Evidence map›Paper›PMID 36616660›Full record

ArticleSensors (Basel, Switzerland)2022

Analog Lock-In Amplifier Design Using Subsampling for Accuracy Enhancement in GMI Sensor Applications.

José M Algueta-Miguel, J Jesús Beato-López, Antonio J López-Martín

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.

  1. Article
  2. 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

3 authors.

José M Algueta-MiguelInstitute of Smart Cities, Universidad Pública de Navarra (UPNA), Campus Arrosadia, 31006 Pamplona, Spain.ORCID 0000-0001-9323-4516
J Jesús Beato-LópezDepartamento de Ciencias, Institute for Advanced Materials and Mathematics INAMAT2, Universidad Pública de Navarra (UPNA), Campus Arrosadia, 31006 Pamplona, Spain.ORCID 0000-0002-9339-3557
Antonio J López-MartínInstitute of Smart Cities, Universidad Pública de Navarra (UPNA), Campus Arrosadia, 31006 Pamplona, Spain.ORCID 0000-0001-7629-0305

Funding

MCIN/AEI/10.13039/501100011033 PID2019-107258RB-C32Public University of Navarre PJUPNA2005
6 · The paper itself

Abstract

A frequency downscaling technique for enhancing the accuracy of analog lock-in amplifier (LIA) architectures in giant magneto-impedance (GMI) sensor applications is presented in this paper. As a proof of concept, the proposed method is applied to two different LIA topologies using, respectively, analog and switching-based multiplication for phase-sensitive detection. Specifically, the operation frequency of both the input and the reference signals of the phase-sensitive detector (PSD) block of the LIA is reduced through a subsampling process using sample-and-hold (SH) circuits. A frequency downscaling from 200 kHz, which is the optimal operating frequency of the employed GMI sensor, to 1 kHz has been performed. In this way, the proposed technique exploits the inherent advantages of analog signal multiplication at low frequencies, while the principle of operation of the PSD remains unaltered. The circuits were assembled using discrete components, and the frequency downscaling proposal was experimentally validated by comparing the measurement accuracy with the equivalent conventional circuits. The experimental results revealed that the error in the signal magnitude measurements was reduced by a factor of 8 in the case of the analog multipliers and by a factor of 21 when a PSD based on switched multipliers was used. The error in-phase detection using a two-phase LIA was also reduced by more than 25%.

Indexed as

GMI sensorlock-in amplifierphase-sensitive detectorsample-and-holdsubsampling

Identifiers

PMID36616660
PMCPMC9823856

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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.