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A Framework for Psychophysiological Classification within a Cultural Heritage Context Using Interest

Karran, AJ, Fairclough, SH and Gilleade, K (2015) A Framework for Psychophysiological Classification within a Cultural Heritage Context Using Interest. ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION, 21 (6). 34.1-34.19. ISSN 1073-0516

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This article presents a psychophysiological construct of interest as a knowledge emotion and illustrates the importance of interest detection in a cultural heritage context. The objective of this work is to measure and classify psychophysiological reactivity in response to cultural heritage material presented as visual and audio. We present a data processing and classification framework for the classification of interest. Two studies are reported, adopting a subject-dependent approach to classify psychophysiological signals using mobile physiological sensors and the support vector machine learning algorithm. The results show that it is possible to reliably infer a state of interest from cultural heritage material using psychophysiological feature data and a machine learning approach, informing future work for the development of a real-time physiological computing system for use within an adaptive cultural heritage experience designed to adapt
the provision of information to sustain the interest of the visitor.

Item Type: Article
Additional Information: "© ACM, 2015. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions in Computer-Human Interaction, v.21(6) 2015. http://dx.doi.org/10.1145/2687925
Uncontrolled Keywords: 0806 Information Systems
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Divisions: Natural Sciences & Psychology (closed 31 Aug 19)
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Date Deposited: 10 Jul 2015 10:08
Last Modified: 04 Sep 2021 14:37
DOI or ID number: 10.1145/2687925
URI: https://researchonline.ljmu.ac.uk/id/eprint/587

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