Evidence map›Paper›PMID 32729524›Full record

ArticleBiosensors & bioelectronics2020

Breathable, large-area epidermal electronic systems for recording electromyographic activity during operant conditioning of H-reflex.

Young-Tae Kwon, James J S Norton, Andrew Cutrone, Hyo-Ryoung Lim, Shinjae Kwon, Jeongmoon J Choi, Hee Seok Kim, Young C Jang, Jonathan R Wolpaw, Woon-Hong Yeo

Open access · greenAbstract read
In one paragraph

Article in Biosensors & bioelectronics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.5field-weighted citation impact, top 10% 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.

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

11 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. 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

10 authors at 4 institutions in 1 country.

Young-Tae KwonGeorge W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
James J S NortonNational Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, 12208, USA; Stratton VA Medical Center, Albany, NY, 12208, USA.
Andrew CutroneNational Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, 12208, USA.
Hyo-Ryoung LimGeorge W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Shinjae KwonGeorge W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Jeongmoon J ChoiSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Hee Seok KimDepartment of Mechanical Engineering, University of South Alabama, Mobile, AL, 36608, USA.
Young C JangSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Wallace H. Coulter Department of Biomedical Engineering and Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Jonathan R WolpawNational Center for Adaptive Neurotechnologies, Wadsworth Center, New York State Department of Health, Albany, NY, 12208, USA; Stratton VA Medical Center, Albany, NY, 12208, USA.
Woon-Hong YeoGeorge W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Wallace H. Coulter Department of Biomedical Engineering and Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Flexible and Wearable Electronics Advanced Research Program, Neural Engineering Center, Institute for Materials, and Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, 30332, USA. Electronic address: whyeo@gatech.edu.
Georgia Institute of Technology · USNew York State Department of Health · USThe Wallace H. Coulter Department of Biomedical Engineering · USUniversity of South Alabama · US

Funding

Training and DisseminationP41EB018783 · NIBIB · WADSWORTH CENTER · PI Yi Chen · 2014 to 2026
$15.4M
Dynamics and Causal Functions of Large-Scale Cortical and Subcortical NetworksU01NS108916 · NINDS · WADSWORTH CENTER · PI WOLPAW, JONATHAN RICKEL · 2018 to 2019
$1.4M
Corticospinal control of spinal reflex plasticityI01CX001812 · VA · STRATTON VETERANS ADMIN MEDICAL CENTER · PI WOLPAW, JONATHAN RICKEL · 2019 to 2023
–
CSRD VA I01 CX001812NIBIB NIH HHS P41 EB018783NINDS NIH HHS U01 NS108916
6 · The paper itself

Abstract

Operant conditioning of Hoffmann's reflex (H-reflex) is a non-invasive and targeted therapeutic intervention for patients with movement disorders following spinal cord injury. The reflex-conditioning protocol uses electromyography (EMG) to measure reflexes from specific muscles elicited using transcutaneous electrical stimulation. Despite recent advances in wearable electronics, existing EMG systems that measure muscle activity for operant conditioning of spinal reflexes still use rigid metal electrodes with conductive gels and aggressive adhesives, while requiring precise positioning to ensure reliability of data across experimental sessions. Here, we present the first large-area epidermal electronic system (L-EES) and demonstrate its use in every step of the reflex-conditioning protocol. The L-EES is a stretchable and breathable composite of nanomembrane electrodes (16 electrodes in a four by four array), elastomer, and fabric. The nanomembrane electrode array enables EMG recording from a large surface area on the skin and the breathable elastomer with fabric is biocompatible and comfortable for patients. We show that L-EES can record direct muscle responses (M-waves) and H-reflexes, both of which are comparable to those recorded using conventional EMG recording systems. In addition, L-EES may improve the reflex-conditioning protocol; it has potential to automatically optimize EMG electrode positioning, which may reduce setup time and error across experimental sessions.

Indexed as

Biosensing TechniquesH-ReflexConditioning, OperantElectronicsHumansReproducibility of Resultsand Breathable fabricElectromyographyLarge-area epidermal electronic system (L-EES)Multi-channel nanomembrane electrodesNeuromuscular response

Identifiers

PMID32729524
PMCPMC7484316
OpenAlexW3037673893

What OpenQuestion holds

Textmetadata
LicenceTDM
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.