Muscle Synergies Control during Hand-Reaching Tasks in Multiple Directions Post-stroke.

Muscle Synergies Control during Hand-Reaching Tasks in Multiple Directions Post-stroke.
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DOI:
10.3389/fncom.2018.00010
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发表时间:
2018
影响因子:
3.2
通讯作者:
Carmeli E
Carmeli E
中科院分区:
医学4区
文献类型:
--
作者:
Israely S;Leisman G;Machluf CC;Carmeli E

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目的:提出肌肉协同模型来代表脑干和脊髓的简化运动控制机制。本研究的目的是调查的可行性,这种控制机制在中风后的个人在多个方向的手达到运动的执行过程中,与非中风个人的康复。方法:12名非脑卒中和13名脑卒中后患者参加了这项研究。肌肉协同作用提取的EMG数据,记录在手达到任务,使用NMF算法。使用方差占比(VAF)和均方误差(MSE)评价两组的最佳协同作用次数。交叉验证程序进行了定义一组有代表性的协同作用。应用相似性指数和K-means算法验证了这组协同效应的存在,同时也比较了不同运动方向下群体间协同效应的调制特性。采用相似性指数和系统聚类分析方法对各组间协同效应进行了比较。结果如下:选择四种协同作用以最佳地捕获EMG数据中的方差,对照组和研究组的平均VAF分别为0.917 ± 0.034和0.883 ± 0.046的数据方差,各自的MSE分别为0.007和0.016。协同作用的代表性集合被设置为从向可达空间的中心的运动中提取。两种协同作用在组间具有不同的肌肉激活平衡。7个和17个聚类划分了对照组和研究组的肌肉协同作用。对照组表现出在协同作用的时域(调制)中的振幅激活的逐渐变化,如由相似性指数所反映的,而研究组表现出所有运动方向和协同作用的代表性集合之间的一致的显著差异。研究结果支持存在一组具有代表性的协同作用,这些协同作用被调节以执行不同方向的运动。结论:脑卒中后个体与非脑卒中个体相比,对不同运动方向协同激活的调节不同。不同的肌肉激活平衡,相似值和组间协同作用的不同分类支持了这一结论。
Purpose: A muscle synergies model was suggested to represent a simplifying motor control mechanism by the brainstem and spinal cord. The aim of the study was to investigate the feasibility of such control mechanisms in the rehabilitation of post-stroke individuals during the execution of hand-reaching movements in multiple directions, compared to non-stroke individuals. Methods: Twelve non-stroke and 13 post-stroke individuals participated in the study. Muscle synergies were extracted from EMG data that was recorded during hand reaching tasks, using the NMF algorithm. The optimal number of synergies was evaluated in both groups using the Variance Accounted For (VAF) and the Mean Squared Error (MSE). A cross validation procedure was carried out to define a representative set of synergies. The similarity index and the K-means algorithm were applied to validate the existence of such a set of synergies, but also to compare the modulation properties of synergies for different movement directions between groups. The similarity index and hierarchical cluster analysis were also applied to compare between group synergies. Results: Four synergies were chosen to optimally capture the variances in the EMG data, with mean VAF of 0.917 ± 0.034 and 0.883 ± 0.046 of the data variances, with respective MSE of 0.007 and 0.016, in the control and study groups, respectively. The representative set of synergies was set to be extracted from movement to the center of the reaching space. Two synergies had different muscle activation balance between groups. Seven and 17 clusters partitioned the muscle synergies of the control and study groups. The control group exhibited a gradual change in the activation in the amplitude in the time domain (modulation) of synergies, as reflected by the similarity index, whereas the study group exhibited consistently significant differences between all movement directions and the representative set of synergies. The study findings support the existence of a representative set of synergies, which are modulated to execute movements in different directions. Conclusions: Post-stroke individuals differently modulate the activation of synergies to different movement directions than do non-stroke individuals. The conclusion was supported by different muscle activation balances, similarity values and different classifications of synergies among groups.
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