Research project The project will be focused on the case study of preventative physiotherapy for fall prevention. Preventative physiotherapy training is an increasingly important part of aging well. Emerging AI systems present novel opportunities for transforming physiotherapy. Coming to market already are products that allow patients to train at home, where the technology can assess their capabilities and suggest individual training programs.
The aim is to explore how to design novel preventive AI-based physiotherapy interventions for home environments directed at different segments of the population, while at the same time critically reflect on the role of technologies in these types of interventions.
The project combines a design-oriented investigation of the domain with targeted development of adequate machine learning technology and hardware. Technically, we focus specifically on novel movement analysis methods using machine learning techniques to process video or biosensory data, that can assist in balance exercises at home. This creates the need to influence technologies from a careful understanding of the practices and settings that they will be integrated into. The design research will be guided by the question: “How to make human movement models available as a design material for the design of new preventative physiotherapy interventions?”. The aim is to explore how to design novel preventive AI-based physiotherapy interventions for home environments directed at different segments of the population, while at the same time critically reflect on the role of technologies in these types of interventions.
