Evidence map›Paper›PMID 29976851›Full record

ArticleSensors (Basel, Switzerland)2018

Nonlinear Flow Sensor Calibration with an Accurate Syringe.

Paolo Jose Cesare Biselli, Raquel Siqueira Nóbrega, Francisco Garcia Soriano

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 22% of its field
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

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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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 at 1 institution in 1 country.

Paolo Jose Cesare BiselliIntensive Care Unit, University Hospital, University of Sao Paulo, Av. Prof Lineu Prestes, 2565, Butantã, São Paulo, SP 05508-000, Brazil. p_biselli@hotmail.com.
Raquel Siqueira NóbregaIntensive Care Unit, University Hospital, University of Sao Paulo, Av. Prof Lineu Prestes, 2565, Butantã, São Paulo, SP 05508-000, Brazil. raquelsnobrega@hu.usp.br.
Francisco Garcia SorianoIntensive Care Unit, University Hospital, University of Sao Paulo, Av. Prof Lineu Prestes, 2565, Butantã, São Paulo, SP 05508-000, Brazil. gsoriano@usp.br.
Universidade de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flow sensors are required for monitoring patients on mechanical ventilation and in respiratory research. Proper calibration is important for ensuring accuracy and can be done with a precision syringe. This procedure, however, becomes complex for nonlinear flow sensors, which are commonly used. The objective of the present work was to develop an algorithm to allow the calibration of nonlinear flow sensors using an accurate syringe. We first noticed that a power law equation could properly fit the pressure-flow relationship of nonlinear flow sensors. We then developed a software code to estimate the parameters for this equation using a 3 L syringe (calibration syringe). Finally, we tested the performance of a calibrated flow sensor using a different 3 L syringe (testing syringe) and a commercially available spirometer. After calibration, the sensor had a bias ranging from −1.7% to 3.0% and precision from 0.012 L to 0.039 L for volumes measured with the 3 L testing syringe. Calibrated sensor performance was at least as good as the commercial sensor. This calibration procedure can be done at the bedside for both clinical and research purposes, therefore improving the accuracy of nonlinear flow sensors.

Indexed as

CalibrationHumansRespiration, ArtificialSoftwareSpirometrySyringescalibrationflow sensormechanical ventilationnonlinear

Identifiers

PMID29976851
PMCPMC6068951
OpenAlexW2851137343

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.