Evidence map›Paper›PMID 31150334›Full record

ArticleIEEE transactions on bio-medical engineering2020

Global Innervation Zone Identification With High-Density Surface Electromyography.

Chuan Zhang, Nicholas Dias, Jinbao He, Ping Zhou, Sheng Li, Yingchun Zhang

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

6 authors.

Chuan Zhang
Nicholas Dias
Jinbao He
Ping Zhou
Sheng Li
Yingchun Zhang

Funding

ENGINEERING FOR NEUROLOGIC REHABILITATIONR24HD050821 · NICHD · REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB · PI RYMER, WILLIAM ZEV · 2005 to 2014
$7.9M
Electromechanical Modeling Approach in Assessing Female SUIR00DK082644 · NIDDK · UNIVERSITY OF HOUSTON · PI ZHANG, YINGCHUN · 2013 to 2015
$690k
Imaging of 3D Innervation Zone Distribution in Spastic Muscles from High-Density Surface EMG RecordingsR21HD090453 · NICHD · UNIVERSITY OF HOUSTON · PI LI, SHENG, ZHANG, YINGCHUN · 2017 to 2018
$434k
High density Surface EMG Assessment of the Pelvic Muscle Hypertonicity Associated with Interstitial Cystitis/Bladder Pain SyndromeR21DK113525 · NIDDK · UNIVERSITY OF HOUSTON · PI ZHANG, YINGCHUN · 2017 to 2018
$433k
High-density Surface EMG Assessment of Motor Unit Alterations of the External Anal Sphincter Associated with AgingR56AG053778 · NIA · UNIVERSITY OF HOUSTON · PI ZHANG, YINGCHUN · 2017 to 2017
$205k
NIA NIH HHS R56 AG053778NICHD NIH HHS R21 HD090453NICHD NIH HHS R24 HD050821NIDDK NIH HHS R00 DK082644NIDDK NIH HHS R21 DK113525
6 · The paper itself

Abstract

objectiveThe aim of this study is to compare the performance of three strategies in determining the global innervation zone (IZ) distribution.

methodsHigh-density surface electromyography was recorded from the biceps brachii muscle of seven healthy subjects under isometric voluntary contractions at 20%, 50%, and 100% of the maximal voluntary contraction and supramaximal musculocutaneous nerve stimulations. IZs were detected: first, by visual identification in a column-specific manner (IZ-1D); second, based on decomposed bipolar mapping of motor unit action potentials (IZ-2D); and third, by source imaging in the three-dimensional muscle space (IZ-3D).

resultsAll three IZ detection approaches have exhibited excellent trial-to-trial repeatability. Consistent IZ results were found in the axial direction of the arm across all three approaches, yet a difference was observed in the mediolateral direction.

conclusionsAmong all three approaches, IZ-3D is capable of providing the most comprehensive information regarding the global IZ distribution, while maintaining high consistency with IZ-1D and IZ-2D results. SIGNIFICANCE: IZ-3D approach can be a potential tool for global IZ imaging, which is critical to the clinical diagnosis and treatment of neuromuscular disorders.

Indexed as

Muscle, SkeletalAdultAlgorithmsElectromyographyFemaleHumansMaleMuscle ContractionSignal Processing, Computer-Assisted

Identifiers

PMID31150334
PMCPMC7135959

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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.