Evidence map›Paper›PMID 40707971›Full record

Trial reportJournal of neuroengineering and rehabilitation2025

Effects and neural mechanisms of a brain-computer interface-controlled soft robotic glove on upper limb function in patients with subacute stroke: a randomized controlled fNIRS study.

Xiang Ji, Xia Lu, Yi Xu, Wenbin Zhang, Han Yang, Chenghui Yin, Hewei Wang, Caili Ren, Yingying Ji, Yongqiang Li and 2 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 8 pooled it
–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

14 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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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

12 authors.

Xiang Ji *Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Xia Lu *Department of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Yi Xu *School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China.
Wenbin Zhang *College of Computer Science and Software Engineering, Hohai University, Nanjing, China.
Han Yang *School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China.
Chenghui YinDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China.
Hewei WangDepartment of Rehabilitation, Huashan Hospital, Fudan University, Shanghai, China.
Caili RenDepartment of Rehabilitation, Wuxi Central Rehabilitation Hospital, The Affiliated Mental Health Center of Jiangnan University, Wuxi, China.
Yingying JiDepartment of Rehabilitation, Wuxi Central Rehabilitation Hospital, The Affiliated Mental Health Center of Jiangnan University, Wuxi, China.
Yongqiang LiDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China. liyongqiang@njmu.edu.cn.
Guilan HuangDepartment of Rehabilitation, Wuxi Central Rehabilitation Hospital, The Affiliated Mental Health Center of Jiangnan University, Wuxi, China. huangguilan211@163.com.
Ying ShenDepartment of Rehabilitation Medicine, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China. shenying@njmu.edu.cn.

Funding

Jiangsu Province Hospital clinical diagnosis and treatment of technological innovation "Open bidding for selecting the best candidates" project No.JBGS202414National Key Research & Development Program of China No.2022YFC2009700Open Research Fund of State Key Laboratory of Digital Medical Engineering 2025-K10the Competitive Project of Jiangsu Province's Key Research and Development Program No.BE2023034the Key Project of Jiangsu Province's Key Research and Development Program No.BE2023023-2Youth Project of the Wuxi Municipal Health Commission No.Q202414
6 · The paper itself

Abstract

background and purposeThe brain-computer interface-based soft robotic glove (BCI-SRG) holds promise for upper limb rehabilitation in subacute stroke patients, yet its efficacy and neural mechanisms are unclear. This study aimed to investigate the therapeutic effects and neural mechanisms of BCI-SRGs by functional near-infrared spectroscopy (fNIRS).

methodsForty subacute stroke patients with left-sided hemiparesis were randomized into the BCI-SRG (n = 20) and soft robotic glove (SRG) (n = 20) groups. Both groups received 20 sessions of intervention over 4 weeks in addition to conventional rehabilitation. The BCI-SRG group was trained using a soft robotic glove controlled by a brain‒computer interface (BCI), whereas the SRG group used the same soft robotic glove without BCI control. The clinical outcomes included the Action Research Arm Test (ARAT), the Fugl-Meyer Assessment Upper Limb (FMA-UL), and Modified Barthel Index (MBI) scores. In addition, fNIRS was used to explore potential clinical brain mechanisms. All assessments were performed before treatment and after 4 weeks of treatment.

resultsA total of 39 participants completed the intervention and clinical assessments (BCI-SRG: n = 20; SRG: n = 19). Compared with the SRG group, the BCI-SRG group showed greater improvements in the ARAT (Z = - 2.139, P = 0.032) and FMA-UL (Z = - 2.588, P = 0.010), with no notable difference in the MBI (Z = - 1.843, P = 0.065). fNIRS data were available for 35 participants (BCI-SRG: n = 17; SRG: n = 18). Within-group comparisons revealed significant postintervention increases in cortical activation in the bilateral sensorimotor cortex (SMC) and medial prefrontal cortex (MPFC) in the BCI-SRG group, whereas no significant changes were observed in the SRG group. Between-group comparisons further revealed significantly greater changes in HbO concentrations in the BCI-SRG group than in the SRG group across the same cortical regions. Moreover, changes in prefrontal activation (post-pre) were positively correlated with improvements in ARAT scores, with significant correlations observed in the left dorsal lateral prefrontal cortex (LDLPFC) (Ch9, r = 0.592, P = 0.012; Ch25, r = 0.488, P = 0.047) and right dorsal lateral prefrontal cortex (RDLPFC) (Ch19, r = 0.671, P = 0.003).

conclusionsBCI-SRG training significantly enhances upper limb function and facilitates bilateral motor and sensory cortical reorganization. PFC activation is correlated with functional improvements, suggesting a potential mechanism underlying the benefits of rehabilitation in stroke patients.

trial registrationThis trial was registered under the Chinese Clinical Trial Registry (ChiCTR2400082786) and was retrospectively registered on April 8, 2024.

Indexed as

Brain-Computer InterfacesParesisRoboticsStrokeStroke RehabilitationUpper ExtremityAdultAgedFemaleHumansMaleMiddle AgedSpectroscopy, Near-InfraredBrain‒computer interfaceFunctional near-infrared spectroscopySoft robotic gloveStrokeUpper limb

Identifiers

PMID40707971
PMCPMC12288246

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.