Improving context-aware applications for the well-being domain: Model-driven design guided by medical knowledge

Computing applications for among others well-being and health become increasingly advanced as a result of their sensor-based awareness of the context in which they are used. Context-aware applications have the potential of providing enriched services to their users, i.e. services that are appropriate for the context at hand. A challenge for the design of context-aware applications is to identify and develop service enrichments which are effective and useful while not being overly complex and costly. It is hard to imagine, both for the designer and end-user, all possible relevant contexts and best possible corresponding enriched services. An enriched service which is not appropriate for the context at hand can irritate or even harm the user, and (eventually) leads to avoiding the use of the service. This paper discusses a model-driven approach that incorporates domain knowledge concerning the causal relationship between context factors and human conditions. We believe that such an approach facilitates the identification and development of appropriate sensor-based context-aware services. We focus on context-aware applications for the well-being domain