Tele-rehabilitation System Based on Augmented Feedback for People with Parkinson’s Disease: Design Principles

Recent advances both in the technological and scientifi c fi elds allow the development of novel systems for motor and cognitive rehabilitation in subjects with Parkinson’s disease (PD) based on wearable sensors, on-board intelligence and new motor learning and biofeedback principles. It is in fact possible to obtain information about body movement by means of unobtrusive sensor(s) positioned on the trunk and other body segments (legs, arms) and processing the signals by a portable and unobtrusive unit, which may even be a smartphone or a dedicated miniaturized embedded system. The main requirement of a system to be worn by a PD patient is that of being as transparent as possible for the user. Hence an adequate processing capability on a sensor node is desirable, together with more advanced computational capability on the main processing unit. Regarding algorithms, it is essential to transform raw signals to informative data, which can either be information about impairment or amelioration of specifi c movements, or coding of movements into biofeedback instructions to guide the user in performing a specifi c motor task. The need for a continuous, accessible and personalized neuro-rehabilitative program requires the service to be delivered in the patient’s home environment, necessitating a telemedicine infrastructure.