Evidence map›Paper›PMID 34207899›Full record

ArticleSensors (Basel, Switzerland)2021

Respiration Monitoring via Forcecardiography Sensors.

Emilio Andreozzi, Jessica Centracchio, Vincenzo Punzo, Daniele Esposito, Caitlin Polley, Gaetano D Gargiulo, Paolo Bifulco

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

22 citing papers in PubMed, 50 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. A Flexible PVDF Sensor for Forcecardiography.Sensors (Basel, Switzerland) · 2025
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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

7 authors at 2 institutions in 2 countries.

Emilio AndreozziDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy.ORCID 0000-0003-4829-3941
Jessica CentracchioDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy.ORCID 0000-0003-3422-8727
Vincenzo PunzoDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy.
Daniele EspositoDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy.ORCID 0000-0003-0716-8431
Caitlin PolleySchool of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0002-1918-0393
Gaetano D GargiuloSchool of Engineering, Design and Built Environment, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0002-2616-2804
Paolo BifulcoDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy.ORCID 0000-0002-9585-971X
University of Naples Federico II · ITWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients' discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R

Indexed as

ElectrocardiographyRespirationHeartHumansMonitoring, PhysiologicReproducibility of ResultsSignal Processing, Computer-Assistedcontinuous monitoringforcecardiographyforce-sensitive resistorsforce sensorrespiration

Identifiers

PMID34207899
PMCPMC8228286
OpenAlexW3170162235

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.