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EMG Patterns in Robot Assisted Reaching Movements of Upper Arm

机译:机器人辅助上臂伸手动作中的肌电图模式

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摘要

Variations in muscle activation, underlying improvements in muscle strength and muscle function, in response to training of patients with congenital or acquired brain injuries, are still poorly understood. Much better results in sensorimotor and cognitive processes are promised by the emerging robot-mediated therapy. One of the most interesting features of a robot-mediated therapy is the ability to quantify the performance of the rehabilitation tasks proposed to the patient. Although the shoulder is the most complex joint in the body, both as to freedom range and for the muscular-tendon structure, not so many commercial or research devices have been proposed to study its movements and no study has proposed a standardized, quantitative electromyographic assessment during robot-assisted reaching movements of the upper arm. This study aimed to develop a quantitative assessment of the electromyographic pattern of the arm's muscles involved in reaching movements robot-assisted by means of indices used to describe effectively the main features of the pattern in four normal subjects and to implement rehabilitation strategies patients oriented. Each subject underwent the proposed motor task and EMG recording, repeating the trial three times; for a total of twelve reaching movements for each sequence. Number of EMG activations and deactivations recorded for each of the eight studied muscles are gathered. The proposed method effectively described the main pattern's features in normal subjects.
机译:响应于对先天性或后天性脑损伤患者的训练,肌肉活化的变化,肌肉力量和肌肉功能的根本改善仍然知之甚少。新兴的机器人介导的疗法有望在感觉运动和认知过程中取得更好的结果。机器人介导的治疗方法最有趣的功能之一是能够对建议给患者的康复任务进行量化。尽管就自由范围和肌腱结构而言,肩部是人体中最复杂的关节,但并未提出太多用于研究其运动的商业或研究装置,也没有研究提出标准化的定量肌电图评估方法在机器人辅助上臂的移动过程中。这项研究旨在通过指标来定量评估机器人参与协助运动的手臂肌肉的肌电图模式,该指标可有效描述四个正常受试者的肌电图模式的主要特征,并实施以患者为导向的康复策略。每个受试者都接受了建议的运动任务和EMG记录,重复了3次试验;每个序列总共十二个到达动作。收集记录的八种研究肌肉中每一种的肌电图激活和失活次数。所提出的方法有效地描述了正常人的主要模式特征。

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