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Enregistrement W3046850665 · doi:10.11159/icbes20.129

Development of a near-field sensor to study the effect of glucose concentration

2020· article· en· W3046850665 sur OpenAlexvenueno aff
Kseniya Zavyalova, Andrey Zapasnoy, Aleksandr Gorst, Aleksandr Mironchev, Andrey Klokov

Notice bibliographique

RevueProceedings of the World Congress on Electrical Engineering and Computer Systems and Science · 2020
Typearticle
Langueen
DomaineEngineering
ThématiqueMicrowave and Dielectric Measurement Techniques
Établissements canadiensnon disponible
Organismes subventionnairesRussian Science Foundation
Mots-clésField (mathematics)Computer scienceMathematics

Résumé

récupéré en direct d'OpenAlex

In this study a near-field sensor design has been developed to study the effect of glucose concentration in a biological medium.The sensor is a combined emitter in the form of a symmetric dipole and an annular frame.The sensor is powered at the input of a symmetric dipole.This sensor was designed to maximize the amount of bound energy in its near zone.The near field of radiowave radiation should not experience absorption in the conducting medium and significant distortion due to small inhomogeneities because of its nature.Therefore, we studied the possibility of creating a sensor sensitive to changes in glucose concentration based on the near-field effect.A biological medium, such as a person's hand or wrist, is generally a conductive medium.The developed combined sensor showed its consistency in the study of solutions with different glucose contents in a numerical model.The research was based on experimental and theoretical studies, as well as on numerical modeling of the influence of the dielectric constant of biological materials (media) on the reflected signal of the sensor.To begin with, we modeled the sensor and tested its sensitivity on the blood layer with different values of glucose concentrations.Next, we carried out a detailed numerical study of the influence of all layers.The main components of the biological medium are blood, fat, muscles and bones.From the point of view of diagnosing glucose in the blood of a person, the most simple and convenient places for diagnosis are his limbs (arms and legs), in particular the wrist.In these limbs, the following layers can be conditionally distinguished: skin, which in turn is divided into epidermis and dermis (the main component of this layer); hypodermis, which forms the cell space, which includes fatty deposits and blood vessels; the next biological layer is the muscles that occupy most of the space of a human limb; in the center of all layers is a bone.Microwave diagnostics is based on establishing the relationship of changes in the dielectric constant of the medium and the parameters of the probing signal.In theoretical studies, the dielectric constant is usually approximated using the Debye model, or a slightly modified version of it -the Cole-Cole model.It was the latter model that made it possible to calculate the permittivity of the substances listed above in a wide frequency range.We independently calculated the dependences of the real part of the dielectric constant of blood, fat, muscle and bone on a frequency in the range from 10 MHz to 10 GHz.As one would expect, substances containing an aqueous solution (blood, muscles and skin) have a higher dielectric constant in a wide frequency band.The same feature is also characteristic of the imaginary part of the dielectric constant.The features of the near-field interaction of the sensor with various substances of the biological medium were studied by us based on the analysis of the behavior of the real part of the radiation power flux density (Poynting vector).The formation of such a flow is a characteristic feature of the interference interaction of overlapping evanescent fields, regardless of their origin (in this case, the opposing fields of the probe and the field reflected from the substance overlap).The calculation results allowed us to estimate the depth of radiation penetration into the studied sample of the substance.Another important parameter of the sensor is its coordination with the studied sample of biological substance, which means that all radiated energy must penetrate into the sample.Such a parameter is the voltage standing wave coefficient, and the resistance of the near-field source should be consistent with the resistance of human blood, since the change in its dielectric constant is the most important for our consideration.During the simulation, the thickness of the layer of blood

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,002

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,011
Tête enseignante GPT0,210
Écart entre enseignants0,200 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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