Evidence map›Paper›PMID 36712933›Full record

ArticlePNAS nexus2023

Customizable, reconfigurable, and anatomically coordinated large-area, high-density electromyography from drawn-on-skin electrode arrays.

Faheem Ershad, Michael Houston, Shubham Patel, Luis Contreras, Bikram Koirala, Yuntao Lu, Zhoulyu Rao, Yang Liu, Nicholas Dias, Arturo Haces-Garcia and 3 more

Erratum issuedAbstract read
In one paragraph

Article in PNAS nexus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
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  5. Review
  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Faheem ErshadDepartment of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16801, USA.ORCID https://orcid.org/0000-0002-3353-9606
Michael HoustonDepartment of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA.ORCID https://orcid.org/0000-0002-1951-084X
Shubham PatelDepartment of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, 16801, USA.ORCID https://orcid.org/0000-0002-0046-9031
Luis ContrerasDepartment of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA.
Bikram KoiralaDepartment of Mechanical Engineering, University of Houston, Houston, TX, 77204, USA.
Yuntao LuDepartment of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, 16801, USA.
Zhoulyu RaoDepartment of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA, 16801, USA.
Yang LiuDepartment of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA.
Nicholas DiasDepartment of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA.
Arturo Haces-GarciaDepartment of Engineering Technology, University of Houston, Houston, TX, 77204, USA.
Weihang ZhuDepartment of Mechanical Engineering, University of Houston, Houston, TX, 77204, USA.
Yingchun ZhangDepartment of Biomedical Engineering, University of Houston, Houston, TX, 77204, USA.
Cunjiang YuDepartment of Biomedical Engineering, Pennsylvania State University, University Park, PA, 16801, USA.ORCID https://orcid.org/0000-0002-0155-0368

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate anatomical matching for patient-specific electromyographic (EMG) mapping is crucial yet technically challenging in various medical disciplines. The fixed electrode construction of multielectrode arrays (MEAs) makes it nearly impossible to match an individual's unique muscle anatomy. This mismatch between the MEAs and target muscles leads to missing relevant muscle activity, highly redundant data, complicated electrode placement optimization, and inaccuracies in classification algorithms. Here, we present customizable and reconfigurable drawn-on-skin (DoS) MEAs as the first demonstration of high-density EMG mapping from in situ-fabricated electrodes with tunable configurations adapted to subject-specific muscle anatomy. The DoS MEAs show uniform electrical properties and can map EMG activity with high fidelity under skin deformation-induced motion, which stems from the unique and robust skin-electrode interface. They can be used to localize innervation zones (IZs), detect motor unit propagation, and capture EMG signals with consistent quality during large muscle movements. Reconfiguring the electrode arrangement of DoS MEAs to match and extend the coverage of the forearm flexors enables localization of the muscle activity and prevents missed information such as IZs. In addition, DoS MEAs customized to the specific anatomy of subjects produce highly informative data, leading to accurate finger gesture detection and prosthetic control compared with conventional technology.

Identifiers

PMID36712933
PMCPMC9837666

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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.