Evidence map›Paper›PMID 41012922›Full record

ArticleSensors (Basel, Switzerland)2025

Approximate Analytical Approach for Fast Prediction of Microwave Sensor Response: Numerical Analysis and Results.

Antonio Cuccaro, Raffaele Solimene, Sandra Costanzo

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Antonio CuccaroDepartment of Informatics, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria, 87036 Rende, Italy.ORCID 0000-0003-3332-9075
Raffaele SolimeneDepartment of Engineering, University of Campania Luigi Vanvitelli, 81031 Aversa, Italy.ORCID 0000-0003-1808-4671
Sandra CostanzoDepartment of Informatics, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria, 87036 Rende, Italy.ORCID 0000-0002-8028-2268

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In medical applications, microwave sensors are usually employed to work in direct contact with the human body, therefore requiring an accurate prediction of the electromagnetic interactions with biological tissues. While full-wave simulations can be useful to achieve the above task, they are computationally expensive, especially for iterative sensor optimization. Analytical models may offer a more efficient alternative, but they are often complex, and they must be formulated in a practical way to be useful. As a result, approximate approaches can be advantageous. Traditional approaches, such as plane-wave approximations and transmission-line models, often fail to capture key sensing features. This paper presents an approximate analytical model for standard-aperture sensor configurations to predict the sensor response in terms of the reflection coefficient when placed above a layered medium. The model is based on the assumption that the electromagnetic interaction is primarily governed by the sensor's dominant mode. Full-wave simulations in the 2-3 GHz frequency range (relevant for medical applications) demonstrate strong agreement with the analytical model, thereby validating its effectiveness as a first-order approximation for sensor-tissue interactions. This provides a reliable and computationally efficient tool to properly manage microwave sensors design in medical applications.

Indexed as

antennaselectromagneticsmeasurementsmicrowave sensorspropagation

Identifiers

PMID41012922
PMCPMC12473196

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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.