Human-Computer Interaction with Adaptable & Adaptive Motion-based Games for Health

Jan David Smeddinck

Physical activity plays a major role both in prevention and in the treatment of afflictions linked to a modern sedentary lifestyle and improvements on life expectancy, for example though the application area of physiotherapy. Motion-based games for health (MGH) are being discussed in research and industry for their ability to play a supportive role in health, by offering motivation to engage in treatments, objective insights on status and development, and guidance regarding treatment activities. Difficulty settings in games are typically limited to few discrete tiers. For most serious applications in health, more fine-grained and far-reaching adjustments are required. The need for applying adjustments on complex sets of parameters can be overwhelming for patient-players and even trained professionals. Automatic adaptivity and efficient manual adaptability are thus major concerns for the design and development of MGH. Despite a growing amount of research on specific methods for adaptivity, general considerations on human-computer interaction with adaptable and adaptive MGH are rare. This thesis therefore focuses on establishing and augmenting theory for adaptability and adaptivity in human-computer interaction in the context of MGH. Working with older adults and people with Parkinson's disease as frequent target groups that can benefit from tailored activities, explorations and comparative studies that investigate the design, acceptance, and effectiveness of MGH are presented. The outcomes encourage the application of adaptivity for MGH following iterative human-centred design that considers the respective interests of stakeholders, provided that the users receive adequate information and are empowered to exert control over the automated system when desired or required, and if adaptivity is embedded in such a way that it does not interfere with the users' sense of competence or autonomy.

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