Survey on Emotion Sensing Using Mobile Devices

Abstract

The rapid development and ubiquity of mobile and wearable devices promises to enable researchers to monitor users' granular emotional data in a less intrusive manner. Researchers have used a wide variety of mobile and wearable devices for this purpose, and have proposed various approaches to sense users' emotional states. In this survey, we utilise three established digital libraries ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ACM Digital Library</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Xplore Digital Library</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Springer Nature</i> ). We analysed and critically assessed the different approaches used in the three stages (perception, learning, inference) of a typical mobile emotion sensing framework, following a structured paper selection process. The contribution of this survey is three-fold; first, we document all the latest relevant literature on mobile emotion sensing research; second, we describe how mobile and wearable devices use their sensing and computing capabilities to monitor human emotions; third, we discuss challenges and opportunities of mobile emotion sensing to demonstrate the potential of this thriving field of research.