The successful implementation of pervasive computing technologies in healthcare does not only depend on technical issues but also on acceptability and acceptance issues. In this paper we focus on factors that facilitate or inhibit user acceptance of pervasive computing in healthcare. We present selected findings of the research project dasiaPerCoMed - Pervasive Computing in Healthcarepsila. The project is based on two case studies in pre- and post-clinical healthcare. In the first study, the potential of pervasive computing technologies for the treatment of acute cardiovascular diseases is investigated, in the second case study, the potential for the treatment of multiple sclerosis (MS) is evaluated. A qualitative user acceptance analysis of the two case studies shows the following results: the main factor of user acceptance is the perceived medical usefulness. Furthermore, acceptance is strongly inhibited if data privacy or if subjective norms are violated. Usability only presents a decisive factor of acceptance if problems with usability reduce the perceived usefulness.
Two case studies revealed a number of crucial factors for the adoption of pervasive computing in healthcare. These factors included proof of medical benefit, user participation, and financial clarification. The case studies were conducted under the Pervasive Computing in Medical Care (PerCoMed) project to analyze the risks and obstacles, along with the benefits and potentials of pervasive computing in healthcare. The Stroke Angel and the MS Nurses case studies were specifically conducted in real healthcare settings with real end users, such as patients and medical personnel, to examine the stages of innovation from prototype development to routine use. The Stroke Angel case study covered the adoption of a mobile stroke diagnosis and data transmission device for emergency medical services (EMS). Stroke Angel was evaluated through a process analysis and a user acceptance analysis.