eHealth and the Internet of Things

Les Ball

, Andrea Symkowiak

, Simeon Keates

, David Bradley

and Simon Brownsell

SECAM, University of Abertay Dundee, Bell Street, Dundee DD1 1HG, U.K

James Cook University Hospital, Marton Road, Middlesborough TS4 3BW, U.K.

Keywords: eHealth, Internet of Things, Observational Data.

Abstract: To respond to an ageing population, eHealth strategies offer significant opportunities in achieving a

balanced and sustainable healthcare infrastructure. Advances in technology both at the sensor and device

levels and in respect of information technology have opened up other possibilities and options. Of

significance among these is what is increasingly referred to as the Internet of Things, the interconnection of

physical devices to an information infrastructure. The paper therefore sets out to position the Internet of

Things at the core of future developments in eHealth.

1 INTRODUCTION

In 2012 Dr Margaret Chan of the World Health

Organization wrote that:

“Population ageing is a global phenomenon that

is both inevitable and predictable. It will change

society at many levels and in complex ways,

creating both challenges and opportunities …”

A globally ageing population in which the

growth in the numbers of older people is

increasingly ever more rapidly (Kinsella and Wan,

2009), places additional demands on resources. This

in turn poses societal challenges in ensuring access

and mobility while preventing trends such as

increasing urbanisation and the depopulation of rural

areas. The underlying vision is thus one of an

eHealth environment where needs are met through

the sustainable organisation and the structuring of

the physical and information environments to meet

the changing needs of an ageing population.

Thus mobility must be considered not just as an

ability to move within the physical environment,

with all that that implies, but also mobility within

the information environment. It is argued that

enhanced mobility within the information

environment then acts to support physical mobility,

for instance through developments in mobile

healthcare (mHealth).

This overarching vision of an eHealth

infrastructure which integrates the physical and the

information environments implies the need for

sustainable solutions which maximise benefits whilst

optimising the use of resources in each of the short-,

medium- and long-terms. Such solutions must

address and support issues such as:

 The level of provision between urban and rural

communities.

 Housing and the balance between new build

and refit or refurbishment.

 The ability to effectively assess need,

specifically within the home environment.

 Means of capturing new and novel forms of

data such as observational data.

 Design strategies to be adopted in relation to

each and all of these issues.

 Tools to support the effective assessment of the

impact of change.

It must be recognised that many current systems

have over time been the subject of evaluation,

review, and indeed change. This has resulted in an

interest, and indeed in some cases an investment, in

maintaining the status quo, resulting in a degree of

compartmentalisation and technological lock-in

which acts to inhibit the introduction of new

concepts, methods and ideas. For instance,

physiological sensors might be considered as an

element of telehealth and not of telecare, implying

also a shift from societal to health related issues.

Similarly, home based and mobile eHealth systems

often tend to be separated rather than viewed as a

continuum such as that of Figure 1.

In presenting the discussion, it is recognised that

many of the individual components are themselves

the subject of study, but what is generally lacking is

139

Ball L., Symkowiak A., Keates S., Bradley D. and Brownsell S..

eHealth and the Internet of Things.

DOI: 10.5220/0004336701390142

In Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems (PECCS-2013), pages 139-142

ISBN: 978-989-8565-43-3

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

Hardware Modules

Home Sensors

Physiological Sensors

Appliances

User Systems

Communications Backbone

Software Modules

Monitoring

Analysis

Interpretation

Knowledge

Control

Design

Access

Usability

HCI

Firmware

Embedded Technologies

Smart Phones

Cameras

Operating Systems

Applications

Mobile Systems

Inclusion

Accessability

Targetted Users

User Driven

System Drivers

Near Field Communications

Thin Client Devices

Identification Technologies

Cyber Security

Internet of Things

System Elements

Cloud Computing

Electronic Health

Records

Support Services

Health Information

Interface

User Specific

Remote Access

Software Download

Figure 1: eHealth modules configured around a

communications backbone.

their integration into a cohesive system. Key issues

are:

1. Detection and identification of behavioural

changes indicative of a change in status.

2. The detection and reporting of emergency

conditions.

3. Incorporation of physiological monitoring.

4. An ability to extend functions into the mobile

environment.

5. Integration within health informatics.

6. Establishment of user needs and requirements.

7. Identification of resources and their

interactions.

8. Infrastructure and sustainability issues.

9. Design strategies and methods.

10. Decision support tools to inform on options and

outcomes.

The key focus here is therefore that of the

information infrastructure, and in particular, the role

of the Internet of Things as a means of integrating a

range of smart objects within that infrastructure

(Kortuem et al., 2010); (Mattern and Floerkemeier,

2010).

2 THE Internet of Things

The underlying concept of the Internet of Things is

the interconnection of discrete smart objects to

provide information about both location and activity.

Working from this base, consideration can be given

to the potential range of actions and applications.

Falling within the action group are:

 Information & Analysis – Monitoring the

behaviour of objects in both space and time.

 Situational Awareness – Real-time monitoring

of and interaction with the environment.

 Data & Information Driven – Distributed and

networked sensors contributing to a rich

information environment driven by advanced

data analysis and visualisation.

While in relation to applications:

 Logistics – Materials handling, location and

transfer.

 Health – Real-time monitoring of conditions

and detection of change.

 Smart Environments – Direct management of

the environment in response to the individual.

 Personal – Social networking and interaction,

virtual communities and security.

2.1 Lifestyle Monitoring, eHealth

and the Internet of Things

Lifestyle monitoring (Brownsell (1) et al., 2011);

(Majeed, 2006) is here taken to encompass:

(i) Responding to changes in behaviour indicative

of a change in need structured around the use

of a range of sensors distributed throughout an

individual’s home environment. The sensor

data is then interpreted to attempt to identify

behavioural and other changes indicative of a

change in need. However, there remains a

sparsity of data with all current installations

essentially being experimental in nature. The

proposed approach is intended to support data

integration and the use of techniques and

methods such as knowledge and discovery as

part of a learning system to support data

analysis.

(ii) Support for emergency conditions such as falls.

Referring to the above, strategies such as:

 The recording of movement in and about the

environment.

 Monitoring the utilisation of space (rooms).

 Observing the pattern of use of appliances.

 Monitoring the use of cupboards, refrigerators

and wardrobes.

have all been considered and potentially could be

linked through the joint concepts of smart objects

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and the Internet of Things

Developments in sensor technology are likely to

lead in the near future to the availability of a range

of initially wearable, and ultimately implantable,

sensors capable of monitoring and recording a range

of physiological parameters (Al-Jobouri, 2011);

(Espina et al., 2006); (Luprano et al., 2006). The

data from these sensors can then be linked through

mobile communications and hence back to the home

and to medical support.

However, the use of home-based, wearable and

implantable devices brings with it ethical, both

human and machine related, considerations which

will need to be addressed. In particular, there are the

concerns of allocating the responsibility for the well-

being of an individual to an autonomous computer

based system which makes decisions on their behalf

(Bowes et al., 2012); (Perry et al., 2010); (Torrance,

2008).

3 EXEMPLARS

3.1 Emotive Computing and Ehealth

The authors have proposed that emotive computing

may have a role to play in eHealth by providing

information on a user’s state of well being through

the interpretation of everyday actions (Ball et al.,

2011); (Bradley et al., 2011). The translation of this

speculative approach into the wider concept of

home-based and mobile lifestyle monitoring will

require developments both in technology and the

means of analysing and interpreting the resulting

data. This implies developments in mobile

applications to manage the data transfer as well as

transitions from the home environment to the mobile

environment. This will in turn require the creation of

accessible applications and the education of

developers in support of the wider concepts of e-

Inclusion to maximise the potential benefit through

the integration of diverse and disparate data streams.

Developments in this area are therefore likely to

include:

 New forms of non-intrusive sensors capable of

gathering emotion related data in a range of

environments.

 Novel forms of application to maximise the

levels of user interaction in relation to the

gathering of such emotion related data.

 New and novel means of analysing and

interpreting the data generated.

3.2 Collection and Management of

Observed Data

It is argued that observation has the potential to be a

significant additional data source to compliment data

derived from sensors. Such observational data has

the ability to provide information on a range of

factors such as general levels of ‘untidiness’ or

‘cleanliness’ and can also report on issues such as

odours which may not be detectable by other means

(Brownsell (2) et al., 2011); (Brownsell (3) et al.,

2011).

Observers range from care professionals such as

the warden of sheltered or monitored

accommodation, a carer or a health visitor to

individuals such as family and friends who are not

trained in observation, but whose relationship may

enable them to identify issues in ways which might

not otherwise be possible. Issues impacting on

implementation include:

 Data capture and interpretation skills of the

observer.

 Data checking and validation.

 Data security.

While means could include:

 Interpretation of freeform text.

 Structured questionnaire in which the answer to

each question establishes the next question.

Placing this into the context of the Internet of

Things, this implies the use of devices such as

tablets and mobile phones integrated with a series of

accessible smart applications to direct the user in

relation to the data capture processes.

3.3 Impact Areas and User Groups

To develop the arguments in the paper and prove the

potential for utilising both observational and

emotive data in improving the health and wellbeing

of an ageing population in particular, it is necessary

to identify target users. Work undertaken in the area

of telecare to establish such groups (Brownsell (1) et

al., 2011), plus the preliminary results of an as yet

incomplete literature review suggest the following

potential impact areas and user groups.

 The Well Elderly, these are older individuals

currently requiring no or low levels of support

where the aim is the detection of change to

ensure the earliest appropriate intervention.

 Progressive neurological diseases such as

Alzheimer’s or dementia to identify change in

order to adjust provision accordingly.

The aim is thus to establish a case study to evaluate

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141

both the technology and the user responses in order

to properly establish and identify those areas where

the resulting interventions are most likely to be

effective.

4 CONCLUSIONS

Faced with an ageing population there is a need to

undertake a radical review of the way in which

eHealth systems, and sub-systems such as telecare

and lifestyle monitoring are designed, developed and

implemented. This is not to suggest that work in

these areas to date is of no value, but rather that it is

regarded as having established the foundation on

which new concepts such as the Internet of Things

can be introduced.

It is in this context therefore that the paper sets

out in Section 1 its position regarding the underlying

issues and concerns that need to be addressed in

moving forward, and follows this in Section 2 with

an argument for adopting an approach based on the

Internet of Things as un overarching strategy. Then

in Section 3, two exemplars as to how this approach

may influence the approach to eHealth are

presented, in each case based on research concepts

which are currently under evaluation and

development by the authors.

The overarching conclusion is therefore that

there is a need for a new and novel approach to the

design, development and operation of all forms of

eHealth systems, and that the Internet of Things

provides one possible means of achieving the

necessary shift in both thinking and approach.

ACKNOWLEDGEMENTS

The authors would like to thank Mark Hawley and

John Isaacs in particular for their contributions to the

background to the paper.

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