A Multimodal Deep Log-Based User Experience (UX) Platform for UX Evaluation

Sensors (Basel). 2018 May 18;18(5):1622. doi: 10.3390/s18051622.

Abstract

The user experience (UX) is an emerging field in user research and design, and the development of UX evaluation methods presents a challenge for both researchers and practitioners. Different UX evaluation methods have been developed to extract accurate UX data. Among UX evaluation methods, the mixed-method approach of triangulation has gained importance. It provides more accurate and precise information about the user while interacting with the product. However, this approach requires skilled UX researchers and developers to integrate multiple devices, synchronize them, analyze the data, and ultimately produce an informed decision. In this paper, a method and system for measuring the overall UX over time using a triangulation method are proposed. The proposed platform incorporates observational and physiological measurements in addition to traditional ones. The platform reduces the subjective bias and validates the user's perceptions, which are measured by different sensors through objectification of the subjective nature of the user in the UX assessment. The platform additionally offers plug-and-play support for different devices and powerful analytics for obtaining insight on the UX in terms of multiple participants.

Keywords: EEG; eye-tracking; facial expression; galvanic skin response; interaction tracker; mix-method approach; self-reporting; user experience evaluation; user experience measurement; user experience platform.