Tesis Alberdi Aramendi Ane

188 Pages·2017·3.47 MB·English

Early diagnosis of disorders based on
behavioural shifts and biomedical signals
Ane Alberdi Aramendi
October 2017
Electronics and Computing Department
Faculty of Engineering
Mondragon University

Early diagnosis of disorders based on behavioural shifts
and biomedical signals
A thesis submitted
in fulfillment of the requirements for the degree of
Doctor of Philosophy
Ane Alberdi Aramendi
Supervised by:
Dr. Asier Aztiria Goenaga
and
Dr. Adrian Basarab
Committee:
Chair: Dr. Diego L´opez de Ipin˜a Gonz´alez de Artaza (Universidad de Deusto)
Member: Dr. Jos´e Javier Yanguas Lez´aun (Fundaci´on INGEMA)
Member: Dr. Javier Mar Medina (Hospital Alto Deba)
Member: Dr. Maria Goreti Carvalho Marreiros (Polytechnic Institute of Porto)
Secretary: Dr. Maitane Barrenechea Carrasco (Mondragon Unibertsitatea)
October 2017
Electronics and Computing Department
Faculty of Engineering
Mondragon University
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©2017 Ane Alberdi Aramendi.
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Atte ta amai,
“Education is a progressive discovery of our own ignorance.”
-William James Durant. 1965.

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Originality Statement
I declare that I am the sole author of this work. This is a true copy of the final document, including
any revision which may have been ordered by my examiners. I understand that my work may be
available to the public, either at the university library or in electronic format.

Abstract
There are many disorders that directly affect people’s behaviour. The people that are suffering from
suchadisorderarenotawareoftheirsituation,andtoooftenthedisordersareidentifiedbyrelativesor
co-workers because they notice behavioural shifts. However, when these changes become noticeable,
it is often too late and irreversible damages have already been produced. Early detection is the key
to prevent severe health-related damages and healthcare costs, as well as to improve people’s quality
of life.
Nowadays, in full swing of ubiquitous computing paradigm, users’ behaviour patterns can be
unobtrusively monitored by means of interactions with many electronic devices. The application of
this technology for the problem at hand would lead to the development of systems that are able to
monitor disorders’ onset and progress in an ubiquitous and unobtrusive way, thus enabling their early
detection. Some attempts for the detection of specific disorders based on these technologies have
been proposed, but a global methodology that could be useful for the early detection of a wide range
of disorders is still missing.
Thisthesisaimstofillthatgapbypresentingasmaincontributionaglobalscreeningmethodology
for the early detection of disorders based on unobtrusive monitoring of physiological and behavioural
data. The proposed methodology is the result of a cross-case analysis between two individual valida-
tionscenarios: stressintheworkplaceandAlzheimer’sDisease(AD)athome,fromwhichconclusions
that contribute to each of the two research fields have been drawn. The analysis of similarities and
differences between the two case studies has led to a complete and generalized definition of the steps
to be taken for the detection of a new disorder based on ubiquitous computing.
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