Towards Ambient Intelligence for the Ageing Citizens
Julia Kantorovitch
, Jouni Kaartinen
, Luis Collantes Abril
, Ricardo de las Heras Martín
José Alberto Martínez Cantera
, Johan Criel
and Marcel Gielen
VTT, Vuorimiehentie 3, 02044 Espoo, Finland
Indra, 28223 Pozuelo de Alarcón (Madrid), Spain
Telefonica I+D, 47151 Valladolid, Spain
ROBOTIKER-Tecnalia,Parque Tecnológico de Bizkaia, edif. 202, E-48170, Zamudio, Spain
Alcatel-Lucent, Copernicuslaan 50 2018 Antwerpen, Belgium
Mextal the technology company 5674TB Nuenen, The Netherlands
Keywords: Ambient Intelligence, elderly, home environment, assistance, adaptive interaction.
Abstract: This research presents a system, currently under development, which aims at providing an intelligent
ambient able to improve the quality of life and delivering customized support to elderly people in need of
assistance, according to their own specific situation, and in a non-intrusive and respectful way.
Celebrating a 100
birthday is a privilege only
reserved for a happy few. However through modern
technology and medical progress, these ‘few’ have
grown to a bigger group than ever before. People
older than 64 in the euro area are about 18% of the
total population in 2005 and it’s supposed to grow
up to 30% by 2050 (Eurostat Yearbook, 2008). Thus
this situation has favoured the need to exploit
technologies that address the issues posed by
demographic ageing and trying to decrease the costs
of health-care systems because so far it seems very
high. Technologies that can support independent
living at home rather than being institutionalized are
envisaged as one of the main solutions for a
significant reduction of health-care costs.
The research described in this paper has
addressed these needs developing a comprehensive
reliable adaptive distributed service system that can
serve multiple categories of elderly people, assisting
them in their everyday life, helping them to stay
independently at home as long as possible and
moreover, increasing their comfort and safety and
social wellbeing. In following, the related research
addressing aging citizen’s needs (with position of
our research in the field) are discussed in chapter 2.
The intelligent distributed service system and
targeted applications are presented in Chapter 3.
Market opportunities are discussed in Chapter 4.
Finally, Chapter 5 concludes the paper identifying
further R&D challenges still faced by researchers.
The use of information technologies for assisting
people with medical needs and for enabling ageing
citizens to manage their well-being and safety has
been considered in the recent past. Various existing
initiatives can be divided in four big groups:
Domotics and sensor networks
Video telephony and iTV
With the rise of more advanced robots, their
usage for elderly care has increased slowly. In many
of the projects however, the robots, which were
created for a more generally purpose, are being
reused for the elderly (Shinozaki et al., 2005), which
may cause the problem. The main advantages are
that a robot can give the elderly an immediate
feedback on his or her actions, reacting on the spot
of external stimuli. Furthermore, a robot can also be
used to execute physical work of which the elderly is
Kantorovitch J., Kaartinen J., Abril L., Martín R., Cantera J., Criel J. and Gielen M. (2009).
AmIE - Towards Ambient Intelligence for the Ageing Citizens.
In Proceedings of the International Conference on Health Informatics, pages 421-424
DOI: 10.5220/0001433404210424
not capable anymore. On the other hand, robots can
not replace human touch in everyday life assistance.
PERS (Personal Emergency Response Services)
are the best-known elderly assistance systems at the
moment (Porteus and Brownsell, 2000, Kenchiku,
2005). The system acts as an emergency button for
elderly to press when they are in trouble. Also more
automated solutions with activity monitoring
features are available. The great advantage of the
PERS systems is that they are a relatively easy to
deploy as use.
Domotics and sensor networks have started its
uptake about a decade ago (Fellbaum and Hampicke,
2002, Van Berlo and Fellbaum, 1999., Van Berlo,
2005, MOBILALARM, 2005), but because of its
high purchase price only recently more and more
elderly homes are including it in their buildings. One
example is the Besta-flats in Norway. But domotics,
as some robots, are made for a broader public and
only later repurposed for the elderly. However they
also offer big advantages: they are passive and non-
intrusive technologies which make them very
comfortable and safe for the elderly.
iTV (interactive Television) was originally
represented as a means of linking individuals
together by providing each with an electronically
mediated representation of the other’s voice and
visual presence (Wellens, 1979), providing a way of
deploying video telephony service. This type of user
interaction based on “social television” concept, is
nowadays being exploited into many other different
new services for all the inhabitants at home, thanks
to the development of the Internet, broadband
communications and specific devices such as STBs
(Set-Top-Boxes) and mobile phones.
Obviously, four groups are complementary,
meaning that only a combination of technologies
could be positive and really profitable for the
elderly. Moreover, through these complementarities
and their own progresses, these technologies and
services for users at home seem to trend to a
seamless integration. For example, some domotic
systems include teleassistance service (PERS) -even
a step ahead with a telemedicine service-, and can be
controlled by a TV set with a remote control or even
a touch screen. Thus presented research, referred
here as AmIE (AmIE, 2008), tries to observe the
best practices from technologies discussed above,
emphasising unique features of non-intrusiveness
and versatile adaptability of the offered services.
The main building blocks of AmIE service system
are presented in Fig.1. The heart of the systems is
the Intelligent Rule Engine. The AmIE system
operation is based on the rules which are defined by
means of interactions with health care professionals.
Rules define when and how to provide help,
compensate some behaviours, uplift the person, keep
track of the behaviour and send alarm signals. The
system also monitors vital parameters such as
pulsioximetry, electrocardiography, temperature,
blood pressure, heart rhythm, breathing and glucose
level. In this case rules enable the system to
understand for example when those medical
parameters are low or high and consequently
generate an alarm, when and how the system should
interact with the user in case of behavioural
disturbances, emotional or memory problems and to
support the user during activities of daily living.
Figure 1: AmIE service system – building blocks.
An environment equipped with an infrastructure
of sensors and actuators, including body sensors,
medical devices, domotics equipment, RFID tags, as
well as sensors of various kinds (temperature,
humidity, pressure, movement and presence
detectors, etc.) monitors what happens in the space
and collects data of various kinds and log
behaviours. Data collected by the sensors are
processed, interpreted, stored, correlated, and
ultimately mapped into decisions and decision rules.
AmIE will be able to discover hidden information
applying Data Mining techniques over collected
data, identifying, in some cases, patterns and
correlations between these data that could reveal
trends and future users’ behaviour, making in this
HEALTHINF 2009 - International Conference on Health Informatics
way predictions based in the medical and
behavioural history of each user. Key components of
service system are context-awareness and databases
whose task is to digest all the raw data and to learn
and act based upon it. Such system intelligence is
partly centralized (i.e. home server) and partly
The adaptive system intelligence enabled by
innovative developments and technologies in the
domain of sensors data fusion, semantic modelling
and automatic reasoning of information coming
from different sources (sensors, user profiles,
calendars, home agenda) will insure the reliable
personalised on demand service delivery.
Security and privacy implications are concerned
particularly when employing sensing technology and
recording/monitoring behaviour of people.
Furthermore, the issue of personalization involves
storing and using an embedded user model for the
purposes of automatically selecting and adapting
functionality and services offered. It is important to
keep the user informed about the data that will be
collected and how it will be used. Obviously, this is
all related to legal and ethical issues too, managed
by an Ethical Committee.
3.1 Applications and Services
The scenarios below give an idea about applications
and services provided by AmIE system.
Wellness Evaluation. Anna is a 75-year-old woman
who lives in her own apartment. AmIE system
gathers automatically online information about her
current wellness status. An online wellness profile is
estimated by combining data from several sources.
The system collects sensor data from wearable
sensors, environment sensors, wellness self-
evaluations, social proximity (nurse, family,
friends,…), health record information, etc. The
online profile can be utilized by Anna herself,
relatives and health care professionals to personalize
the services offered to Anna. Anna has several
wearable sensors, such as a motion detector in her
wrist watch. The system notices when Anna is active
and performing her exercises, and also when Anna is
passive and not doing much. The AmIE system
stores also some information from bed sensors about
the sleep quality, about how many times certain
electrical appliances are used or different doors
opened during the day, how many phone calls or
visitors Anna has had today, etc. Anna’s mental
wellbeing is analysed through interactive games,
such as memory games. In addition, information
from possible medical measurement devices, such as
blood pressure meter, is collected by the system.
Anna can give her own assessment on her current
condition to the system by touching a corresponding
smiley face. A nurse or a family member visiting
Anna can give their opinion on Anna’s condition
using the same method or by using a web or mobile
phone service. This information together with sensor
information described above is combined to indicate
Anna’s current condition with e.g. “traffic light
Supporting Independent Living. Dealing with the
activities of the daily living, Anna is assisted in
doing the laundry, cooking and shopping. A washing
machine equipped with RFID tags may warn about
incompatibilities among the clothes being entered
into the machine. A refrigerator keeping track of the
foodstuff available may refresh the shopping list or
advice some alternative food recipes based on user
preferences, diets or health recommendations. Using
a simple device with several buttons for
communication, Anna may contact a call center for
further assistance in reserving time to barber or ask
for any other home assistance like cleaning or
shopping. Easy to use video TV communication is
available in Anna’s home to communicate with
friends, family, or share photos and gaming, but also
to communicate with medical staff if she feels some
need for this.
Nowadays, various systems for home assistance are
already being commercialised. Companies such as
Tunstall, Mextal, Philips and Siemens
Communications and Tadiran Spectralink Ltd in
Europe or Telehealth Broadband in the US,
commercialise teleassistance and telemedicine
AmIE offers several innovations that constitute
strengths also in the market. AmIE does not only
perform a diagnosis but also predicts future
problems and helps the user improve his/her daily
habits to remain healthy for a longer time. The
system is expected to have a highly degree of
acceptance by the elderly users since the interaction
is not a roughly configured one, but adapted to each
user and situation (multimodal interaction).
Moreover, its design is based on the principle of
non-intrusiveness so that the user’s daily life is not
affected by the system elements. AmIE is positioned
at the boundary between self-monitoring and life-
style applications on one side and professional
monitoring and elderly care at the other side (see
Fig.2). This positioning has the advantage of
evolving along with the user from comfort services
and life style applications to assisted living in a
natural way.
AmIE - Towards Ambient Intelligence for the Ageing Citizens
Figure 2: The position of AmIE in the market. Source:
Parks Associates 2008.
The above discussions show that there is a good
possibility to address market and add-value service
delivery for elder. However, there are some
substantial challenges that still have to be dealt with:
Health is such a delicate matter, that it can not be
left in an automatic system’s hands.
Skills to interact with a computer: the elderly are
quite reluctant to technology and are not usually
accustomed to interacting with it.
Who is our customer? It is found that in different
areas Age Care is organized with different model
(Scandinavia vs. South Europe). Payer and end-
user is not always the same person.
Do we know the real needs/resources of the
elderly to solve our task in a proper way? Old
people are not just one target group based on age,
instead a huge group of individuals with different
needs and ever changing mental, physical and
perceptual capabilities.
In comparison to other available solutions, AmIE
will act as a preventing and assisting intelligent
system. Still several R&D challenges need to be
addressed to achieve its ambitious goals:
Reasoning and Intelligence. In order to add
intelligence to the system, technologies related with
Artificial Intelligence are applied. However there is
still a challenge to build a reliable usage and context
models from low-level sensors. Thus the health care
professional help will be involved to ensure that
collected data covers wide range of situations.
Living Ontologies. Ontologies are indispensable
elements of the AmIE rule definition module.
However grounding of ontologies in evolving, real-
world communities and service activation process is
still an open issue.
User Information. One key issue for AmIE is the
acquisition of information about the user, its
processing and analysis to derive predictions and
intelligent interaction with the user. Personal up-to-
date data access is a risen challenge concerned with
architectural, regulator and commercial issues.
Shinozaki, R., at al., 2005. Communication and Control of
a Home Robot Using a Mobile Phone. 6th Pacific Rim
Conference on Multimedia, Jeju Island, Korea,
November 13-16
Porteus, J. and Brownsell, S., 2000. Using Telecare.
Exploring Technologies for Independent Living for
Older People. Brighton: Anchor Trust, Pavilion.
Kenchiku, K., 2005. Introducing New PC emergency Call
Systems. Presentation at the IAHSA Symposium in
Norway, June 27-29.
Fellbaum, K. and M. Hampicke, 2002. Human-Computer
Interaction in a Smart Home Environment. Symposium
"Domotics and Networking", Miami, Nov 11-12.
Van Berlo, A., 2005. Smart Houses and smart living for
senior citizens: chances and markets. Silver Economy
in Europe Conference in Bonn, Germany Feb 16-17.
Van Berlo, A. and Fellbaum, K., 1999. Smart Home
Technology: Useful Applications for older people.
Assistive technology Research Series 6, pp.508-512.
MOBILALARM, 2005. Validating European Mobile
Alarm Services for Inclusion and Independent Living.
D 2.1 Market Analysis.
Finkelstein, S.M. Speedie, S., Potthoff, S., and Ratner, E.,
2005. Home Telehealth Provides an Independent
Living Option for the Elderly, In proceedings
TELEHEALTH 2005 Banff Canada July 17-19
Eurostat Publications Office, 2008. EUROPE IN
FIGURES, Eurostat Yearbook 2008
AmIE project home,, 2008
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