Evidence map›Paper›PMID 41708167›Full record

ArticleBMJ open2026

Efficacy and neural mechanisms of a vibrotactile-enhanced, brain-controlled soft robotic glove for upper limb rehabilitation after stroke: a multicentre randomised controlled trial protocol.

Kai Leng Catherine Chan, Chengjie Yan, Xinyue Wang, Sisi Huang, Wenjun Dai, Yan Luo, Yihui Cheng, Baoguo Xu, Wenbin Zhang, Ying Shen

Abstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2026. 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.

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

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

10 authors.

Kai Leng Catherine ChanDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
Chengjie YanDepartment of Neurorehabilitation, Kunshan Rehabilitation Hospital, Kunshan, Jiangsu, China.
Xinyue WangDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.ORCID http://orcid.org/0009-0003-8428-3182
Sisi HuangDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
Wenjun DaiDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.ORCID http://orcid.org/0000-0003-2625-3033
Yan LuoDepartment of Neurorehabilitation, Kunshan Rehabilitation Hospital, Kunshan, Jiangsu, China.
Yihui ChengDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China.
Baoguo XuSchool of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China shenying@njmu.edu.cn w.b.zhang@hhu.edu.cn xubaoguo@seu.edu.cn.
Wenbin ZhangCollege of Computer Science and Software Engineering, Hohai University, Nanjing, Jiangsu, China shenying@njmu.edu.cn w.b.zhang@hhu.edu.cn xubaoguo@seu.edu.cn.
Ying ShenDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, Jiangsu, China shenying@njmu.edu.cn w.b.zhang@hhu.edu.cn xubaoguo@seu.edu.cn.ORCID http://orcid.org/0000-0001-8308-9562

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSoft robotic gloves (SRGs) integrated with brain-computer interfaces (BCIs) have demonstrated potential in facilitating motor recovery after stroke by enabling active, intention-driven rehabilitation. Emerging evidence suggests that incorporating vibrotactile stimulation (VTS) into SRG-BCI systems may further enhance sensorimotor feedback. The objective of this study is to evaluate the therapeutic efficacy and underlying neural mechanisms of BCI-driven, intention-based glove activation compared with automated glove-assisted training, with VTS applied identically in both groups. METHODS AND ANALYSIS: This multicentre, single-blind, randomised controlled trial will involve 48 post-stroke patients within 1 week to 3 months after stroke onset, with stratification by time since stroke during randomisation. Participants will be randomly assigned to either the BCI-SRG group (n=24) or SRG group (n=24). Both groups will receive identical VTS. Patients in the BCI-SRG group will actively initiate movements of the SRG through motor imagery, while those in the SRG group will receive automated glove-assisted training without BCI control. The intervention will be administered 5 days per week for 4 weeks. The primary outcome measure is the Fugl-Meyer Assessment of Upper Extremity. Secondary outcome measures include Wolf Motor Function Test, International Classification of Functioning, Disability and Health Generic Set, Barthel Index, Modified Ashworth Scale, Semmes-Weinstein Monofilament Test, as well as event-related spectral perturbation and event-related desynchronisation. All assessments will be conducted at both baseline and post-intervention. ETHICS AND DISSEMINATION: Ethics approval of this study protocol has been obtained from the Ethics Committee of the First Affiliated Hospital with Nanjing Medical University (2025-SR-508). The findings will be disseminated through peer-reviewed journals, conference presentations and communication with scientific, professional and general public audiences. TRIAL REGISTRATION NUMBER: ChiCTR2500106951.

Indexed as

Brain-Computer InterfacesRoboticsStrokeStroke RehabilitationUpper ExtremityHumansMulticenter Studies as TopicRandomized Controlled Trials as TopicRecovery of FunctionSingle-Blind MethodVibrationRandomized Controlled TrialREHABILITATION MEDICINEStroke

Identifiers

PMID41708167
PMCPMC12918676

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.