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

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.