Electromechanical Impedance Sensing Under Humid Conditions: Experimental Insights and Compensation Using Machine Learning.

Mads Kofod Dahl, Jaamac Hassan Hire, Milad Zamani, Alexandru Luca, Farshad Moradi

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

5 authors.

Mads Kofod DahlDepartment of Electrical and Computer Engineering, Aarhus University, 8200 Aarhus, Denmark.ORCID 0009-0006-4330-6730

Jaamac Hassan HireDepartment of Electrical and Computer Engineering, Aarhus University, 8200 Aarhus, Denmark.ORCID 0000-0002-3714-7773

Milad ZamaniSDU Microelectronics, Department of Mechanical and Electrical Engineering, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark.ORCID 0000-0002-8718-7095

Alexandru LucaDepartment of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus, Denmark.ORCID 0000-0002-7995-9251

Farshad MoradiSDU Microelectronics, Department of Mechanical and Electrical Engineering, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark.ORCID 0000-0001-7077-8545

Funding

Innovation Fund Denmark 2081-00027A

6 · The paper itself

Abstract

This work investigates the effect of ambient humidity on the Electromechanical Impedance (EMI) signatures of steel-reinforced concrete (RC) for structural health monitoring (SHM). The influence of varying relative humidity (%RH) is quantified using three RC blocks containing piezoelectric sensors bonded to the steel reinforcements of the RC blocks. We show that the the Root Mean Squared Deviation (RMSD) score is strongly affected by humidity, highlighting the need to address humidity effects to achieve robust damage detection using EMI. Using the reactive component of the EMI (

Indexed as

CNNelectro mechanical impedanceEMIhumiditymachine learningmulti modal sensingpiezoelectricreinforced concreteSHMstructural health monitoring

Identifiers

PMID41682459

DOI10.3390/s26030943

PMCPMC12899882

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.