Enhancing E-Nose Performance via Metal-Oxide Based MEMS Sensor Arrays Optimization and Feature Alignment for Drug Classification.

Ruiwen Kong, Wenfeng Shen, Yang Gao, Dawu Lv, Ling Ai, Weijie Song, Ruiqin Tan

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

7 authors.

Ruiwen KongFaculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China.

Wenfeng ShenCenter of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0003-3370-9801

Yang GaoResearch and Manufacturing Base of Olfactory Sensors in China Sensing Valley, Bengbu 233040, China.

Dawu LvCenter of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.

Ling AiCenter of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0001-7681-1510

Weijie SongCenter of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.ORCID 0000-0001-8129-8889

Ruiqin TanFaculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China.

Funding

NBSTI 2023Z021Zhejiang Natural Science Foundation LGF22F010008

6 · The paper itself

Abstract

This article introduces a novel approach to improve electronic nose classification accuracy by optimizing sensor arrays and aligning features. This involves selecting the best sensor combinations and reducing redundant information for better odor recognition. We employ a feature alignment algorithm to address the discrepancies that impede model sharing between electronic nose devices. Our research focuses on overcoming challenges associated with material selection and the constraints of transferring classification models across different electronic nose devices for drug classification. We fabricated six SnO

Indexed as

Electronic NoseMetalsMicro-Electrical-Mechanical SystemsAlgorithmsHumansOdorantsPharmaceutical PreparationsTin CompoundsMetalsPharmaceutical Preparationsstannic oxideTin Compoundselectronic nosefeature alignmentMEMSReliefF algorithmtransfer learning

Identifiers

PMID40099565

DOI10.3390/s25051480

PMCPMC11902490

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.