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Accuracy Evaluation of Remote Photoplethysmography Estimations of Heart Rate in Gaming Sessions with Natural Behavior
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. Federal University of Fronteira Sul, Chapecó, Brazil. (Interaction Lab)ORCID iD: 0000-0001-6479-4856
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Interaction Lab)ORCID iD: 0000-0002-9972-4716
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Interaction Lab)ORCID iD: 0000-0001-9287-9507
2018 (English)In: Advances in Computer Entertainment Technology: 14th International Conference, ACE 2017, London, UK, December 14-16, 2017, Proceedings / [ed] Adrian David Cheok, Masahiko Inami,Teresa Romão, Springer Publishing Company, 2018, 1Chapter in book (Refereed)
Abstract [en]

Remote photoplethysmography (rPPG) can be used to remotely estimate heart rate (HR) of users to infer their emotional state. However natural body movement and facial actions of users significantly impact such techniques, so their reliability within contexts involving natural behavior must be checked. We present an experiment focused on the accuracy evaluation of an established rPPG technique in a gaming context. The technique was applied to estimate the HR of subjects behaving naturally in gaming sessions whose games were carefully designed to be casual-themed, similar to off-the-shelf games and have a difficulty level that linearly progresses from a boring to a stressful state. Estimations presented mean error of 2.99 bpm and Pearson correlationr = 0.43, p < 0.001, however with significant variations among subjects. Our experiment is the first to measure the accuracy of an rPPG techniqueusing boredom/stress-inducing casual games with subjects behaving naturally.

Place, publisher, year, edition, pages
Springer Publishing Company, 2018, 1.
Series
Information Systems and Applications, incl. Internet/Web, and HCI
Keywords [en]
Games, Emotion assessment, Remote photoplethysmography, Computer vision, Affective computing
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
URN: urn:nbn:se:his:diva-14772DOI: 10.1007/978-3-319-76270-8ISI: 000432607700035Scopus ID: 2-s2.0-85043535153ISBN: 978-3-319-76269-2 (print)ISBN: 978-3-319-76270-8 (electronic)OAI: oai:DiVA.org:his-14772DiVA, id: diva2:1185319
Funder
EU, European Research Council, Project Gamehub ScandinaviaAvailable from: 2018-02-23 Created: 2018-02-23 Last updated: 2018-06-14

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Bevilacqua, FernandoEngström, HenrikBacklund, Per

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