基于高斯过程的人体步态关节力矩估计

doi:10.3969/j.issn.1006-9771.2022.08.015

Abstract

Abstract:

Objective To propose an estimation method of lower limb joints torques based on Gaussian process to achieve the accurate estimation of the lower limb joint torques in human gait.

Methods According to the characteristics of the natural gait joint torques curve, the squared exponential kernel function was selected to explore the interrelationship between the joint angle and the joint torques. A data fusion model based on Gaussian process was established. The lower limb joint angle was used as the input of the model, and the output was the joint torque.

Results One healthy subject walked on the gait running platform with a walking speed of 0.8 m/s. Three joint-torque experiments were conducted using the proposed Gaussian process. The results showed that most of the predicted values fell within the confidence intervals and 89% of the r² values were greater than 0.8.

Conclusion This method could achieve accurate estimation of joint torques. The potential application of this research is to optimize exoskeleton robots, control active prosthesis, and adjust the joint torque of humanoid robots.

Key words: Gaussian process, human gait, joint torque

CLC Number:

R496

LI Siqi,ZHANG Yuling,YANG Jiantao. Estimation of joint torques in human gait based on Gaussian process[J]. 《Chinese Journal of Rehabilitation Theory and Practice》, 2022, 28(8): 989-992.

Figures/Tables 3

References 20

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关节	第1次	第2次	第3次
踝关节	0.9129	0.9685	0.9450
膝关节	0.6278	0.8815	0.9516
髋关节	0.8668	0.9468	0.8778

Estimation of joint torques in human gait based on Gaussian process

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