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 Seiten 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.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence