A fuzzy-based adaptive rehabilitation framework for home-based wrist training

Computer-based rehabilitation systems have emerged as promising assistive tools for effective training and diagnosis and gained popularity in clinical settings. For many patients, home-based rehabilitation can be really beneficial in their therapy journeys since it can eliminate the obstacles encountered by many of them in clinics, such as travel distance and cost. However, an effective home-training system requires a good adaptation mechanism that conforms to both the patient's abilities and the therapist's performance requirements. This paper introduces a Web-enabled wrist rehabilitation framework that adopts the fuzzy logic approach to provide adaptive tasks for the patient while considering the therapist training guidance. We also assess the effectiveness of the framework while coping with different training parameters by simulating a number of performance scenarios and experimenting with normal subjects. Simulation results, as well as experimental analysis, demonstrated the ability of the proposed framework to adapt to patient's performance and therapist's feedback.