Towards an Ethical Framework for the Design and Development of

Inclusive Home-based Smart Technology for Older Adults and People

with Disabilities

Emma Murphy

, Damian Gordon

, Brian Keegan

, Julie Doyle

, Ioannis Stavrakakis

and Dympna O’Sullivan

ASCNet Research Group, School of Computer Science, Technological University Dublin, Dublin 7, Ireland

Netwell CASALA, Dundalk Institute of Technology, Dundalk, Co. Louth, Ireland

julie.doyle@dkit.ie

Keywords: Digital Ethics, Digital Health, Older Adults, People with Disabilities, Human Centred Design, Co-creation.

Abstract: Unique ethical, privacy and safety implications arise for people who are reliant on home-based smart

technology due to health conditions or disabilities. In this position paper we highlight a need for a reflective,

inclusive ethical framework that encompasses the life cycle of smart home technology design. We present

key ethical considerations in the design, development and deployment of smart home-based technology for

older adults and people with disabilities. Using ethical theories, human-centred design and personas we

explore how some of these critical issues can be addressed. Finally, we propose a novel ethical framework for

the development of inclusive home-based smart technology which combines these key considerations with

existing models of design.

1 INTRODUCTION

The planning, design, development and

implementation of home-based smart technology to

enhance the quality of life of a particular individual is

a complex and evolving challenge, and these

complexities can be amplified when end users are

older or have a disability. Unique ethical, privacy and

safety implications arise for people who are reliant on

technology due to health conditions or disabilities.

The aim of home-based smart technology is to

provide utility to an end user by enhancing their

independence and improving quality of life, but if

attention has not also been paid to ethical and privacy

issues, the end user can have difficult and unfair

choices to make.

While ethical approaches have been applied to

particular aspects and phases of smart home-based

https://orcid.org/0000-0001-6738-3067

https://orcid.org/0000-0002-3875-4065

https://orcid.org/0000-0003-0445-108X

https://orcid.org/0000-0003-4017-6329

https://orcid.org/0000-0001-6127-3000

https://orcid.org/0000-0003-2841-9738

technology design and evaluation there is a need for

a practical ethical framework that spans the

technology life cycle and that can address the specific

requirements of people with sensory, physical or

cognitive impairments. In this position paper, we

argue human-centred design and participatory

techniques must form part of a larger multi

stakeholder ethical framework for the design of

inclusive smart spaces for older people and people

with disabilities.

2 HOME-BASED SMART

TECHNOLOGY

Home-based smart technology encourages

independent living at home with the support of smart

technologies. Specialised assistive devices,

614

Murphy, E., Gordon, D., Keegan, B., Doyle, J., Stavrakakis, I. and O’Sullivan, D.

Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People with Disabilities.

DOI: 10.5220/0010879900003123

In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF, pages 614-622

ISBN: 978-989-758-552-4; ISSN: 2184-4305

smartphone or tablet based applications, on-body or

passive sensing technology can be used to increase,

maintain, or improve the functional capabilities of

older adults or individuals with disabilities. Feedback

and information from monitoring technology can be

relayed to occupants or shared with informal

caregivers to aid with decision making about a

person's health and wellbeing.

Challenges in the development of inclusive smart

technology include how to develop understandable

and usable technologies so that they meet individual

variations in needs and abilities so that they help to

maintain autonomy, provide meaningful activities,

address the emotional state of individuals and

promote social inclusion (Nunes, 2015). Moreover,

there is a great variety within these user groups, such

as differences in demographics (e.g., socioeconomic

status) and personality, but also due to the diversity

of specific conditions, each with different

behavioural, cognitive, and emotional consequences.

It is, therefore, vital to have extensive insight into the

dynamic needs, wishes, and abilities of these user

groups and a reiterated theme in the literature is the

essential requirement to involve older adults or

individuals with disabilities in identifying which

needs technologies should meet as well as in the

development and evaluation of such technology

(Jovanovic, 2021; Mannheim, 2019; Cesta, 2018;

Elers, 2018). A review of the literature has

highlighted the following as ethical considerations

when developing smart assistive technologies.

Informed Consent.

The pervasive nature of some smart devices raises

issues of technological understanding and consent. In

addition, older adults or persons with specific

disabilities might have a reduced or even

compromised ability to decide for themselves about

the use of smart technology (O’Connor, 2017).

Privacy.

Smart devices gather a broad spectrum of data about

their users, ranging from in-application activity to

communications to movement and location data.

Combined with their pervasive nature, data can be

collected and used in ways that are not always clear

to end users (O’Connor, 2017; Gochoo, 2021).

Security.

Security in smart spaces refers to securing the IoT

devices and the networks they're connected to. This

involves physical security as well as security of the

data from intrusion and cyber attacks. Users need to

trust in these devices and that their data is secured

(Karale, 2021). Choosing the right technology to fit

the requirements is crucial in avoiding over or

unnecessary surveillance. For example when it comes

to security, a motion sensing device may be sufficient

in place of a camera to determine if a busy path is

clear of traffic to ensure safe passage.

Autonomy.

Technology should be designed to accommodate

existing living patterns and should offer users control

and influence over their lives and well-being

(FakhrHosseini, 2019).

Safety.

Ensuring the safety of older adults and persons with

disabilities is crucial to their independence and

quality of life. From a technology standpoint, safety

and technological reliability are highly coupled and it

is important that evaluations of smart technologies are

not limited to testing in laboratory settings designed

to simulate potential end user environments rather

than more complex real world environments (Pigini,

2017).

Data Accuracy.

The accuracy of data collected in smart spaces

depends on a number of factors including the

reliability of the device, device configuration or

placement, device misuse or misunderstanding.

Smart sensors can also generate false positives and

inferences, recommendations and predictions based

on inaccurate data will contain errors (Aramendi

2019).

Data Sharing.

Data collected via smart technologies is often shared

with manufacturers and third parties. This can be for

varied purposes, to help the manufacturer to improve

the product or to aggregate data for analytics and

insights. Older adults or persons with disabilities may

wish to share data with formal or informal caregivers

but they should have control over how and with

whom their own data is shared (Doyle et al., 2015).

Data management policies should be available and

accessible (Mocrii, 2018).

Transparency and Trust.

Transparency enables end users to understand the

smart system. It incorporates previous factors such as

privacy and data management and ensuring that these

are well understood by those using the system.

Transparency is important at both the device and

system levels (Yao, 2019). Understanding how the

data is stored and managed is essential for trust of

Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People

with Disabilities

615

system and data Doyle et al. (2015). To trust decisions

computed by smart systems, users need to know how

that system arrives at its conclusions and

recommendations. Trust is related to data accuracy

and transparency above and explanation below

(Cannizzaro, 2020).

Explanation.

Existing approaches to explanations for smart

systems are tailored more towards interpretations that

are more suitable for modelers and less for technically

inexperienced users. The majority of smart systems

do not incorporate explanation capabilities (Nikou,

2019).

Acceptability.

Immersive technology requires immersive data to

understand the environment and the individual. This

means allowing technology access to our personal

spaces. This can be intrusive if not done correctly and

tailored for the cohort. Passive, low impact, low

visibility, low maintenance and high reliability

should be considered as high priority requirements

when dealing with older adults and people with

disabilities. These requirements have a cost trade off

over disposable low cost IoT devices.

It is accepted that end users make trade-offs when

using smart technology, for example, data privacy for

functionality (Singh et al., 2016) or increased

autonomy, security over privacy for better

surveillance, increased functionality or better

displays for less explanations or usability for

complexity. We argue that these trade-offs should not

be inevitable, particularly for persons who are reliant

on technology. We posit that an ethical, user driven

framework incorporating a design-driven approach

can reduce or eliminate these trade-offs by better

understanding the needs and requirements of end

users.

3 ETHICS AND TECHNOLOGY

In terms of ethical frameworks, individual ethical

theories place different weight on the importance of

intentions versus outcomes in evaluating actions.

Deontology emphasises the intention to act in

accordance with our duties (intentions), and believes

the consequences of our actions have no ethical

relevance. The utilitarian view is that everyone's

interests have equal weight, and as form of

consequentialism, judges actions by their results or

outcomes. Virtue ethics becomes increasingly

popular in philosophy of technology, for example,

Vallor (2016) has argued that virtue ethics with its

focus on choices that aim at the ‘good life' is ideally

suited for managing complex, novel, and

unpredictable moral landscapes, just the kind of

landscape that today’s emerging technologies

present. Value Sensitive Design (Friedman, 2013),

defined as “a theoretically grounded approach to the

design of technology that accounts for human values

in a principled and comprehensive manner

throughout the design process” could be considered

an example of Vallor’s (2016) application of virtue

ethics to technology.

It is fair to say that the software engineering

process has traditionally been driven by a more

utilitarian approach by focusing on outcomes in terms

of the development of commercial products or

services. But a blind spot for intentions has led to

many high profile ethical technology failures where

software has displayed unintended consequences

(e.g. biases or privacy violations) or been used in a

different and unethical manner from that for which is

was originally designed (e.g. data harvesting

applications embedded in social media or facial

recognition technology used for commercial purposes

when it had originally been developed for law and

order purposes). The recent emphasis on data

management and governance and high profile data

breaches have led to high level data management

frameworks incorporating ethics, for example the UK

Department for Digital, Culture, Media & Sport

(2020) formulated an ethics framework in its National

Data Strategy.

Figure 1: Framework to assess individual invasiveness of

the outcome of data processing vs. societal value (O’Keefe

and O’Brien, 2018).

At lower levels, frameworks such as that by O’Keefe

and O’Brien (2018) (Figure 1 and Table 1) offer

organisations a practical guide to implementing data

ethics. These frameworks have tended to follow the

traditional trajectory in software engineering by

focusing more on outcomes than intentions. Recent

welcome developments have shifted the emphasis

HEALTHINF 2022 - 15th International Conference on Health Informatics

616

Table 1: First Principles Ethical Test (O’Keefe and

O’Brien, 2018).

First Principles Ethical Test:

“Does the outcome of your design/algorithm/process

outcome contribute positively to ‘the good’, or positive

preservation of human rights?” (O'Keefe and O’Brien,

2018)

Does it preserve or enhance human dignity?

Does it preserve the autonomy of the human?

Is the processing necessary and proportionate?

Does it uphold the common good?

from outcomes to intentions to reduce blind spots in

technology development, for example Consequence

Scanning is an Agile approach that fits within an

iterative development cycle and encourages

organisations to consider the potential consequences

of their product or service on people, communities

and the planet (Brown, 2019).

Research projects involving human participants

undergo ethical assessments and more recently data

protection impact assessments that are built on some

of the outcome-focused ethical frameworks presented

above but typically these occur at the end of the

technology design phase. This point of ethical

evaluation is usually late in the development of the

technology or research project and focus on the

impact of the system as designed on the research

participants. At this point, it is arguably too late for

researchers to consider questions such as “should this

technology ever have been developed in the first

place?”. We argue that a framework is required that

allows us to reflect on ethical issues - those related to

both intentions and outcomes - at challenge points

throughout the technology life cycle.

4 HUMAN CENTRED DESIGN

Most technology lifecycle models involve a user

requirements phase, for example the incorporation of

use cases as part of purpose and process

specifications within a practical IoT design

methodology (Bahga and Madisetti, 2021). However

it can be difficult to capture the complex requirements

involved in designing home-based smart technology

for older adults and people with disabilities without

involving them directly in the process.

Human-centred participatory approaches to

technology that involve end users at every stage of the

design process from requirements gathering to

prototype design and iterative development are not

novel. Design thinking, first proposed in 1969

(Simon, 1969) as a three step process is most

commonly applied to technology using the five stage

user centred, iterative design model developed by the

Hasso-Plattner Institute of Design at Stanford

University (see figure 2).

Figure 2: Five stages of Design Thinking (Hasso Plattner

Institute of Design, 2010).

However, we need to acknowledge that even

when a user-centred approach such as design thinking

is adopted, designs can still be technology-led or

driven by researchers rather than end users (Rogers

and Marsden, 2013) due to practical constraints such

as meeting requirements of funders or commercial

technology partners involved in the design. The

tensions between the requirements of relevant

stakeholders and a genuine user centred approach are

important to acknowledge for a holistic ethical

approach to design.

There are multiple stakeholders involved in the

creation, implementation and deployment of home-

based smart technology for health and wellbeing.

Social models of research and care for older adults

and people with disabilities have progressed

participatory approaches to technology design and

have led to more inclusive approaches to the entire

research process. There is a growing body of research

exploring ethnographic methodologies for a co-

researcher approach in the areas of developing age-

friendly concepts, (Buffel, 2015; Egan et al., 2014)

and disability research (Cappelen and Andersson,

2021). Rather than passively taking part in a task or

design phase, research participants can be viewed as

partners in the entire research lifecycle, with a focus

on conceptual issues of identity, participation and

support networks (Carroll and Rosson, 2013). It

should be acknowledged that some applications of

participatory approaches to technology design have

been critiqued as having a narrow interpretation of

ethnographic methods as a requirements gathering

exercise and have ignored core insights of

ethnographic inquiry, such as the relationship

between researcher and subject (Dourish, 2006). An

honest understanding of the relationship is crucial to

being able to evaluate ethical risk through the entire

design lifecycle.

A further criticism of Human Centred Design has

been the perception that the latest technology

Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People

with Disabilities

617

advancements may not be utilised with a user driven

approach (Norman, 2005). This critique highlights

the need to involve multistakeholder design teams

that involve technology experts co-designing with

end users so that technological capabilities are well

matched to user needs. Furthermore human centred

does not preclude innovative technology designs. For

example recent state-of-the-art IoT environments

have explored how systems can be more human

centric by incorporating contextual elements that

have meaning for users such as time and space based

on proxemic interactions (Calderon, et al., 2016).

5 PERSONAS AND ETHICS

Personas are a useful tool in a human centred design

approach to understand and communicate user needs

and requirements. If designers want to test potential

solutions, but don’t have continuous access to the

end-users, they can create fictional characters that can

be used to represent a collection of the kinds of people

who could be using that potential solution, called

personas (Cooper, et al., 2014). Although some

researchers have criticised the use of personas by

pointing out that real customers are preferable to the

use of personas, there are many cases where this is not

possible, so personas are an effective, if somewhat

inferior, alternative (Salminen, et al., 2018). Studies

such as Long (2009) have shown that personas can

result in many benefits, including: more usable

designs, more user-centred discussions, and more

effective communication in design teams.

In this case, we have developed personas for this

process for design ideation to help create stories that

bring to life the existing data, theory and literature

(Gordon, et al., 2013) to help to understand and

communicate the key ethical issues presented above.

The two personas are as follows:

John Neat

John is a software

developer and has a

good understanding

of data flow and

privacy issues. John

has low vision and is

a wheelchair user.

John relies on various smart devices for daily

activities. He has concerns regarding the data

management for some of the commercial devices that he

uses. As a software developer he is well aware that even

if the creator of an application is very scrupulous about

their own data management, the application will

invariably use third-party libraries whose data

management policies may be impossible to

determine. For example he is concerned with how his

voice recordings for his voice assistant are stored and

shared with third party companies. However despite his

concerns, this is the only device that is accessible and so

he needs to make a difficult decision between his daily

activities and his personal privacy.

John is married to Judy, and they have two teenage

children, Gloria and Edward, who also use the family

smart speaker, which again, John is concerned that this

data will be shared, and that marketing companies will

have an extensive profile about his children before they

even become adults.

Mary Noble

Mary is a retired

Mathematics teacher,

and keeps up to date

with the national maths

curriculum so that she

can try to take the state

exams each year, she

feels this helps her to

monitor her cognitive

functions.

Mary has been diagnosed with a Mild Cognitive

Impairment that may be the early stages of dementia. She

has high blood pressure, high cholesterol and type II

diabetes that she manages with medication. Mary has an

old fashioned large keyed flip phone that she uses for

making calls. Her children recently gave her an iPad which

gathered dust for a while but her neighbour Kathleen

showed her how to use a great app called Rekall that has

a collection of puzzles, a diarying feature that she uses

with her neighbour, and a calendar feature that reminds

her of key events during the day, and during the week.

Mary has recently joined a research project that

involves her using a prototype of a smart pill box that

helps her to manage her complex medication routine and

is linked to an app on her iPad and alerts her when

something is wrong in relation to her medication dosage,

timing or frequency. Her daughter and neighbour

Kathleen are also sent alerts. Her pharmacist is also part

of the study and the system updates him when she needs

a medication refill.

HEALTHINF 2022 - 15th International Conference on Health Informatics

618

Mary is enjoying taking part in the research and while

she finds the technology useful, she does not fully

understand how her data is used in the project. She enjoys

the regular meetings with the research team when they

call to her house to interview her about the technology.

She is anxious that she will not be able to answer their

questions or use the technology if her memory

deteriorates.

In the first persona, John Neat, we have tried to

synthesise the unique ethical and privacy implications

that arise for people who are reliant on a device or

technology due to health conditions or disabilities.

Accessibility requirements can generate unique

challenges and lack of choice that can pose difficult

choices for individuals and create an unfair trade-off

between personal ethical concerns with benefits to

health and everyday quality of life. In this persona,

John has to balance his independence through the use

of a voice assistant and the risk to privacy of his

family. We have tried to visualise this trade-off using

a matrix based on the O’Keefe and O’Brien (2018)

model presented in figure 1 but this time considering

the utility of a technology vs. the ethical risk posed

(see figure 3).

Figure 3: Considering the trade-off between utility and

ethical risk that is particularly relevant to older adults and

people with disabilities.

In the second persona we describe a smart pill

dispenser that sends alerts to the end user and their

network of care. We tried to highlight in this persona

the challenges that need to be addressed when a

research participant has low digital literacy which

will affect her use of the devices but her

understanding of the data flow and data management

within the research project. If these are not accessible

and controllable by the user, there are ethical risks

around autonomy and consent for the research and

related technology. Mary also has a cognitive

impairment that may worsen over time and this also

highlights that there can be ethical risks for the

sustainability of a system that is designed to support

a person at a point in time but may become redundant

if their situation, health or capabilities change.

Finally, we tried to illustrate the importance of the

relationship between a researcher and participants in

studies that deploy home-based smart technologies.

Participants like Mary may enjoy the social aspects of

being part of a research project and the effects of this

need to be considered after the technology is

withdrawn and a study ends. The relationships

between participants, their networks of care,

researchers, technology designers need to be

considered in the design of any research project that

involves home-based smart technology.

6 PROPOSED 5D FRAMEWORK

This research proposes a new ethical framework, that

we have entitled the 5D Framework, for the

development of inclusive home-based smart

technology by combining the research presented

above with aspects of the five-phase design thinking

model proposed by the Hasso-Plattner Institute of

Design (d.school), at Stanford, USA (Apiyanti and

Dewi, 2019), as well as elements of the UK Design

Council’s Double Diamond Model (Howard, et al.,

2008).

Crucially, the Framework emphasises that the

user is at the heart of the entire framework - they must

be the co-designers of the system; in combination

with the O’Keefe and O’Brien ethics model and the

practical application of ethics in value-sensitive

design (Friedman, 2013), these two dimensions are

present in all five stages of the framework. The

Design Team are a team of participants that include

the end-user, as well as experts in technology and

relevant health domain i.e. clinicians, occupational

therapists, physiotherapists etc.

In Appendices A and B we have presented two

checksheets that can be used as prompts for system

developers with some of the key ethics issues that are

important for these systems, echoing themes

identified in Section 2, as well as the O’Keefe and

O’Brien (2018) Framework and in value-sensitive

design (Friedman, 2013). The checksheet in

Appendix A focuses on data-level ethical

considerations, and the one in Appendix B focuses on

system-level issues. The 5D Framework is as follows:

1. Discover

•

In this stage the full Design Team must begin a two-

way dialogue with the end-user (and other parties) in

a thoughtful manner to understand their needs. If

Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People

with Disabilities

619

they cannot locate any end-users, they should use

personas such as those provided in Section 5.

• They may use techniques from Software

Engineering, including Requirements Gathering and

Knowledge Elicitation (Sommerville, 2015), and the

IoT design methodology from Bahga and Madisetti

(2014).

• They may use design and research techniques

including interviews, ethnographical diarying, and

shadowing (Creswell, 2021).

• From an ethics perspective, the three main ethical

theories from Section 3 (Deontology, Utilitarianism,

and Virtue ethics) need to be considered.

• Assess potential benefit and harm for every

stakeholder group as proposed in (Friedman, 2013)

• Basic research ethics protocols must also be used,

adhering to standard policies and codes, and it would

be expected to undergo a formal ethics approval.

2. Define

• In this stage the full Design Team are trying to

encapsulate their findings from the Discover Stage

into a series of models, noting key challenges (pinch

points and pain points) as well as existing

affordances. Again, the end-user is a core member of

the Design Team, and they are both the subject of

the design, and the architect of the solutions. For the

times they are not available, the personas can be

used.

• They may use techniques from Software

Engineering, including Use Case Diagrams and Data

Flow Diagrams (Sommerville, 2015) and the IoT

design methodology from Bahga and Madisetti

(2014).

• They may use design techniques such as MindMaps

(or Spider Diagrams) and Gap Analysis to help

clarify their thinking (Buzan and Griffiths, 2013).

• They may also refer to Assistive Technology models

such as the HAAT (Human, Activity, Assistive

Technology) and the TAM (Technology Acceptance

Model) (Cook, et al., 2020).

• From an ethics perspective, the O’Keefe and

O’Brien (2018) Framework (looking at Dignity,

Autonomy, Necessity, and Good)

3. Develop

• In this stage the full Design Team are working on

identifying a range of potential approaches to

addressing the issues identified in the two previous

stages. Again, the end-user will be a vital force in

the stage.

• They may use techniques from Software

Engineering including Paper Prototyping and

“Wizard of Oz” Prototyping (Sommerville, 2015), as

well as the two personas, and the IoT design

methodology from Bahga and Madisetti (2014)

• They may use design techniques such as the Six

Thinking Hats and Ishikawa Diagrams (Michalko,

2006).

• A research ethics review should be conducted at this

point to ensure that none of the proposed solutions

diverge significantly from the formal ethics

approval.

• This is likely to be the most iterative and

cyclical stage.

4. Deliver

• In this stage the full Design Team are selecting a

single potential solution from those developed in the

previous stage, and it is vital that the end-user is

asked and listened to, as well as using personas

where needed.

• They may use techniques from Software

Engineering including Vertical and Horizontal

Prototyping (Sommerville, 2015).

• They may use design techniques including User

Stories and Storyboards (Sommerville, 2015),

Personas, Empathy Maps (Hasso Plattner Institute of

Design, 2010)

• The ethics checksheets in Appendices A and B

should be discussed in meetings and reflected on

carefully. The team may also consider undertaking a

Data Protection Impact Assessment at this stage

(Bieker, 2016).

5. Determine

• In this stage the full Design Team are testing the

effectiveness of their solution. The system is

deployed and the team are determining what aspects

of the system work well, and which are not fully

serving their purpose. This section includes

considerations relating to maintenance and

sustainability.

• They may use techniques from Software

Engineering including User Acceptance Testing and

Performance Testing (Sommerville, 2015).

• They may use design techniques such as group-

based roleplay and the Think-Aloud Protocol

(Norman, 1986).

• They may use educational techniques such as

Reflective Practice and Metacognitive Strategies

(Gravells and Simpson, 2014).

• The ethics checksheets in Appendices A and B are

crucial at this stage of the process. They must also

consider undertaking a Data Protection Impact

Assessment at this stage (Bieker, 2016). as well as

the O’Keefe and O’Brien (2018) First Principle Test.

A research ethics review should also be done at this

point to make sure no research ethics violations have

occurred. All team members must consider if there

are any lingering ethical issues that need to be

addressed.

7 CONCLUSIONS

The development of inclusive home-based smart

technology presents many unique ethical challenges,

HEALTHINF 2022 - 15th International Conference on Health Informatics

620

and when this is allied with these systems being

developed for older adults and people with

disabilities, the ethical concerns and considerations

grow significantly. In this paper we have outlined a

framework for navigating some of these ethical issues

using a range of techniques from Software

Engineering, Education, and Research Methods to

produce a coherent new ethics driven approach that

we have entitled “The 5D Framework” that puts the

user at the heart of the process.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the support of the

Erasmus+ programme of the European Union. The

European Commission's support for the production of

this publication does not constitute an endorsement of

the contents, which reflect the views only of the

authors, and the Commission cannot be held

responsible for any use which may be made of the

information contained therein. This material is based

upon works supported by the Science Foundation

Ireland under Grant No. 19/FFP/6917.

REFERENCES

Apiyanti, S. and Dewi, L., 2019, Design Thinking of the

Inclusive Education Learning Strategy in the 5.0

Society Era”. 4th International Conference on

Education and Regional Development (ICERD), pp.

631-642.

Aramendi, AA, Weakley, A., Goenaga, AA., Schmitter-

Edgecombe, M., Cook, DJ, (2018). Automatic

assessment of functional health decline in older adults

based on smart home data, Journal of Biomedical

Informatics, 81: 119-130.

Bahga, A., & Madisetti, V., 2014, Internet of Things: A

hands-on approach. Vijay Madisetti Publishers.

Bieker, F., Friedewald, M., Hansen, M., Obersteller, H. and

Rost, M., 2016, September. A Process for Data

Protection Impact Assessment under the European

General Data Protection Regulation. In Annual Privacy

Forum (pp. 21-37). Springer, Cham.

Brown S. (2019) Consequence Scanning Manual Version 1.

London: Doteveryone.

Buffel, T., Phillipson, C.and Scharf, T. (2012) Ageing in

urban environments: Developing ‘age-friendly’ cities.

Critical Social Policy, 32: 597-617.

Buzan, T. and Griffiths, C., 2013. Mind Maps for Business,

Using the Ultimate Thinking Tool to Revolutionise How

You Work. 2nd Edition, Pearson.

Calderon, M. A., Delgadillo, S. E., & Garcia-Macias, J. A.

(2016). A More Human-Centric Internet of Things with

Temporal and Spatial Context. Procedia Computer

Science, 83, 553-559.

Cannizzaro S, Procter R, Ma, S, Maple C (2020) Trust in

the smart home: Findings from a nationally

representative survey in the UK. PLoS ONE 15(5):

e0231615.

Cappelen, B. and Andersson, A.P., (2021). Trans-Create–

Co-Design with Persons with Severe Disabilities. In

Universal Design 2021: From Special to Mainstream

Solutions (pp. 87-101). IOS Press.

Carroll, J. and Rosson, M. (2013) Wild at Home: The

Neighborhood as a Living Laboratory for HCI. ACM

Transactions in Computer Human Interaction 20, 3,

Article 16 (July 2013)

Cesta, A., Cortellessa, G., Fracasso, F., Orlandini, A., &

Turno, M. (2018). User Needs and Preferences on AAL

systems that Support Older Adults and their Carers.

Journal of Ambient Intelligence and Smart

Environments, 10(1), 49-70

Cook, A.M., Polgar, J.M., Encarnação, P., 2020, Assistive

Technologies: Principles and Practice, 5th ed., Mosby.

Cooper, A., Reimann, R., Cronin, D. and Noessel, C., 2014.

About Face: The Essentials of Interaction Design. John

Wiley & Sons.

Creswell, J.W., 2021, A Concise Introduction to Mixed

Methods Research, SAGE publications, ISBN-

1544355750.

Dourish, P. (2006) Implications for design. In Proceedings

of the SIGCHI Conference on Human Factors in

Computing Systems (CHI '06). Association for

Computing Machinery, New York, NY, USA, 541–

550.

Doyle, J., Caprani, N., Bond, B. (2015) Older adults'

attitudes to self-management of health and wellness

through smart home data, 2015 9th International

Conference on Pervasive Computing Technologies for

Healthcare (PervasiveHealth), pp. 129-136.

Elers, P., Hunter, I., Whiddett, D., Lockhart, C., Guesgen,

H., & Singh, A. (2018). User Requirements for

Technology to Assist Aging in Place: Qualitative Study

of Older People and their Informal Support Networks.

JMIR mHealth and uHealth, 6(6), e10741

FakhrHosseini M., Lee C., Coughlin J.F. (2019) Smarter

Homes for Older Adults: Building a Framework

Around Types and Levels of Autonomy. In: Zhou J.,

Salvendy G. (eds) Human Aspects of IT for the Aged

Population. Social Media, Games and Assistive

Environments. HCII 2019. Lecture Notes in Computer

Science, vol 11593. Springer, Cham

Friedman, Batya, Peter H. Kahn, Alan Borning, and Alina

Huldtgren. 2013. “Value Sensitive Design and

Information Systems.” In Early Engagement and New

Technologies: Opening up the Laboratory, 59–95.

Gochoo, M.; Alnajjar, F.; Tan, T.-H.; Khalid, S. Towards

Privacy-Preserved Aging in Place: A Systematic

Review. Sensors 2021, 21, 3082.

Gordon, D., Fennell, A., O'Leary, C., O'Connor, J. (2013)

"Persona-Based Teaching: A New Approach to

Exploring the Dimensions of Universal Design using

Personas and Scenarios", in Proceedings of "Is

Towards an Ethical Framework for the Design and Development of Inclusive Home-based Smart Technology for Older Adults and People

with Disabilities

621

Universal Design in Education Any of My Business?"

AHEAD Conference, Dublin, Ireland, March 12th &

13th, 2013.

Gravells, A. and Simpson, S., 2014. The Certificate in

Education and Training. Learning Matters Press.

Hasso Plattner Institute of Design (2010) An Introduction

to Design Thinking: PROCESS GUIDE. Available:

https://web.stanford.edu/~mshanks/MichaelShanks/file

s/509554.pdf

Howard, T.J., Culley, S.J. and Dekoninck, E., 2008.

Describing the Creative Design Process by the

Integration of Engineering Design and Cognitive

Psychology Literature. Design studies, 29(2), pp.160-

180.

Howard, T.W., 2015. Are Personas Really Usable?.

Communication Design Quarterly Review, 3(2), pp.20-

26.

Jovanovic, M & De Angeli, A& Mcneill, A & Coventry, L.

(2021). User Requirements for Inclusive Technology

for Older Adults. Int J Hum-Comput Int. 10.1080/

10447318.2021.1921365.

Karale A. The Challenges of IoT Addressing Security,

Ethics, Privacy, and Laws, Internet of Things, 2021,

15:100420

Long, F., 2009, Real or Imaginary: The Effectiveness of

Using Personas in Product Design. In Proceedings of

the Irish Ergonomics Society annual conference (Vol.

14, pp. 1-10).

Mannheim, I., Schwartz, E., Xi, W., Buttigieg, S. C.,

McDonnell-Naughton, M., Wouters, E., & van Zaalen,

Y. (2019). Inclusion of Older Adults in the Research

and Design of Digital Technology. Int J Environ Res

Public Health, 16(19), 3718.

Michalko, M., 2006. Thinkertoys: A Handbook of Creative-

Thinking Techniques. Random House Digital, Inc.

Mocrii, D., Chen, Y., Musilek, P. (2018) IoT-based Smart

Homes: A Review of System Architecture, Software,

Communications, Privacy and Security ,Internet of

Things, 1–2:81-98.

Nikou S. (2019) Factors driving the adoption of smart home

technology: An empirical assessment, Telematics and

Informatics, 45:e10128.

Norman, D.A., 1986. User centered system design: New

perspectives on human-computer interaction. CRC

Press.

Norman, D.A.,. 2005. Human-Centered Design Considered

Harmful. Interactions 12(4), 14–19.

Nunes F, Verdezoto N, Fitzpatrick G, Kyng M, Grönvall E,

Storni C (2015). Self-care technologies in HCI: Trends,

tensions, and opportunities. ACM Trans Comput

Interact 22, 33:1–33:45

O’Connor, Y., Rowan, W., Lynch, L., & Heavin C.

(2017)Privacy by Design: Informed Consent and

Internet of Things for Smart Health, Procedia

Computer Science,113:653-658.

O'Keefe K. and O. Brien, D. (2018). Ethical Data and

Information Management: Concepts, Tools and

Methods (1st. ed.). Kogan Page Ltd., GBR.

Pigini, L., Bovi, G., Panzarino, C., Gower, V., Ferratini, M.,

Andreoni, G., Sassi, R., Rivolta, M.W., Ferrarin, M.

(2017). Pilot test of a new personal health system

integrating environmental and wearable sensors for

telemonitoring and care of elderly people at home

(SMARTA project). Gerontology, 63: 281-286

Rogers, Y. and Marsden, G. (2013) Does he take sugar?:

moving beyond the rhetoric of compassion. interactions

20, 4 (July 2013), 48-57.

Salminen, J., Jansen, B.J., An, J., Kwak, H. and Jung, S.G.,

2018. Are Personas Done? Evaluating their Usefulness

in the Age of Digital Analytics. Persona Studies, 4(2),

pp.47-65.

Simon, H (1969) The Sciences of the Artificial (3rd Edition,

1996), MIT Press.

Singh,R., Cassell, B. Keshav,S. and Brecht, T. (2018)

TussleOS: managing privacy versus functionality trade-

offs on IoT devices. SIGCOMM Comput. Commun.

Rev. 46, 3, Article 3

Sommerville, I., 2015. Software Engineering 10th Edition.

Pearson, ISBN-9781292096131.

Vallor S (2016) Technology and the Virtues. Oxford

University Press, New York.

Yao, Y., Basdeo, J. R., Kaushik, S., & Wang, Y. (2019).

Defending my castle: A co-design study of privacy

mechanisms for smart homes. In CHI 2019 -

Proceedings of the 2019 CHI Conference on Human

Factors in Computing Systems (Conference on Human

Factors in Computing Systems - Proceedings). ACM.

Zajicek, M. (2001). Interface design for older adults. In R.

Heller, J. Jorge, and R. Guedj (Eds.), Proceedings of the

2001 EC/NSF workshop on Universal accessibility of

ubiquitous

Moore, R., Lopes, J. (1999). Paper templates. In

TEMPLATE’06, 1st International Conference on

Template Production. SCITEPRESS.

Smith, J. (1998). The book, The publishing company.

London, 2

edition.

UK Department for Digital, Culture, Media & Sport (2020)

National Data Strategy. Available: https://

www.gov.uk/government/publications/uk-national-

data-strategy/national-data-strategy

APPENDIX

Appendix A: SmartTech Data-Level Ethics Checksheet.

Available: https://tinyurl.com/ynd3274e

Appendix B: SmartTech System-Level Ethics Checksheet.

Available: https://tinyurl.com/388zhper

HEALTHINF 2022 - 15th International Conference on Health Informatics

622