E. I. Konstantinidis, A. Billis and P. D. Bamidis
Laboratory of Medical Informatics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
Keywords: Cloud-computing, Web service, Physical training, Cognitive training, Medical record.
Abstract: Organizing, tracking, monitoring, and acting upon personal health and especially cognitive and physical
training information has nowadays become a necessary and important procedure. This is true particularly for
special groups of people with cognitive or physical impairments (or both). Elderly people with mild
cognitive impairments, autistic children and other categories of people with impairments may obtain
benefits by having their daily cognitive and physical activity been monitored. This piece of work, proposes
an approach towards a solution for a physical and cognitive medical record held upon the cloud, and
accessed through web services. In this way, various semantically described exercises and training platforms
may exchange information with the record system and access user performance results obtained in the
context of a standardized description of exercises with suitably associated results and scores.
A famous ancient greek quotation has expressed the
importance of having in good health both mind and
body: “a sound mind into a sound body”; this has
praised the need for people to equally keep their
minds and bodies in good shape, so as to have a
well balanced life and overall improved well being,
that also includes their phychological status and self-
It is common knowledge that nowadays, the
western way of life has changed dramatically, and is
mainly characterized by a complete absence of any
kind of physical activity among daily living
activities (Trost et al, 2002). This situation has led to
many severe health problems responsible for a
significant percentage of deaths among the western
world, such as obesity (Fox and Hillsdon, 2007),
coronary artery disease (Fox et al, 1972), arterial
hypertension, mobility impairments. There is
sufficient evidence that people, who try to keep fit
through exercise, are benefited to a certain extent in
several aspects of their health, including: reduced
risk of cardiovascular disease (Braith And Stewart,
2006), (Pollock et al, 2000), prevention of the
development of arterial hypertension, control of
diabetes, increased fat utilisation which can help to
control weight, lowering the risk of obesity
(Kesaniemi et al, 2001), maintenance of cognitive
functions and decreased risk of developing
depression and dementia in senior citizens (Van
Boxtel et al, 1997), (Perrig-Chiello et al, 1998) and
finally moderation of stress (Hill et al, 1993).
It is imperative that in recent years, numerous
information and communication technology (ICT)
resources have become available to facilitate
exercise and enrich a fitness training program. Apart
from the traditional gym equipment, such as plain
stationary or ergometer bikes, treadmills, dumbbells,
there are also new trends in the way physical
exercise is performed, such as “exergaming”
(Bogost, 2005). Exergaming, which has lately drawn
the attention of training experts, is a form of exercise
through the use of video games whose main focus is
the improvement and promotion of physical health
of individuals through interactive game play. The
way individuals can train themselves through a
video game, is to physically interact with its content.
Physical interaction means that a trainee via his/her
body movements can manipulate a virtual character
on the game screen, imitating this way different
kinds of sport activities, like walking or running
(Bonanni et al, 2006), (Mumford et al., 2008). Great
examples of commercial exergaming platforms are
Nintendo Wii Fit, XBOX Kinect, DDRs (Dance
Dance Revolution) like Dance Town (focus on
elderly population), ConnectAndPlay, Positive
Gaming and many others (Billis et al, 2010).
I. Konstantinidis E., Billis A. and D. Bamidis P..
DOI: 10.5220/0003450405290534
In Proceedings of the 1st International Conference on Cloud Computing and Services Science (CLOSER-2011), pages 529-534
ISBN: 978-989-8425-52-2
2011 SCITEPRESS (Science and Technology Publications, Lda.)
Apart from the health problems related to
physical inactivity, people are also exposed to
cognitive and mental illnesses. These might occur at
any time of the human’s lifespan, from early stages
of human life to old age. Examples of such cognitive
illnesses are attention deficit-hyperactivity disorder
(ADHD), autism spectrum disorders, schizophrenia,
dementia and stroke. Most of the above mentioned
pathological situations result to multiple cognitive
and other deficits, thereby leading to partial brain
mulfunctioning. Much research has focused on the
design and the application of cognitive intervention
and rehabilitation programs (Solberg et al., 1994),
(Merzenich et al, 1996) so to ameliorate most of the
effects that the above mentioned situations have on
human cognitive health.
Computer-assisted interventions have shown
some very promising results in several areas of
therapy and rehabilitation research (Hofmann et al,
1996), (Galante et al, 2007), (Tárraga et al, 2006),
(Barnes et al, 2009). Computer games have also
proved to be of great value for the overall brain
function in several cases (Gamberini et al, 2006),
(Green and Bavelier, 2003).
All this plethora of applications and technology
devices form a significant field of interest as their
primary goal is to promote and enhance either the
physical or cognitive human health. These
applications target to a wide range of groups with
either different or similar profiles of health
This piece of research work focuses on a service
that can support special groups of people towards
their physical and cognitive health, as well as, their
independent living. The aim of the paper is to
propose an approach towards a solution for a
physical and cognitive medical record held upon the
cloud, and accessed through web services, thus
delivering a PaaS for the development, testing and
deployment of either already existing software
solutions or future developments. So, in the
remaining of this paper the principles of the
undertaken architecture and the technical design
details of the proposed service are described, with
emphasis drawn upon the web service architecture
and the underlying database. It is shown in section 2
how the service combines structures, methods and
functionalities on cognitive exercises against
cognitive decline with physical activity in the
framework of an advanced ambient assisted living
environment (Konstantinidis et al, 2010). Section 3
presents scenarios of use, while a critical discussion
and outlook are provided in the final section.
As mentioned already, the main service is comprised
of three different categories according to the training
• Cognitive Training
• Physical Training
• Independent Living
The service functionalities and methods are designed
in a way that they are able to be consumed by
already existing as well as future applications and
hardware systems that deal with data related to the
above three categories. Thus, sensors that monitor
movements inside the house (movement and activity
patterns), software dedicated to cognitive training
and rehabilitation and various training equipment,
such as recumbent bikes and/or ergometers and/or
treadmills, which offer a variety of physical
exercising possibilities according to the special
needs and disabilities of each user, find a ready-to-
use and well described data layer supporting their
main functionalities.
2.1 Data Layer
The proposed service implements a model based on
the integration of independent components,
accomplishing different scopes of application, which
provide heterogeneous data and semantics.
According to these requirements the proposed
architecture supports the integration of the data and
the co-ordination of the components’ functionalities,
while acting either independently or in the
framework of an interconnected training
Independent fundamental entities in the database
provide information for the candidate applications
(the kind of the application, the available exercises,
the score algorithm, the target group, etc.) and the
type of exercises they support (description of
exercise, difficulty levels, required devices if any,
etc.). As a result, the database includes a
semantically described schema of different training
systems. This schema is updated by including new
training components and new training devices.
The upper data layer provides information about
the user interactions with the available training
components, performance, daily compliance to the
training schedule and monitoring of activities. The
proposed service acts as the heart of the training data
repository. This repository depicts the cognitive and
physical health of the user.
CLOSER 2011 - International Conference on Cloud Computing and Services Science
2.2 Methods and Structures
The main functionality of the three independent
components is met by means of a server side system,
whose main component is the proposed service. The
web service is responsible for providing all methods
and functions in order to support the three
independent component functions as it is depicted in
Figure 1. Moreover, the web service is responsible
for the authentication of the system’s users
according to their role and the provision of access
rights on certain information of the database.
Figure 1: The web service supports the three independent
Providing programming access to the system’s
features and services, the Web Service includes the
Simple Object Access Protocol (SOAP), Web
Services Definition Language (WSDL), and the
XML Schema Definition language (XSD). These
standards are supported by a wide range of
development tools on a variety of platforms.
The web service provides structures (an example
is given in Table 2) as inputs and outputs to all
supported methods. All structures and methods are
well described by a human readable document which
is publicly available. Moreover, each structure is
accompanied by an “error” structure in order to
facilitate appropriate message exchange with the
Table 1: Structure for senior’s demographic data example.
<s:complexType name="user"> <s:sequence>
<s:element minOccurs="1" maxOccurs="1"
name="user_id" type="s:int"/>
<s:element minOccurs="0" maxOccurs="1"
name="lname" type="s:string"/>
<s:element minOccurs="1" maxOccurs="1"
name="birthdate" type="s:dateTime"/>
For example, in order to add an activity
performed by a user we use the method shown in
Table 2. It behaves as a log file of the user’s
progress and activities. The required attributes that
must be provided are shown in Table 2.
Table 2: User cognitive activity attributes.
Attribute Description
user_id The ID of the user performing the activity
ctcactivityid The Cogntitive Training Activity performed
by the User
ctcid The Cognitive Training Component used by
the user in order to perform the Activity
datetimestart The date and time that the activity started
datetimeend The date and time that the activity ended
score The score achieved by the User
level The level of difficulty of the performed
Cognitive Training Activity
An example using LLM web service method to
record user’s performance to a certain CTC activity:
ctcactx = new CTCUserActivity();
ctcactx.ID = 0;
ctcactx.ctcid = 4;
ctcactx.ctcactivityid = 3;
ctcactx.user_id = 10;
ctcactx.datetimestart = new
DateTime(2010, 6, 21, 10, 00, 00);
ctcactx.score = "23";
ctcactx.level = 5;
ctcsac = AddCTCUserActivity(ctcactx,
“username”, “password”);
if (ctcsac.error.ErrorCode == 0)
ctcactx =
More information on the complete list of
functionalities and data structures that are supported
by the web service can be found at
2.3 User’s Roles
As discussed above, the web service is responsible
for the authentication of the system’s users
according to their role. Different roles accomplish
different privileges on data and methods based on
the relation link among users (supported by the
service). The main roles of the system are:
A user is performing the system’s activities and has
the privileges for his own data and methods. The
therapist is able to monitor the users related to him.
She/he is responsible for accessing the daily
schedule programme and providing special
notifications to individual users. The administrator
of the system has all the available privileges for
supporting the system and adding new
functionalities. Finally, the “relative” role is a user
that may monitor another user’s performance
without being able to modify anything.
The open architecture enables already developed or
future products to benefit by gaining access to
correlative results of familiar applications or
enriching their results by different types of
applications. The former strategy enables
applications to compare their results with results
from familiar applications regarding a specific user.
As the training components, their functions,
exercises and results are semantically described the
cognitive and physical performance curve is
comparable among different applications. As a
result, each application and protocol has the
opportunity to be enriched in form of several
different amounts of data results. The latter strategy,
which makes use of heterogeneous data information,
provides semantic data of different scopes for each
user. For example, a cognitive training component
for elderly people may enrich its results by having
access or correlating them with the user’s (specific
user) physical training activity. Useful results may
accrue by the type and intensity of affection or even
mood, if any, among training activities.
Figure 2: The proposed service acts as a gateway of
intercommunication among different applications on the
Meanwhile, the semantically described training
activities and their results should be the spark for
evaluating different standards on cognitive and
physical training. As a result, a life-long physical
and cognitive medical record is to take shape.
Forming a holistic framework, the proposed
platform serves an abstract semantic communication
layer among training applications and protocols.
Cloud computing may promote this layer as a
gateway of intercommunication among applications
serving different scopes of data, as depicted in
Figure 2.
Figure 3: Indicative Cognitive Training results during an
iterative trial of the system by senior citizens within the
Long Lasting Memories European Commission Project
(see for further details).
The described service has been initially
developed for the needs of the Long Lasting
Memories European Commission Project (LLM EU
project, 2010). This project utilizes a number of
remotely operated screens, which are embedded in
the independent living environment and connected
to training equipment (like recumbent bikes,
ergometers or treadmills). Light physical exercises
are combined with a targeted set of cognitive
exercises, while the environment's sensors ensure the
safe and enduring application of this training,
adjusting, intervening or providing motivation
according to each person’s achievements and
status/situation (Frantzidis & Bamidis, 2009). Figure
3 depicts results of cognitive training during a
certain period of time. The results show summarized
scores (and not raw data – i.e. log files) during a
session of similar exercises (Cognitive Training in
this case). Thus, each score represents a meaningful
status of the user’s performance, which is available
through the cloud and may accompany each user
(senior in this case) in every aspect/step of his/her
life, thereby contributing to the continuity of care
EU policy target.
CLOSER 2011 - International Conference on Cloud Computing and Services Science
The research presented in this paper focuses on the
development of an integration scheme for various
independent applications that target on the
promotion of physical and cognitive health. The
integration of the applications is tackled on the basis
of a web service and a database schema. Possible
usage extension of the proposed framework is the
creation of an application gateway, where each
application will be able to interchange information
and data through the data pool that is created and be
shared via the open web service’s architecture and
database scheme. A possible extension to the
existing infrastructure could be the introduction of
an additional web service implementing Dynamic
Decision Support System techniques in order to
provide some automation techniques and add
intelligence to the end system.
The existing framework combined with the
future developments will allow the creation of a
unique data pool that will focus on the physical and
cognitive status of possible users, envisaging to set
some standard way and technology for describing
and exploiting applications within the nowadays
chaotic field of physical and mental health.
This work is partially funded by the LLM Project
( through the ICT
Policy Support Programme (ICT PSP) as part of the
Competitiveness and Innovation Framework
Programme of the European Commission.
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