Evidence map›Paper›PMID 35414211›Full record

ReviewJournal of the Royal Society, Interface2022

Robustness of electrocardiogram signal quality indices.

Saifur Rahman, Chandan Karmakar, Iynkaran Natgunanathan, John Yearwood, Marimuthu Palaniswami

Abstract readReview
In one paragraph

Review in Journal of the Royal Society, Interface, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Quantifying the Suitability of Biosignals Acquired During Surgery for Multimodal Analysis.IEEE open journal of engineering in medicine and biology · 2024
    Article
  20. 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

5 authors.

Saifur RahmanSchool of Information Technology, Deakin University, Geelong 3225, Australia.ORCID 0000-0001-8345-0952
Chandan KarmakarSchool of Information Technology, Deakin University, Geelong 3225, Australia.ORCID 0000-0003-1814-0856
Iynkaran NatgunanathanSchool of Information Technology, Deakin University, Geelong 3225, Australia.
John YearwoodSchool of Information Technology, Deakin University, Geelong 3225, Australia.
Marimuthu PalaniswamiDepartment of Electrical and Electronic Engineering, University of Melbourne, Melbourne, Victoria 3010, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrocardiogram (ECG) signal quality indices (SQIs) are essential for improving diagnostic accuracy and reliability of ECG analysis systems. In various practical applications, the ECG signals are corrupted by different types of noise. These corrupted ECG signals often provide insufficient and incorrect information regarding a patient's health. To solve this problem, signal quality measurements should be made before an ECG signal is used for decision-making. This paper investigates the robustness of existing popular statistical signal quality indices (SSQIs): relative power of QRS complex (SQI

Indexed as

AlgorithmsSignal Processing, Computer-AssistedElectrocardiographyHumansReproducibility of ResultsSignal-To-Noise Ratiocardiovascular diseaseselectrocardiogramsignal quality indicesSQAstatistical signal quality indicesthreshold‌

Identifiers

PMID35414211
PMCPMC9006023

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.