Emotion Recognition in Usability Testing: A Framework for Improving Web Application UI Design

Abstract

Traditional usability testing methods often lack the ability to fully capture different aspects of the user experience (UX). The focus of this research work is to propose a framework and develop its comprehensive prototype to improve usability testing and UX analysis by integrating session recording, interaction logging, and emotion recognition methods. A trained emotion recognition model based on MobileNetV2 architecture in conjunction with Hotjar and Google Analytics is proposed to add more context to the user experience during usability testing. The results obtained during the testing of a developed framework prototype showed that UI testing based on UX principles and integration of emotion recognition can be a powerful tool for improving the UI of web applications. It is recommended to improve UI testing processes by incorporating these aspects and data analysis methods. This would provide a more complete and more objective picture of the usability of the interface.