Assistance control strategy for upper-limb rehabilitation robot based on motion trend

IF 1 4区工程技术 Q4 ENGINEERING, MECHANICAL

Mechanical Sciences Pub Date : 2023-11-21 DOI:10.5194/ms-14-503-2023

Haojun Zhang, Tao Song, Leigang Zhang

{"title":"Assistance control strategy for upper-limb rehabilitation robot based on motion trend","authors":"Haojun Zhang, Tao Song, Leigang Zhang","doi":"10.5194/ms-14-503-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Robot-assisted rehabilitation has proven to improve a subject's upper-extremity motor function. However, it is still challenging to control the robot to provide minimal assistance based on the subject's performance. This paper proposes a motion-trend-based assistance control strategy to solve this problem. The control strategy provides the corresponding normal and tangential forces by constructing an adaptive virtual assistance force field around a predetermined training trajectory. In the normal direction, a performance function based on the position-tracking error and normal motion trend is established to adjust the normal assistance force field strength in real time; in the tangential direction, a performance function based on the tangential interaction force and tangential motion trend is established to adjust the tangential assistance force field strength in real time. Additionally, good motion trends can quickly reduce the assistance force field. The normal motion trend represents the state of the subject moving toward the target trajectory, and the tangential motion trend represents the state of increasing tangential interaction force. Finally, the performance of this control strategy was evaluated by training experiments with eight healthy subjects. Preliminary experiments showed that the normal assist force in the active movement phase was 92.48 % smaller than that in the poor phase, and the tangential assist force was 90.73 % smaller than that in the slack phase. And the normal assist force and tangential assist force will become zero within 0.2 s when the subject has a good tendency to move. This shows that the control strategy proposed in this paper can quickly adjust the assistance according to the subject's motor performance. In addition, the assistance can be quickly reduced when the subject has a good movement trend. Future work will incorporate OpenSim (muscle and bone simulation software) to develop a pathway suitable for the subject's arm rehabilitation.","PeriodicalId":18413,"journal":{"name":"Mechanical Sciences","volume":"97 2","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechanical Sciences","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.5194/ms-14-503-2023","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}

引用次数: 0

Abstract

Abstract. Robot-assisted rehabilitation has proven to improve a subject's upper-extremity motor function. However, it is still challenging to control the robot to provide minimal assistance based on the subject's performance. This paper proposes a motion-trend-based assistance control strategy to solve this problem. The control strategy provides the corresponding normal and tangential forces by constructing an adaptive virtual assistance force field around a predetermined training trajectory. In the normal direction, a performance function based on the position-tracking error and normal motion trend is established to adjust the normal assistance force field strength in real time; in the tangential direction, a performance function based on the tangential interaction force and tangential motion trend is established to adjust the tangential assistance force field strength in real time. Additionally, good motion trends can quickly reduce the assistance force field. The normal motion trend represents the state of the subject moving toward the target trajectory, and the tangential motion trend represents the state of increasing tangential interaction force. Finally, the performance of this control strategy was evaluated by training experiments with eight healthy subjects. Preliminary experiments showed that the normal assist force in the active movement phase was 92.48 % smaller than that in the poor phase, and the tangential assist force was 90.73 % smaller than that in the slack phase. And the normal assist force and tangential assist force will become zero within 0.2 s when the subject has a good tendency to move. This shows that the control strategy proposed in this paper can quickly adjust the assistance according to the subject's motor performance. In addition, the assistance can be quickly reduced when the subject has a good movement trend. Future work will incorporate OpenSim (muscle and bone simulation software) to develop a pathway suitable for the subject's arm rehabilitation.

查看原文本刊更多论文

基于运动趋势的上肢康复机器人辅助控制策略

摘要事实证明，机器人辅助康复可以改善受试者的上肢运动功能。然而，如何根据受试者的表现来控制机器人以提供最小程度的辅助仍是一项挑战。本文提出了一种基于运动趋势的辅助控制策略来解决这一问题。该控制策略通过围绕预定的训练轨迹构建自适应虚拟辅助力场，提供相应的法向力和切向力。在法线方向上，建立基于位置跟踪误差和法线运动趋势的性能函数，实时调整法线辅助力场强度；在切线方向上，建立基于切线相互作用力和切线运动趋势的性能函数，实时调整切线辅助力场强度。此外，良好的运动趋势可以快速降低辅助力场。正常运动趋势代表受试者向目标轨迹移动的状态，而切向运动趋势则代表切向相互作用力增加的状态。最后，通过对 8 名健康受试者进行训练实验，对这一控制策略的性能进行了评估。初步实验表明，主动运动阶段的法向辅助力比贫乏阶段小 92.48%，切向辅助力比松弛阶段小 90.73%。而当被试运动趋势良好时，法向辅助力和切向辅助力会在 0.2 秒内变为零。这表明本文提出的控制策略可以根据被试的运动表现快速调整辅助力。此外，当受试者运动趋势良好时，还可以快速减少辅助。未来的工作将结合 OpenSim（肌肉和骨骼模拟软件），开发出适合受试者手臂康复的路径。

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分钟内获得全文求助全文

来源期刊

Mechanical Sciences ENGINEERING, MECHANICAL-

CiteScore

2.20

自引率

7.10%

发文量

审稿时长

29 weeks

期刊介绍： The journal Mechanical Sciences (MS) is an international forum for the dissemination of original contributions in the field of theoretical and applied mechanics. Its main ambition is to provide a platform for young researchers to build up a portfolio of high-quality peer-reviewed journal articles. To this end we employ an open-access publication model with moderate page charges, aiming for fast publication and great citation opportunities. A large board of reputable editors makes this possible. The journal will also publish special issues dealing with the current state of the art and future research directions in mechanical sciences. While in-depth research articles are preferred, review articles and short communications will also be considered. We intend and believe to provide a means of publication which complements established journals in the field.