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International Journal of Science and Research (IJSR)
ISSN (Online): 2319-7064
Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438
Volume 4 Issue 1, January 2015
www.ijsr.net
Licensed Under Creative Commons Attribution CC BY
A Survey of E-Healthcare Information System
based on Android Application
Sonali L. Tupe1
, Nandkumar P. Kulkarni2
1
Department of Information Technology, Smt. Kashibai Navale College of Engineering, Pune-41, India
2
Asst. Professor, Department of Information Technology, Smt. Kashibai Navale College of Engineering, Pune-41, India
Abstract: The unintended medical errors are a big threat to patient safety. Therefore, there is a challenge of delivering safe healthcare
is important now days. An attempt to meet these demands, healthcare systems have increasingly focusing at deploying information
knowledge to scale resources, to decrease queues, to minimize or avoid the errors, and to give modern facilities in remote communities.
The computer-aided tools are not vital for interpreting patient specific data in order to determine the most suitable therapy from the
diagnosis. In order to make sound decision making on treatment and diagnosis for individual perspective, all the relevant health
information of the patient needs to be available and transparently accessible to them regardless of the location. Mobile application is
helpful to the doctor and patient or doctor communicate with each other very quickly, the distance between them does not matter or too
long. For the optimization of medical data, better quality and accuracy in the decision making as well as shared access to the database a
new technology Android Application deployed. The apps in E-Healthcare Information System remotely monitor biomedical signals
from the patient. The recorded biomedical signals of the patient transmit to doctors or patients from a server to mobile application. The
most significant issues in E-healthcare information systems is to optimize the medical data quality extracted from distributed and
heterogeneous environments, which can improve diagnostic and treatment decision making. This paper provides a novel comparison of
the state of the art solutions available in the E-healthcare information system and it also proposes a multi-agent web service structure
which is based on service oriented architecture for the optimization of medical data.
Keywords: Android Mobile Device, Personal Area Network, Machine-to-Machine, Wearable Sensor
1. Introduction
In recent times the mobile application, which become great
interest to research initially offered for the information
retrieval such as email, calendar, contacts, and stock market
and weather information. Now a day's there is a demand for
medical application. In previous, the information concerning
an individual patient is a composite, and it gets generated
from a variety of sources. This information maintained by
many different applications and it is creating in various
media formats. In traditional, the decision analysis made
good outcomes even though there is an uncertainty
surrounding the decision. So, sensitivity analysis with the
help of decision analysis is the use of the best methodology
for expert opinion.
In latest technology, the human body is connected to
wearable sensors that gather various health parameters such
as Heart Rate Variability (HRV) or electrocardiogram
(ECG). Wearable sensors capture the information in Machine
to Machine (M2M) gateway. The obtained information is
sent over to server PC using internet and then to the mobile
application through the internet. The packet transfer using
user datagram protocol (UDP) to server and plots biomedical
signals on mobile device [1]. The UDP protocol is a simple
OSI transport layer protocol for client/server network
applications based on Internet Protocol (IP).
The wireless machine to machine (M2M) healthcare solution
use Android mobile devices successfully implemented in a
global network [1]. The Service-Oriented Architecture
(SOA) is a combination of Techniques and methods for
scheming and developing software in the form of
interoperable services. The Multi-Agent Systems (MAS)
composed of several interacting intelligent agents within the
environment. It can be used to solve the problems that
impossible for an individual agent.
This paper organized as follows: Section 2 presents the
Existing System Architecture, Section 3 describe Literature
Survey. Section 4 illustrate Proposed System Architecture,
Section 5 draws the conclusion and future scope.
2. Existing System Architecture
Figure 1 shows the sensors complicated devices that are in
general used to sense and react to electrical or optical signals.
A Sensor converts the bodily parameter (for example
temperature, blood pressure etc.) into a signal that measured
electrically. The sensors can be classified based on power
requirement such as an active sensor that require supply and
passive sensor which do not require power supply. The
wearable sensor based on Tiny Operating System (OS) that is
a component-based operating system. The Tiny OS is an
embedded operating system written in the nesC programming
language. Its applications had written in nesC that is a dialect
of the C language. The M2M gateways link one or more
locally networked devices to a wired or wireless broadband
connection. The M2M gateway is more secure as well as
more energy efficient that is offer secure link between doctor
and patient the private information does not get stolen.
The mobile device based on Android operating system (OS)
that based on the Linux kernel and now developed by
Google. Android designed for touch screen mobile devices
like smart phone. Android provides the ability to run
Paper ID: SUB1590 143

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applications. The users are downloading and installing the
APK file, or downloading using application store program
that allow the user to install, update, and remove applications
for smart phones. The hardware platform of Android is the
32-bit Advance RISC Machine Version (ARMv7)
architecture. The biomedical signals mean graphical
representation of waves.
Figure 1: System Architecture for E-healthcare Information
System
3. Literature Survey
The physiological parameters of a patient collect by wearable
sensors stored in M2M gateway and transfer over the
network. The Microsoft Access database used to store the
data that contains a Table in which the different settings for
the sensors are store. During the transmission for avoid
corruption of data, communications protocol used. In order to
get the right value of the sensor sent, data is divided by 100
[5].
M2M Gateway [9], demands mobile applications that
provide more security. The M2M communication means one
machine communicates with another one without interfering
the human beings and transfer data through network. M2M
services implemented three entities like M2M service
platform, M2M gateway, and M2M terminals.
EMI issue [12], in hospital environments Electromagnetic
Interference (EMI) issues, arises which are also called Radio
Frequency Interference (RFI). The RFI can disrupt almost
any electrical or electronically controlled device. It causes
lack of data to a total loss of data. The Automatic Repeat
Request (ARQ) protocol is used to recover from the
erroneous transmission. Due to Discrete-Time Markov Chain
Model data packet transmits successfully.
Tele-cardiology means real-time transmission of Electro
Cardio Graphic (ECG) signals over a wireless network. But
due to the high collision rate of data packet required frequent
retransmissions that cause unpredictable delays and jitters in
a wireless network. It degrades the quality of real-time ECG
services. So, to prevent collision enhanced Quality of Service
(QoS) aware MAC coordination introduced [8].
EDPF [13], the monitored bio-signals data from the patients
are transferred through a radio access network and core
network by the network service provider to the e-Health
service provider. The Earliest Delivery Path First (EDPF)
scheduling is used to choose packets to be transmitted over
the network so that the delay requirements can be satisfied. It
will reduce the delay for treatment of critical patient.
The Distributed Coordination Function (DCF) extends its
Contention window (CW) volume to obtain the congestion
level on the channel when it loses packet due to collision.
The new modification to DCF (N-DCF) and Fast Collision
Resolution (FCR) algorithm has improved the throughput
performance [14].
IPv6 [3], this technique can be used for the data transmission
over the network without packet losses and to extend the
range of healthcare services. In order to prevent packet losses
in data transmission, some existing protocols of the
6LoWPAN like hierarchical routing used.
The Dynamic Host Configuration Protocol (DHCP) is
stateful. It used for distributed network configuration
parameter such as IP address for interface and services [7].
To accomplish the cardiologists' opinions of the ECG
monitoring quality, Simple Mean Opinion Score (MOS) test
developed [11]. The Bluetooth gateway device that contains
two radios (Bluetooth + IEEE 802.15.4) can bridge
Bluetooth network an IEEE 802.15.4 network. The device
formed is called "Personal-Area Network Hub" (PAN-HUB)
[10].
Table 1: Protocol Comparison
Sr.
No.
Protocol Layer Packet error
detection and
correction
Packet
loss
rate
Routing
delay
1 Communications [5] Application High Low Low
2 User Datagram
Protocol (UDP) [1]
Transport Low Low Low
3 Ad-hoc on demand
Distance Vector
(AODV) [3]
Physical Low Low Low
Table 2: Algorithm Comparison
Sr.
No.
Algorithm Throughput
improves
Delay Advantage Disadvantage
1 Earliest
Delivery Path
First (EDPF)
scheduling
[13]
Low Low Schedule
packets
delivered at
the primary
to the host.
The packet not
scheduled it
dropped
without
transmission.
2 Carrier Sense
Multiple
Access
(CSMA) [10]
High Low Easy to
implement.
CSMA could
not recover
packet from the
collision.
3 Carrier Sense
Multiple
Access /
Collision
Avoidance
(CSMA)/CA
[10]
High Low RTS/CTS
provide
virtual carrier
sense.
Not efficient as
CSMA/CD
4 Fast Collision
Resolution
(FCR) [14]
High Low It achieves
high
throughput
performance.
The number of
stations affects
the
Performance of
the FCR
algorithm.

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Table 3: Technique Comparison
Sr.
No.
Technique Mobility Flexibility Packet
loss
Collision
1 Internet Protocol
version IPv 6 [1]
Yes Yes Low Low
2 Internet Protocol
version IPv 4 [1]
No No High High
4. Proposed System Architecture
Figure 2 shows that the user makes a request to the service
agent then service provider verifies that users authenticate or
not. If the user authentic then required service provide to that
user. The Service-Oriented Architecture (SOA) will be used
to cope with the distributed environment for E-healthcare
Information Systems. The goal of SOA is to offer enhance
healthcare systems to users. A web service technology widely
accepted as one traditional implementation of SOA. The
companies, organization, or individual developers can
distribute functional entities that catalog and publish their
service components to a Universal Description, Discovery,
and Integration (UDDI) for public use. Web services are like
as a single transaction, example the querying of a medical
record, or more complex multiservice. The study starts with
creating static and dynamic models for medical data quality
in terms of data withdraw so that the objects and processes
defined. The plan of healthcare Intelligent Agents (IAs)
follows the classification of the medical data quality models.
The aim of the IA enables to offer external communication
for mutual service, internal inference shells for monitoring
and tracking of the data extraction process, and a printing
report service.
In Evolutionary computing optimizing data selection the data
is extract by general practice that is agent. After that data is
migrate. In data processing include cleaning, updating. A
multi-agent framework will be monitor, discover any data
inconsistency between original and actual medical records.
The finally data analysis is done by collaborator and load
clinician. The proposed algorithm can be able to function
accurately and efficiently on multi domains with multi
objectives Quality of Service (QoS) attributes. The quality of
data analysis in terms of its accuracy, integrity, consistency,
completeness and uniqueness verify.
The client can then use Simple Object Access protocol
(SOAP) to actually call one of the operations listed in the
WSDL using XML or HTTP. It is used to describe the
client/server interface that should between web service
clients and servers.
Figure 2: Proposed System Architecture
5. Comparison of Existing and Proposed
System
The issue is data selection and quality optimization in
distributed environment of E-healthcare Information System.
Computer-aided tools are not compulsory for understand
patient-specific data in order to conclude the most suitable
therapy from the diagnosis. To be work out over the problem
of data selection and quality optimization by using Evolution
Computing Algorithm into SOA of web service will be use.
The proposed system will be practically deployed and
integrated with E-healthcare information systems for local
hospitals. The experimental results will be show that the
proposed EA was able to optimize the medical data workflow
on a medical experimental data. It reduces the medical error.
It can receive data in real time. The better quality and
accuracy in the decision making, shared access to database.
The time is less consumable by proposed system. The
miscommunication can be reduced and provide user with the
best service. The patient life can be more secure. The
enhancing security and privacy of patient information will be
providing.
The cost is reducing through decreased paperwork. It reduces
duplication of test and improves the health of patient. The
physician has immediate access to patient information. The
patient can save time not by having to revisit to clinic to pick
up the test result and through the scheduling appointments.
The care plan can be change as assessment results gather.
There is no need to manually information enter into system
because this step is eliminate.
6. Conclusion and Future Scope
The existing system which highly dependent on the server,
must have network connection and hard for non-expert users.
While the data transfer over network cause loss of quality of
data in term of accuracy, integrity which raise problem of
data selection and quality optimization in a distributed e-
Healthcare environment. The future work is to resolve the

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problem of data selection and quality optimization in a
distributed environment. For this purpose focused on medical
data extraction for the SOA-based healthcare systems.
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