Proprioception enhancement for robot assisted neural rehabilitation: a dynamic electrical stimulation based method and preliminary results from EEG analysis.

Yuze Jiao, Weiqun Wang, Jiaxing Wang, Zeng-Guang Hou
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Abstract

Objective.In recent years, the robot assisted (RA) rehabilitation training has been widely used to counteract defects of the manual one provided by physiotherapists. However, since the proprioception feedback provided by the robotic assistance or the manual methods is relatively weak for the paralyzed patients, their rehabilitation efficiency is still limited. In this study, a dynamic electrical stimulation (DES) based proprioception enhancement and the associated quantitative analysis methods have been proposed to overcome the limitation mentioned above.Approach.Firstly, the DES based proprioception enhancement method was proposed for the RA neural rehabilitation. In the method, the relationship between the surface electromyogram (sEMG) envelope of the specified muscle and the associated joint angles was constructed, and the electrical stimulation (ES) pulses for the certain joint angles were designed by consideration of the corresponding sEMG envelope, based on which the ES can be dynamically regulated during the rehabilitation training. Secondly, power spectral density, source estimation, and event-related desynchronization of electroencephalogram, were combinedly used to quantitatively analyze the proprioception from multiple perspectives, based on which more comprehensive and reliable analysis results can be obtained. Thirdly, four modes of rehabilitation training tasks, namely active, RA, DES-RA, and ES-only training, were designed for the comparison experiment and validation of the proposed DES based proprioception enhancement method.Main results.The results indicated that the activation of the sensorimotor cortex was significantly enhanced when the DES was added, and the cortex activation for the DES-RA training was similar to that for the active training. Meanwhile, relatively consistent results from the multiple perspectives were obtained, which validates the effectiveness and robustness of the proposed proprioception analysis method.Significance.The proposed methods have the potential to be applied in the practical rehabilitation training to improve the rehabilitation efficiency.

增强机器人辅助神经康复的运动感觉:基于动态电刺激的方法和脑电图分析的初步结果。
目的:近年来,机器人辅助(RA)康复训练已被广泛应用,以弥补物理治疗师提供的徒手康复训练的缺陷。然而,由于机器人辅助或人工方法对瘫痪病人的本体感觉反馈相对较弱,其康复效率仍然有限。本研究提出了一种基于动态电刺激(DES)的本体感觉增强方法和相关的定量分析方法,以克服上述局限性:首先,针对 RA 神经康复提出了基于 DES 的本体感觉增强方法。在该方法中,构建了指定肌肉的表面肌电图(sEMG)包络与相关关节角度之间的关系,并根据相应的sEMG包络设计了特定关节角度的电刺激(ES)脉冲,在此基础上可在康复训练过程中动态调节ES。其次,结合脑电图的功率谱密度、源估计和事件相关非同步化等方法,从多个角度对本体感觉进行定量分析,从而获得更全面、更可靠的分析结果。第三,设计了四种康复训练任务模式,即主动训练、RA训练、DES-RA训练和ES训练,对所提出的基于DES的本体感觉增强方法进行对比实验和验证:结果表明,加入DES后,感觉运动皮层的激活明显增强,DES-RA训练的皮层激活与主动训练相似。同时,从多个角度得出了相对一致的结果,这验证了所提出的本体感觉分析方法的有效性和稳健性:意义:所提出的方法有望应用于实际康复训练中,以提高康复效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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