Sens-e-motion: Capturing and visualising emotional status of computer users in real time

Emotion has been demonstrated to play an important role in the learning process. The capturing of these emotions is increasingly being digitally automated as researchers explore how technology can enhance student learning as well as teaching methodologies. More specifically, what emotions should be captured and how information about the captured emotions should be visualised has not been well researched in the context of teaching and learning. The study presented in this paper aims to produce a proof of concept prototype, called Sens-e-motion, that integrates multiple types of digital emotional monitoring and visualises the results in a meaningful way to the users. The monitoring includes facial expression recognition, blink-rate, text sentiment analysis, and keyword analysis. The prototype was designed and implemented as a web chat application with a RESTful web service backend and a NoSQL database. In this paper, we present the design of our system and describe technical details of it. Possible future research and development is also discussed.