下肢肌电信号的自相关分析对偏瘫步态的初步评估

Ping-lu Wang
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引用次数: 6

摘要

为了探讨偏瘫步态康复的评价方法,招募志愿者进行标准化步行试验。肌电图信号从每条下肢的6个肌肉群收集。提出了改进的自相关分析与步态分析相结合的方法。步态周期的完成是用百分比来描述的,步态质量是用周期特征来评价的,峰值出现在记录的从零相位开始的100%、200%、300%和400%的步态周期上。从0到1.0用特定的数字来评估相似度,越接近1.0表示相似度越高。然后评估左右两侧平衡控制能力的功能。基于测量和数值结果对步态质量进行初步评估。该方法的效果与临床专业人员的定性评价明显一致,并通过案例研究进行了验证。更多的临床研究将进一步证实该方法的有效性。所提出的评估方法也有可能在未来作为机器人辅助康复的生物反馈。
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Autocorrelation analysis of lower limb EMG signals for the initial evaluation of hemiparetic gaits
In order to investigate evaluation methodology for hemiparetic gaits on rehabilitation purpose, volunteering subjects are recruited on the standardized walking trials. EMG signals are collected from six muscle groups on each lower limb. Improved autocorrelation analysis combined with gait analysis is then proposed. As the completion of gait cycle is described by percentage, gait quality is evaluated by the periodic characteristics and the peak value occurs on 100 %, 200%, 300%, and 400% of gait cycles from zero phase that are recorded. The similarities are assessed by specific number from 0 to 1.0, and the more approach to 1.0, the higher similarity is represented. Then the function of balance control ability is assessed between left and right sides. The resulting evaluation of gait qualities are initially assessed based on measuring and numerical outcome. The effect of the proposed method is verified by a case study as it is clearly agreed with the qualitative evaluation obtained from clinical professionals. More clinical studies will be carried out to further confirm the effectiveness of this proposed method. The proposed evaluation methodology could also be potentially used as the bio-feedback for the robotic-assisted rehabilitation in future.
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