Evidence map›Paper›PMID 40658181›Full record

ArticleMedical & biological engineering & computing2025

Reconfiguration planning and structure parameter design of a reconfigurable cable-driven lower limb rehabilitation robot.

Jinghang Li, Keyi Wang, Yanzhuo Wang, Yi Yuan

Abstract read
PubMed Publisher
In one paragraph

Article in Medical & biological engineering & computing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Jinghang LiCollege of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, Heilongjiang, China.
Keyi WangCollege of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, Heilongjiang, China. wangkeyi@hrbeu.edu.cn.
Yanzhuo WangCollege of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, Heilongjiang, China.
Yi YuanJoint Department, Ningbo No.2 Hospital, Ningbo, 315010, Zhejiang, China.

Funding

National Natural Science Foundation of China 52175006Natural Science Foundation of Heilongjiang Province LH2023E064Yongjiang Innovation and Science Initiative 2035 2024Z200
6 · The paper itself

Abstract

Reconfigurable cable-driven parallel robots (RCDPRs) have attracted much attention as a novel type of cable-driven robot that can change their cable anchor position. The reconfigurable cable-driven lower limb rehabilitation robot (RCDLR) employs RCDPRs in lower limb rehabilitation to achieve multiple training modes. This paper investigates the reconfiguration planning and structural parameter design of the RCDLR. The RCDLR aims to fulfill the requirements of early passive rehabilitation training. Therefore, motion capture data are analyzed and mapped to the target trajectory of the RCDLR. Through dynamics modeling, the Wrench-Feasible Anchor-point Space (WFAS) is defined, from which an objective function for optimal reconfiguration planning is derived. The genetic algorithm is used to solve the optimal reconfiguration planning problem. Additionally, we propose the reconfigurability and safety coefficients as components of a structure parameter design method aimed at satisfying multiple target rehabilitation trajectories. Finally, numerical simulations are implemented based on the instance data and target trajectories to compute the specific structure parameters and verify the effectiveness of the reconfiguration planning method.

Indexed as

Lower ExtremityRehabilitationRoboticsAlgorithmsComputer SimulationEquipment DesignHumansCable-driven parallel robotsMotion captureReconfiguration planningRehabilitation robotStructure parameter design

Identifiers

PMID40658181

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.