The concept of self-adapting applications delivering enriched end-user services is highly promising. These context-aware applications can be seen in increasing numbers in a wide range of fields, including that of health and well-being. Using sensors to collect context data and smart reasoning algorithms to deduce higher-level information, they have the potential to adapt their behavior in real time to better suit the context at hand. However, the development process for these types of systems is challenging, as the user needs and preferences in different contexts are not easy to anticipate at design time. If services offered by the application do not align with the user needs in some situations, the user may disregard the application altogether. In order to address this challenge, we propose to use medical knowledge related to well-being in the development process of context-aware well-being systems. We believe that this approach allows for improved identification and design of effective context-aware services for well-being support.
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