SHECARE: Shared Haptic Environment on the Cloud for Arm Rehabilitation Exercises

Abstract

It is well known that home exercise is as good as rehab center. Unfortunately, passive devices such as dumbbells, elastic bands, stress balls and tubing that have been widely used for home-based arm rehabilitation do not provide therapists with the information needed to monitor the patient’s progress, identify any impairment, and suggest treatments. Moreover, the lack of interactivity of these devices turns the rehabilitation exercises into a boring, unpleasant task. In this thesis, we introduce a family of home-based post-stroke rehabilitation systems aimed at solving the aforementioned problems. We call such applications: “Shared Haptic Environment on the Cloud for Arm Rehabilitation Exercises (SHECARE)”. The systems combine recent rehabilitation approaches with efficient, yet affordable skeleton tracking input technologies, and multimodal interactive computer environment. In addition, the systems provide a real-time feedback to the stroke patients, summarize the feedback after each session, and predict the overall recovery progress. Moreover, these systems show a new style of home-based rehabilitation approach that motivate the patients by engaging the whole family and friends in the rehabilitation process and allow the therapists to remotely assess the progress of the patients and adjust the training strategy accordingly. Two mathematical models have been presented in this thesis. The first model is developed to find the relationship between upper extremity kinematics and the associated forces/strength. The second model is used to evaluate the medical condition of the stroke patients and predict their recovery progress depending on their performance history. The objective assessments, clinical tests, and the subjective assessments, usability studies have shown the feasibility of the proposed systems for rehabilitation in stroke patients with upper limb motor dysfunction.