Wei Wang

Research Fellow

“We feel and know that we are eternal”

Baruch Spinoza

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Towards Adaptive User Interfaces: A Model-Driven Approach for mHealth Applications Targeting Chronic Disease

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1

Abstract

This paper explains a PhD research direction about adaptive user interfaces in mobile health apps.

The problem is that many health apps use a one-size-fits-all design. This can make apps harder to use for people with chronic diseases.

The paper proposes a model-driven approach for designing interfaces that can change based on a person’s needs.

The goal is to make mobile health apps easier to use, more personal, and more supportive over time.

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🔍 Abstract

The increasing prevalence of chronic diseases and the importance of self-management highlight the need for user-friendly mHealth systems that cater to the diverse needs of users. However, existing applications often employ a one-size-fits-all design strategy, overlooking individual user characteristics and interaction history. As a result, there is a noticeable research gap when it comes to AUIs for chronic disease-related applications, indicating the need of further investigation in this area. In this paper, I provide an overview of my current progress, including the findings from a systematic review of AUI research in the chronic disease domain and preliminary results regarding end users’ understanding and expectations regarding AUI solutions for individuals with particular chronic diseases.

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📝 Citation

Wei Wang. "Towards Adaptive User Interfaces: A Model-Driven Approach for mHealth Applications Targeting Chronic Disease." In 2023 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pp. 296-298. IEEE, 2023. UPV