Evidence map›Paper›PMID 40006324›Full record

ArticleSensors (Basel, Switzerland)2025

Accuracy of the Instantaneous Breathing and Heart Rates Estimated by Smartphone Inertial Units.

Eliana Cinotti, Jessica Centracchio, Salvatore Parlato, Daniele Esposito, Antonio Fratini, Paolo Bifulco, Emilio Andreozzi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. 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
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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.

Eliana CinottiDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, I-80125 Naples, Italy.ORCID 0009-0004-1588-271X
Jessica CentracchioDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, I-80125 Naples, Italy.ORCID 0000-0003-3422-8727
Salvatore ParlatoDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, I-80125 Naples, Italy.ORCID 0009-0000-9314-5126
Daniele EspositoDepartment of Information and Electrical Engineering and Applied Mathematics, University of Salerno, Via Giovanni Paolo II, 132, I-84084 Fisciano, Italy.ORCID 0000-0003-0716-8431
Antonio FratiniCollege of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK.ORCID 0000-0001-8894-461X
Paolo BifulcoDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, I-80125 Naples, Italy.ORCID 0000-0002-9585-971X
Emilio AndreozziDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, I-80125 Naples, Italy.ORCID 0000-0003-4829-3941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Seismocardiography (SCG) and Gyrocardiography (GCG) use lightweight, miniaturized accelerometers and gyroscopes to record, respectively, cardiac-induced linear accelerations and angular velocities of the chest wall. These inertial sensors are also sensitive to thoracic movements with respiration, which cause baseline wanderings in SCG and GCG signals. Nowadays, accelerometers and gyroscopes are widely integrated into smartphones, thus increasing the potential of SCG and GCG as cardiorespiratory monitoring tools. This study investigates the accuracy of smartphone inertial sensors in simultaneously measuring instantaneous heart rates and breathing rates. Smartphone-derived SCG and GCG signals were acquired from 10 healthy subjects at rest. The performances of heartbeats and respiratory acts detection, as well as of inter-beat intervals (IBIs) and inter-breath intervals (IBrIs) estimation, were evaluated for both SCG and GCG via the comparison with simultaneous electrocardiography and respiration belt signals. Heartbeats were detected with a sensitivity and positive predictive value (PPV) of 89.3% and 93.3% in SCG signals and of 97.3% and 97.9% in GCG signals. Moreover, IBIs measurements reported strong linear relationships (R

Indexed as

Heart RateRespirationRespiratory RateSmartphoneAccelerometryAdultElectrocardiographyFemaleHumansMaleMonitoring, PhysiologicSignal Processing, Computer-AssistedYoung Adultaccelerometerbreathing ratecardiorespiratory monitoringgyrocardiographygyroscopeheartbeat detectionheart raterespirationseismocardiographysmartphone

Identifiers

PMID40006324
PMCPMC11859794

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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.