Evidence map›Paper›PMID 42663910›Full record

ReviewMedical & biological engineering & computing2026

Impact of EMG-based interfaces for hand motor rehabilitation in stroke: A systematic review with evidence gap map and meta-analysis.

Cristian D Guerrero-Mendez, Natanael Pereira Batista, José Osmar Alves Filho, Carina Marconi Germer, Leonardo Abdala Elias

Abstract readReview
PubMed Publisher
In one paragraph

Review in Medical & biological engineering & computing, 2026. 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.

Cristian D Guerrero-MendezDepartment of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas - UNICAMP, Campinas, 13083-852, SP, Brazil.ORCID http://orcid.org/0000-0003-1019-9423
Natanael Pereira BatistaDepartment of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas - UNICAMP, Campinas, 13083-852, SP, Brazil.ORCID http://orcid.org/0000-0001-8502-0032
José Osmar Alves FilhoDepartment of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas - UNICAMP, Campinas, 13083-852, SP, Brazil.ORCID http://orcid.org/0000-0001-8471-8594
Carina Marconi GermerDepartment of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas - UNICAMP, Campinas, 13083-852, SP, Brazil.ORCID http://orcid.org/0000-0002-7323-3767
Leonardo Abdala EliasDepartment of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas - UNICAMP, Campinas, 13083-852, SP, Brazil. leoelias@unicamp.br.ORCID http://orcid.org/0000-0003-4488-3063

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electromyography (EMG)-based interventions have been proposed to improve hand/wrist motor recovery after stroke; however, their clinical value remains uncertain, as evidence for their effectiveness is inconsistent. This systematic review with meta-analysis evaluated the impact of different EMG-based rehabilitation approaches compared with non-EMG-based interventions in individuals with stroke. Seven databases were searched from inception to November 17, 2025, in accordance with PRISMA guidelines. Randomized controlled trials comparing EMG-based and non-EMG-based interventions for post-stroke hand or wrist rehabilitation were eligible. Interventions were classified into four categories: EMG-triggered electrical stimulation (EMG-ES), EMG-ES combined with other interventions, EMG-based robotic platforms, and EMG biofeedback combined with other interventions. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool, and certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Meta-analyses were conducted for clinical outcomes classified according to the International Classification of Functioning, Disability and Health (ICF) domains at post-intervention, follow-up <3 months, and follow-up ≥3 months. Thirty-eight studies involving 1,132 participants were included, of which 31 contributed to the meta-analyses. Eight studies were judged to have a low risk of bias, 13 to have some concerns, and 17 to have a high risk of bias. EMG-ES alone was not superior to conventional therapy. In contrast, EMG-ES combined with other interventions produced greater improvements across all ICF domains. EMG-based robotic platforms reduced wrist and finger spasticity, with effects sustained at long-term follow-up. EMG biofeedback primarily improved outcomes within the ICF body functions and structures domain. The effectiveness of EMG-based interventions depends on the rehabilitation strategy. EMG-ES, combined with other therapies, may be prioritized, whereas EMG-based robotic platforms may be useful in reducing spasticity. Further high-quality studies are needed to establish the clinical effectiveness of EMG-biofeedback approaches.

Indexed as

EMG-based interventionHandMeta-analysisStroke rehabilitationWrist

Identifiers

What OpenQuestion holds

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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.