Evidence map›Paper›PMID 35009640›Full record

ArticleSensors (Basel, Switzerland)2021

Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study.

Andrey Briko, Vladislava Kapravchuk, Alexander Kobelev, Alexey Tikhomirov, Ahmad Hammoud, Mugeb Al-Harosh, Steffen Leonhardt, Chuong Ngo, Yury Gulyaev, Sergey Shchukin

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

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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

10 authors at 3 institutions in 2 countries.

Andrey BrikoDepartment of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
Vladislava KapravchukDepartment of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.ORCID 0000-0001-8585-4408
Alexander KobelevDepartment of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.ORCID 0000-0001-6715-7668
Alexey TikhomirovDepartment of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.ORCID 0000-0002-5989-9044
Ahmad HammoudDepartment of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
Mugeb Al-HaroshDepartment of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
Steffen LeonhardtChair of Medical Information Technology, RWTH Aachen University, 52074 Aachen, Germany.ORCID 0000-0002-6898-6887
Chuong NgoChair of Medical Information Technology, RWTH Aachen University, 52074 Aachen, Germany.
Yury GulyaevKotelnikov Institute of Radioengineering and Electronics (IRE) of Russian Academy of Sciences, 125009 Moscow, Russia.
Sergey ShchukinDepartment of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.
Bauman Moscow State Technical University · RURWTH Aachen University · DEInstitute of Radio-Engineering and Electronics · RU

Funding

Deutsche Forschungsgemeinschaft LE 817/41-1Russian Foundation for Basic Research 20-58-12006
6 · The paper itself

Abstract

The electrical impedance myography method is widely used in solving bionic control problems and consists of assessing the change in the electrical impedance magnitude during muscle contraction in real time. However, the choice of electrode systems sizes is not always properly considered when using the electrical impedance myography method in the existing approaches, which is important in terms of electrical impedance signal expressiveness and reproducibility. The article is devoted to the determination of acceptable sizes for the electrode systems for electrical impedance myography using the Pareto optimality assessment method and the electrical impedance signals formation model of the forearm area, taking into account the change in the electrophysical and geometric parameters of the skin and fat layer and muscle groups when performing actions with a hand. Numerical finite element simulation using anthropometric models of the forearm obtained by volunteers' MRI 3D reconstructions was performed to determine a sufficient degree of the forearm anatomical features detailing in terms of the measured electrical impedance. For the mathematical description of electrical impedance relationships, a forearm two-layer model, represented by the skin-fat layer and muscles, was reasonably chosen, which adequately describes the change in electrical impedance when performing hand actions. Using this model, for the first time, an approach that can be used to determine the acceptable sizes of electrode systems for different parts of the body individually was proposed.

Indexed as

Muscle, SkeletalMyographyElectric ImpedanceElectrodesHumansReproducibility of Resultsbionic controlelectrical impedanceelectrode systemmathematical modelMRI reconstructionneuromuscular interfaceorthosesPareto optimalityphysical modelingprosthesis

Identifiers

PMID35009640
PMCPMC8747741
OpenAlexW4200505475

What OpenQuestion holds

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LicenceCC BY
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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.