Evidence map›Paper›PMID 40942707›Full record

ArticleSensors (Basel, Switzerland)2025

Facilitated Effects of Closed-Loop Assessment and Training on Trans-Radial Prosthesis User Rehabilitation.

Huimin Hu, Yi Luo, Ling Min, Lei Li, Xing Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

5 authors.

Huimin HuDepartment of Biomedical Engineering, Chongqing University, Chongqing 400044, China.
Yi LuoDepartment of Biomedical Engineering, Chongqing University, Chongqing 400044, China.
Ling MinDepartment of Biomedical Engineering, Chongqing University, Chongqing 400044, China.
Lei LiDepartment of Biomedical Engineering, Faculty of Engineering, Hong Kong Polytechnic University, Hong Kong SAR, China.
Xing WangDepartment of Biomedical Engineering, Chongqing University, Chongqing 400044, China.

Funding

Graduate Scientific Research and Innovation Foundation of Chongqing CYS240069National Key Research and Development program of China 2020YFC2009703、2020YFC2009702the National Natural Science Foundation of China Youth Fund 31700856、62206032
6 · The paper itself

Abstract

(1) Background: Integrating assessment with training helps to enhance precision prosthetic rehabilitation of trans-radial amputees. This study aimed to validate a self-developed closed-loop rehabilitation platform combining accurate measurement in comprehensive assessment and immediate interaction in virtual reality (VR) training in refining patient-centered myoelectric prosthesis rehabilitation. (2) Methods: The platform consisted of two modules, a multimodal assessment module and an sEMG-driven VR game training module. The former included clinical scales (OPUS, DASH), task performance metrics (modified Box and Block Test), kinematics analysis (inertial sensors), and surface electromyography (sEMG) recording, verified on six trans-radial amputees and four healthy subjects. The latter aimed for muscle coordination training driven by four-channel sEMG, tested on three amputees. Post 1-week training, task performance and sEMG metrics (wrist flexion/extension activation) were re-evaluated. (3) Results: The sEMG in the residual limb of the amputees upgraded by 4.8%, either the subjects' number of gold coins or game scores after 1-week training. Subjects uniformly agreed or strongly agreed with all the items on the user questionnaire. In reassessment after training, the average completion time (CT) of all three amputees in both tasks decreased. CTs of the A1 and A3 in the placing tasks were reduced by 49.52% and 50.61%, respectively, and the CTs for the submitting task were reduced by 19.67% and 55.44%, respectively. Average CT of all three amputees in the ADL task after training was 9.97 s, significantly lower than the pre-training time of 15.17 s. (4) Conclusions: The closed-loop platform promotes patients' prosthesis motor-control tasks through accurate measurement and immediate interaction according to the sensorimotor recalibration principle, demonstrating a potential tool for precision rehabilitation.

Indexed as

AmputeesArtificial LimbsAdultBiomechanical PhenomenaElectromyographyFemaleHumansMaleMiddle AgedProsthesis DesignTask Performance and AnalysisVirtual Realityclosed-loop rehabilitationmultimodal assessmentmyoelectric prosthesisvirtual reality

Identifiers

PMID40942707
PMCPMC12430971

What OpenQuestion holds

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Registered trials

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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.