Healthiness Monitoring using IoT Solutions

This article discusses the concept of healthiness monitoring using IoT solutions in healthcare. It explores the benefits, challenges, and recommendations for implementing IoT in healthcare. The article also provides a case study analysis and proposes a new system for improving health monitoring projects. Find study material and solved assignments on Desklib.

RUNNING HEAD: HEALTHINESS MONITORING USING IOT SOLUTIONS
Healthiness Monitoring using IoT Solutions
Topic: Interoperability of IoT Systems
Name of the Student:
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Word Count: 2095
Author Note
Date of Publication

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Introduction
A. Motivation
The concept of Internet of Things, is network-based physical device’s combination to
support various functions and possible telemetry. In medical technology, IoT-based devices,
such as implants, wearables, home monitoring systems, sensors and other applications, have
been observed to leave a potentiality on connecting providers and their patients, while
coupling with the AI techniques for various innovations (Catarinucci et al., 2015). Nowadays,
sensors have replaced the extra staff, for maintenance, measurement and other features.
However, due to the complexity of the human health monitoring systems, problems of
security and privacy to such systems are required to be resolved, as they belong to extremely
sensitive asset (Bhatt, Dey & Ashour, 2017). Since, the amount (stats) of cardiovascular-
related deaths are very high, as stated by WHO (refer to Appendix), thus electrocardiograph
is selected as the major area of the whole health monitoring system. Also, prophylaxis’s two
options are also suggested for reducing the catastrophic consequences. Currently, few designs
and prototypes record and process the heart’s electrical activity, through wearables. Multiple
hardware and software are used in the solutions. Accordingly, proposed system’s by
(Amendola et al., 2014) and (Gope & Hwang, 2016) are analysed, as they used wealthy
equipment, however lacked appropriate technical specifications. Thus, a need of a new
system for analysing and monitoring the human health’s state is demanded from the IoT and
cloud technologies.
B. Structure of the Paper
Thus, the following study comprises of sections which, firstly discuss the existing
projects and researches conducted by the former researchers, on the same topic. Secondly, a
case study analysis is provided on the ‘IoT in Healthcare solutions’ which demonstrates the
benefits, challenges and other features, which were analysed after deep study on the subject.
Also, a recommendable system is introduced which can improve the current state of the
health monitoring projects. The paper finally concludes with the overall knowledge gained
from the work, in a brief.
Literature Review
Currently, various solutions are presented with respect to the monitoring procedures
of a person’s condition. Based on the works by Amendola et al. (2014), a platform of

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MySignals, has developed eHealth applications for the respective patients, using the medical
devices. The respective product has implementation of both software and hardware solutions.
Benefits of the solution is observed as by flexibility features, like connection ability under 20
dissimilar sensors, access and implementation of the project to the market and, also the API
and cloud services, responsive availability. However, major disadvantages lie on the costing
(yearly tariff plans near to 300 Euros for a single solution; also, hardware costs are 2,000
Euros), and also absence of appropriate device security and certification.
“ECG dongle” is another project, developed by Gelogo, Hwang & Kim (2015). The
provided solution comprises of a cardiograph device, which is shaped as a USB dongle, along
with Android application of the project and extensive cloud storage. Advantages are observed
to be the portability of the device and the cheaper rate of costing (about 65 USD/device).
Quantitative data analysis have proven that patients and their family members, were
moreover interested in the following project, due to its efficiency and affordable rate.
However, problems were calculated as disadvantages of the system, as it moreover, depended
on an external device, and also, the whole research was left in in uncompleted state. Thus,
determination of corrective diagnosis results, in the preliminary state is impossible to be
considered and thus, doctor’s consultancy is necessitated. Also, there is a high probability of
extensive technical errors.
Farahani et al. (2018) has provided a system, which used a costly and primitive
equipment-based system. The system monitors the patient’s health, under specific
calculations, operated by the MATLAB software’s usage. The whole project is difficult to be
initiated by an amateur or, an organization, since the MATLAB is a premium software (and
costs a lot of money), which needs particular amount of funding. Researchers, only stopped
the project in the prototype stage, and did not go any further.
Kodali, Swamy & Lakshmi (2015) developed a software (named “Health-Op”) which
had the same functionalities of monitoring patient’s health, and tracking the heart rate, pulse
rate, high & low pressure, and other features. However, it was also an expensive software,
where advanced wireless technology’s usage was also lacking, in a major way. Also, the
usage of cloud technologies were absent. Major drawback was due to the specificity of ‘one
device usage only’ design, which restricted its overall flexibility, as well.

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Case Study Analysis
The use of IoT in healthcare has been significantly visible since a long time, while use
case lists are continuously growing. Targetable benefits of IoT in healthcare, across the range
of use cases, can be described as:
 Greater engagement of patients: With the deployment of IoT systems, patience feel
as a part of playing an active characteristic during their healthcare journey. The
respective devices are not only limited to remote monitoring usage and factors
(portability, light, simple, etc.); additionally, the interference of patient accessed data,
has changed as well. Use of applications and software programs are supported by the
patients, for monitoring their own health information, impact and progress- under the
well-being of the healthcare projects.
 Improved patient outcome: Caretakers, nurses and other secondary staffs can access
the patient’s information (real-time), to enable them for better decision making, and
outcome deliverance. On an execution of a real-time diagnosis based on real-time
evidence, it benefits the whole involved officials, directly. Also, remote monitoring of
patients can help patients to decrease the amounts of doctor visit, re-admissions and
hospital stays.
 Low errors: During the automatic collection and transmission of data, under the
automated workflows, the range of errors are contrasted to the manual reporting and
collection systems. The rates of errors are observed to be low.
 Enhancement of Patient’s experience: Patients are the core of healthcare, thus the
requirements of the patients are the utmost priority. Therefore, IoT improves patient’s
experience through the timed diagnosis and intervention, proactive treatments, better
outcomes, and greater outcome results of treatment.
According to the survey data by Kulkarni & Sathe (2014), total count of remotely monitored
patients, using interconnected devices, has increased by 47% to 7.3 million in 2016, while a
compound annual growth of more than 49% is predicted by 2021. However, the growth is
unreliable, if the underlying challenges are not properly maintained.
After the analysis of the above described researches (in the Literature Review) mechanism,
advantages and disadvantages, it can be stated that the projects were incomplete and
unsuccessful with respect to the deployment of IoT based device in the Healthcare field. Most

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of the projects were left in the incomplete stages, while lacking appropriate attention on the
security and privacy matters, ease of operation and cost-friendliness.
Recommendation
Based on the incompleteness and inefficiency of the heart monitoring systems, a
general architectural system can be considered for appropriate suggestion. The overall
mechanism of the system would consist of on-board sensors, on the body of the patients,
which initiate a connection to the key microcontroller, to process data and transmit them to a
cloud storage space, under a wireless network connection. Doctors would be able to access
the data and send recommendations, based on the cloud service. Refer to Figure 1 for the
demonstration of the electrocardiograph device’s architecture. Also, cost-effectiveness is to
be maintained.
Figure 1: Proposed healthcare IoT project’s architecture
(Source: Author)
Firstly, for the selection of the Data Transmission Protocol, the broker server (on the
basis of protocols like XMPP, MQTT, JMS, AMQP) is to be deployed on a local server or a
cloud storage for transferring data to IoT. Also, client programs are needed to be installed on
the responding devices. Due to the advantageous features of MQTT (Message Queuing
Telemetry Transport), due to its protocol a-synchronicity, compactness, unstable
communication support, QoS support and ease of integration; however, has security issues.
Thus, for corrective response, connection to a broker under TLS/SSL implementation on
hardware’s modules of cryptography.
During assembling the device, the following components are to be used:
 AD8232 module (printed circuit board) (Moosavi et al., 2015) based on Cardiograph,
for heart rate monitoring, via heart bioelectric signals formation.

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Figure 2: AD8232 module based Cardiograph
(Source: Author)
 Secondly, MPU-6050-MOD is a gyro-accelerometer, to combine the 3-axis
accelerometer and three-axis gyroscope, for determination of patient’s body position
while the measurement is enabled. Position of a patient’s body affects the
measurement (Wu et al., 2017).
 For security maintenance between the cloud and the deployed sensors, Cryptochip
Atmel ATECC508A co-processor is initiated to allow the persistent encryption key’s
generation, utilizing algorithms (cryptographic) on elliptical curves.
For the IoT’s cloud service provider, with respect to deployment and initial goal of cost-
effectiveness, Amazon Web Services IoT is the selected platform for the project, to enhance
the safest solution (Laplante & Laplante, 2016). Also, AWS complies with the HIPAA,
which is the US Data Transmission and Protection Act, for secure usage in of the AWS
environment during processing, storage and maintenance of the medical data.
Also, for the selection of the main controller, among popular boards like ESP (Ugrenovic
& Gardasevic, 2015), Raspberry (Gupta, Patchava & Menezes, 2015) and Arduino would be
featured with built-in communication (wireless) modules. Anyone among these can be
selected, however Arduino lacks the wireless communication module functionality, thus is
inefficient in the following aspect. Best option is to use the ESP32 for the development of the
hardware, as 12-bit analog-to-digital converter is already included, unlike others. Also, it is
cost-effective, portable and supports communication interfaces (Farahani et al., 2018).
For the software development, open source OS of- Mongoose OS has been chosen for
meeting all the supportive modules, popular programming platforms, cloud services,
availability and debugging. The platform also supported direct-debugging in the browser,
JavaScript and C support, updates and other cloud services (Elhoseny et al., 2018).

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Moreover, the developed system is proposed as an effective and functional medical
equipment, which accesses the monitoring state of the human heart’s electrical activity,
collection of data and transmission of the gathered information to the cloud storage, under a
TLS connection and protocol of MQTT, along with one-level of QoS (Quality of Service).
The results of the transferred data in the cloud is formatted in JSON, which is a text-
formatted lightweight data exchange arrangement.
Figure 3: Prototype model
(Source: Author)
A regular prototype of the model represented a patient’s ECG statistics, in 15 seconds.
Graphical representation of the ECG is shown in figure 4, where the noise and interference
filtering is initiated by the AD8232 hardware module. The abscissa shows the ADC’s
oscillation amplitude’s maximum value, under probable range of 212 .The ordinate shows the
discrete time values, under activity values of fixed cardiac electric.
Figure 4: ECG’s graphical demonstration
(Source: Author)
Power consumption is the only critical factor of the devices. Thus, planned steps of
using lithium batteries of 2500 mAh capacity, can be used to provide an enabled period of
125 hours of on-going work.

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To the extents of understanding the importance of the prototype in influencing the
current scenario of degraded, improvable and costly systems, the unlikeness of the system is-
 It correctively measures the heart rate and ECG within the optimized time period (<15
seconds) and, simple to use.
 The device supports cloud storage functionalities and portability, improving the
overall use to doctors, patients and the involved individuals.
 The overall cost of the prototype is about $20, which is a very affordable price for any
dedicated medical equipment.
 The device also serves to the privacy and security policies, while taking accounts on
Health Insurance Portability and Accountability Act (Thota et al., 2018).
Conclusion
The following paper has analysed the existent components of hardware and software
in the field of medical solution’s construction, under the usage of different cloud and IoT
services. Significant attention has been paid to the privacy and security. The knowledge
gained from the former researches by the fellow researchers (in the Literature Review) has
paved a foundation of signifying the important considerations, for appropriate suggestion.
The suggested model has particular properties which secure cloud services connection
development, under the HIPAA requirements. The designated prototypical features has better
functionality to compete with current ECG measuring instruments, along with affordable
price. Further, the research can be extended to storage and processing of data transmission,
maintenance with the data statistics, while neural networks and artificial intelligence can be
used for defining the diseases, predictions and decision making processes.

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References
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Catarinucci, L., De Donno, D., Mainetti, L., Palano, L., Patrono, L., Stefanizzi, M. L., &
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Appendix
Figure: Cardiograms measurement devices in market of USA
(Source: GrandMountain forecast and research)
Figure: 10 Top causes of death counts (globally) (2015)
(Source: World Health Organization)