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Interest Detection while Reading Newspaper Articles by Utilizing a Physiological Sensing Wristband

Soumy Jacob; Shoya Ishimaru; Andreas Dengel
In: Proc. UbiComp2018 Adjunct (Hrsg.). The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing. International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp-2018), October 8-12, Singapore, Singapore, Pages 78-81, ISBN 978-1-4503-5966-5, ACM, 2018.


In this paper, we present how physiological measures including heart rate (HR), electrodermal activity (EDA) and blood volume pulse (BVP) can be retrieved from a wristband device like an E4 wristband and further used to detect the interest of a user during a reading task. From the data of 13 university students on 18 newspaper articles, we have classified their interest level into four classes with an accuracy of 50%, and 68% with binary classification (interesting or boring). This research can be incorporated in the real-time prediction of a user's interest while reading, for the betterment of future designs of human-document interaction.