Systematic Literature Review of Internet of Things Solutions

Oriented to People with Physical and Intellectual Disabilities

Max Ulloa

, Daniela Prado-Cabrera

and Priscila Cedillo

Department of Computer Sciences, Universidad de Cuenca, Av. 12 de Abril, Cuenca, Ecuador

Keywords: Disability, Internet of Things, IoT, Physical, Intellectual, Cognitive.

Abstract: The Internet of Things (IoT) has become a revolutionary technology. It allows hundreds of devices to connect

and collect information, send and receive data over the internet, and other activities. The IoT has been applied

in various fields; one of them is to support people with disabilities. The interconnection of devices has allowed

people to develop activities autonomously, improving their quality of life. Although it is an emerging

technology and there are several secondary studies about the collection of evidence on IoT devices, very few

are applied to people with disabilities. Based on the systematic review results, taxonomies related to the

addressed topic determine research gaps for scientific progress and non-duplication of existing solutions. Thus,

this article present the planning stage of a future study presenting IoT solutions applied to people with

disabilities, aiming to answer the following research question: What Internet of Things solutions exist for

people with disabilities? The results are presented, and the discussion describes the principal features of the

IoT solutions oriented to people with physical and intellectual disabilities.

1 INTRODUCTION

Worldwide, more than 1000 million people suffer

some kind of disability, of which between 110 and

190 million have affections that limit their daily tasks.

Unfortunately, these numbers rise due to the aging

population and the increase in chronic diseases

globally (OMS, 2017). In Ecuador, there are 418.392

people registered with some kind of disability, from

which 46,34% represents the people with a physical

disability, 22,60% with intellectual, 14,05% auditory,

11,60% visual, and 5,41% psychosocial problems

(CONADIS, 2020). These numbers indicate a fairly

wide percentage of people who need assistive

technologies to preserve their independence as much

as possible and support health personnel during their

activities. Moreover, according to Holloway and

Dawes, people with disabilities can be helped by

assistive technology to improve their well-being

(Holloway & Dawes, 2016).

In this context, the IoT solutions could provide

assistive technology based on connecting everyday

objects to the internet. IoT devices and components

https://orcid.org/0000-0003-1524-9805

https://orcid.org/0000-0003-1241-1782

https://orcid.org/0000-0002-6787-0655

exchange and process information collected through

sensors and provide value added services to end-users

(Barrio, 2018). Therefore, people with disabilities and

health personnel can be supported by IoT technology,

which can solve problems in several areas.

Health is one of the most popular fields supported

by IoT, it plays a very important role in improving the

precision, reliability and productivity of the electronic

elements used in this area (Joyia et al., 2017). Also,

in the disabilities scope it has also provided support

and improved the quality of life of people with visual,

hearing and physical problems, among others, since it

has proven to be a powerful tool that contributes to

the independence and participation of people

(Domingo, 2012). In the context of the mIoT (medical

Internet of Things) and disabilities, several

technological solutions for people have emerged,

which have been oriented towards the design of

assistive technologies and improved rehabilitation

practices (Holloway & Dawes, 2016). There are a

wide variety of tools created using IoT technology.

Thus, it is necessary to condensate their existence in

a study that evidences the existing solutions into a

228

Ulloa, M., Prado-Cabrera, D. and Cedillo, P.

Systematic Literature Review of Internet of Things Solutions Oriented to People with Physical and Intellectual Disabilities.

DOI: 10.5220/0010480902280235

In Proceedings of the 7th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2021), pages 228-235

ISBN: 978-989-758-506-7

secondary contribution, which provides insights for

engineers, researchers, and health personnel.

This study aims to carry out a systematic literature

review that addresses the information and answers the

following research question: "What Internet of Things

solutions exist for people with disabilities?". This

question will be answered by focusing on the

extraction criteria and the final discussion on how IoT

solutions support, enable or improve various

problems whether they are minor, moderate or severe.

Also, defining how the IoT technology benefits

children, adolescents, adults, older adults, among

other actors from the health area. All of this

emphasizes the kind of support, the type of

instruments created, and the patient's characteristics.

Finally, this paper is structured as follows: Section

2 presents the related work, where it has been

explained the existence of secondary studies related

to IoT devices to disabilities. Then, in Section 3, the

systematic literature review is presented, its protocol,

execution and results; finally, Section 4 presents the

conclusions and further work.

2 RELATED WORK

Over the years, systematic reviews have addressed

IoT-related topics in various fields. On the one hand,

some reviews emphasized general aspects of IoT

technology; for example, Madakam, Ramaswamy &

Tripathi (2015) provided an overview of IoT

architectures and their use in people's daily lives;

however, they do not emphasize solutions for people

with disabilities. Other reviews, such as the one

presented by Aqeel (2020) and Tiwari (2017)

presented a complete overview of the components of

IoT and various security problems typical of

emerging technologies. These studies represent a

significant contribution because they are focused on

determining the high degree of trust in IoT

applications. However, similar to previous authors,

those studies do not address IoT solutions for people

with disabilities.

On the other hand, there are studies focused on the

use of technology for disabilities, such as the study by

Colpani & Homem (2015) in which they perform a

systematic review related to the treatment of

disabilities with technology, gather virtual reality

solutions and augmented reality for the treatment of

people with cognitive impairment. Also, Cedillo,

Sanchez, Campos & Bermeo (2018) proposed a

secondary study on Ambient Assisted Living (AAL),

which seeks to establish hardware and software

relationships that solve specific disabilities. Although

there are secondary studies that collect health-

oriented IoT solutions; the existing literature on IoT

solutions for people with disabilities has not been

addressed, nor has any classification been presented

to guide the healthcare professional in selecting the

best IoT device to support their clinical activities.

3 THE SYSTEMATIC

LITERATURE REVIEW

A systematic review of the literature seeks to follow

a scientific, repeatable, and replicable method to

collect information on a specific topic. It is necessary

to follow a set of tasks to get a solid foundation and

potential gaps in the field of study. For this specific

case, the topic is related to IoT solutions focused on

solving problems for people with disabilities. This

study follows the Kitchenham & Charters (2007)

methodology, which covers the three phases: (i)

planning the review, (ii) conducting the review, and

(iii) the review report.

Finally, this paper is structured as follows:

Section 2 presents the related work, where it has been

explained the existence of secondary studies related

to IoT devices to disabilities. Then, in Section 3, the

systematic literature review is

3.1 Planning the Review

The following sub-tasks or activities make up the

planning stage: 1) defining the research questions, 2)

the strategy to be followed for the search of primary

studies, 3) establishing the criteria for the selection of

primary studies, 4) assessing the quality of the

studies, 5) establishing the data extraction strategy, 6)

defining the synthesis strategy.

3.1.1 Research Question

Here is stated the question that covers the entire

research. For this study, the main research question

is: "Which Internet of Things solutions exist for

people with disabilities?" In order to answer this

question, the following sub-questions are also

defined:

• RQ1.

Which disabilities have been supported by

IoT technology?

• RQ2. What kind of IoT devices and applications

are the most used in the IoT area for health care?

• RQ3. How have studies of disabilities that rely

on IoT technologies been addressed?

Systematic Literature Review of Internet of Things Solutions Oriented to People with Physical and Intellectual Disabilities

229

3.1.2 Data Sources and Search Strategy

The search strategy will be performed in two different

ways: automatic search and manual search.

Automatic searches require a combination of words

based on the research questions, and manual searches

are applied in relevant conferences, journals, and

books.

For the automatic search the following digital

libraries have been selected: IEEE Xplore Digital

Library because it is a research database on Computer

Science, Electrical and Electronic Engineering

applied to various areas; ACM Digital Library, which

has a complete collection of articles that cover fields

of computer science and information technology: and,

lastly, PubMed featuring biomedical and life science

literature. The search string defined to retrieve the

articles from the mentioned libraries is: (Disability

OR Handicap) AND (Internet of Things OR IoT). In

order to obtain a more significant number of existing

solutions and to be able to evaluate them later, it will

be carried out according to the methodology of

Kitchenham (B. Kitchenham, 2007), which proposes

that the search be performed considering

coincidences in the title, abstract and keywords and if

the library allows it in the complete text. This string

will be adapted to each digital library.

For this systematic review, all scientific articles

were considered regardless of their year of

publication, this for two reasons, on the one hand, IoT

technology is emerging and, on the other, being an

exploratory study, it seeks to find the development

milestone of IoT suitable for disabilities.

Additionally, the journals were the manual search

was performed were Disability and Rehabilitation:

Assistive Technology Journal (Q2), Technology and

Disability (Q4), for the conferences the selected ones

were VAAT, i-CREATe, W4A'18 and ICSC . They

provide relevant studies on technology and

disabilities. This search was performed to

complement the automated search to cover the cases

in which the conference proceedings or journals did

not appear in the digital libraries.

3.1.3 Extraction Criteria

This strategy will attempt to answer each sub-

question raised in the research. The strategy will

ensure that data extraction criteria are met and will

also facilitate classification. The complete list of

extraction criteria is presented in Table A at the

following URL: https://n9.cl/dis3.

Selection of Primary Studies. The articles must go

through a selection process, there they will be

evaluated by different established inclusion and

exclusion criteria. All the excluded articles will be

considered to verify the inclusion and exclusion

criteria among the research group's people.

Inclusion criteria: Studies that meet any of the

following criteria will be included in the research:

• Studies dealing with related topics on the Internet

of Things for health intervention to people with

any disability.

• Studies containing Internet of Things technology

architectures and solutions for people with

disabilities.

Exclusion criteria: The articles that will not be

considered in this study are:

• Articles dealing with disability and technology

but not oriented to the Internet of Things.

• Duplicate studies, in which case the complete

study will be chosen.

• Short papers (less than five pages)

• Studies that are written in a different language

than English.

Quality Assessment. Two aspects have been

considered to evaluate each study's quality: i) The

relevance of the conference or journal in which the

article is published. In this case, the articles have been

classified into three categories, as shown in the web

annex, Table B. ii) The number of citations the article

has. The classification is also done in 3 categories:

high, medium, and low. Citations are considered,

according to Google's academic citation count. To not

penalize potentially useful papers, they have been

classified according to the year, as shown in the web

annex on Table C and Table D. The URL to access

the web annex is: https://n9.cl/dis3.

3.2 Conducting the Review

Preliminary results are presented in Fig 1. Selected

studies were chosen after applying the inclusion and

exclusion criteria. In total, 104 articles were obtained,

of which 19 were selected. Of these, 12 are from

IEEEXplore, four from PubMed, two from ACM, and

one from manual search.

3.2.1 Methods of Analysis and Synthesis

The analysis methods and synthesis show the

systematic review results; the statistical tables show

individual results of each criterion concerning the

number of studies that speak or are related to that

subject, which can be seen in this link:

ICT4AWE 2021 - 7th International Conference on Information and Communication Technologies for Ageing Well and e-Health

230

https://n9.cl/g82cj. The bubbles presented on Fig. 2

and Fig. 3 are generalized results.

Synthesis and Results. Results are presented in Fig.2

and Fig. 3. These figures are represented by a pair of

coordinates (X, Y). Fig. 2 shows the axis of the

ordinates represented by EC3: Population, in the axis

of the abscissa, is represented by EC 7: Use of IoT.

Then in Fig.3. EC1 represents ordinates axis: Type of

disability, and EC7: Use of IoT; besides, on the axis

of the abscissa EC5: Hardware or devices and EC6:

Software.

Figure 1: Found papers.

Discussion Criteria per Criteria.

EC1. Type of Disability. Most of the solutions are

aimed at people with physical or motor disabilities.

Some of them combine with mental or cognitive

rehabilitation systems (Alapetite & Hansen, 2017;

Brik et al., 2018; Iyswariya et al., 2020; Li et al.,

2019). Others emphasize their intervention in

disabilities associated with speech difficulties; for

example, Malavasi et al. (2017) developed low-cost

experimental systems for environmental control

through simplified and accessible user interfaces, and

many of the activities focus on automatic speech

recognition.

While others develop solutions aimed at people

with visual disabilities, for example, combine the

benefits of the IoT and existing devices such as mobile

phones, Husing & Lim (2020) proposed a system

called InWalker to extend the typical white cane's

functionality. They introduced several new features

that improve security and trust among blind people.

Finally, other solutions are geared towards

rehabilitation, either at home (Agyeman et al., 2019;

Agyeman & Al-Mahmood, 2019) or in clinical

environments (Errobidart et al., 2017; G. Postolache

et al., 2019).

EC2. Degree of Disability. Regarding the degree of

disability, it was found that very few solutions

precisely specify this attribute of the population. Two

of the nineteen articles indicate that the IoT devices

they present are aimed at people with moderate

disabilities. Errobidart et al. (2017) offer a prototype

that has been installed in a Public Rehabilitation

Center. Moreover, Bissoli et al. (2019) point out

instead that people with motor disabilities can be

supported by employing an eye-tracking solution so

that they can control and monitor a smart home;

which has a positive effect on their independence;

particularly this type of solution is suitable for this

degree of disability as it involves the constant need

for supervision.

Figure 2: Comparison between EC3: Population and EC7:

Use of IoT.

EC3. Age Group. The majority of the research

involved in this systematic review is not directed at a

specific population group. Aljahdali et al. (2018)

directed their study to older adults, in which designed

a smart walking assist device for frail and visually

impaired people to reduce the risk of falls and costly

emergency interventions and hospitalizations; the

proposed device is based on the Internet of Things

(IoT) concept to determine and communicate the

location and path of the person for possible action in

emergencies.

Although the study found that the IoT device is

aimed at older adults who require particular care, the

IoT principle can be used to help the same age group

in their daily activities, not necessarily in

emergencies. For example, with reminder services,

such as taking medicine, turning off the kitchen,

closing the window when leaving the apartment,

location coordinates of things and people. Other types

of monitoring services, such as chronic disease status;

PubMed

IEEE

Searching res ults : (+66)

Manual searching (+38)

104

Filtering by inclusion and exclusion

criterio (-83)

Filtering by full-text

scanning (-2)

Primary studies

ACM

Children

Adolescents

Adults

Older adults

General public

Treatment/

Rehabilitation

Assistive

device

Others

EC3. Population

EC7. Use of IoT

Systematic Literature Review of Internet of Things Solutions Oriented to People with Physical and Intellectual Disabilities

231

Figure 3: Comparison between EC1: Type of disability, EC5: Hardware or devices, and EC6: Software.

or social services, help maintain contact with other

people (Sharma et al., 2013).

Other studies propose solutions-oriented to adults

(Li et al., 2019; Postolache et al., 2020). Li et al.

(2019) propose Riobot, a design tool for generating

mechanisms that can connect, motorize, and actuate

static objects to perform simple physical tasks; users

only need to take a short video to manipulate an object

to demonstrate intended physical behavior.

Furthermore, Postolache et al. (2020) develop an

IoT device whose objective is to monitor physical

rehabilitation. It combines strategies of serious games

of virtual reality and wearable sensor network to

improve the patient's commitment during physical

rehabilitation and evaluate its evolution.

EC4. Type of Solution. In this extraction criteria, it

can be seen that it is essential to have software to

manage the IoT hardware. That is why all the selected

roles have coincided in the same.

EC5. Hardware or Devices. In this extraction

criteria, it is showed that most of the solutions have

been oriented to the use of smart devices (Agyeman

et al., 2019; Agyeman & Al-Mahmood, 2019;

Alapetite & Hansen, 2017; Aljahdali et al., 2018;

Amiri et al., 2017; Hung et al., 2019; Husin & Lim,

2020; Iyswariya et al., 2020; Mulfari et al., 2014; O.

Postolache et al., 2020; Ranjan et al., 2020; Singh et

al., 2015).

Alapetite & Hansen (2017) develop devices that

can interact with the user through voice and gaze

recognition. Other solutions implement wearable

technologies with game aids to rehabilitate people

with disabilities in the upper extremities (Agyeman &

Al-Mahmood, 2019; G. Postolache et al., 2019). Also,

daily use objects oriented to people with disabilities

has been presented. An example is a smart walking

device that helps users walk by themselves (Aljahdali

et al., 2018).

The hardware technology that is also widely

applied for people with disabilities is home

automation, which allows users to function efficiently

in their daily activities (Bissoli et al., 2019; Brik et al.,

2018; Errobidart et al., 2017; Li et al., 2019; Malavasi

et al., 2017; Singh et al., 2015).

Finally, the use of biosensors is a rarely used

hardware technology, since, as can be seen in the

research carried out, only 3 of the studies are focused

on its use (Grigoriadis et al., 2016; G. Postolache et

al., 2019).

EC6. Software. Regarding the software, in general,

IoT is composed of monitoring systems (Alapetite

& Hansen, 2017; Aljahdali et al., 2018; Brik et al.,

2018; Errobidart et al., 2017; Grigoriadis et al., 2016;

Hung et al., 2019; Mulfari et al., 2014; G. Postolache

et al., 2019; Singh et al., 2015). This reality is

understandable because biosensors, home

automation, and smart devices generate information

that needs to be operated from a specific system.

Other articles refer to the use of serious games to

treat certain types of disabilities (Agyeman et al.,

2019; Agyeman & Al-Mahmood, 2019; O.

Postolache et al., 2020).

EC7. Use of the IoT. In this extraction criteria, it is

presented that most of the IoT solutions are used as

assistive devices. The vast majority of which belong

to home automation solutions and smart devices

Vis ual

Motora

Speech

disability

Co gnitive/

intellectual

Unspecific

disability

Treatment/

Rehabilitation

Assistive

device

Others

Domotic

Smart devices

Bio-sensorsProsthesis

Monitoring

Systems

Augmented

Reality

Serious

games

EC1. Type of disability

EC5. Hardware or devices EC6. Software

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(Alapetite & Hansen, 2017; Aljahdali et al., 2018;

Bissoli et al., 2019; Brik et al., 2018; Chand et al.,

2019; Errobidart et al., 2017; Husin & Lim, 2020;

Iyswariya et al., 2020; Malavasi et al., 2017; Mulfari

et al., 2014; Singh et al., 2015). Moreover, some

solutions are oriented to the use of devices for

treatment and rehabilitation (Agyeman & Al-

Mahmood, 2019; Agyeman et al., 2019; Amiri et al.,

2017; Grigoriadis et al., 2016; Hung et al., 2019a; G.

Postolache et al., 2019), and, finally, one of the

articles was classified as "other", it is because it is a

device that allows generating IoT devices for people

with disabilities (Li et al., 2019).

EC8. Phase(s) in Which the Studies are based. In

the case of the phases of the studies analyzed, the vast

majority have gone through the analysis, design, and

implementation, but very few have been able to be

tested. Some of the articles whose implementation

has been tested are those that include home

automation solutions or use smart devices (Amiri et

al., 2017; Bissoli et al., 2019; Errobidart et al., 2017;

Husin & Lim, 2020; Iyswariya et al., 2020; Li et al.,

2019; O. Postolache et al., 2020).

EC9. Type of Validation. As for the type of

validation, the vast majority have used prototypes, the

same ranging from domotics houses to automate and

facilitate access to certain features of the houses

(Bissoli et al., 2019; Errobidart et al., 2017; Li et al.,

2019) to prototypes that include the development of

smart devices (Agyeman et al., 2019; Agyeman & Al-

Mahmood, 2019; Alapetite & Hansen, 2017;

Aljahdali et al., 2018; Amiri et al., 2017; Husin &

Lim, 2020; Iyswariya et al., 2020; Mulfari et al.,

2014; O. Postolache et al., 2020; Ranjan et al., 2020).

Into this minority, the revised articles have been

written to deepen the concepts or develop

experiments.

EC10. Approach Scope. Even though IoT devices

are of great interest to the industry, such as hospitals

or are designed for direct users; most of the articles

that are part of this work are oriented to the academy

This be due to the fact that being emerging

technologies, they are not yet in commercial

distribution; or, failing that, it is still exclusive for

particular sectors, as is the case of smart bulbs by

Philips (2020).

Moreover, the solution presented by Grigoriadis

et al. (2016) shows an IoT solution-oriented to people

diagnosed with multiple sclerosis.

EC11. Methodology. Of the 19 articles reviewed,

only one paper is the extension of previous research.

Malavasi et al. (2017) develop a solution that is the

continuation of an existing project called cloudCAST

(Clinical Applications of Speech Technology); the

authors present the development of low-cost

experimental systems through the use of automatic

speech recognition systems, while the other articles

reviewed propose their methodologies starting from

the design and architecture of their solutions.

EC12. Area of Study. The articles that were part of

this systematic review belong to computing and

electronics, and they complement the developments

with extensive knowledge of the health area,

particularly medicine.

EC13. Country. The demographic results show that

most studies were originated in India. Iraq, Italy,

Portugal, and the USA. Latin American countries like

Argentina and Brazil also presents solutions. In this

context, this study provides insights into the

relationship between a country and the use and study

of IoT technology-oriented to people with disability.

EC14. Year. The studies reviewed are on the time

range from 2014 to 2020. After it, the year 2014

represents a milestone for developing these devices;

this article presents the use of integrated systems for

multiple devices in intelligent environments that

allow care and support to people with disabilities

(Mulfari et al., 2014).

4 CONCLUSIONS AND FURTHER

WORK

In this study, the systematic review of the literature

on IoT solutions for people with disabilities was

presented. It was developed based on the Kitchenham

methodology; and, three sub-research questions were

raised, which allow to answer the question of What

Internet of Things solutions exist for people with

disabilities?

Among the results, we can highlight that all the

solutions found include hardware and software

together. Similarly, researchers have focused on the

development of home automation solutions to

provide greater accessibility to the various elements

that homes have. In addition, smart devices have also

been developed to make life activities easier for

people with specific disabilities, such as mobility or

reduced visibility.

The use of IoT technology in treatment and

rehabilitation is essential, since this has been

achieved by implementing smart devices and

biosensors in order to obtain more effective results;

primary studies have relevant information. However,

Systematic Literature Review of Internet of Things Solutions Oriented to People with Physical and Intellectual Disabilities

233

in an extended version of the article, new extraction

criteria must be added to better segment the results,

such as the term disability, which can be treated as

limitations in carrying out activities or restrictions on

participation in normal environments; All this so that

the information can be classified in a formal

taxonomy so that health professionals can use it, so it

is necessary to complete these activities in later work.

ACKNOWLEDGEMENTS

This work is part of the research project: “Design of

architectures and interaction models for assisted

living environments aimed at older adults. Case

study: playful and social environments” Therefore,

we thank DIUC of Universidad de Cuenca for its

support.

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