Impact of EMG-based interfaces for hand motor rehabilitation in stroke: A systematic review with evidence gap map and meta-analysis
- 1Department of Electronics and Biomedical Engineering, School of Electrical and Computer Engineering, University of Campinas - UNICAMP, Campinas, 13083-852 SP Brazil
- 2Neural Engineering Research Laboratory, Center for Biomedical Engineering, University of Campinas - UNICAMP, Campinas, 13083-881 SP Brazil
- 3Department of Physical Therapy, Faculdade Israelita de Ciências da Saúde Albert Einstein, Hospital Israelita Albert Einstein, São Paulo, Brazil
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.
Graphical abstract: The graphical abstract summarizes the findings of a systematic review and meta-analysis including 38 studies and 1,132 participants. Four types of sEMG-based rehabilitation interfaces were examined across the International Classification of Functioning, Disability and Health (ICF) domains of Body Functions and Structures, Activity, Participation, and Patient-reported outcomes. The symbols indicate the direction of the observed effects and the certainty of the evidence according to GRADE. The results suggest that the effects of sEMG-based rehabilitation vary according to the type of interface. The combination of sEMG-triggered electrical stimulation with other interventions produced the most consistent improvements across the ICF domains. In contrast, sEMG-triggered stimulation alone and sEMG-biofeedback combined with other interventions showed fewer and less consistent benefits. sEMG-based robotic platforms also showed potential, particularly for reducing spasticity. Together, these findings favor the use of combined sEMG-triggered interventions while supporting further investigation of sEMG-based robotic approaches in rehabilitation.
Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s11517-026-03660-7.
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BibTeX
@article{guerreromendez2026impact,
title = {{Impact of EMG-based interfaces for hand motor rehabilitation in stroke: A systematic review with evidence gap map and meta-analysis}},
author = {Cristian D. Guerrero-Mendez and Natanael Pereira Batista and José Osmar Alves Filho and Carina Marconi Germer and Leonardo Abdala Elias},
journal = {Medical \& Biological Engineering \& Computing},
year = {2026},
month = aug,
doi = {10.1007/s11517-026-03660-7},
url = {https://doi.org/10.1007/s11517-026-03660-7},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Impact of EMG-based interfaces for hand motor rehabilitation in stroke: A systematic review with evidence gap map and meta-analysis
AU - Cristian D. Guerrero-Mendez
AU - Natanael Pereira Batista
AU - José Osmar Alves Filho
AU - Carina Marconi Germer
AU - Leonardo Abdala Elias
PY - 2026
DA - 2026/08/28
JO - Medical & Biological Engineering & Computing
DO - 10.1007/s11517-026-03660-7
UR - https://doi.org/10.1007/s11517-026-03660-7
AB - 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. Graphical abstract: The graphical abstract summarizes the findings of a systematic review and meta-analysis including 38 studies and 1,132 participants. Four types of sEMG-based rehabilitation interfaces were examined across the International Classification of Functioning, Disability and Health (ICF) domains of Body Functions and Structures, Activity, Participation, and Patient-reported outcomes. The symbols indicate the direction of the observed effects and the certainty of the evidence according to GRADE. The results suggest that the effects of sEMG-based rehabilitation vary according to the type of interface. The combination of sEMG-triggered electrical stimulation with other interventions produced the most consistent improvements across the ICF domains. In contrast, sEMG-triggered stimulation alone and sEMG-biofeedback combined with other interventions showed fewer and less consistent benefits. sEMG-based robotic platforms also showed potential, particularly for reducing spasticity. Together, these findings favor the use of combined sEMG-triggered interventions while supporting further investigation of sEMG-based robotic approaches in rehabilitation. Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s11517-026-03660-7.
SN - 0140-0118
SN - 1741-0444
ER -