Evidence map›Paper›PMID 36755939›Full record

ArticleMethodsX2023

Methods for the metrological characterization of wearable devices for the measurement of physiological signals: state of the art and future challenges.

G Cosoli, L Antognoli, L Scalise

Abstract read
In one paragraph

Article in MethodsX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
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.

G CosoliDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, v. Brecce Bianche, Ancona 60131, Italy.
L AntognoliDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, v. Brecce Bianche, Ancona 60131, Italy.
L ScaliseDepartment of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, v. Brecce Bianche, Ancona 60131, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wearable devices are rapidly spreading in many different application fields and with diverse measurement accuracy targets. However, data on their metrological characterization are very often missing or obtained with non-standardized methods, hence resulting in barely comparable results. The aim of this review paper is to discuss the existing methods for the metrological characterization of wearable sensors exploited for the measurement of physiological signals, highlighting the room for research still available in this field. Furthermore, as a case study, the authors report a customized method they have tuned for the validation of wireless electrocardiographic monitors. The literature provides a plethora of test/validation procedures, but there is no shared consensus on test parameters (e.g. test population size, test protocol, output parameters of validation procedure, etc.); on the other hand, manufacturers rarely provide measurement accuracy values and, even when they do, the test protocol and data processing pipelines are generally not disclosed. Given the increasing interest and demand of wearable sensors also for medical and diagnostic purposes, the metrological performance of such devices should be always considered, to be able to adequately interpret the results and always deliver them associated with the related measurement accuracy.•The sensor metrological performance should be always properly considered.•There are no standard methods for wearable sensors metrological characterization.•It is important to define rigorous test protocols, easily tunable for specific target applications.

Indexed as

Measurement accuracyMetrological characterizationTest protocolTest protocol for the validation and the metrological characterization of wearable sensors for physiological monitoringValidationWearable devices

Identifiers

PMID36755939
PMCPMC9900615

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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.