Evidence map›Paper›PMID 42280891›Full record

ArticleSensors (Basel, Switzerland)2026

Portable and Digital MOX Sensor Electronic Nose with Thermal Modulation: Design, Stability Analysis, and Long-Term Validation.

Víctor González, Juan Álvaro Fernández, Patricia Arroyo, Jesús Lozano

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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

4 authors.

Víctor GonzálezIndustrial Engineering School, University of Extremadura, 06006 Badajoz, Spain.ORCID 0009-0002-8724-638X
Juan Álvaro FernándezIndustrial Engineering School, University of Extremadura, 06006 Badajoz, Spain.ORCID 0000-0002-0203-7689
Patricia ArroyoIndustrial Engineering School, University of Extremadura, 06006 Badajoz, Spain.ORCID 0000-0002-5918-1788
Jesús LozanoIndustrial Engineering School, University of Extremadura, 06006 Badajoz, Spain.ORCID 0000-0003-0905-9546

Funding

European Union, the European Regional Development Fund, and the Regional Government of Extremadura GR24182Spanish Ministry of Science an Innovation PDC2023-145853- C41
6 · The paper itself

Abstract

A portable electronic nose based on modern digital metal oxide (MOX) gas sensors and programmable temperature modulation was developed and validated. The system integrates four modern commercially available MOX sensors capable of generating temperature-dependent odor fingerprints and multidimensional sensor responses compared with conventional fixed-temperature operation. The performance of the device was assessed in terms of sensor stability, repeatability, and pattern-recognition capability under long-term operation. As a proof of concept, the electronic nose was applied to the discrimination of Extra Virgin Olive Oil and pomace oil. Repeatability analysis using the Root Mean Squared Error (RMSE) demonstrated stable responses across one month of measurements. Temperature-modulated signals were processed using Principal Component Analysis (PCA) and classified with k-Nearest Neighbors (KNNs) and Multilayer Perceptrons (MLPs), achieving 100% accuracy after selecting the most repeatable sensor. These results highlight the robustness and analytical potential of temperature-modulated digital MOX sensors and demonstrate the feasibility of a compact and highly reproducible electronic-nose platform suitable for complex odor-analysis tasks in real-world applications.

Indexed as

chemometricsdigital MOX gas sensorsmachine learningtemperature-modulated electronic nose

Identifiers

PMID42280891
PMCPMC13259520

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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.