In order to maximise recovery, therapy should be tailored to each patient individually. This can be done by adapting therapy exercises based on the initial level of impairment of the patient and on the performance reached during the different therapy sessions. Such therapy personalization ensures that patients stay motivated throughout the therapy. Robots can provide objective measurements to assess the impairment level of the patient and to monitor improvements throughout the therapy. These features empower continuous adaptation of the difficulty level of the exercises and of the therapy plan, according to the patient’s needs. Assessment-driven therapy is a promising method, which has the potential to truly optimize the current approach to rehabilitation. However, some challenges need to be addressed before this method can be implemented in the clinics, such as the choice of relevant assessments and parameters to ensure a meaningful and efficient adaptation.
T2-Minimally-supervised robot-assisted therapy in the clinic.
Therapy dose seems to be a limiting factor for patients’ recovery. Some studies suggested that increasing the dose may lead to better recovery. However, due to limited resources, clinics cannot easily implement more intensive therapy plans. Minimally-supervised robot-assisted therapy might be an alternative solution to increase therapy dose without increasing the burden of work for the therapists, since the patients could train with the robots without constant supervision. However, to minimize therapists’ intervention, these devices need to meet several requirements, such as high usability and ability to adapt the therapy plan to the patients. Clinicians and engineers should discuss which functions can be better trained and which type of device should be used during minimally-supervised therapy. Importantly, therapists’ experience should be considered when implementing decision-making algorithms into the robots. Tight collaboration is needed in order to efficiently integrate minimally-supervised robotic therapy into the clinical environment.
T3-Minimally-supervised robot-assisted therapy at home:
Robots suitable for home-use need to be developed to strengthen the continuum of therapy after discharge from clinics. Tight collaborations between engineers and clinicians allow the development of appropriate devices maximising compliance and therapy effectiveness, at the same time taking into account portability and low cost.