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基于电容式传感器的连续步态阶段自适应估计

Adaptive estimation of continuous gait phase based on capacitive sensors.

作者信息

Xu Dongfang, Zhang Zhitong, Crea Simona, Vitiello Nicola, Wang Qining

机构信息

Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China.

Beijing Engineering Research Center of Intelligent Rehabilitation Engineering, Beijing, China.

出版信息

Wearable Technol. 2022 Jun 17;3:e11. doi: 10.1017/wtc.2022.4. eCollection 2022.

Abstract

Continuous gait phase plays an important role in robotic prosthesis control. In this paper, we have conducted the offline adaptive estimation (at different speeds and on different ramps) of continuous gait phase of robotic transtibial prosthesis based on the adaptive oscillators. We have used the capacitive sensing method to record the deformation of the muscles. Two transtibial amputees joined in this study. Based on the strain signals of the prosthetic foot and the capacitive signals of the residual limb, the maximum and minimum of estimation errors are 0.80 rad and 0.054 rad, respectively, and their corresponding ratios in one gait cycle are 1.27% and 0.86%, respectively. This paper proposes an effective method to estimate the continuous gait phase based on the capacitive signals of the residual muscles, which provides a basis for the continuous control of robotic transtibial prosthesis.

摘要

连续步态阶段在机器人假肢控制中起着重要作用。在本文中,我们基于自适应振荡器对机器人小腿假肢的连续步态阶段进行了离线自适应估计(在不同速度和不同斜坡上)。我们采用电容传感方法记录肌肉的变形。两名小腿截肢者参与了本研究。基于假肢足部的应变信号和残肢的电容信号,估计误差的最大值和最小值分别为0.80弧度和0.054弧度,它们在一个步态周期中的相应比例分别为1.27%和0.86%。本文提出了一种基于残余肌肉电容信号估计连续步态阶段的有效方法,为机器人小腿假肢的连续控制提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44ab/10936350/1eeee9190fae/S2631717622000044_fig1.jpg

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