Design of interactive system interfaces using machine learning techniques: a review of design and usability

Authors

DOI:

https://doi.org/10.26439/interfases2022.n016.6028

Keywords:

user interface (UI), user experience (UX), machine learning (ML), usability

Abstract

This article presents different approaches to user interface design through machine learning techniques. It reviews various approaches to interface design, such as combinational optimizers, frameworks, and free-of-text interface design. Moreover, it shows how interface design with machine learning techniques is based on usability and user experience (UX). Likewise, the design process uses interactions stored in persistence systems or databases, which are then analyzed with machine learning techniques. Another design approach uses sketches and graphic layouts and, after evaluating their usability, uses image recognition algorithms to generate the interfaces; these designs are generally for mobile devices. Some techniques also analyze usability but focus more on the user’s bodily functions (movement, biological functions such as blood pressure, heartbeat, etcetera); this data can also be analyzed with machine learning algorithms to generate user interfaces.

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References

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Published

2022-12-23

Issue

Section

Review papers

How to Cite

Design of interactive system interfaces using machine learning techniques: a review of design and usability. (2022). Interfases, 16(016), 202-214. https://doi.org/10.26439/interfases2022.n016.6028