field of medical
health care. Latest researches are shown with high peaks in
the graph.
B. Challenges of IoT in healthcare
After a brief research we listed some significant
challenges in the domain of iot. We believe that if these
challenges are met in the field of iot, we can improve iot
standard in the field of medical care. IoT can provide more
reliable and better services in the field of medical health
care.
Due to IoT there is revolutionary change in the field of
internet communication; this has a lot of contribution in the
growth of many challenging domains but especially in the
field of medical things. This is the one of major reasons to
close the gap between doctors, patient and healthcare
services by its ease, accuracy and flexibility. IoT enable the
doctors and hospital staff to do their work more precisely and
actively with less effort and intelligence.
TABLE II. CHALLENGES OF IOT
Challenges In Medical Domain
References
Challenges
[31]
Managing device diversity
Scale, data volume and performance
Flexibility and evolution of applications
Data privacy
Need for medical expertise
[31]
CPU capa city
Memory of the system
Constrained over network performance
like bandwidth
[7]
Data exchange
Availability of resources
Privacy
[3]
Hardware implementation and design
optimization issues
[8]
Security challenges
[12] [3],[32],
[24]
Interoperability
[3],31 ,[18]
Technical challenges: Modeling
relationship between acquired
measurement and diseases.
Software implementation of medical
analytic schemes.
[14]
Intelligence in Medical Care.
[9]
Real time processing
System predictability
Low power consumption
[32]
Data integration
[31], [18]
Unstructured, growing and diverse data
at exponential rate
[19]
3. Searched number of challenges in the field of iot in medical domain
We have selected these Challenges on the basis of
contribution of different researchers in the field of IoT from
different resources. On the basis of selection and rejection
criteria we have selected papers from different authentic
repositories like ACM, IEEE and Elsevier etc. We have
included those challenges which were most recent in the
field of IoT with context of healthcare. The purpose was to
list challenges of IoT in medical healthcare domain.
C. Benefits of iot in healthcare:
Iot has many advantages to individuals, society, the
environment, consumers and business, as with every
technology there are some benefits with some drawbacks.
Following table provide the list of major benefits we
have from iot. Though, iot is very beneficial in the domain of
the medical health care. Iot based applications and systems
have transformed the world into an imaginary world which
human of 90’s thought about. Due to Iot there is
revolutionary change in the field of internet communication;
this has a lot of contribution in the growth of many
challenging domains but especially in the field of medical
things. This is the one of major reasons to close the gap
between doctors, patient and healthcare services by its ease,
accuracy and flexibility. IoT enable the doctors and hospital
staff to do their work more precisely and actively with less
effort and intelligence. Proof of this is above mentioned table
II of applications.
This integration of iot in the field of medical has
provided incredible advantages to patients; iot is very easy to
use.
TABLE III. BENEFITS OF IOT
Sr. #
Benefits In Medical Domain
References
Benefits
1
Make life more convenient
Healthcare is chea p
Outcome of patient is imp roved
Management of diseases is real -
time
Life quality is Improved
user end experience is improved
care for patient is increased
costs reduction
Ultima te benefit is healthier and
longer lives, Maximum diseases
management and prevention
children’s / elder parents progress is
monitored
Major change in health of patient
will make an automatic alert to
different parties, save lives and t ime
Resources of iot other iot devices
[31]
2
Medication is on t ime
Patient care will be intimated to
family mem bers
[9]
3
Simplicity
Affordab ility
Ease to use
[25]
4
Doctors can manage patients
records easily
[30]
5
Energy efficiency which inc lude
time,
money etc.
[24]
6
Doctors Off t ime medical services by
IoT
[28]
4. Searched number of benefits in the field of iot in medical domain
We have selected these benefits on the basis of
contribution of different researchers in the field of IoT from
different resources. On the basis of selection and rejection
criteria we have selected papers from different authentic
repositories like ACM, IEEE, and Elsevier etc. We have
included those benefits which were most recent in the field
of IoT with context of healthcare. As the field of the iot is
emerging and expanding very quickly, so it was very
important to list the benefits of the iot in medical healthcare.
The purpose was to list benefits of IoT in medical healthcare
domain.
IV. EXPLANATION OF WORK
In this research paper, we have discussed mainly the
applications, future challenges and benefits of internet of
things (IoT) based on the work done by different researchers
in the field of IoT. All the applications we researched are
from the medical healthcare systems. Most of the
applications are from the research papers which are
published in 2016. Actually there are many challenges that
has to be counter but we have briefly identified some of the
significant challenges in the file of iot in context of
healthcare that are detailed discussed in section III. We
believe that if these challenges are met in the field of iot, we
can improve iot standard in the field of medical care. iot can
provide more reliable and better services in the field of
medical health care.
As a result we can say that Iot based applications and
systems have transformed the world into a imaginary world
which human of 90’s thought about. Iot enable the doctors
and hospital staff to do their work more precisely and
actively with less effort and intelligence. That is mentioned
above in the section III.
V. CONCLUSION & FUTURE WORK
In this paper, we provided an overview related to IoT
services and technologies in healthcare. A number of
research challenges have been identified, which are expected
to become major research trends in the next years. The most
relevant application fields have been presented, and a
number of use research benefits identified. We hope that this
work will be useful for researchers and practitioners in the
field, helping them to understand the huge potential of IoT in
medical domain and identification of major challenges in
IOMT. This work will also help the researchers to
understand applications of IOT in healthcare domain.
REFERENCES
[1] Internet of Things (IoT): number of connected devices
worldwide from 2012 to 2020 (in billions).
https://www.statista.com/statistics/471264/iot-number-of-connected-
devices-worldwide/
[2] Institute of health metrics and evaluation, 2015
http://www.healthdata.org/pakistan
[3] Foteini Andriopoulou, Tasos Dagiuklas, and Theofanis
Orphanoudakis, Integrating IoT and Fog Computing for Healthcare
Service Delivery, Springer International Publishing Switzerland.
doi: 10.1007/978-3-319-42304-3_11
[4] Beibei Dong, Jingjing Yang, Yanli Ma and Xiao Zhang*,
Medical Monitoring Model of Internet of Things Based on the
Adaptive Threshold Difference Algorithm, International Journal
of Multimedia and Ubiquitous Engineering 2016. doi:
10.14257/ijmue.2016.11.5.08
[5] Willian D. de Mattos and Paulo R.L. Gondim, “M-Health Solutions
Using 5GNetwork s and M2 M Communications, Published by the
IEEE Computer Society 2016.ISSN: 1520-9202
[6] Karan Motwani, Divesh Mirchandani, YogeetaRohra, Heena
Tarachandani & Prof. Anjali Y eole, Smart Nursing Ho me
Patient Monitoring System, Imperial Journal of Interdisciplinary
Research (IJIR), Vol-2, Issue-6, 2016. ISSN: 2454-1362
[7] Shu-yuan Ge, Seung-Man Chun, Hyun-Su Kim and Jong-Tae Park,
Design and Implementation of Interoperable IoT Healthcar e
System Based on International Standards, 2016 13th IEEE Annual
Consumer Communications & Networking Conference (CCNC).
doi: 978-1- 4673-9292-1
[8] Georges Matar, jean-marc Lina,Georges Kaddoum, Anna Riley,
Internet of Things in Sleep Monitoring: An Application for
Posture Recognition Using Supervised Learning.
doi :10.13140/RG.2.2.21729.30561
[9] Chao-Hsi Huang, Kung-Wei Che ng, RFID Technology
Combined with IoT Application in Medical Nursing System ,
Volume 3, Number 1, pages 20-24, January 20 14. ISSN: 2186-
5140
[10] Yua n Jie Fa n, Yue Hong Yin, Member, IoT-Based Smart
Rehabilitation System, IEEE, Li Da Xu, Senior Member, IEEE,
Yan Zeng, and Fan Wu, IEEE TRANSACTIONS ON
INDUSTRIAL INFORMATICS, VOL.10, NO.2, MAY 2014. E-
ISSN: 2395-0072
[11] I ULIAN A CHIUCHISAN, OAN A GEM AN, An Approach ofa
Decision Support and Home Monitoring System for Patients with
Neurological Disorders using Internet of Things Concepts,
Wseas transactions on systems, volume 13, 2014. E-ISSN: 2224-
2678
[12] Robert S .H. Istepanian, Ala Sungoor, Ali Faisal, Nada Philip,
INTERNET OF M-HEALTH THINGS “ m-IO T” , Assisted
Living 2011, IET Seminar on, 16 April 2012. doi:
10.1049/ic.2011.0036
[13] Dr. Salah S. Al- Majeed, Dr. Intisar S. Al-Mejibli, Prof. Jalal
Karam, Home Telehealth by Internet of T hings (IoT) ,
Canadian Conference on Electrical and Computer Engineering
Halifax, Canada,May 3-6, 2015. doi : 978-1-4799-5829-0
[14] Hyun Jung La Han Ter Jung, and Soo Dong Kim *, Extensible
Disease Diagnosis Cloud Platfor m with Medical Sensors and IoT
Devices, 2015 3rd International Conferenceon Future Internet of
Things and Cloud. doi : 10.1109/FiCloud.2015.65
[15] Diego Gachet Páez, Fernando Aparicio, Manuel de Buenaga, and
Juan R. Ascanio1, R. Hervás et al. Big Data and IoT for Chronic
Patient s Monitoring, (Eds.): UCAmI 2014, LNCS 8867, pp. 416
423, 2014. doi : 10.1007/978-3-319-13102-3_68
[16] K.B. Sundhara Kumar and Krishna Bai ravi, “IoT Based Health
Monitoring System for Autistic Patients, Symposium on Big
Data and Cloud Computing Challenges (ISBCC 16’), Smart
Innovation, Systems and Technologies 49, © Springer Internat
ional Publishing Switzerland 201 6. doi : 10.1007/978-3-319-
30348-2_32
[17] K. Divya Krishna, V. Akkala, R. Bharath, P. Rajalakshmi, A.M.
Moham med, Computer Aided Abnormality Detection for
Kidney on FPGA Based IoT Enabled Portable Ultrasound Imaging
System, S.N. Merchant, U.B. Desai, 1959-0318/© 2016 AGBM.
Published by Elsevier Masson SAS. doi :
10.1016/j.irbm.2016.05.001
[18] Boyi Xu, Lida Xu, Hongming Cai, Lihong Jiang, Yang Luo &
Yizhi Gu, The design of an m-Health monitoring system based
on a cloud computing plat form, Talor & Francis 2015. doi:
10.1080/17517575.2015.1053416
[19] Pallavi Chavan , Prerna More, Neha Thorat, Shraddha Yewale &
Pallavi Dhade, “ECG - Remote Patient Monitoring Using Cloud
Computing, Imperial Journal of Interdisciplinary Research (IJIR)
Vol-2,Issue-2 , 2016 , ISSN : 2454-1362
[20] Harshal Arbat1, Srishty Choudhary2 & Kumkum Bala, IOT
Smart Health Band, Imperial Journal of Interdisciplinary Research
(IJIR) Vol-2, Issue-5, 2016. ISSN: 2454-1362
[21] 1,2Lei Yu, Ya ng Lu , XiaoJuan Zhu , “ Smart Hospital based on
Internet of Things, journal of netwroks, vol 7, NO. 10, October
2012. doi :10.43.4/jnw.7.10.1654-1661
[22] Avik Ghose, Priyanka Sinha, Chirabrata Bhaumik, Aniruddha
Sinha, Amit Agrawal, Anirban Dutta Choudhury, UbiHeld-
Ubiquitous Healthcare Monitoring System for Elderly and Chronic
Patients”, ubiComp’13, September 8-12, 2013, Zurich,
Switzerland. doi: 10.1145/2494091.2497331
[23] K. M. Chaman Kumar, “ A New Methodology for Monitoring
OSA Patients Based on IoT, international journal of innovative
research & development, Vol 5 issues 2, 2016. ISSN: 2278
0211.
[24] Rashmi Singh, A Proposal for Mobile E-Care Health Service
System Using IOT for Indian Scenario, Journal of Network
Communications and Emerging Technologies (JNCET) Volume
6, Issue 1, January (2 016) © EverScience Publications. ISSN:
2395-5317.
[25] Chetanya Puri, Arijit Ukil and Soma Bandyopadhya y, iCarMa:
Inexpensive Cardiac Arrhythmia Management An IoT
Healthcare Analytics Solution, IoT of Health'16, June 30 2016.
doi: 10.1145/2933566.2933567
[26] Ihor Vasyltsov, Seunghwan Lee, “Entro py Extraction from Bio-
Signals in Healthcare IoT”, IoTPTS'15, April 14 -17, 2015,
Singapore. doi : 10.1145/2732209.2732213
[27] Vivek Chandel, Arijit Sinharay, Nasimuddin Ahmed, Exploiting
IMUSensors for IOT Enabled Health Monitoring, IoT of
Healt h’16June 30 -302016. doi : 10.1145/2933566.2933569
[28] Michael Fischer, Monica Lam,From Books to Bots: Using
Medical Literature to Create a Chat Bot, IoT of Health’ 16, June
30, 2 016,Singapore. doi : 10.1145/2933566.2933573
[29] Mrs. Anjali S. Yeole, Dr. D. R. Kalbande, “ Use of Internet of
Things (IoT) in Healthcare: A Survey, doi :
10.1145/2909067.2909079
[30] Duddela Dileep Kumar1 & Pratti Venkateswar lu,“Secured Smart
Healthcare Monitoring System Based on IOT, Imperial Journal
of Interdisciplinary Research (IJIR), Vol-2, Issue-10, 2016. ISSN:
2454-1362.
[31] http://www.tcs.com/resources/white_papers/Pages/Internet-of-
Things-Medical-Devices.aspx
[32] Vasileios Tsoutsourasm Dimirta Azariadi, Konstantina
Koliogewrgi, Sotirios Xydis a nd Dimitrios Sou dris,Software
Design and Optimization of ECG Signals Analysis and Diagnosis
for Embedded IoT Devices, doi:10.1007/978-3-319-42304-3_15
[33] Sultan Alasmari, Mohd Anwar, “Security & Privacy Challenges in
IoT-based Health Cloud”, 2016 International Conference on
Computational Science and Computational Intelligence,doi:
10.1109/CSCI.2016.43
[34] Ghulam Muhammad, SK Md Mizanur Rahman, Abdulhameed
Alelaiwi, and Atif Alamri, “Smart Health Solution Integrating IoT
and Cloud: A Case Study of Voice Pathology Monitoring” IEEE
Communications Magazine January 2017, doi:
10.1109/MCOM.2017.1600425CM
[35] S. M. Riazul islam 1, (member,ieee) , daehan kwak 2 , MD. Humaun
kabir1 , mahmud hossain3, and kyung-sup kwak1, (member,ieee),
“The Internet of Things for HealthCare: A Comprehensive Survey”,
IEEE, The journal for rapid open access publishing. doi:
10.1109/ACCESS.2015.2437951
[36] Darshan K R, Anandakumar K R, “A Comprehensive Review on
Usage of Internet of Things (IoT) in Healthcare System”,
International Conference on Emerging Research in Electronics,
Computer Science and Technology 2015,IEEE, doi: 978-1-4673-
9563-2
[37] Daphney Stavroula Zois “Sequential Decision Making in
Healthcare IoT: Real Time Health Monitoring, Treatments and
Interventions”,IEEE, doi: 978-1-5090-4130-5
[38] KUO - HUIYEH, (Senior Member, IEEE), “A Secure IoT-Based
Healthcare System With Body Sensor Networks” IEEE, The journal
for rapid open access publishing. doi:
10.1109/ACCESS.2016.2638038
Gulraiz Javaid Joyia
Research scholar at College of Electrical and
Mechanical Engineering, NUST, Rawalpindi.
ingrgulraiz@gmail.com
Rao Muzamal Liaqat
Research scholar at College of Electrical and
Mechanical Engineering, NUST, Rawalpindi.
muzammilliaqat@gmail.com
Aftab Farooq
Research scholar at College of Electrical and
Mechanical Engineering, NUST, Rawalpindi.
aftabfarooq2012@gmail.com
Dr. Saad Rehman
Research Supervisor at College of Electrical
and Mechanical Engineering, NUST,
Rawalpindi.
saadrehman@ce.nust.edu.pk
... High technology costs, poor image quality, lack of usage services, and the inability to integrate Internet medical care with mainstream healthcare services, most of which disappeared by 1980, led to a decade of hiatus in telemedicine activities (21,22). It was not until the mid-1990s, due to the rapid growth of the Internet, that Internet-based medicine was once again seen as a relevant solution to the problems of licensing and quality of healthcare (23). Telemedicine has also attracted interest in the healthcare community due to its ability to reduce costs and save time for both patients and healthcare professionals (24,25). ...
... Internet diagnosis and treatment activities are provided by a single medical institution, as a result, medical resources are isolated from each other, and it is difficult for patients to make referrals. The localization nature of medical insurance has also weakened its capability to break through geographical space limitations (23). However, it has been deeply rooted in China's telemedicine industry and has the largest number of business outlets and the largest application scale, helping to ease patients' difficulty in getting medical services to a large extent and achieving strong usage intention by patients. ...
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Introduction As a form of platform economy, telemedicine is not growing as fast as other digital platforms. The existing literature seldom pays attention to how licensing policy affects the development of telemedicine platform models. Methods This paper uses the method of multi-case study and the theory of policy implementation as mutual adaptation to research the influence mechanism of telemedicine platform licensing policy on the platform model in China. Results The findings of the current study are as follows: (1) three models can be classified in accordance with different platform providers in China: medical institution platform, Internet company platform and local government platform; (2) bargaining power, reputation mechanism and resource specificity are important dimensions in the analysis of platform models; (3) as an implementer in the process of licensing policy, the platform provider can not only directly determine the establishment and formation of platform model but also indirectly affect the sustainable development of platform model by affecting the supplier and the demander of platform; and (4) The impact between licensing policy and platform model is dynamic and bidirectional, mainly exerted via administrative orders, market-oriented mechanism and medical insurance. Conclusions The research enlightens practical exploration in telemedicine and enriches the theoretical innovation in platform.
... The IoT is having an increasing impact in the medical field in assisting with monitoring patients and supporting healthcare activities [6,7]. The Internet of Medical Things (IoMT) is a subdivision of the IoT that deals with interconnected medical devices and equipment that constitute healthcare information technology. ...
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... Industry 4.0, from the healthcare perspective. may be perceived as solutions for individuals (e.g., broadly defined eServices, such as wearable technology, the Internet of Medical Things) [24,25], solutions for healthcare institutions (e.g., bigdata for clinical trials) [26,27], and new medical treatment and health therapies (new medical procedures) [23,28]. In this paper, we define Health 4.0 as healthcare development under the new possibilities created by the Fourth Industrial Revolution, which is also called Industry 4.0 [12]. ...
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... Medical procedures are making increasing use of new technologies: surgery uses robots for precision and remote operations [14]; modern implants and prostheses are available, e.g., bionic implants and prostheses printed with 3D printers [15][16][17]; analytical and diagnostic data are being massively exploited thanks to new technologies that collect and analyse such data, e.g., through the use of AI [18]; routine medical procedures use medical devices, e.g., real-time monitoring of the user's health indicators to support and control the medical practice [19,20]. Industry 4.0, from the healthcare perspective, may be perceived as solutions for individuals (e.g., broadly defined eServices such as wearable technology; Internet of Medical Things) [21,22]; solutions for healthcare institutions (e.g., big-data for clinical trials) [23]; new medical treatment and health therapies (new medical procedures) [18]; intelligent computing (UAV computing) [24]; digital twins (DTs) [25]. We define Health 4.0 as healthcare operating under the new opportunities created by the fourth industrial revolution [7]. ...
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Literature research on cocreation in healthcare indicates the theoretical sophistication of research on collaboration between healthcare professionals and patients. Our research continues in the new area of Health 4.0. Cocreation has become an essential concept in the value creation process; by involving consumers in the creation process, better results are achieved regarding product quality and alignment with customer expectations and needs. In addition, consumer involvement in the creation process improves its efficiency. Cocreation allows for more efficient diagnosis and treatment of patients, as well as better and more effective use of the skills and experience of the health workforce. Our main objective is to determine the scope and depth of the cocreation of health services based on modern technological solutions (Health 4.0). We selected four cases involving Health 4.0 solutions, verified the scale and scope of cocreation using them as examples, and used the cocreation matrix. We used literature, case studies, and interviews in our research. Our analysis shows that patients can emerge as cocreators in the value creation process in Health 4.0. This can happen when they are genuinely involved in the process and when they feel responsible for the results. The article contributes to the existing theory of service cocreation by pointing out the limited scope of patient involvement in the service management process. For cocreation in Health 4.0 to increase the effectiveness of medical services, it is necessary to implement the full scope of cocreation and meaningfully empower the patient and medical workers in the creation process. This article verifies the theoretical analysis presented in our team’s previous article.
... Healthcare professionals, patients, and other stakeholders can be interconnected through different electronic devices to exchange valuable related information with each other. Considering this, the structural (connection, communication, and information generation) and the usability (application) aspects are vital components in IoMT [2][3][4]. IoMT successfully utilizes the new wave of information explosion, the scale of inter-connectivity among electronic devices that we have never seen before, and the healthcare revolution transforming our notion of traditional healthcare systems. Effective prevention of diseases, patient-centric healthcare, real-time distance-based monitoring with automatic diagnosis support tools, improved collaboration among caregivers and patients, sustainable health and longevity, and low-cost healthcare for everyone are critical examples of IoMT applications [5]. ...
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The concept of the Internet of Medical Things brings a promising option to utilize various electronic health records stored in different medical devices and servers to create practical but secure clinical decision support systems. To achieve such a system, we need to focus on several aspects, most notably the usability aspect of deploying it using low-end devices. This study introduces one such application, namely FedSepsis, for the early detection of sepsis using electronic health records. We incorporate several cutting-edge deep learning techniques for the prediction and natural-language processing tasks. We also explore the multimodality aspect for the better use of electronic health records. A secure distributed machine learning mechanism is essential to building such a practical internet of medical things application. To address this, we analyze two federated learning techniques. Moreover, we use two different kinds of low-computational edge devices, namely Raspberry Pi and Jetson Nano, to address the challenges of using such a system in a practical setting and report the comparisons. We report several critical system-level information about the devices, namely CPU utilization, disk utilization, process CPU threads in use, process memory in use (non-swap), process memory available (non-swap), system memory utilization, temperature, and network traffic. We publish the prediction results with the evaluation metrics area under the receiver operating characteristic curve, the area under the precision–recall curve, and the earliness to predict sepsis in hours. Our results show that the performance is satisfactory, and with a moderate amount of devices, the federated learning setting results are similar to the single server-centric setting. Multimodality provides the best results compared to any single modality in the input features obtained from the electronic health records. Generative adversarial neural networks provide a clear superiority in handling the sparsity of electronic health records. Multimodality with the generative adversarial neural networks provides the best result: the area under the precision–recall curve is 96.55%, the area under the receiver operating characteristic curve is 99.35%, and earliness is 4.56 h. FedSepsis suggests that incorporating such a concept together with low-end computational devices could be beneficial for all the medical sector stakeholders and should be explored further.
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With the rapid growth of the aging world population, proper health care has become a prior issue in all countries; especially during the life altering COVID – 19 pandemics. While everything is getting digitized, the ease in providing medicinal services in an online basis is still a factor in today’s era. Current medical system is expanding by leaps and bounds in the last couple of decades for their considerable aim towards wireless and e-health monitoring systems providing remote monitoring of patients. But the tools used to deal with health conditions are tedious to maintain and limited to specific number of parameters. Incorporating patient’s data into a database and accessing the system in the form of a mobile application with proper medical assurance and diagnosis will demonstrate that this proposed system will be efficient to provide the patient a proper consultation from anywhere. It reduces the number of hospitals visits, saves time, and is convenient for both physician and patient.
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The integration of the IoT and cloud technology is very important to have a better solution for an uninterrupted, secured, seamless, and ubiquitous framework. The complementary nature of the IoT and the could in terms of storage, processing, accessibility, security, service sharing, and components makes the convergence suitable for many applications. The advancement of mobile technologies adds a degree of flexibility to this solution. The health industry is one of the venues that can benefit from IoT–Cloud technology, because of the scarcity of specialized doctors and the physical movement restrictions of patients, among other factors. In this article, as a case study, we discuss the feasibility of and propose a solution for voice pathology monitoring of people using IoT–cloud. More specifically, a voice pathology detection system is proposed inside the monitoring framework using a local binary pattern on a Mel-spectrum representation of the voice signal, and an extreme learning machine classifier to detect the pathology. The proposed monitoring framework can achieve high accuracy of detection, and it is easy to use.
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The ever-increasing advancement in communication technologies of modern smart objects brings with it a new era of application development for IoT (Internet of Things) based networks. In particular, owing to the contactless-ness nature and efficiency of data retrieval of mobile smart objects, such as wearable equipment or tailored bio-sensors, several innovative types of healthcare systems with body sensor networks (BSN) have been proposed. In this paper, we introduce a secure IoT-based healthcare system which operates through BSN architecture. To simultaneously achieve system efficiency and robustness of transmission within public IoT-based communication networks, we utilize robust crypto-primitives to construct two communication mechanisms for ensuring transmission confidentiality and providing entity authentication among smart objects, the local processing unit and the backend BSN server. Moreover, we realize the implementation of the proposed healthcare system with the Raspberry PI platform to demonstrate the practicability and feasibility of the presented mechanisms.
Chapter
The medical domain is one of the most rapidly expanding application areas of Internet of Things (IoT) technology. For chronic diseases, this technology can be highly useful for the patient, providing constant monitoring and ability for timely intervention of medical staff in case of an emergency. This intended system behavior imposes new requirements to the design and implementation of processing flows implemented on embedded IoT devices which are already constrained by limited computational capabilities and power budget. This work aims at designing and implementing such a bio-medical signal analysis flow based on the case study of arrhythmia detection using electrocardiogram signals and machine learning techniques. Different architectural decisions of the flow are explored at high level and the final optimized version is implemented on a state-of-the-art IoT node. The evaluation of the execution flow on this device provides information on the actual requirements of each sub-component of the flow combined with an analysis of its behavior as computational requirements of the machine learning algorithms scale up.
Chapter
Internet of Things (IoT) technologies provide many opportunities for providing healthcare applications such as home based assisted living and well-being application solutions. Nowadays, numerous IoT devices are used to monitor users’ healthcare status and transmit the data directly to remote data centers through the cloud computing paradigm. This direct interconnection of the large amount of devices for remote storage, processing, and retrieval of medical records in the cloud demands a reliable network connection imposing many challenges related to network connectivity and traffic. This chapter deals with the transfer of the computing intelligence from cloud to the edge network. Fog computing operates closer to the user, on network edge, enabling accurate service delivery with low response time avoiding delays and network failures that may interrupt or delay the decision process and healthcare service delivery. An architectural model is proposed and a set of use cases illustrate the benefits of the IoT and fog computing integration.
Conference Paper
In today's world of connectivity, with the advancement of Internet of Things (IoT) all entities are connected to each other by some communication means. The Internet of Things for the medical equipment will produce data that can go a long way in not only increasing equipment efficiency, but also patient health. The Internet of Things (IoT) is increasingly being recognized by industry and different services mainly in healthcare. This paper describes the various Internet of Things (IoT) enable devices and its practices in the area of healthcare for toddler, children, chronic care, monitoring of critical patients, operation theaters and medicine dispenser.
Article
Purpose: Ultrasound scanning has been widely used for preliminary diagnosis as it is non-invasive and has good scope for the doctors to analyze many diseases. Due to lack of trained radiologists in remote areas, tele-radiology is used to diagnose the scanned ultrasound data. Availability of online radiographers and having communication facility for the portable ultrasound are issues in tele-radiology for using ultrasound scanning in remote health-care. In these situations, Computer Aided Diagnosis (CAD) will be beneficial in diagnosing the patients with minimal manual intervention. Methods: We proposed FPGA based CAD algorithm for abnormality detection of kidney in ultrasound images. The proposed algorithm works in the following way: as a pre-processing, an ultrasound image is denoised and region of interest of kidney in ultrasound image is segmented. Intensity histogram features and Haralick features are extracted from the segmented kidney region. Based on extracted features, the classification algorithm is implemented in two stages. In first stage, a Look Up Table (LUT) based approach is used to differentiate between normal and abnormal kidney images. In second stage, after confirming the abnormality, Support Vector Machine (SVM) with Multi-Layer Perceptron (MLP) classifier trained with extracted features is used to further classify the presence of stone or cyst in kidney. The proposed algorithm is implemented on a FPGA based Xilinx Kintex-7 board. Results: The proposed algorithm gave an accuracy of 98.14%, sensitivity of 100% and specificity of 96.82% in detecting the exact abnormality present in kidney ultrasound images. Conclusion: The proposed algorithm and its hardware implementation will be beneficial for diagnosing the kidney in absence of radiologists and internet connectivity.
Conference Paper
Inertial Measurement Units (IMUs) embedded in commercial mobile devices are a good choice for continuous monitoring in healthcare domain due to their attractive form factor and low power consumption. We present improved and accurate sensing algorithms using a single IMU to sense basic events like step count, stride length, fall, immobility etc. Our algorithms have been shown to perform better than the state of the art algorithms, and are implemented in such a way that IMU is not bound to any specific position or orientation with respect to the user. We propose a 3-layer based framework for a complete end-to-end system architecture for IoT enabled health monitoring, useful for application in areas like individual fitness monitoring and elderly care.
Conference Paper
The American Medical Association Family Medical Guide is a comprehensive medical reference book for non-medical professionals. The book uses a series of flow charts to help users diagnose their symptoms by answering yes and no questions. The idea presented in this paper is to leverage the information in the book to make a chat bot for a mobile phone user. We develop a tool for crowd workers to train the chat bot using the information in the book. We present a framework for the crowd worker. Information is classified as symptom, diagnosis, or care. The chat bot makes the information accessible to people that primarily use a mobile phone and are not medical professionals. By having the data on the phone, we are able to make the data actionable by integrating it with the computational capabilities and sensors of the phone.