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|Title:||The effectiveness of combined robotic hand training with neuromuscular electrical stimulation for the stroke rehabilitation||Authors:||Rong, Wei||Degree:||M.Phil.||Issue Date:||2013||Abstract:||Stroke is one of the leading causes of long-term disability worldwide. Most stroke survivors suffer from upper extremity dysfunction and require long-term post-stroke rehabilitation to regain their impaired arm functions, especially hand functions. Novel rehabilitation techniques are needed to provide more effective rehabilitation treatment than the conventional therapy. The neuromuscular electrical stimulation (NMES) technique is widely used in stroke rehabilitation to reduce muscle spasticity, increase muscle strength and improve motor function recovery. Robot-assisted therapy, which has been developed in recent years for post-stroke rehabilitation, could be a valuable part of long-term, task-related, high-intensity training programs. Currently, NMES and robotic techniques are utilized separately in hand rehabilitation, and the effectiveness of a combination of NMES and robotic techniques has not been studied. The aim of this study is to develop a new robotic hand system that is combined with the NMES technique to investigate its effectiveness on post-stroke rehabilitation. The NMES-robot system developed for this study was continuously controlled by electromyography (EMG) from volitional muscle activities on the muscles that related to finger extension and flexion on the affected side of stroke subjects. A tracking task experiment with nine different assistive combinations from the NMES and robot components was designed to evaluate the system performance of chronic stroke subjects (n = 8). The results showed that the assistance from the robot could improve the range of motion (ROM) during finger extension and enhance the movement accuracy with reduced root mean square error (RMSE). The assistance from the NMES component could increase the voluntary muscle activities on finger joint, reduce the excessive muscular activities on elbow joint, and improve the muscle coordination of finger and elbow joints. The results indicated that the best combination was when the assistance from the NMES and robot was 50% and 50%, respectively, which resulted in the lowest RMSE during the finger-tracking task, with larger ROM, higher voluntary muscle activations on the finger joints, and less muscle co-contraction on finger and elbow joints.
A 20-session training program with this NMES-robot system was developed and conducted in a pilot study with stroke subjects (n = 3) to investigate the training effects of the system for post-stroke hand rehabilitation. All the subjects improved their hand function after the 20-session training program, which was reflected by the changes in clinical outcome measurements of Action Research Arm Test (ARAT), Fugl-Meyer Assessment on shoulder and elbow (FMA S/E) and Wolf Motor Function Test (WMFT). Reduced muscle spasticity was also observed after the training via decreased Modified Ashworth Scale (MAS). The EMG analysis results suggested that the upper limb training program with the assistance from the NMES-robot system could improve muscle coordination between agonist and antagonist muscle pairs on finger and elbow joints. This is the first study to investigate the combined effects of the NMES and robot on hand rehabilitation. The finger tracking performance was improved with the combined assistance from the EMG-driven NMES-robot hand system. The upper limb functions were improved on chronic stroke patients after the 20-session hand training with the combined assistance from the EMG-driven NMES-robot. The findings demonstrated EMG-driven NMES-robot applied to the chronic stroke improved hand function and tracking performance.
|Subjects:||Cerebrovascular disease -- Patients -- Rehabilitation.
Hong Kong Polytechnic University -- Dissertations
|Pages:||x, 124 leaves : ill. (some col.) ; 30 cm.|
|Appears in Collections:||Thesis|
View full-text via https://theses.lib.polyu.edu.hk/handle/200/7364
Citations as of Oct 1, 2023
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