ABSTRACT
Home-based hand rehabilitation has excellent potential as it may reduce patient dropouts due to travel, transportation, and insurance constraints. Being able to perform exercises precisely, accurately, and in a repetitive manner, robot-aided portable devices have gained much traction these days in hand rehabilitation. However, existing devices fall short in allowing some key natural movements, which are crucial to achieving full potential motion in performing activities of daily living. Firstly, existing exoskeleton type devices often restrict or suffer from uncontrolled wrist and forearm movement during finger exercises due to their setup of actuation and transmission mechanism. Secondly, they restrict passive metacarpophalangeal (MCP) abduction-adduction during MCP flexion-extension motion. Lastly, though a few of them can provide isolated finger ROM, none of them can offer isolated joint motion as per therapeutic need. All these natural movements are crucial for effective robot-aided finger rehabilitation. To bridge these gaps, in this research, a novel lightweight robotic device, namely "Flexohand", has been developed for hand rehabilitation. A novel compliant mechanism has been developed and included in Flexohand to compensate for the passive movement of MCP abduction-adduction. The isolated and composite digit joint flexion-extension has been achieved by integrating a combination of sliding locks for IP joints and a wire locking system for finger MCP joints. Besides, the intuitive design of Flexohand inherently allows wrist joint movement during hand digit exercises. Experiments of passive exercises involving isolated joint motion, composite joint motions of individual fingers, and isolated joint motion of multiple fingers have been conducted to validate the functionality of the developed device. The experimental results show that Flexohand addresses the limitations of existing robot-aided hand rehabilitation devices.
ABSTRACT
The research presents a novel controller designed for robotic systems subject to nonlinear uncertain dynamics and external disturbances. The control scheme is based on the modified super-twisting method, input/output feedback linearization, and time delay approach. In addition, to minimize the chattering phenomenon and ensure fast convergence to the selected sliding surface, a new reaching law has been integrated with the control law. The control scheme aims to provide high performance and enhanced accuracy via limiting the effects brought by the presence of uncertain dynamics. Stability analysis of the closed-loop system was conducted using a powerful Lyapunov function, showing finite time convergence of the system's errors. Lastly, experiments shaping rehabilitation tasks, as performed by healthy subjects, demonstrated the controller's efficiency given its uncertain nonlinear dynamics and the external disturbances involved.
ABSTRACT
STUDY DESIGN: Descriptive. INTRODUCTION: Rehabilitation programs that focus on motor recovery of the upper limb require long-term commitment from the clinicians/therapists, require one-to-one caring, and are usually labor-intensive. PURPOSE OF THE STUDY: To contribute to this area, we have developed a sensored hand glove integrated with a computer game (Flappy Bird) to engage patients playing a game where the subject's single/multiple fingers are involved, representing fine motor skill occupational therapeutic exercises. METHODS: We described the sensored rehab glove, its hardware design, electrical and electronic design and instrumentation, software design, and pilot testing results. RESULTS: Experimental results supported that the developed rehab glove system can be effectively used to engage a patient playing a computer game (or a mobile phone game) that can record the data (ie, game score, finger flexion/extension angle, time spent in a therapeutic session, etc.) and put it in a format that could be easily read by a therapist or displayed to the therapists/patients in different graph formats. CONCLUSIONS: We introduced a sensored rehab glove for home-based therapy. The exercise training using the glove is repetitious, functional, and easy to follow and comply with.
