Evidence map›Paper›PMID 37177661›Full record

ReviewSensors (Basel, Switzerland)2023

Multi-Transduction-Mechanism Technology, an Emerging Approach to Enhance Sensor Performance.

Youssef Ezzat Elnemr, Aya Abu-Libdeh, Gian Carlo Antony Raj, Yumna Birjis, Haleh Nazemi, Pavithra Munirathinam, Arezoo Emadi

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Youssef Ezzat ElnemrDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.ORCID 0009-0009-4363-2888
Aya Abu-LibdehDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.ORCID 0000-0003-1336-8149
Gian Carlo Antony RajDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.ORCID 0009-0002-4851-2024
Yumna BirjisDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.ORCID 0000-0003-3519-1858
Haleh NazemiDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.ORCID 0000-0002-6143-4094
Pavithra MunirathinamDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.
Arezoo EmadiDepartment of Electrical and Computer Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada.ORCID 0000-0003-2034-1120

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional sensor systems employ single-transduction technology where they respond to an input stimulus and transduce the measured parameter into a readable output signal. As such, the technology can only provide limited corresponding data of the detected parameters due to relying on a single transformed output signal for information acquisition. This limitation commonly results in the need for utilizing sensor array technology to detect targeted parameters in complex environments. Multi-transduction-mechanism technology, on the other hand, may combine more than one transduction mechanism into a single structure. By employing this technology, sensors can be designed to simultaneously distinguish between different input signals from complex environments for greater degrees of freedom. This allows a multi-parameter response, which results in an increased range of detection and improved signal-to-noise ratio. In addition, utilizing a multi-transduction-mechanism approach can achieve miniaturization by reducing the number of required sensors in an array, providing further miniaturization and enhanced performance. This paper introduces the concept of multi-transduction-mechanism technology by exploring different candidate combinations of fundamental transduction mechanisms such as piezoresistive, piezoelectric, triboelectric, capacitive, and inductive mechanisms.

Indexed as

capacitiveelectronic noseenergy harvestinghybrid nanogeneratorsmicroelectromechanical systemsmulti-transductionpiezoelectricsensortransduction mechanismstriboelectric

Identifiers

PMID37177661
PMCPMC10181588

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.