ReviewDiagnostics (Basel, Switzerland)2022
Automatic ECG Quality Assessment Techniques: A Systematic Review.
Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Introduction to electrocardiogram signal quality assessment and estimated accuracy for textile electrodes.Scientific reports · 2025Article
- Automated detection of non-physiological artifacts on ECG signal: UK Biobank and CRIC.Computers in biology and medicine · 2025Article
- Usefulness of Atherogenic Indices for Predicting High Values of Avoidable Lost Life Years Heart Age in 139,634 Spanish Workers.Diagnostics (Basel, Switzerland) · 2024Article
- Validation of a New and Straightforward Algorithm to Evaluate Signal Quality during ECG Monitoring with Wearable Devices Used in a Clinical Setting.Bioengineering (Basel, Switzerland) · 2024Article
- An Open-Source Graphical User Interface-Embedded Automated Electrocardiogram Quality Assessment: A Balanced Class Representation Approach.Diagnostics (Basel, Switzerland) · 2023Article
- Motion Artifacts Reduction for Noninvasive Hemodynamic Monitoring of Conscious Patients Using Electrical Impedance Tomography: A Preliminary Study.Sensors (Basel, Switzerland) · 2023Article
- Medical Applications of Nonadditive Entropies.Entropy (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular diseases are the leading cause of death, globally. Stroke and heart attacks account for more than 80% of cardiovascular disease-related deaths. To prevent patient mismanagement and potentially save lives, effective screening at an early stage is needed. Diagnosis is typically made using an electrocardiogram (ECG) analysis. However, ECG recordings are often corrupted by different types of noise, degrading the quality of the recording and making diagnosis more difficult. This paper reviews research on automatic ECG quality assessment techniques used in studies published from 2012-2022. The CinC11 Dataset is most often used for training and testing algorithms. Only one study tested its algorithm on people in real-time, but it did not specify the demographic data of the subjects. Most of the reviewed papers evaluated the quality of the ECG recordings per single lead. The accuracy of the algorithms reviewed in this paper range from 85.75% to 97.15%. More clarity on the research methods used is needed to improve the quality of automatic ECG quality assessment techniques and implement them in a clinical setting. This paper discusses the possible shortcomings in current research and provides recommendations on how to advance the field of automatic ECG quality assessment.
Indexed as
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What OpenQuestion holds
Registered trials
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.