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Author:Makkonen, Tommi
Title:Analyysimenetelmä musiikin kuuntelun aiheuttamille fysiologisille muutoksille
An analysis method for physiological changes evoked by music listening
Publication type:Master's thesis
Publication year:2009
Pages:48 s. + liitt. 5      Language:   fin
Department/School:Elektroniikan laitos
Main subject:Sovellettu elektroniikka   (S-66)
Supervisor:Sepponen, Raimo
Instructor:Huotilainen, Minna
Electronic version URL: http://urn.fi/URN:NBN:fi:aalto-201203091377
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark S80     | Archive
Keywords:response detection
spontaneous signals
music
electromyography (EMG)
skin conductance responses (SCR)
heart rate (HR)
vasteilmaisu
spontaanit signaalit
musiikki
elektromyografia (EMG)
ihon sähkönjohtavuusvasteet (SCR)
pulssi (HR)
Abstract (eng): The focus of the work was to develop an analysis method for spontaneous responses recorded during music listening.
A new non-statistical method for automatic response detection and analysis was implemented.
The algorithm detects activation in electromyography and electrodermal activity.
Detected responses were studied in time domain and frequency domain by graphical user interface Physitools, which was also developed.

The practical application was to study facial electromyography, skin conductance and heart rate recorded during disliked, neutral, and liked music excerpts.
The hypothesis was that neutral music will evoke the lowest physiological activity.

The detection algorithm managed to indicate real skin conductance responses reliably.
Also electromyographic activity can be detected if signal-to-noise ratio is good.
Heart rate was found to alter most during liked music while all the other activity was found to be higher in the case of disliked music.

Response detection gives an opportunity to study physiological signals effectively with higher signal-to-noise ratio and it also may reveal event-related information in spontaneous data.
For the future research spontaneous responses are proposed to be studied during component-controlled music listening.
Abstract (fin): Työssä kehitettiin uusi analyysimenetelmä musiikin kuuntelun aikana mitatuille fysiologisen tilan signaaleille.
Menetelmällä ilmaistaan signaaleista automaattisesti tutkimuksen kannalta mielenkiintoisia vasteita, mikä mahdollistaa yksittäisten vas-teiden ominaisuuksien tutkimisen.
Koko signaalianalyysin mahdollistavaksi käyttöympäristöksi ohjelmoitiin graafinen käyttöliittymä Physitools.

Kehitettyä menetelmää sovellettiin koehenkilöistä mitattujen signaalien analyysissä.
Erityisesti tutkittiin epämieluisan, neutraalin ja mieluisan musiikin kuuntelun vaikutuksia kasvolihasaktivaatioon, ihon sähkönjohtavuuden muutoksiin ja pulssiin.

Vasteilmaisualgoritmilla saavutettiin parhaimmat tulokset ihon sähköjohtavuusvasteiden tapauksessa.
Algoritmin todettiin sopivan myös lihasvasteiden ilmaisuun, jos supistumisen aiheuttama aktivaatio on voimakasta verrattuna kohinatasoon.
Mielimusiikki aiheutti eniten pulssimuutoksia, ja epämieluisa musiikki sai aikaan eniten aktivaatiota ihon sähkönjohtavuudessa ja kasvolihaksissa.

Vasteiden ilmaisu tarjoaa mahdollisuuden tutkia yksittäisten aktivaatiohetkien ominaisuuksia korkeammalla signaali-kohinasuhteella.
Aktivaatioilmaisun avulla saatetaan saada esiin tapahtumasidonnaista aktivaatiota spontaanin aktivaation signaalista.
Vasteiden määrää ja ominaisuuksia ehdotetaan tutkittavaksi kehitetyllä analyysimenetelmällä piirrekomponentteihin eritellyn musiikin tapauksessa.
ED:2010-03-26
INSSI record number: 39383
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