Furthermore, the distribution over the years within each of the criteria is presented. In this review, a set of 97 publications representing 72 active exoskeletal devices for hand assistance and rehabilitation is analysed.
To this end, we propose a set of classification criteria to help categorise devices. To date, a multitude of exoskeletal devices employing distinct technologies have been proposed, making navigating this field a challenging task. Robots are effective tools for aiding in the restoration of hand function through rehabilitation programs or by providing in-task assistance. This study provides a solution to potential problems in the family-oriented application of exoskeleton rehabilitation robots. The results indicate that the exoskeleton rehabilitation robot can output the corresponding torque to assist in progressive resistance training. Muscle activity of biceps brachii and triceps brachii under each training load decreases significantly when subjects with the exoskeleton robot. The assessment experiment of the exoskeleton rehabilitation robot shows that the dynamic recognition accuracy of this control method is 80.21%. We also propose a surface electromyography-based control method, which uses k- Nearest Neighbor algorithm to classify surface electromyographic signals under progressive training loads, and utilizes principal component analysis to improve the recognition accuracy to control the exoskeleton to provide muscle strength compensation. According to the rehabilitation training task, we use torque limit mode to ensure stable torque output at variable velocity. At the same time, the overall weight of the exoskeleton is controlled at only 3.03 kg.
The exoskeleton’s lightweight structure is designed based on the kinematic model of the elbow joint and ergonomics sizes of the arm. This article aims to design a surface electromyography-controlled lightweight exoskeleton rehabilitation robot for home-based progressive resistance training. However, there are few studies on upper arm exoskeletons for rehabilitation training of muscle strength. Nowadays, the rehabilitation robot has been developed for rehabilitation therapy. This paper reviews the current research status of hand function rehabilitation devices based on various types of hand motion recognition technologies and analyzes their advantages and disadvantages, reviews the application of artificial intelligence in hand rehabilitation robots, and summarizes the current research limitations and discusses future research directions. The recovery of motor function is achieved chiefly through compensatory strategies, such as hand rehabilitation robots, which have been available since the end of the last century. Therefore, one of the essential goals of post-stroke rehabilitation is to restore hand function. In hemiplegic patients with movement disorders, the impairment of upper limb function, especially hand function, dramatically limits the ability of patients to perform activities of daily living (ADL). Various sensory, motor, cognitive and psychological disorders may remain in the patient after survival from a stroke. The incidence of stroke and the burden on health care and society are expected to increase significantly in the coming years, due to the increasing aging of the population.
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