Download The Active Ageing At Home Project: building a

The Active Ageing At Home Project: building a
comprehensive ICT system to improve well-being
of ageing people
Marco Pistoia1 and Paolo Casacci2
Corresponding Author:
Full name: Paolo Casacci
Address of institution: eResult s.r.l., Piazzale Luigi Rava n.46 – 47522 Cesena (FC) ITALY
Email: [email protected]
Phone Number: +39 0547 1901264
Area of contribution: Well-being and active ageing
Keywords: active ageing, guidance, support, monitoring, caregiver, wellness, socialization
Acknowledgments: The authors gratefully acknowledge the financial support from
the Italian Ministry of University and Research (MIUR) through the project “Active
Ageing at Home” (CTN01_00128_297061, Area TAV - Tecnologie per gli Ambienti
di Vita).
1
Marco Pistoia
eResult s.r.l., Piazzale Luigi Rava n.46 – 47522 Cesena (FC) - ITALY, e-mail: [email protected]
2 Paolo Casacci
eResult s.r.l., Piazzale Luigi Rava n.46 – 47522 Cesena (FC) - ITALY, e-mail: [email protected]
2
1 Introduction
The constant increase of the life expectancy and the consequent aging phenomenon
will inevitably produce in the next 20 years deep social changes that lead to the need
of innovative services for elderly people, focused to maintain independence, autonomy
and, in general, improve the wellbeing.
In this context, the Active Ageing At Home project aims at realizing services for
elderly people to improve the quality of life by means of ICT solutions, both fixed and
mobile (wearable and not), pervasive and with low invasiveness according to Ambient
Intelligence (AmI) paradigms. The proposed solutions want to improve the sense of
safety and comfort perceived by self-sufficient elderly in their home environment.
3
2 Conclusion
The Active Ageing At Home Project aims at realizing personalized services which can
guide people to carry out a healthy life style and to maintain their level of autonomy in
different dimensions (security, mobility, memory, sociality). The goal is to allow
individuals to have an active role in managing their own health and in maintaining
good health conditions. These goals are pursued by the creation of a “virtual” model of
the person which reflects important characteristics that are specific of each one (e.g.
personal profile, risk factors, harmful behaviors, tastes and personal preferences,
eating habits, level of physical activity, sleep/wake rhythm, etc..) and that can provide
personalized indications by interacting with the individual to make her/him more
conscious of unhealthy behavior3.
The principal aim is to obtain a personal guidance system to guide people’s
behavior and habits for their benefit, their well-being and for applying preventive
actions. This will be obtained by means of gateways on the person (home gateway,
mobile phone/smartphone, wearable dedicated devices) providing information which
can help in changing the habits toward behaviors which prevents diseases or reduce
their worsening.
The technologies that will be proposed are largely based on heterogeneous,
distributed and connected smart-sensors, smart-actuators and smart-devices integrated
into a scalable technological platform, which is context-aware and enables services to
assist and monitor users in their own life environment4.
The platform is meant as an extension of other domotic solutions inside the home
environment and it will be “compliant” with the new open platform in the AAL
domain as the ones promoted by the Integrated Project universAAL (FP7 N°247950)
and the coordinated action EIP-AHA (European Innovation Partnership on Active and
Healthy Ageing ).
The platform will be based on a cloud infrastructure in order to organize the
collected data in a remote system, thus assuring reliability, scalability, security,
performance and independence from the device or application used to access to the
3 A. Talamo, S. Giorgi, B. Mellini. “Designing technologies for ageing: is simplicity always a leading
criterion?” In Proceedings of the 9th ACM SIGCHI Italian, Chapter International Conference on ComputerHuman Interaction: Facing Complexity (CHItaly), P. Marti, A. Soro, L. Gamberini, and S. Bagnara (Eds.).
ACM, New York, NY, USA, pp. 33-36 , 2011.
4 A. Losardo, G. Matrella, F. Grossi, I. De Munari, P. Ciampolini “Indirect wellness monitoring through
AAL environments”, in Gerontechnology; 11(2):330 doi: http://dx.doi.org/10.4017/gt.2012.11.02.492.00 ,
2012
4
data. Special attention will be devoted to manage privacy and sensitive information.
ICT solutions with an high technological impact will be developed to extend the time
elderly people can live autonomously (and respecting their privacy) in their homes,
promoting the “porting” process of AmI technologies to the new sector of the “Silver
economy” and making involved technologies pervasive, by means of identification
and removal of technology barriers. The AmI platform will infer knowledge by
integrating automatic tools for reasoning, knowledge discovery, and ontologies, acting
also as a decision support system in the contexts of monitoring, security, assistance
and inclusion.
The proposed solutions cannot substitute the capabilities and experience of the
caregivers, but rather, they provide technological support, which allows reduction of
the cognitive load and stress on the people leading to a reduction of the general cost of
the assistance and an increase of the quality of service too5.
The maintenance of the autonomy in aged people is strictly connected to the regular
execution of physical activity, even light activity, which allows thwarting the
reduction of the mobility level. For this reason, a Personal Fitness system will be
implemented. It will propose the execution of exercises to the user and will evaluate
correct execution by means of a gesture recognition system, assigning a score to each
exercise. The proposed exercises will depend on the profile of the user, the level of
mobility (defined on the base of the scores obtained during the exercises) and on the
user’s preferences. The data collected during the training will be sent to a remote
server. The server will infer information on the general healthcare status and
eventually identify the degradation of parameters such as strength, coordination,
balance.
All of collected data will be processed by means of analysis systems, capable to
extract key information on demand by different stakeholders (relatives, caregivers,
service providers) identifying automatically the critical situations and allowing an
efficient monitoring of the well-being level of the user reducing the cognitive burden
required to the stakeholders6.
The psychological and physical well-being of the person will be considered in its
whole. Socializing services will be realized that consider the expectations of the
person, no more as a passive consumer of services but as a proactive, conscious, critic
and informed customer. Such expectations go behind simple prevention activities: they
require personalized services realized with the active involvement of the people
making the most of their residual resources to bring benefits to the whole community.
5 McCreadie C. and Tinker A., The acceptability of assistive technology to older people. in Ageing and
Society vol 25(1), pp. 91-110, 2005.
6 J. Han, M. Kamber. “Data Mining: Concepts and Techniques”, 2nd ed. The Morgan Kaufmann Series
in Data Management Systems, Jim Gray, Series Editor Morgan Kaufmann Publishers, 2006.
5
The project also aims at creating a support network (composed of relatives, family
doctors, neighbors,…) offering new forms of social services in which the
technological and human aspects are intimately and closely integrated. The monitoring
services provided in the past from the support network are now characterized by a
combination of sensors network with a new class of caregivers, who represent the
reference people for the “new” elderly. In this vision, the caregivers act as “human
sensors”, collecting information on the people, other than being resources to manage
services.
References
1. A. Losardo, G. Matrella, F. Grossi, I. De Munari, P. Ciampolini “Indirect wellness
monitoring through AAL environments”, in Gerontechnology; 11(2):330 doi:
http://dx.doi.org/10.4017/gt.2012.11.02.492.00 , 2012
2. A. Talamo, S. Giorgi, B. Mellini. “Designing technologies for ageing: is simplicity
always a leading criterion?” In Proceedings of the 9th ACM SIGCHI Italian, Chapter
International Conference on Computer-Human Interaction: Facing Complexity
(CHItaly), P. Marti, A. Soro, L. Gamberini, and S. Bagnara (Eds.). ACM, New York,
NY, USA, pp. 33-36 , 2011.
3. J. Han, M. Kamber. “Data Mining: Concepts and Techniques”, 2nd ed. The Morgan
Kaufmann Series in Data Management Systems, Jim Gray, Series Editor Morgan
Kaufmann Publishers, 2006.
4. McCreadie C. and Tinker A., The acceptability of assistive technology to older people. in Ageing and Society vol 25(1), pp. 91-110, 2005.