Abstract:
In order to differentiate the affective state of a computer user as it changes from relaxation to stress, features derived from pupil dilation and periorbital temperature...Show MoreMetadata
Abstract:
In order to differentiate the affective state of a computer user as it changes from relaxation to stress, features derived from pupil dilation and periorbital temperature are processed with machine learning techniques. When absolute signal values are used together with entropy based features, the accuracy of affective classification is observed to increase. When decision tree (C4.5) is tested for classification, best accuracy of detection of neutral versus aroused states is above 90%.
Date of Conference: 23-25 April 2014
Date Added to IEEE Xplore: 12 June 2014
Electronic ISBN:978-1-4799-4874-1
Print ISSN: 2165-0608