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primarily correlation method. In the further study,
the results in a more sophisticated way might be
presented instead of just showing graphs and
correlation results. If linear regression model is
applied for the data, strong statistical predictor of the
reported emotional response can be obtained based
on these physiological responses. Secondly, this
study applied relatively loose threshold on the p-
value of 0.01 for the correlation results. If more
strict and robust statistical threshold is applied for
the data, e.g., p-value of 0.002, it is expected to find
noticeable physiological responses strongly
associated with emotional dimensions.
Despite a few limitations above, this study could
examine an availability of physiological signals for
emotion recognition in HCI and our result can be
helpful to provide the basis for the emotion
recognition technique in HCI. Further, we will
expand the approach of examining other affective
dimensions such as coping potential or novelty.
ACKNOWLEDGEMENTS
This research was supported by the Converging
Research Center Program through the Ministry of
Science, ICT and Future Planning, Korea (2013K00
0329 and 2013K000332).
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RelationshipbetweenAffectiveDimensionsandPhysiologicalResponsesInducedbyEmotionalStimuli-Baseon
AffectiveDimensions:Arousal,Valence,IntensityandApproach
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