Displacement Estimation Using 3D-Printed RFID Arrays for Structural Health Monitoring.

Metin Pekgor, Reza Arablouei, Mostafa Nikzad, Syed Masood

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it

0cells of the map it votes in

2citing 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

2 citing papers in PubMed.

RFID-embedded mattress for sleep disorder detection for athletes in sports psychology.Scientific reports · 2025
Article
Displacement Estimation via 3D-Printed RFID Sensors for Structural Health Monitoring: Leveraging Machine Learning and Photoluminescence to Overcome Data Gaps.Sensors (Basel, Switzerland) · 2024
Article

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.

Metin PekgorDepartment of Mechanical and Product Design Engineering, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0001-9634-4630

Reza ArabloueiData61, Commonwealth Scientific and Industrial Research Organisation, Pullenvale, QLD 4069, Australia.ORCID 0000-0002-6932-2900

Mostafa NikzadDepartment of Mechanical and Product Design Engineering, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.

Syed MasoodDepartment of Mechanical and Product Design Engineering, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0001-9472-1527

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radio frequency identification (RFID) tags are small, low-cost, wearable, and wireless sensors that can detect movement in structures, humans, or robots. In this paper, we use passive RFID tags for structural health monitoring by detecting displacements. We employ a novel process of using 3D printable embedded passive RFID tags within uniform linear arrays together with the multiple signal classification algorithm to estimate the direction of arrival using only the phase of the backscattered signals. We validate our proposed approach via data collected from real-world experiments using a unipolar RFID reader antenna and both narrowband and wideband measurements.

Indexed as

Radio Frequency Identification DeviceAlgorithmsHumansPrinting, Three-Dimensional3D printingdirection of arrivalmultiple signal classificationRFIDstructural health monitoring

Identifiers

PMID36433408

DOI10.3390/s22228811

PMCPMC9697010

What OpenQuestion holds

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LicenceCC BY

Read underepoch 390

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.