ID 2407: Helping Designers Design Mobile and Wearable Health Systems
Master’s Thesis
Objective
In cooperation with the Fraunhofer Institute for Digital Medicine MEVIS we aim to develop an all-encompassing framework that eases the path for designers to craft effective and user-friendly mobile and wearable health systems. Our vision is to merge theoretical insights and practical application for an enhanced design process for health technology.
Methodology
This work utilizes a mixed-method approach. We’ll start with a literature review and user interviews to gain real-world insights. Unveiling mobile and wearable systems’ design factors such as transparency and controllability is our first step into the larger exploration.
We aim to bridge the gap between academia and practical design. Through extensive analysis of each facet (transparancy, controllability, and further) and its design implications, a ‘design space’ of concrete design exemplars will be created. Out of that concrete tools that increase understanding and implementation will be developed.
One such tool is a ‘card toolbox.’ ([1,2]) designed for the mobile and wearable healthcare designers. The tool will be tested in a user study involving healthcare designers. This gives real-world validation to our tools and recommendations, sending them out into the field to make a real impact.
Profile
- strong research and analytical skills
- Knowledge of and/or strong interest in design theory, mobile and wearable technology and usibility studies
- Experience in design software and technical writing
Supervisors
[1] Nadal, C., McCully, S., Doherty, K., Sas, C., & Doherty, G. (2022, April). The TAC toolkit: supporting design for user acceptance of health technologies from a macro-temporal perspective. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 1-18).
[2] Buschek, D., Eiband, M., & Hussmann, H. (2022). How to Support Users in Understanding Intelligent Systems? An Analysis and Conceptual Framework of User Questions Considering User Mindsets, Involvement, and Knowledge Outcomes. ACM Transactions on Interactive Intelligent Systems, 12(4), 1-27.