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The final published version can be found at https://doi.org/10.1109/JSAC.2020.3042421
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Abstract— Internet of Things has been one of the catalysts in
revolutionizing conventional healthcare services. With the
growing society, traditional healthcare systems reach their
capacity in providing sufficient and high-quality services. The
world is facing the aging population and the inherent need for
assisted-living environments for senior citizens. There is also a
commitment by national healthcare organizations to increase
support for personalized, integrated care to prevent and manage
chronic conditions. Many applications related to In-Home Health
Monitoring have been introduced over the last few decades, thanks
to the advances in mobile and Internet of Things technologies and
services. Such advances include improvements in optimized
network architecture, indoor networks coverage, increased device
reliability and performance, ultra-low device cost, low device
power consumption, and improved device and network security
and privacy. Current studies of in-home health monitoring
systems presented many benefits including improved safety,
quality of life and reduction in hospitalization and cost. However,
many challenges of such a paradigm shift still exist, that need to be
addressed to support scale-up and wide uptake of such systems,
including technology acceptance and adoption by patients,
healthcare providers and policymakers. The aim of this paper is
three folds: First, review of key factors that drove the adoption
and growth of the IoT-based in-home remote monitoring; Second,
present the latest advances of IoT based in-home remote
monitoring system architecture and key building blocks; Third,
discuss future outlook and our recommendations of the in-home
remote monitoring applications going forward.
Index Terms— Internet of Things, IoT, Ambient assisted living,
eHealth, In-home, mHealth, Remote monitoring, Middleware,
Tutorial.
I. INTRODUCTION
N-HOME health monitoring allows patient care to continue
at home after a patient is discharged from the hospital. It
This work was supported in part by FCT/MCTES through national funds
and when applicable co-funded EU funds under the project UIDB/50008/2020,
in part by the Brazilian National Council for Scientific and Technological
Development (CNPq) via Grant No. 309335/2017-5.
Nada Y. Philip is with the Faculty of Science, Engineering and Mathematics
at Kingston University London, UK (n.philip@kingston.ac.uk).
Joel J. P. C. Rodrigues is with the Federal University of Piauí (UFPI),
Teresina-PI, Brazil and with Instituto de Telecomunicações, Portugal (e-mail:
joeljr@ieee.org).
allows healthcare providers to reach patients outside of the four
walls of the hospital, perform proper monitoring of patient
health conditions, continue to deliver quality care and identify
at-risk populations. It also helps patients stay connected with
their health providers, enable them to remain compliant with
treatment plans and improve their health conditions.
Internet of Things (IoT) based in-home health monitoring
applications are one of the key mobile health (mHealth)
applications that provide proactive and preventive digital health
interventions [1],[2]. Digital health is “a broad umbrella term
encompassing eHealth (which includes mHealth), as well as
emerging areas, such as the use of advanced computing
sciences in ‘big data’, genomics and artificial intelligence”[2].
Whereas mHealth can be defined as “mobile computing,
medical sensor, and communications technologies for health
care” [3].
Over the years there has been a booming in the number of
mHealth applications in the market. According to Global
Market Insights, mHealth Market size is set to exceed $289.4
billion by 2025 [5].
This prolific increase in mHealth applications and in-home
health monitoring is due to three main factors:
A. Current healthcare services limitations and health
policymakers’ planning directions.
Globally, the population aged 65 and over is growing faster
than all other age groups. According to an estimate by the
World Health Organization (WHO), the number of individuals
over 60 years will nearly double from 12% to 22% during the
2015-2050 period. Approximately 80% of older adults have at
least one chronic disease and 77% have at least two [4].
The incoming ‘Silver Tsunami’ will generate higher medical
needs and caregiving, which will ultimately place more and
Honggang Wang is with University of Massachusetts Dartmouth, North
Dartmouth, MA, USA (emai:hwang1@umassd.edu)
Simon Fong is with the Faculty of Science and Technology, University of
Macau, Macau SAR and with ZIAT of Chinese Academy of Science, China
(ccfong@um.edu.mo).
Jia Chen is with IBM (jia.chen.nyc@gmail.com).
Internet of Things for In-Home Health
Monitoring Systems: Current Advances,
Challenges and Future Directions
Nada Y. Philip, Senior Member, IEEE, Joel J. P. C. Rodrigues, Fellow, IEEE,
Honggang Wang, Senior Member, IEEE, Simon Fong, Jia Chen
I
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more pressure on an already stressed healthcare system.
Therefore, finding novel ways and leveraging technology to
manage the health of populations efficiently and cost
effectively, will be the key to sustainably provide the best
quality of care. Accordingly, treating individuals remotely with
the support of technology is on the agenda and plan of national
and global health policymakers. Recently the WHO
organization created a framework for categorizing digital health
interventions [2]:
• Interventions for clients: clients are individuals who are
potential or current users of health services.
• Interventions for healthcare providers: Healthcare
providers are members of the health workforce who deliver
health services.
• Interventions for a health system or resource managers:
managers are involved in the administration and planning of
public health systems.
• Interventions for data services: This includes functionality
to support steps related to data collection, management and
processing.
In most of the above intervention groupings, remote health
monitoring applications are part of the end-to-end intervention
system. Remote health monitoring applications links the client
via sensors and home hub to the healthcare providers and
resource managers via cloud data services.
To address limited health and social care resources, National
Health Services’ (NHS) policies and plans are set to change the
services models to keep patients treatment at home and
community centers to reduce hospitalization, cost and provide
a better quality of life. As an example, NHS UK, sets out five
changes to the NHS service model to address such needs [6]:
• Boost ‘out-of-hospital’ care: to dissolve the historic divide
between primary and community health services.
• NHS redesign: to reduce pressure on emergency services
at hospitals.
• Empowering patients and personalized care: patients to get
more control over their health.
• Digitally-enabled care: to be part of the primary and
outpatient care pathways across the NHS.
• Integrated care systems: to focus on population health and
partnerships between local NHS organizations.
The key enabler of these 5 major practical changes to the
health service model is the remote health monitoring
applications. The above mentioned ‘out of hospital’ care,
reducing emergency hospital services, personalized care,
digitally enables care and integrated care systems models
cannot happen without remote health monitoring types of
applications. In fact, the fast increasing focus towards precision
medicine and personalized care is one of the factors fueling the
global mHealth market [5].
B. The advances in the underlying enabling technologies in
terms of mobile phone capabilities, wireless communications,
sensors, wearables and IoT architectures and protocols.
The relatively low cost and proliferation of mHealth
applications, due to the massive penetration of smartphones, is
making it a promising investment direction across the globe. In
2017, it is estimated that 500 million smartphones new users
from China and India were connected to the internet globally
[5].
Internet of Things (IoT) is an evolving IT revolution
providing a paradigm shift in several areas including
Healthcare. The term ‘‘Internet-of-Things’’ can be defined as “
an umbrella keyword to cover various aspects related to the
extension of the Internet and the Web into the physical realm,
by means of the widespread deployment of spatially distributed
devices with embedded identification, sensing and/or actuation
capabilities, to enable a whole new class of applications and
services" [7]. Such applications will continue to rise due to the
development of the recent communication protocol specifically
designed for IoT devices such as NB-IoT, LoraWan or Sigfox.
In addition, the latest development in the IoT communication
infrastructure including 3GPP standard (5G IoT) is well
positioned to provide low-power, low-data-rate, and wide-area
coverage cellular connections to diverse types of IoT devices
[8].
There has been an increase in the development of intelligent
medical devices (e.g. blood pressure device, glucose meter,
temperature sensors, weight scale, etc..) and wearable sensors
(to measure e.g. ECG, accelerometer, SPo2, Heart rate, etc..),
with features focusing on low power, small size, portability and
easy to wear and use. Wearable sensors have gradually been
developed in the form of accessories (e.g. bands, rings), smart
clothing, body attachments and body insertions (e.g. insulin
pumps, pacemakers). Alongside this development in wearable
sensors, there have been advancements in the design of smart
textiles, smart clothing, or e-textile, that consist of conductive
textile material that is attached to or woven together. The
tremendous advancements in low-profile and bioelectronics,
nano technologies and materials have led to the development of
implantable sensors and biomedical devices for remote
diagnosis and monitoring. Many challenges were resolved
during this development including the size of the sensors,
battery life and the development of stretchable and skin-
attachable electronic devices that can continuously and
unobtrusively monitor individuals’ activity and biomedical
signals without any restriction to the individual’s daily
activities. Wearable devices are equipped with wireless
transceivers modalities, e.g. Bluetooth, Zigbee, infrared, radio-
frequency identification (RFID), WiFi and near-field
communication (NFC) technologies. Such technologies allow
the wearables to connect to other smart devices (e.g.
Smartphone) to enable remote diagnosis and monitoring for
better quality care [9].
C. The reported evidence on the benefits of mHealth
applications in terms of quality of care and reduction of cost
In-Home health monitoring applications have evolved over
the last few decades, addressing many healthcare conditions.
They aimed to provide more efficient and effective healthcare
services and contributed to a better quality of life and reduction
in cost. There has been a sharp increase in the number of
mHealth smartphone applications targeting various disease
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remote monitoring and self-management, helping patients
better manage their health conditions and enabling independent
living. It aims to empower individuals through disease
prevention, health promotion and condition self-management
[5].
Based on [12] an estimated 7.1 million patients were
remotely connected to health monitoring devices in 2016,
which contributed to a saving of £1bn (over five years) for the
NHS by reducing bed blocking and unnecessary appointments.
In addition to the above mentioned benefits of remote health
monitoring, it gives patients confidence that their conditions
(e.g. heart rate, blood pressure, SPo2 levels and sleep quality)
are monitored and alerts could be generated to inform their
healthcare professionals in real time [12]. In fact, one study has
shown that home monitoring of patients with congestive heart
failure leads to lower hospitalization rates and improved
mortality [14]. A meta-analysis study on the effectiveness of
mHealth interventions for patients with diabetes reported that
over a period of a year on average, mHealth interventions
improve glycemic control (HbA1c) compared to conventional
care by as much as 0.8% for patients with type 2 diabetes and
0.3% for patients with type 1 diabetes [11].
In this paper, we first set the stage by presenting the main
components of IoT based In-home health monitoring system
along with some examples. Inspired by the main technology
building blocks of IoT based in-home health monitoring
systems, section II provides an extensive discussion on the
technology advances used in such systems. Section III identifies
the main challenges and future directions in developing
successful IoT in-home health monitoring systems that could
scale up and lead to successful deployment in national
healthcare services. Section IV concludes the paper with a
summary.
II. C
URRENT ADVANCES IN IOT TECHNOLOGIES AND
SERVICES FOR IN-HOME HEALTH MONITORING APPLICATIONS
IoT technology is one of the main enablers of in-home health
monitoring system architecture. Fig. 1 represents a typical
example of the main building blocks of IoT in-home health
monitoring systems. Fig.1 demonstrates the functional modules
of such systems and their interaction. The cloud hub of the
system consists of several modules (storage server, feature
extraction module and decision support system). The patient
hub handles the interaction with the patient, wearable sensors
and devices and the transfer of the patient’s vital signs and the
receiver of the treatment plan. Healthcare professional hub
applications interact with the medical staff and facilitate
patients’ treatment. In IoT based in-home health monitoring
systems, the communication between the cloud hub and other
user applications related to the patient’s and healthcare
professional hub is via interoperable and secure Cloud
Communications API (e.g. based on RESTful web services).
There has been a tremendous increase of such applications
for chronic disease self-management (e.g. Diabetes and
Cancer), medication adherence (Smart pills), assistive living
(Parkinson and mild cognitive conditions) and many more.
Table I present a summary of several of such applications. It
includes a brief description of the systems, their advantages and
lists the sensors used in the remote monitoring [53] - [62].
The architecture of IoT based in-home health monitoring
systems typically includes five main key IoT technologies as
shown in Fig. 2. Inspired by these five technologies, the
following sub-sections presents the current advances in IoT
technologies and services for in-home health monitoring
applications.
A. mHealth and assistive sensors
These represent invasive and non-invasive sensors used to
monitor biomedical signals and living environment changes.
Biomedical signals depend on the individual’s lifestyle, mental
and medical conditions (e.g. diabetes, COPD, Cancer and
mental disorder). Such medical conditions need the
management and control of some parameters, e.g. Glucose
level, blood pressure, temperature, ECG and weight. And hence
the need for sensors devices to measure these conditions. For
the living environment, it depends on the assistive living
technologies that individuals needs, e.g. personal alarms, sensor
mats, camera, etc. To enable communications of the measured
signal with the surrounding world, these sensors are attached to
wireless communications modalities including, RFID, NFC,
Bluetooth and BLE, WiFi and Zigbee.
Fig. 1. IoT based in
-home remote monitoring system architecture
Healthcare Cloud
Hub
• Decision support system (DSS)
• Patients records data storage
• Feature Extractions
Patient Hub
• Educational
information
• Motivational dialogue
• history
• Diary
• Reminder
• Questionnaires
• Vital signs
(Heart Rate,
SpO2, and
ECG)
• Medication
adherence
• Glucose level,
Blood
pressure,
temperature,
and Weight
measurement
• Patients
dialogues
PAN
BAN
DSS data
Treatment plan
• Rehabilitation
• Prevention
• Diagnosis
• Treatment/ Follow-up
• Adherence
• Lifestyle Management
Healthcare Professional Hub
(Nurse, GP, Physician, Nutritionist and Physiotherapist)
Fig. 2. Key technologies for IoT based In
-home health monitoring systems
Cloud
Computing
Middleware
layer
Short range
communications
networks
mHealth and
assistive sensors
IoT applications
IoT
technologies
for In-home
health
monitoring
systems
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Table 1 represents a list of sensors and devices related to
some chronic disease management, adherence and assisted
living applications. Most of these sensors and devices are
manufactured with data communications standards to allow
interoperability and communications with applications.
Examples of such standards are the ISO/IEEE 11073 Personal
Health Data (PHD) and oneM2M. They both are designed to
allow message communications with devices using application
layer protocols including Hyper TextTransfer Protocol (HTTP),
Constrained Application Protocol (CoAP), and Message
Queuing Telemetry Transport (MQTT).
B. Short-range communications networks
Short-range communications networks are represented in this
discussion as Wireless sensor networks (WSN) and Personal
Area Networks (PAN): WSN, is a network composed of a set
of sensors to monitor different health conditions and/or
assistive living parameters. Usually, this is referred to as
Wireless Body Area Network (WBAN) in the case of wearable
required to be worn by individuals. PAN, is a network that
allows communications between sensor(s) and personal
computer devices, e.g. smartphone using short-range
communications that include e.g. Bluetooth, BLE, WIFI and
Zigbee. It depends on the required bandwidth. For instance,
for sensor signals with a low bandwidth of 0.5 Hz, such as SPo2
signal, BLE is sufficient to be used to transmit the data [16].
While 25 lead ECG signals bandwidth can reach 500Hz would
need WiFi communications modalities as the required
bandwidth is high [16]. Fig. 3 presents some of the IoT
communications protocols in terms of data rate and range [17].
Recent protocols are specifically designed for IoT devices such
as NB-IoT, LoraWan or Sigfox. They are designed to use low-
power wide-area networks (LPWAN) that enable the
connection of a large number of devices at a low bit rate, low
energy consumption and low cost. In particular, the IEEE
802.15.6, is a wireless body area network (WBAN) standard
developed for enhanced health monitoring, which supports data
rates up to 10Mbps, 1-2 meters range, low power, and high
TABLE
I
EXAMPLES OF MHEALTH AND ASSISTED LIVING SENSORS AND APPLICATIONS
Fig. 3.
IoT protocols in terms of range and data rate
