A Modified Dynamic Movement Primitive Algorithm for Adaptive Gait Control of a Lower Limb Exoskeleton

IF 3.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Human-Machine Systems Pub Date : 2024-09-27 DOI:10.1109/THMS.2024.3458905
Lingzhou Yu;Shaoping Bai
{"title":"A Modified Dynamic Movement Primitive Algorithm for Adaptive Gait Control of a Lower Limb Exoskeleton","authors":"Lingzhou Yu;Shaoping Bai","doi":"10.1109/THMS.2024.3458905","DOIUrl":null,"url":null,"abstract":"A major challenge in the lower limb exoskeleton for walking assistance is the adaptive gait control. In this article, a modified dynamic movement primitive (DMP) (MDMP) control is proposed to achieve gait adjustment with different assistance levels. This is achieved by inclusion of interaction forces in the formulation of DMP, which enables learning from physical human–robot interaction. A threshold force is introduced accounting for different levels of walking assistance from the exoskeleton. The MDMP is, thus, capable of generating adjustable gait and reshaping trajectories with data from the interaction force sensors. The experiments on five subjects show that the average differences between the human body and the exoskeleton are 4.13° and 1.92° on the hip and knee, respectively, with average interaction forces of 42.54 N and 26.36 N exerted on the subjects' thigh and shank. The results demonstrated that the MDMP method can effectively provide adjustable gait for walking assistance.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":"54 6","pages":"778-787"},"PeriodicalIF":3.5000,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Human-Machine Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10697288/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

A major challenge in the lower limb exoskeleton for walking assistance is the adaptive gait control. In this article, a modified dynamic movement primitive (DMP) (MDMP) control is proposed to achieve gait adjustment with different assistance levels. This is achieved by inclusion of interaction forces in the formulation of DMP, which enables learning from physical human–robot interaction. A threshold force is introduced accounting for different levels of walking assistance from the exoskeleton. The MDMP is, thus, capable of generating adjustable gait and reshaping trajectories with data from the interaction force sensors. The experiments on five subjects show that the average differences between the human body and the exoskeleton are 4.13° and 1.92° on the hip and knee, respectively, with average interaction forces of 42.54 N and 26.36 N exerted on the subjects' thigh and shank. The results demonstrated that the MDMP method can effectively provide adjustable gait for walking assistance.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用于下肢外骨骼自适应步态控制的修正动态运动基元算法
用于辅助行走的下肢外骨骼面临的一大挑战是自适应步态控制。本文提出了一种改进的动态运动基元(DMP)(MDMP)控制,以实现不同辅助水平下的步态调整。这是通过在 DMP 中加入交互力来实现的,这样就能从物理上的人机交互中学习。根据外骨骼提供的不同步行辅助水平,引入了一个阈值力。因此,MDMP 能够根据交互力传感器的数据生成可调整的步态和重塑轨迹。对五名受试者的实验表明,人体与外骨骼在髋关节和膝关节上的平均差异分别为 4.13° 和 1.92°,受试者大腿和小腿上的平均交互力分别为 42.54 N 和 26.36 N。结果表明,MDMP 方法可有效提供可调步态的行走辅助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Human-Machine Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
7.10
自引率
11.10%
发文量
136
期刊介绍: The scope of the IEEE Transactions on Human-Machine Systems includes the fields of human machine systems. It covers human systems and human organizational interactions including cognitive ergonomics, system test and evaluation, and human information processing concerns in systems and organizations.
期刊最新文献
Table of Contents Call for Papers: IEEE Transactions on Human-Machine Systems IEEE Transactions on Human-Machine Systems Information for Authors IEEE Systems, Man, and Cybernetics Society Information IEEE Systems, Man, and Cybernetics Society Information
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1