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Author:Rinta-Koski, Olli-Pekka
Title:Monitoring sleep quality with non-invasive sensors
Huomaamattomat mittausmenetelmät unen laadun tarkkailussa
Publication type:Licentiate thesis
Publication year:2013
Pages:x + 48      Language:   eng
Department/School:Tietojenkäsittelytieteen laitos
Main subject:Informaatiotekniikka   (T-115)
Supervisor:Simula, Olli
Instructor:Hollmén, Jaakko
Electronic version URL: http://urn.fi/URN:NBN:fi:aalto-201306146490
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
Instructions

Reading digital theses in the closed network of the Aalto University Harald Herlin Learning Centre

In the closed network of Learning Centre you can read digital and digitized theses not available in the open network.

The Learning Centre contact details and opening hours: https://learningcentre.aalto.fi/en/harald-herlin-learning-centre/

You can read theses on the Learning Centre customer computers, which are available on all floors.

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Location:P1 Ark Aalto     | Archive
Keywords:sleep analysis
sleep quality
non-invasive sensors
ballistocardiography
unitutkimus
unen laatu
huomaamattomat sensorit
ballistokardiografia
Abstract (eng): Sleep is an important part of health and well-being.
While sleep quantity is directly measurable, sleep quality has traditionally been assessed with subjective methods such as questionnaires.
The study of sleep disorders has for a long time been confined to clinical environments, and patients have had to endure cumbersome procedures involving multiple electrodes placed on the body.
Recent developments in sensor technology as well as data analysis methods have enabled continuous, unobtrusive sleep data recording in the home environment.
This has opened new possibilities for studying various sleep parameters and their effect on the quality of sleep.

This thesis consists of two parts.
The first part is a literature review examining the field of sleep quality research with focus on the application of intelligent methods and signal processing.
The second part is a descriptive data analysis look at sleep data obtained with non-invasive sensors.
Abstract (fin): Uni on terveyden ja hyvinvoinnin keskeinen tekijä.
Unen määrä on helposti mitattavissa, mutta unen laatua on perinteisesti seurattu kyselylomakkeiden kaltaisin subjektiivisin menetelmin.
Unihäiriöiden tutkiminen on pitkään rajoittunut kliinisiin ympäristöihin, ja potilaiden on täytynyt sietää hankalia tutkimusmenetelmiä useine kehoon kiinnitettävine elektrodeineen.
Anturiteknologian ja data-analyysimenetelmien kehittyminen on mahdollistanut unidatan jatkuvan ja huomaamattoman tallentamisen kotiympäristössä.
Tämä on avannut uusia mahdollisuuksia sekä unen ominaisuuksien että niiden unen laatuun vaikuttavien tekijöiden tutkimiselle.

Tämä tutkimus jakautuu kahteen osaan.
Ensimmäinen osa on kirjallisuuskatsaus unen laadun tutkimukseen, painopisteenä älykkäiden menetelmien ja signaalinkäsittelyn soveltaminen.
Toisessa osassa esitellään huomaamattomilla sensoreilla kerättävän unidatan tutkimista ja sen deskriptiivistä data-analyysiä, esimerkkinä ballistokardiografia.
ED:2013-05-16
INSSI record number: 46145
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