Quantitative evaluation of motor functional recovery process in chronic stroke patients during robot-assisted wrist training
Quantitative evaluation of motor functional recovery process in chronic stroke patients during robot-assisted wrist training
复制标题
DOI：
10.1016/j.jelekin.2008.04.002
复制
发表时间：
2009-08-01
影响因子：
2.5
通讯作者：
Au-Yeung, S. S. Y.
中科院分区：
文献类型：
--
作者：
Hu, X. L.;Tong, K. Y.;Au-Yeung, S. S. Y.
本研究旨在探讨慢性脑卒中患者在机器人辅助腕关节训练过程中运动功能的恢复过程。15名中风后患慢性上肢轻瘫的受试者使用交互式康复机器人参加了20次腕部跟踪训练。肌电图（EMG）参数，即，采用肱二头肌（BIC）、肱三头肌（TRI）、腕桡屈肌（FCR）和腕桡伸肌（ECR）4块肌肉的肌电图激活水平及其共收缩指数（CI）监测训练过程中神经肌肉的变化。FCR、BIC和ECR肌群的肌电激活水平在训练过程中均显著降低（P < 0.05），FCR肌群的肌电激活水平较训练前下降11.1%，BIC肌群的肌电激活水平较训练前下降17.1%，ECR肌群的肌电激活水平较训练前下降29.4%。腕关节和肘关节的改良Ashworth评分均降低（P < 0.05）。肌肉对的CI、BIC和TRI（较初始下降21%）、FCR和BIC（较初始下降11.3%）、ECR和BIC（较初始下降49.3%）也显著下降（P < 0.05）。与BIC肌肉相关的CI降低主要是由BIC EMG激活水平的降低引起的，这表明腕部运动与手肘运动的更好隔离。运动后期ECR和FCR的CI降低（P < 0.05），是由于在跟踪任务中拮抗肌对的共收缩期减少。训练前后Fugl-Meyer评估的肩/肘和腕/手评分相关的运动结果也有显著改善（P < 0.05）。根据肌电参数沿着训练过程的演变，由于肌电参数的下降在训练结束前没有达到稳定状态，因此可以通过提供更多的训练课程来获得进一步的运动改善。本研究结果为进一步了解脑卒中后机器人辅助腕关节运动恢复的神经肌肉机制提供了客观、定量的肌电测量手段。(C)2008爱思唯尔有限公司版权所有。
This study was to investigate the motor functional recovery process in chronic stroke during robot-assisted wrist training. Fifteen subjects with chronic upper extremity paresis after stroke attended a 20-session wrist tracking training using an interactive rehabilitation robot. Electromyographic (EMG) parameters, i.e., EMG activation levels of four muscles: biceps brachii (BIC), triceps brachii (TRI, lateral head), flexor carpiradialis (FCR), and extensor carpiradialis (ECR) and their co-contraction indexes (CI) were used to monitor the neuromuscular changes during the training course. The EMG activation levels of the FCR (11.1% of decrease from the initial), BIC (17.1% of decrease from the initial), and ECR (29.4% of decrease from the initial) muscles decreased significantly during the training (P < 0.05). Such decrease was associated with decreased Modified Ashworth Scores for both the wrist and elbow joints (P < 0.05). Significant decrease (P < 0.05) was also found in CIs of muscle pairs, BIC&TRI (21% of decrease from the initial), FCR&BIC (11.3% of decrease from the initial), ECR&BIC (49.3% of decrease from the initial). The decreased CIs related to the BIC muscle were mainly caused by the reduction in the BIC EMG activation level, suggesting a better isolation of the wrist movements from the elbow motions. The decreased CI of ECR&FCR in the later training sessions (P < 0.05) was due to the reduced co-contraction phase of the antagonist muscle pair in the tracking tasks. Significant improvements (P < 0.05) were also found in motor outcomes related to the shoulder/elbow and wrist/hand scores assessed by the Fugl-Meyer assessment before and after the training. According to the evolution of the EMG parameters along the training course, further motor improvements could be obtained by providing more training sessions, since the decreases of the EMG parameters did not reach a steady state before the end of the training. The results in this study provided an objective and quantitative EMG measure to describe the motor recovery process during poststroke robot-assisted wrist for the further understanding on the neuromuscular mechanism associated with the recovery. (C) 2008 Elsevier Ltd. All rights reserved.