Adaptive Augmented Reality in Mobile Applications for Helping People

with Mild Intellectual Disability in Ecuador

Maritzol Tenemaza

, Ang´elica de Antonio

, Jaime Ram´ırez

, Armando Vela

and Diego Rosero

Departamento de Inform´atica y Ciencias de la Computaci´on, Escuela Polit´ecnica Nacional, Quito, Ecuador

Lenguajes y Sistemas Informticos, Universidad Polit´ecnica de Madrid, 28660, Madrid, Spain

Keywords:

R, Maps, Helping People, Mobile Computing, Return Home, Monitoring.

Abstract:

Adaptive Augmented Reality (A

R) is an emerging technology that can support users in their daily life with

useful information for their activities, which are really adapted to the user’s characteristics, as well as the

environment and the context where the activities are taking place. In Ecuador, mild intellectual disability is

being considered as part of the government policies, for this reason we considered developing an app to help

locate people with mild intellectual disability who at one time may feel lost and may not know how to return

home. So the app allows caregivers to always know where their dependents are every time. We adopted A

approach for developing this app so we had to model both user needs and their interests. Apart from User

Model, we will also show the other A

R models required.

1 INTRODUCTION

The last census was held in Ecuador in 2010. Accord-

ing to its forecasts, the life expectancy of the popula-

tion in Ecuador has been growing, and it is expected

that in 2050 it will be 80.5 years old on average

, a

little higher for women, with 83.5 years, compared to

77.6 years for men.

”The range of possible intellectual disability,

based on both intellectual and social criteria, is com-

monly divided into four levels: mild, moderate, severe

and profound. The level of intellectual disability is the

main factor that determines the degree of outside as-

sistance the person with intellectual disability needs

to live a comfortable and productive life”.

As can be seen in table 1, in Ecuador, people with

intellectual disabilities according to census of INEC,

2010

were 192.496, an 1,33% in relation to the total

number of 14.483.499 Ecuadorians.

In addition, table 2 outlines the population belong-

ing to each level of disability in 2010. As can be

observed, the largest group of people with intellec-

http://www.inec.gob.ec/proyecciones poblacionales/

presentacion.pdf

https://www.dads.state.tx.us/news info/publications/

brochures/intellecutaldisabilitybrochure.html

http://www.inec.gob.ec/cpv/index.php?option=com

content&view=article&id=232&Itemid=128&lang=es

Table 1: People with intellectual disabilities in 2010.

Source: Census of INEC 2010.

People Number of

People

Percentage

With intellectual

disabilities

192496 1,33 %

Without intellec-

tual disabilities

14291003 98,67%

Total 14483499 100%

Table 2: People with intellectual disabilities in 2010.

Source: Census of INEC 2010.

Type of intellec-

tual disability

People Percentage

Mild intellectual

disability

163622 85 %

Moderate intel-

lectual disabili-

ties

19250 10%

Severe intellec-

tual Disability

7700 4%

Profound Intel-

lectual Disability

1925 1%

Total 192496 100%

tual disabilities corresponds to that of mild intellec-

tual disabilities.

Considering these data, and observing the projec-

Tenemaza, M., Antonio, A., Ramírez, J., Vela, A. and Rosero, D.

Adaptive Augmented Reality in Mobile Applications for Helping People with Mild Intellectual Disability in Ecuador.

In Proceedings of the 12th International Conference on Web Information Systems and Technologies (WEBIST 2016) - Volume 2, pages 317-324

ISBN: 978-989-758-186-1

317

tion in life expectancy of Ecuadorian population pre-

sented before, we believe that our country will face

an increasing number of population with mild intel-

lectual disabilities in the coming years. This paper

describes a project that aims at improving the qual-

ity of life of people with mild intellectual disability in

Ecuador.

Nowadays, mobile and ubiquitous computing,

supported by tools such as maps and augmented real-

ity can enhance the traditional ways in which disabled

people and their caregivers cope with their situation.

Adaptive Augmented Reality (A

R) is an emer-

gent technology that offers users new possibilities to

interact with their environment. This kind of systems

gives answers to the user’s needs and interests in a

particular context in real time. A

R provides the abil-

ity to create applications that help disabled people be-

cause these systems present useful information over-

lapping reality which can be adjusted to their interests

and individual characteristics (Vera et al., 2014).

In this paper, it is presented the development of

an app, which is an ubiquitous and mobile applica-

tion that allows dependents to come back home and

allows caregivers to always know where their depen-

dents are. The application monitors the location of

person with mild intellectual disabilities and allows

caregivers to be informed.

We are particularly interested in the adaptibility

of augmented reality. In this project we study what

happens when an augmented reality app is used by

elderly people. Consequently this app is developed

observing this group. A research question has been

raised: What will happen when augmented reality is

used by elderly people?

The paper is organized as follows. Section II

introduces all characteristics of the implementation

based on the android mobile platform. In Section III a

usability analysis is presented and ﬁnally, Section IV

provides conclusions.“

2 APP DEVELOPMENT

”Mobile Return” is an app designed to comply with

the following objectives:

1. Allow one or more caregivers to know where the

dependent is.

2. Help people with mild intellectual disabilities to

return to their homes.

The design of an application with user adapted in-

teraction should be driven by the following sources of

knowledge (Fischer, 2001):

• knowledge about the communication agent. For

a simple deﬁnition of the users we deﬁne stereo-

types. For this app, there are two types of users:

– Caregivers: they know how to use a computing

device such as computer,phone, watch or other,

and they are interested in being informed about

the whereabouts of the people they care.

– Dependents: they are not required to have pre-

vious knowledge of the use of a computer, only

being required to have and wear a mobile de-

vice.

• Knowledge about the problem domain: for this

app we consider that:

– The user can move within the area of a circle

around a safe place. This radius is variable and

can be adjusted.

– The return route to the safe place will depend

on the sites known by the dependent.

– The dependent may have more than one care-

giver. Each of them has a priority for alerts.

– The caregivers will deﬁne both the radius of the

permitted area as well as the places known by

the dependent or user.

• Knowledge about communication process: the

way in which the information structures that con-

trol communication is accessible and changeable

by the user. In this application:

– The user interface comprises two alternatives

views: Map and Augmented Reality. In both

views the return path is shown.

– The moment in which a dependent leaves

the permissible area, the system should warn

his/her caregivers by sending a message with

the information on where the dependent is.

– The caregiver can see where the person is

through any device such as tablet, computer or

smart phone.

2.1 Architecture

Considering both the objectives of the app and its re-

strictions, the ﬁrst step is to deﬁne its architectural

model. We applied the MVC

pattern as it is pre-

sented in ﬁgure 1.

The components of the MVC pattern in this app

are the following:

• View, as the user’s position continuously changes,

the user interface logic needs to update frequently

the visualized return route and the visualized lo-

cation of the user. This information is presented

Model View Controller

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318

Figure 1: MVC design pattern for app ”Mobile Return”.

both in the map view and in the augmented reality

view. The GPS needs to be activated in the depen-

dent’s device in order to track the user’s location.

Normally, the GPS allows to know the position

of the user with a possible error of some meters

(Van Diggelen, 2009).

• Controller, it manages user’s eventsand sends raw

data to the model for analysis. It also collects the

information provided by caregivers and sends it to

the model. In addition, it receives the information

required to update the view from the model.

• Model, it comprises the business logic and the

data model. Every time the app receives from the

GPS a new position of the user, it works out the

return route. On the other hand, if the user gets

out of the allowed radius, the app warns the care-

givers and sends messages with the information

required to locate the dependent. This component

implements the following models: User, Adapta-

tion, Context, Interaction, Content and Environ-

ment.

A further decomposition of the MVC components can

be found in ﬁgure 2. Modules or libraries with spe-

ciﬁc features were designed so that they can be reused

in subsequent projects.

2.2 Models Proposed for the A

R app

Besides the architecture, the proposal for A

R mod-

els extends previous works in web applications

(Brusilovsky, 2001), (Brusilovsky and Mill´an, 2007),

(Heckmann, 2006) with information that becomes

relevant when considering A

R systems (Tenemaza

et al., 2015b), (Tenemaza et al., 2015a). Here a de-

scription of each model proposed is described.

• User Model. In terms of the personal and cogni-

tive data represented, the user model is similar to

that of web systems. However, the user model in

R can go far beyond, because the user’s phys-

ical features (for example their stride length or

walking mean velocity) and behaviour (for exam-

ple their walking route) can also be taken into ac-

count and analysed in real-time.

In this app, the User Model also included user

interests, represented as the important places for

the user, such as his/her home, and familiar land-

marks.

• Context Model. This model represents a snap-

shot taken from the situation in which a user is

using the system. It is different from a traditional

context model because it takes into account the

real environment.

In this App, the Context Model observes the cur-

rent user position with respect to his/her home,

considering whether the user came out of the al-

lowed area within a speciﬁed range. This infor-

mation is obtained from the GPS and compass.

• Interaction Model. This model represents the

evolution of the user-system-environment interac-

tion. What distinguishes it from the context model

is that the context is an instant snapshot, while the

interaction model registers the history of interac-

tions and the evolution in the context. It serves as

a data source for enriching the user’s model.

In this app, the Interaction Model registers the

trajectory that the user has followed. Based on

this information, it is possible to infer patterns of

movement of the user. This data will be useful to

update the user model with new places known by

the user.

• Environment Model. This model represents at-

tributes of objects, persons, places, and all other

aspects related to the real physical environment in

which the user utilizes the system. In this app, the

Environment Model takes from Google Cloud the

names of streets, buildings, parks, special places.

• Content Model, speciﬁc information about each

place that can be displayed to the user in the maps

and A2R.

• Adaptation Model. The system should adapt

content, navigation and presentation. The pro-

posed model deﬁnes how to adapt output data

coming from the content model taking into ac-

count interests and other user’s characteristics

represented in the user model. Moreover, it will

consider deﬁned restrictions in the environmental

model and, if necessary, data from the interaction

model. Also, the adaptation should take into con-

sideration the current context. The resulting in-

formation should be presented in a user-friendly,

multimodal form, without forgetting the impor-

tance of the human-computer interface, both for

mobile phones and other A

R devices (Heufe-

mann et al., 2013).

Adaptive Augmented Reality in Mobile Applications for Helping People with Mild Intellectual Disability in Ecuador

319

Figure 2: Architecture for app ”Mobile Return”.

2.3 Analysis the User’s Departure

Allowed Area

Models and architecture must be complemented with

control algorithms. the algorithm analyzes the area of

motion enabled user. It receives the distance of user’s

home to the current position of user, This distance is

calculated by the formule of Haversine

. This for-

mule deﬁne the distance between two points in the

terrestrial surface by using latitude and longitude.

If the distance calculated from position of device

is greater than the area of movement allowed, the app

sends alerts through messages and calls Caregivers.

The distance is calculated at the moment updates

GPS updates, then compares with the radius of move-

ment allowed.

This method sends messages and calls to the care-

givers.

2.4 Analysis of Adaptive Augmented

Reality

To complement the information required for the de-

velopment of this type of app. The use of augmented

http://www.genbetadev.com/cnet/como-calcular-la-

distancia-entre-dos-puntos-geograﬁcos-en-c-formula-de-

haversine

reality as another interface is proposed. We used Be-

yondAr and objects of augmented Reality. These ob-

jects were designed in an activity.xml as observed in

Figure 2.

In the Augmented Reality a compass, the reality

and information of each places known are shown.

The objective of augmented Reality is to offer the

user an other option to return home. The user needs to

observe the compass to see the orientation in the cam-

era. In order to recognize each of the deﬁned sites.

The adaptability was observed in the deﬁnition of

the route because the user will see a route according

to the places known. The calculation of the path is

not a straight line. The current position of the user is

analysed by the route deﬁning.

Although, the GPS tracker only works outdoors.

The GPS tracker used determines the position and

orientation of the user. Aditionally, the position data

consists of two-dimensional coordinates (the altitudi-

nal measurement is very imprecise) and an orientation

angle from a magnetic compass (Reicher et al., 2004).

This information and the position of sites Known are

sent to the module of Augmented Reality.

2.5 Results

Once we have analised how the app was built. Anal-

ysis of results is presented. The app runs in a context

WEBIST 2016 - 12th International Conference on Web Information Systems and Technologies

320

of veriﬁcation of acceptance criteria speciﬁed by each

user. This speciﬁcations were deﬁned in the user sto-

ries in the Product backlog in our agil Methodology

for developing this app. Two situations are described:

1. Data input to initialise the application. There are

three groups of data:

• Personal data of Caregiver and data of user.

This app gets the data of caregiver directly of

the phone that he will use, or, if he does not

have register his information in his device, It

will be necessary to write this information.

• Other information that the caregiver needs to

records is the places known by the user. this

information can be recorded directly from the

map. In this operation, the app captures the

longitude and latitude of each place choosen,

Observed in Figure 3.

• The Caregiver needs to register the radius. It

speciﬁes the area move allowed. The origin

point for this radius is the user’s home. It is

observed in Figure 3, 6.

2. App care to the user:

• When the user comes out of allowed area, the

caregiver will receive calls and messages. The

message contains a URL with the position of

the person. The position can be viewed by us-

ing a web browser or the Google maps applica-

tion of this device. To observed in Figures 4,

• Return path. The user can see the return path

both on the map and augmented reality, it may

be observed in Figure 7. The return path for the

observed person, considers the known points by

the user.

• Augmented Reality The user has of other op-

tion for return his home. Known places are

shown and the distance to your home is speci-

ﬁed through Augmented reality. This result are

show in the Figure 8.

3 USABILITY ANALISYS

Once the results were presented, it is necessary to

consider the usability of the application, as this is one

of the main quality characteristics of a system and the

one more closely related to the acceptability of the

system. Analysing usability required measuring ef-

fectiveness (completion task, number of errors), ef-

ﬁciency (time taken to complete the task), satisfac-

tion (users’s, rating of experiencies) and learnability

Figure 3: Conﬁguration App.

Figure 4: Emergency message received by managers.

(amount of instruction/study required). A success-

ful design requires a balancing of all the different

aspects (usability, functionality, aesthetics etc) (Ian

et al., 2011).

For the usability evaluation, the sample taken was

10 elderly people. After interaction with the app they

and their caregivers answered a questionnaire. Figure

9 summarizes the results.

The questions applied to the users are listed below

in the Tables 3, 4.

For the conception, planning and implementation

of this system it was necessary to take into account

both people with mild mental disabilities and Care-

Adaptive Augmented Reality in Mobile Applications for Helping People with Mild Intellectual Disability in Ecuador

321

Table 3: User survey.

Question number Question

1 The application works correctly? (Yes/not)

2 The app works as expected? (Yes/not)

3 The route back to your home is understood on the map? (yes/not)

4 You needed assistance to use the system? (Yes/not)

5 Augmented Reality seems useful ? (Yes/not)

6 Would you recommend this application? (Yes/not)

7 The map application helps to return to your place of residence when you

doubted about its location? (Yes/not)

8 Additional comments about the application

Table 4: Responsible survey.

Question number Question

1 You received SMS notiﬁcations that were sent by the app? (Yes/not)

2 When the notiﬁcation was received, it was easy to identify on your mo-

bile device the person’s location?

3 The app presents any malfunction in the user’s device of which you are

a caregiver? (Yes/not)

4 The app works as expected? (yes/not)

5 Did you have difﬁculties learning this app? (Yes/not)

6 In the conﬁguration of the application, what was the biggest difﬁculty

you had (enter user data; enter caregiver data; enter the radius of move-

ment; select the home site on the map; select known sites on the map;

data entry interval alerts)?

7 You required assistance to use the system? (Yes/not)

8 The media used to communicate that a user requires help were clear?

(Yes/not)

9 Would you recommend this application? (Yes/not)

10 Does this application help to communicate easily with caregivers at the

time of alert? (Yes/not)

11 Additional comments about the application

givers. We proposed two complementary interfaces,

the Map and the Adaptive Augmented reality, which

were useful for both caregivers and users.

The system was well received by the caregivers,

with a 82.5% of positive responses, while the accep-

tance rate of elderly users is 81% (Eden, 2005).

The interface for caregivers was found to be easy

to learn and use, and it did not require typing a lot

of data. The caregivers had two interfaces to enter

information. The personal information is registered

from the phone and the information of sites known

by the dependent is obtained from the map. The app

was very effective to send messages to and call the

caregivers, and caregiverscould easily ﬁnd the depen-

dents.

The dependents did not have to write any data. But

for these people, it was more difﬁcult to understand

the maps and the augmented reality, specially the

compass. Learning to use the app required more time

because many dependents did not use smartphones.

Some dependents forgot to activate their GPS. This

was the principal error. When the caregiver set the

GPS for them, the system worked very well. Other

error was related to the Internet connection. This app

needs both for normal functionning.

The return path on the map is clearly marked with

a color for easy identiﬁcation and it is updated as the

user moves in both deployment environments. Care-

givers were very quickly interpreting the information,

while the dependents had more difﬁculty to return

home with only the maps and the augmented reality.

Regarding user satisfaction, the app was found

very pleasant for the caregivers and less pleasant for

the dependents. 100% of the caregivers claim they

would use it, while 83% of dependents are satisﬁed

with the application.

Globaly, the results show that the application

meets the expectations.

WEBIST 2016 - 12th International Conference on Web Information Systems and Technologies

322

Figure 5: Emergency call received by Caregivers.

Figure 6: Area allowed.

4 CONCLUSIONS

An app was designed for people with mild intellec-

tual disabilities in Ecuador. The government policies

in Ecuador are giving priority to elderly and disabled

people, and this application is a step forward in this

direction.

Usability in these systems is a key point both for

entering data and displaying information for the user.

Data entry, if any, should be easy and simple, and the

display of results should be clear and adjusted to this

Figure 7: Return path.

Figure 8: Augmented Reality.

type of users. Augmented Reality has proved to be a

useful alternative to provide information, but elderly

and disabled people need to get familiar with this new

technology.

Based on our results, we have conﬁrmed that the

interaction model is very useful to identify potential

routes preferred by the user. Based on this informa-

tion we can get to know the movement patterns of the

user in order to help locate users.

For the future, we will complete the implementation

of the Mobile Return app considering further analysis

of user interests and behavior patterns.

Adaptive Augmented Reality in Mobile Applications for Helping People with Mild Intellectual Disability in Ecuador

323

Figure 9: Results of processing the survey.

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