Evidence map›Paper›PMID 36877361›Full record

ArticlePhysical and engineering sciences in medicine2023

Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes.

Manuel Merino-Monge, Juan Antonio Castro-García, Clara Lebrato-Vázquez, Isabel María Gómez-González, Alberto Jesús Molina-Cantero

Abstract read
In one paragraph

Article in Physical and engineering sciences in medicine, 2023. 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. Review
  2. Article
  3. Intrinsic PPG-ECG Coupling for Accurate and Low-Power Blood Pressure Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  4. Article
  5. 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

5 authors.

Manuel Merino-MongeDepartamento de Tecnología Electrónica, E.T.S.I. Ingeniería Informática, Universidad de Sevilla, Avd. Reina Mercedes s/n, 41012, Sevilla, Sevilla, Spain. manmermon@dte.us.es.ORCID http://orcid.org/0000-0003-0204-4544
Juan Antonio Castro-GarcíaDepartamento de Tecnología Electrónica, E.T.S.I. Ingeniería Informática, Universidad de Sevilla, Avd. Reina Mercedes s/n, 41012, Sevilla, Sevilla, Spain.ORCID http://orcid.org/0000-0003-1128-6879
Clara Lebrato-VázquezDepartamento de Tecnología Electrónica, E.T.S.I. Ingeniería Informática, Universidad de Sevilla, Avd. Reina Mercedes s/n, 41012, Sevilla, Sevilla, Spain.ORCID http://orcid.org/0000-0002-7565-5517
Isabel María Gómez-GonzálezDepartamento de Tecnología Electrónica, E.T.S.I. Ingeniería Informática, Universidad de Sevilla, Avd. Reina Mercedes s/n, 41012, Sevilla, Sevilla, Spain.ORCID http://orcid.org/0000-0002-6041-1480
Alberto Jesús Molina-CanteroDepartamento de Tecnología Electrónica, E.T.S.I. Ingeniería Informática, Universidad de Sevilla, Avd. Reina Mercedes s/n, 41012, Sevilla, Sevilla, Spain.ORCID http://orcid.org/0000-0002-2256-0127

Funding

Ministerio de Ciencia, Innovación y Universidades PID2019-104323RB-C32
6 · The paper itself

Abstract

The analysis of cardiac activity is one of the most common elements for evaluating the state of a subject, either to control possible health risks, sports performance, stress levels, etc. This activity can be recorded using different techniques, with electrocardiogram and photoplethysmogram being the most common. Both techniques make significantly different waveforms, however the first derivative of the photoplethysmographic data produces a signal structurally similar to the electrocardiogram, so any technique focusing on detecting QRS complexes, and thus heartbeats in electrocardiogram, is potentially applicable to photoplethysmogram. In this paper, we develop a technique based on the wavelet transform and envelopes to detect heartbeats in both electrocardiogram and photoplethysmogram. The wavelet transform is used to enhance QRS complexes with respect to other signal elements, while the envelopes are used as an adaptive threshold to determine their temporal location. We compared our approach with three other techniques using electrocardiogram signals from the Physionet database and photoplethysmographic signals from the DEAP database. Our proposal showed better performances when compared to others. When the electrocardiographic signal was considered, the method had an accuracy greater than 99.94%, a true positive rate of 99.96%, and positive prediction value of 99.76%. When photoplethysmographic signals were investigated, an accuracy greater than 99.27%, a true positive rate of 99.98% and positive prediction value of 99.50% were obtained. These results indicate that our proposal can be adapted better to the recording technology.

Indexed as

Signal Processing, Computer-AssistedWavelet AnalysisAlgorithmsElectrocardiographyHeart RateECGEnvelopesHeartbeat detectionPPGWavelet transform

Identifiers

PMID36877361
PMCPMC10209290

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.