肌电控制康复机器人助力中风患者腕部恢复

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"肌电控制腕机器人，用于中风康复" 本文详细探讨了肌电控制的腕部机器人在中风康复中的应用。脑卒中后，患者的运动恢复很大程度上依赖于早期主动参与康复训练以促进大脑的重塑。然而，现有的康复方法往往未能充分利用患者患侧肢体的自愿残余运动。因此，研究团队设计并实施了一种外骨骼型康复机器人系统，旨在通过肌电图（EMG）信号来控制手腕的屈伸运动，以增强患者的主动参与。该系统采用患侧的radial屈腕肌（FCR）和伸腕肌（ECR）的表面肌电图信号，为腕关节提供辅助扭矩。在为期20次的训练课程中，机器人为患者手腕提供恒定的阻力，以促进肌肉的锻炼和功能恢复。研究招募了16名中风患者，以评估该肌电控制机器人的性能和治疗效果。研究结果显示，通过肌电控制的辅助扭矩，中风患者能够实现更大的运动范围，同时激动剂肌肉的EMG信号强度显著降低。这表明患者能够在未完全恢复的运动范围内进行有效的训练。经过20次训练后，虽然实际手腕角度与目标角度之间的运动范围没有显著增加，但均方根误差（RMSE）显著减少，这意味着患者的运动精度有所提高。此外，患者在肌肉力量和临床量表上也表现出明显的改善，证实了该机器人辅助疗法的有效性。这项研究的结论是，通过肌电控制使患者自愿参与的机器人辅助康复可能对上肢运动恢复具有积极影响。这种创新的康复策略有望为中风患者的康复治疗提供新的途径，帮助他们更好地恢复运动功能，减少痉挛，改善运动模式，并最终提高生活质量。关键词：MUSCLE（肌肉）、SYSTEM（系统）、ELECTROMYOGRAPHY（肌电图）、HEMIPARESIS（偏瘫）、EXOSKELETON（外骨骼）、SPASTICITY（痉挛）、MOVEMENTS（运动）、PATTERNS（模式）、THERAPY（疗法）

RES E A R C H Open Access

Myoelectrically controlled wrist robot for stroke

rehabilitation

Rong Song

, Kai-yu Tong

, Xiaoling Hu

and Wei Zhou

Abstract

Background: Robot-assisted rehabilitation is an advanced new technology in stroke rehabilitation to provide

intensive training. Post-stroke motor recovery depends on active rehabilitation by voluntary participation of

patient’s paretic motor system as early as possible in order to promote reorganization of brain. However, voluntary

residual motor efforts to the affected limb have not been involved enough in most robot-assisted rehabilitation for

patients after stroke. The objective of this study is to evaluate the feasibility of robot-assisted rehabilitation using

myoelectric control on upper limb motor recovery.

Methods: In the present study, an exoskeleton-type rehabilitation robotic system was designed to provide

voluntarily controlled assisted torque to the affected wrist. Voluntary intention was involved by using the residual

surface electromyography (EMG) from flexor carpi radialis(FCR) and extensor carpi radialis (ECR)on the affected limb

to control the mechanical assistance provided by the robotic system during wrist flexion and extension in a 20-

session training. The system also applied constan t resistant torque to the affected wrist during the training. Sixteen

subjects after stroke had been recruited for evaluating the tracking performance and therapeutical effects of

myoelectrically controlled robotic system.

Results: With the myoelectrically-controlled assistive torque, stroke survivors could reach a larger range of motion

with a significant decrease in the EMG signal from the agonist muscles. The stroke survivors could be trained in the

unreached range with their voluntary residual EMG on the paretic side. After 20-session rehabilitation training, there

was a non-significant increase in the range of motion and a significant decrease in the root mean square error

(RMSE) between the actual wrist angle and target angle. Significant improvements also could be found in muscle

strength and clinical scales.

Conclusions: These results indicate that robot-aided therapy with voluntary participation of patient’s paretic motor

system using myoelectric control might have positive effect on upper limb motor recovery.

Background

Stroke is the first leading cause of motor disabilities in

many countries, which will significantly affect the daily

activities of stroke survivors. Rehabilitation training pro-

vides an opportunity to improve motor function. Conven-

tionally, it can be conducted by therapists in a one-on-one

manual mode in hospital. In the last two decades, many

advanced rehabilitation technologies are extensively devel-

oped, which provide repetitive, well-controlled assistance

for the patients and relieve therapist from labour-intensive

work [1-4].

Mechanical design is important to decide the joint

kinematics of the extremity in the robot-aided rehabilita-

tion training. There are two types of rehabilitation robot

from the mechanical design point of view: end-effector

based robots, and exoskeleton-type robots. MIT-MANUS

was an example to the end-effector based robots, which

interacted with subjects at the end of robot arm [4]. The

design of end-effector could adapt to subjects with differ-

ent body size. While exoskeleton-type robots can resemble

human anatomy and apply torque to specific joints, more-

over, the working-space of the rehabilitation training pro-

vided by such kinds of exoskeletions could approximate

the working-space performed by human subjects [2,3].

Control strategy is another important factor to affect the

training effect of robot-aided rehabilitation. MIT-MANUS

* Correspondence: k.y.tong@polyu.edu.hk

Interdisciplinary Division of Biomedical Engineering, The Hong Kong

Polytechnic University, Hung Hom Kowloon, Hong Kong

Full list of author information is available at the end of the article

JNER

JOURNAL OF NEUROENGINEERING

AND REHABILITATION

Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and

reproduction in any medium, provided the original work is properly cited.

Song et al. Journal of NeuroEngineering and Rehabilitation 2013, 10:52

http://www.jneuroengrehab.com/content/10/1/52

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