User Modelling for Patient Tailored Virtual Rehabilitation

Intelligent rehabilitation is a novel paradigm in motor rehabilitation empowering assistive technology with artificial intelligence (AI). Central to this paradigm is adaptation, the capacity of the assistive technology to dynamically accommodate to the therapy evolving demands. This chapter overviews several existing AI solutions to implement a decision making model to provide rehabilitation tools with adaptation capabilities, and provides details of a powerful approach capable of exploiting prior knowledge for a quick start and posterior knowledge to guarantee up-to-dated informed decisions. In this solution, a Markov decision process formulates an initial policy optimal within prior knowledge; a policy which is later on allow to evolve on incoming evidence to fit new requirements. This solution ensures short training periods and exhibits convergence with therapists’ criteria. In consequence, intelligent adaptation to dynamic circumstances of the patient and therapy plan is demonstrated a feasible endeavour within a real practical timeline. This might endow assistive technology with the necessary competence to be taken home and/or reduce expert surpervision.