Evidence map›Paper›PMID 34589686›Full record

ArticleArchives of rehabilitation research and clinical translation2021

Electromyography Recordings Detect Muscle Activity Before Observable Contractions in Acute Stroke Care.

Christina Papazian, Nick A Baicoianu, Keshia M Peters, Heather A Feldner, Katherine M Steele

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Archives of rehabilitation research and clinical translation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06574737 (Use of Surface Electromyography as a Tools to Predict Upper Extremity Recovery Function After Stroke), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
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.

NCT06574737 recruitingnot on this mapstarted 2024, after this paper: background citation

Use of Surface Electromyography as a Tools to Predict Upper Extremity Recovery Function After Stroke

Typeobservational_patient_registrySponsorUniversitas PadjadjaranRan2024 to 2025Enrolled30ConditionsUpper Extremity Paresis, Muscle Contracture Upper Arm, Stroke
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Clinical Features to Predict the Use of a sEMG Wearable Device (REMOInternational journal of environmental research and public health · 2023
    Article
  5. Review
  6. Article
  7. 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

5 authors at 1 institution in 1 country.

Christina PapazianDepartment of Mechanical Engineering, University of Washington, Seattle, WA.
Nick A BaicoianuDepartment of Mechanical Engineering, University of Washington, Seattle, WA.
Keshia M PetersDepartment of Mechanical Engineering, University of Washington, Seattle, WA.
Heather A FeldnerDepartment of Rehabilitation Medicine, University of Washington, Seattle, WA.
Katherine M SteeleDepartment of Mechanical Engineering, University of Washington, Seattle, WA.
University of Washington · US

Funding

SCH: Ubiquitous rehabilitation to improve movement after neurologic injury R01EB021935 · NIBIB · UNIVERSITY OF WASHINGTON · PI STEELE, KATHERINE M · 2015 to 2018
$1.6M
NIBIB NIH HHS R01 EB021935
6 · The paper itself

Abstract

objectiveTo evaluate muscle activity in the arms of adult stroke survivors with limited or no arm movement during acute care.

designProspective observational study.

settingAcute care regional stroke center.

participantsWe recruited adults (N=21) who had a stroke within the previous 5 days who were admitted to a level 1 trauma hospital and had a National Institutes of Health Stroke Scale score >1 for arm function at the time of recruitment. A total of 21 adults (13 men, 8 women) with an average age of 60±15 years were recruited an average of 3±1 days after their stroke. Eleven (7 men, 4 women; age, 56±11y) had no observable or palpable arm muscle activity (Manual Muscle Test [MMT]=0) and 10 (6 men, 4 women; age, 64±1y) had detectable activity (MMT>0).

interventionsDual mode sensors (electromyography and accelerometry) were placed on the anterior deltoid, biceps, triceps, wrist extensors, and wrist flexors of the impaired arm.

main outcome measuresThe number of muscle contractions, as well as average duration, amplitude, and co-contraction patterns were evaluated for each participant.

resultsMuscle contractions were observed in all 5 muscles for all participants using electromyography (EMG) recordings. Contractions were easily identified from 30 minutes of monitoring for participants with an MMT >0, but up to 3 hours of monitoring was required for participants with an MMT=0 to detect contractions in all 5 muscles during standard care. Only the wrist extensors demonstrated significantly larger amplitude contractions for participants with an MMT>0 than those with an MMT=0. Co-contraction was rare, involving less than 10% of contractions. Co-contraction of 2 muscles most commonly aligned with the flexor synergy pattern commonly observed after stroke. For participants with an MMT=0, the number of contractions and maximum amplitude were moderately correlated with MMT scores at follow-up.

conclusionsMuscle activity was detected with surface EMG recordings during standard acute care, even for individuals with no observable activity by clinical examination. Wearable sensors may be useful for monitoring early muscle activity and movement after stroke.

Indexed as

ArmElectromyographyHemiplegiaIPR, inpatient rehabilitationList of abbreviations: EMG, electromyographyMMT, manual muscle testMuscle contractionParesisRehabilitationStrokeWearable electronic devices

Identifiers

PMID34589686
PMCPMC8463445
OpenAlexW3172340848

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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.