Estimation of joint torques in human gait based on Gaussian process
10.3969/j.issn.1006-9771.2022.08.015
- VernacularTitle:基于高斯过程的人体步态关节力矩估计
- Author:
Siqi LI
1
;
Yuling ZHANG
1
;
Jiantao YANG
1
Author Information
1. Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, China
- Publication Type:Journal Article
- Keywords:
Gaussian process;
human gait;
joint torque
- From:
Chinese Journal of Rehabilitation Theory and Practice
2022;28(8):989-992
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo 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. MethodsAccording 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. ResultsOne 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. ConclusionThis 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.
