Gait-Oriented Post-Stroke Rehabilitation Tasks Online Trajectory Generation for 1-DOF Hip Lower-Limb Exoskeleton.

Gaetan Courtois, Antoine Dequidt, Jason Chevrie, Xavier Bonnet, Philippe Pudlo
{"title":"Gait-Oriented Post-Stroke Rehabilitation Tasks Online Trajectory Generation for 1-DOF Hip Lower-Limb Exoskeleton.","authors":"Gaetan Courtois, Antoine Dequidt, Jason Chevrie, Xavier Bonnet, Philippe Pudlo","doi":"10.1109/ICORR58425.2023.10304696","DOIUrl":null,"url":null,"abstract":"<p><p>In the field of gait rehabilitation lower limb exoskeletons have received a lot of interest. An increasing number of them are revised to be adapted for post-stroke rehabilitation. These exoskeletons mostly work in complement of conventional physiotherapy in the subacute phase to practice gait training. For this gait training the reference trajectory generation is one of the main issues. This is why it usually consists in reproducing some averaged healthy patient's gait pattern. This paper's purpose is to display the online trajectory generation (OTG) algorithm developed to provide reference trajectories applied to gait-oriented tasks designed based on conventional physiotherapy. This OTG algorithm is made to reproduce trajectories similar to the ones a therapist would follow during the same tasks. In addition, experiments are presented in this paper to compare the trajectories generated with the OTG algorithm for two rehabilitation tasks with the trajectories followed by a therapist in the same conditions. During these experiments the OTG is implemented in a runtime system with a 500µs cycle time on a bench able to emulate late and early patients' interaction. These experiments results assess that the OTG can work at a 500µs cycle time to reproduce a similar trajectory as the one followed by the therapist during the two rehabilitation tasks implemented.</p>","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORR58425.2023.10304696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In the field of gait rehabilitation lower limb exoskeletons have received a lot of interest. An increasing number of them are revised to be adapted for post-stroke rehabilitation. These exoskeletons mostly work in complement of conventional physiotherapy in the subacute phase to practice gait training. For this gait training the reference trajectory generation is one of the main issues. This is why it usually consists in reproducing some averaged healthy patient's gait pattern. This paper's purpose is to display the online trajectory generation (OTG) algorithm developed to provide reference trajectories applied to gait-oriented tasks designed based on conventional physiotherapy. This OTG algorithm is made to reproduce trajectories similar to the ones a therapist would follow during the same tasks. In addition, experiments are presented in this paper to compare the trajectories generated with the OTG algorithm for two rehabilitation tasks with the trajectories followed by a therapist in the same conditions. During these experiments the OTG is implemented in a runtime system with a 500µs cycle time on a bench able to emulate late and early patients' interaction. These experiments results assess that the OTG can work at a 500µs cycle time to reproduce a similar trajectory as the one followed by the therapist during the two rehabilitation tasks implemented.

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
面向步态的中风后康复任务单自由度髋关节-下肢外骨骼的在线轨迹生成。
在步态康复领域,下肢外骨骼受到了广泛的关注。对其中越来越多的进行了修订,以适应中风后的康复。这些外骨骼主要在亚急性期作为传统物理疗法的补充来练习步态训练。对于这种步态训练,参考轨迹的生成是主要问题之一。这就是为什么它通常包括复制一些平均健康患者的步态模式。本文的目的是展示在线轨迹生成(OTG)算法,该算法旨在为基于传统理疗设计的步态导向任务提供参考轨迹。这种OTG算法是为了再现类似于治疗师在相同任务中遵循的轨迹。此外,本文还进行了实验,将OTG算法为两项康复任务生成的轨迹与治疗师在相同条件下遵循的轨迹进行了比较。在这些实验中,OTG在一个运行时系统中实现,该系统在一个能够模拟晚期和早期患者互动的工作台上具有500µs的循环时间。这些实验结果评估了OTG可以在500µs的循环时间内工作,以再现与治疗师在执行两项康复任务期间遵循的轨迹相似的轨迹。
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
CiteScore
0.50
自引率
0.00%
发文量
0
期刊最新文献
Individualized Three-Dimensional Gait Pattern Generator for Lower Limbs Rehabilitation Robots. Individualized Training of Back Muscles Using Iterative Learning Control of a Compliant Balance Board. Influence of Robotic Therapy on Severe Stroke Patients. INSPIIRE - A Modular and Passive Exoskeleton to Investigate Human Walking and Balance. Instrumented Upper Limb Functional Assessment Using a Robotic Exoskeleton: Normative References Intervals.
×
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