A robotic assistant based on fuzzy logic and kinesthetic stimuli for gross motor rehabilitation of children with disabilities

Cerebral Palsy (CP) is considered one of the most common types of motor disability in childhood. Worldwide the latest estimates claim that prevalence of CP is between 1.5 to more than 4 per 1,000 live births. In the same way, children and adolescents with intellectual disabilities are characterized by deficits in fundamental movement skills. For these reasons, it is essential providing early intervention plans for children that present motor difficulties. In this line, this paper describes a robotic assistant that adapts the velocity of its movements to respond to the patient’s profile during therapy sessions. To this aim, the robot uses a fuzzy logic-based inference module that considers three variables of the patient’s profile: disability level, intelligence quotient, and age. During the robot’s preliminary validation, we have obtained encouraging results in both laboratory tests and in the interaction with experts.