Evidence map›Paper›PMID 38314325›Full record

ArticleJRSM cardiovascular disease

Advanced waveform analysis of the photoplethysmogram signal using complementary signal processing techniques for the extraction of biomarkers of cardiovascular function.

Aristide Jun Wen Mathieu, Miquel Serna Pascual, Peter H Charlton, Maria Volovaya, Jenny Venton, Philip J Aston, Manasi Nandi, Jordi Alastruey

Open access · hybridAbstract read
In one paragraph

Article in JRSM cardiovascular disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 4 institutions in 1 country.

Aristide Jun Wen MathieuDepartment of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital, London, UK.
Miquel Serna PascualSchool of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK.
Peter H CharltonDepartment of Public Health and Primary Care, University of Cambridge, Cambridge, Cambridgeshire, UK.ORCID https://orcid.org/0000-0003-3836-8655
Maria VolovayaSchool of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK.
Jenny VentonSchool of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK.
Philip J AstonDepartment of Mathematics, University of Surrey, Guildford, UK.
Manasi NandiSchool of Cancer and Pharmaceutical Science, Faculty of Life Sciences and Medicine, King's College London, London, UK.ORCID https://orcid.org/0000-0001-8585-5363
Jordi AlastrueyDepartment of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, St Thomas' Hospital, London, UK.
King's College London · GBSt Thomas' Hospital · GBUniversity of Cambridge · GBUniversity of Surrey · GB

Funding

British Heart Foundation FS/20/20/34626Wellcome Trust
6 · The paper itself

Abstract

Introduction: Photoplethysmogram signals from wearable devices typically measure heart rate and blood oxygen saturation, but contain a wealth of additional information about the cardiovascular system. In this study, we compared two signal-processing techniques: fiducial point analysis and Symmetric Projection Attractor Reconstruction, on their ability to extract new cardiovascular information from a photoplethysmogram signal. The aim was to identify fiducial point analysis and Symmetric Projection Attractor Reconstruction indices that could classify photoplethysmogram signals, according to age, sex and physical activity. Methods: Three datasets were used: an Results: Key fiducial point analysis and Symmetric Projection Attractor Reconstruction indices, which showed the greatest differences between groups, were found to be consistent across datasets. These indices were related to systolic augmentation, diastolic peak positioning and prominence, and waveform variability. Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques provided indices that supported the classification of age and physical activity, but not sex. Conclusions: Both fiducial point analysis and Symmetric Projection Attractor Reconstruction techniques demonstrated utility in identifying cardiovascular differences between individuals and within an individual over time. Future research should investigate the potential utility of these techniques for extracting information on fitness and disease, to support healthcare-decision making.

Indexed as

fiducial point analysisPhotoplethysmogrampulse wave morphologypulse wave variabilitySymmetric Projection Attractor Reconstructionvascular aging

Identifiers

PMID38314325
PMCPMC10838030
OpenAlexW4391487795

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.