Evidence map›Paper›PMID 42093816›Full record

ArticleMethodsX2026

Predicting motor recovery using surface electromyography in people with severe motor impairment after stroke: A prospective cohort study protocol.

Farah, Vennila J, Aparna Ramakrishna Pai, Arvind N Prabhu, Sivakumar Balasubramanian, Senthil Kumaran D, Margit Alt Murphy, John M Solomon

Abstract read
In one paragraph

Article in MethodsX, 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

8 authors.

FarahDepartment of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India.
Vennila JManipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India.
Aparna Ramakrishna PaiDepartment of Neurology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.
Arvind N PrabhuDepartment of Neurology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India.
Sivakumar BalasubramanianDepartment of Bioengineering, Christian Medical College, Bagayam, Vellore, Tamil Nadu, India.
Senthil Kumaran DDepartment of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India.
Margit Alt MurphyDepartment of Health & Rehabilitation, Institute of Neuroscience and Physiology, University of Gothenburg, Sweden.
John M SolomonDepartment of Physiotherapy, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stroke is a leading cause of long-term disability, resulting in motor impairments that significantly affect the quality of life. Predicting motor recovery is particularly difficult for people with severe motor impairment early after stroke. Traditional assessments are limited in terms of residual muscle activity, which is crucial for tailoring rehabilitation interventions. Incorporating surface electromyography (sEMG) assessment can provide a deeper understanding of motor recovery potential in severe motor impairment. This prospective cohort study aims to develop a TRIPOD-compliant prediction model to examine whether sEMG amplitude recorded from five upper and four lower extremity muscles within the first week of stroke could predict motor recovery at 3 months post-stroke. This prospective study will include 76 participants between the ages of 18-80 years presenting first-ever anterior or middle cerebral artery stroke resulting in a severe motor impairment within the first week of stroke onset. In addition to sEMG recording to evaluate muscle activity, participants will undergo a comprehensive clinical assessment of motor functions and activity at the 1st and 3rd months following stroke onset. Multivariate regression analyses will be used to determine associations between sEMG metrics and recovery outcomes.

Indexed as

Cerebrovascular diseaseElectromyographyFunctional recoveryMotor recoveryPrognosis

Identifiers

PMID42093816
PMCPMC13141797

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.