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Biofeedback med EDA i Tetris
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

In a biofeedback system, data about the user’s physiological

functions is measured and used as input for the system.

EDA is a measurement of a persons stress and it is used in

biofeedback systems.

This essay is about measuring EDA with the Affectiva Q

Sensor in the game Tetris. The relationship between EDA

and the difficulty in the game has been analyzed, both

through correlation analysis and curve fitting. In the game

the difficulty can be controlled by implicit and explicit

biofeedback, and this functionality has been used to see

if users could learn to control their stress through explicit

biofeedback. The result of the study was that there exists

a corrrelation (the average correlation coefficient was

0.472) between EDA and difficulty. It was also shown that

the players could not control their EDA with the help of

explicit biofeedback

Abstract [sv]

I biofeedback-system mäts och registreras data om användarens

fysiologiska funktioner, för sedan kunna användas

som indata till systemet. EDA är ett mått på hur stressad

en person är och används i biofeedback-system.

Denna uppsats handlar om att mäta EDA med hjälp av Affectiva

Q Sensor i spelet Tetris. Sambandet mellan EDA och

svårighetsgraden i spelet har undersökts, både med hjälp

korrelationsanalys och kurvanpassning. I spelet kan svårighetsgraden

styras med implicit och explicit biofeedback, och

med denna funktionalitet har det testats det om det är möjligt

för en spelare att kontrollera sin EDA med hjälp av den

explicita feedbacken. Resultatet var att det finns en korrelation

(medelvärdet för korrelationskoefficienten var 0.472)

mellan EDA och svårighetsgrad, däremot kunde spelarna

inte lära sig att kontrollera sin EDA (stress) när de spelade

Tetris.

Place, publisher, year, edition, pages
2013.
Series
Kandidatexjobb CSC, K13045
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-136080OAI: oai:DiVA.org:kth-136080DiVA: diva2:670528
Educational program
Master of Science in Engineering - Computer Science and Technology
Supervisors
Examiners
Available from: 2013-12-13 Created: 2013-12-03 Last updated: 2013-12-13Bibliographically approved

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CiteExportLink to record
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