Evidence map›Paper›PMID 39479563›Full record

ArticleFrontiers in robotics and AI2024

A greedy assist-as-needed controller for end-effect upper limb rehabilitation robot based on 3-DOF potential field constraints.

Yue Lu, Zixuan Lin, Yahui Li, Jinwang Lv, Jiaji Zhang, Cong Xiao, Ye Liang, Xujiao Chen, Tao Song, Guohong Chai and 1 more

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yue LuCixi Biomedical Research Institute, Wenzhou Medical University, Ningbo, China.
Zixuan LinCixi Biomedical Research Institute, Wenzhou Medical University, Ningbo, China.
Yahui LiCixi Biomedical Research Institute, Wenzhou Medical University, Ningbo, China.
Jinwang LvCixi Biomedical Research Institute, Wenzhou Medical University, Ningbo, China.
Jiaji ZhangNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Cong XiaoCixi Biomedical Research Institute, Wenzhou Medical University, Ningbo, China.
Ye LiangDepartment of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University, Changsha, China.
Xujiao ChenDepartment of Geriatrics, The First Affliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Tao SongNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Guohong ChaiNingbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Guokun ZuoCixi Biomedical Research Institute, Wenzhou Medical University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It has been proven that robot-assisted rehabilitation training can effectively promote the recovery of upper-limb motor function in post-stroke patients. Increasing patients' active participation by providing assist-as-needed (AAN) control strategies is key to the effectiveness of robot-assisted rehabilitation training. In this paper, a greedy assist-as-needed (GAAN) controller based on radial basis function (RBF) network combined with 3 degrees of freedom (3-DOF) potential constraints was proposed to provide AAN interactive forces of an end-effect upper limb rehabilitation robot. The proposed 3-DOF potential fields were adopted to constrain the tangential motions of three kinds of typical target trajectories (one-dimensional (1D) lines, two-dimensional (2D) curves and three-dimensional (3D) spirals) while the GAAN controller was designed to estimate the motor capability of a subject and provide appropriate robot-assisted forces. The co-simulation (Adams-Matlab/Simulink) experiments and behavioral experiments on 10 healthy volunteers were conducted to validate the utility of the GAAN controller. The experimental results demonstrated that the GAAN controller combined with 3-DOF potential field constraints enabled the subjects to actively participate in kinds of tracking tasks while keeping acceptable tracking accuracies. 3D spirals could be better in stimulating subjects' active participation when compared to 1D and 2D target trajectories. The current GAAN controller has the potential to be applied to existing commercial upper limb rehabilitation robots.

Indexed as

3-DOF potential fieldAssist-as-needed (AAN)human-robot interactionradial basis function (RBF) networkrehabilitation robot

Identifiers

PMID39479563
PMCPMC11522331

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.