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Exploring the effect of training on muscle synergies and kinematics of a task

机译：探索训练对任务的肌肉协同作用和运动学的影响

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In this preliminary study we aim to extract muscle synergies in spiral tracking task when performed with the non-dominant hand, and investigate the effect of training on muscle synergies. Three young subjects who were university students (all Females, 21±1 years old, right-handed) volunteered to participate in this study. The subjects were healthy with no history of neuromuscular disease. Each subject performed one of the three tasks chosen randomly in five sessions. The tasks were to track either a circle in a limited time, or a circular spiral or a square spiral. During the task, the trajectory of the pen and EMG signals from eight muscles of the non-dominant hand were simultaneously recorded. Afterwards, the EMG signals were factorized using the Non-Negative Matrix Factorization (NMF) method and synergy modules were extracted. While extracting muscle synergies using NMF, we used the Variance Accounted For (VAF) criteria in order to determine the optimized number of modules. Three synergy modules were determined as the optimum number for the primary EMG signals reconstruction. The P index was introduced to compare the changes in muscle synergies during the training. This index stands for the correlation between the muscle synergies of the trials of each session with the average of muscle synergies in the same session. The results show that mean square error between the desired and the actual trajectories, regardless of the type of training, has decreased for all three subjects. This indicates that the subjects have learned the task during the training sessions. This was incorporated as an index of participants' skill. Moreover, changes in the P index correspond noticeably with subjects tracking skill. In addition, this index can be adjusted during training and there have been noticeable changes in its value between the sessions. The results convey that central nervous system (CNS) adjusts muscle synergies defining given motor behaviors to the desired synergy space, which is the average of synergies, during the training.
机译：在初步研究中，我们的目的是当用非显着手进行的螺旋跟踪任务中提取肌肉协同作用，并调查培训对肌肉协同作用的影响。三个年轻科目是大学生（所有女性，21±1岁，右手）自愿参加这项研究。受试者没有神经肌病病史健康。每个主题在五个会话中随机选择的三个任务中的一个。任务是在有限的时间内跟踪圆圈，或圆螺旋或方形螺旋。在任务期间，同时记录了来自非显着手的八个肌肉的笔和EMG信号的轨迹。然后，使用非负矩阵分解（NMF）方法来分解EMG信号，并提取协同模块。使用NMF提取肌肉协同效应时，我们使用占（VAF）标准的方差以确定优化的模块数。三个协同模块被确定为主EMG信号重建的最佳数字。引入P索引以比较培训期间肌肉协同效应的变化。该指数代表每次会话试验的肌肉协同效应与同一会议中的肌肉协同效应的平均相关性之间的相关性。结果表明，所有三个受试者都有所需和实际轨迹之间所需和实际轨迹之间的平均误差。这表明该科目在培训会议期间已经学会了这项任务。这被纳入参与者的技能指数。此外，P索引的变化明显与受试者跟踪技能相对应。此外，可以在培训期间调整该索引，并且在会话之间存在显着的变化。结果传达了中枢神经系统（CNS）调整培训期间，将给定的电机行为定义的肌肉协同作用调整为所需的Synergy空间，这是培训期间的平均增量。

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