ECGdeli - An open source ECG delineation toolbox for MATLAB
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TLDR
The results show that ECGdeli can reliably detect P waves, QRS complexes and T waves and can contribute to diagnose specific cardiac diseases by analyzing the ECG signal.About:
This article is published in SoftwareX.The article was published on 2021-01-01 and is currently open access. It has received 31 citations till now. The article focuses on the topics: QRS complex & T wave.read more
Citations
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Journal ArticleDOI
Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG.
Giorgio Luongo,Luca Azzolin,Steffen Schuler,Massimo W. Rivolta,Tiago P. Almeida,Juan Pablo Martinez,Diogo C. Soriano,Armin Luik,Björn Müller-Edenborn,Amir Jadidi,Olaf Dössel,Roberto Sassi,Pablo Laguna,Axel Loewe +13 more
TL;DR: A machine learning-based classification of 12-lead-ECG allows discrimination between patients with PV drivers vs those with extra-PV drivers of supraventricular arrhythmia, which may aid to identify patients with high acute success rates to Pulmonary vein isolation as discussed by the authors.
Journal ArticleDOI
Robustness of convolutional neural networks to physiological electrocardiogram noise.
TL;DR: The electrocardiogram (ECG) is a widely used diagnostic tool in healthcare and supports the diagnosis of cardiovascular disorders as mentioned in this paper, and deep learning methods are a successful and popular technique to diagnose cardiovascular disorders.
Posted ContentDOI
AugmentA: Patient-specific Augmented Atrial model Generation Tool
Luca Azzolin,Martin Eichenlaub,Claudia Nagel,Deborah Nairn,Jorge Sanchez,Laura A. Unger,Olaf Doessel,Abdullah Al Jadidi,Axel Loewe +8 more
TL;DR: A patient-specific Augmented Atria generation pipeline (AugmentA) is proposed as a highly automated framework which, starting from clinical geometrical data, provides ready-to-use atrial personalized computational models.
Journal ArticleDOI
Local Electrical Impedance Mapping of the Atria: Conclusions on Substrate Properties and Confounding Factors
Laura A. Unger,Leonie Schicketanz,Tobias Oesterlein,Michael Stritt,Annika Haas,C. Martínez Antón,Kerstin N. Schmidt,Olaf Doessel,Armin Luik +8 more
TL;DR: Local impedance measurements demonstrated their capability to distinguish pathological atrial tissue from physiological substrate, indicating that electrogram- and impedance-based substrate mapping have the potential to complement each other toward better patient outcomes in future.
Journal ArticleDOI
MedalCare-XL: 16, 900 healthy and pathological 12 lead ECGs obtained through electrophysiological simulations
Karli Gillette,Matthias A. F. Gsell,Claudia Nagel,Jule Bender,Bejamin Winkler,Steven Williams,Markus Bär,Tobias Schäffter,Olaf Dössel,Gernot Plank,Axel Loewe +10 more
TL;DR: In this paper , a synthetic dataset of 16,900 12-lead ECGs was generated for validation of machine learning ECG analysis tools in addition to clinical signals, which can be used to enrich sparse clinical data or even replace them completely during training.
References
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Book
Bioelectrical Signal Processing in Cardiac and Neurological Applications
Leif Sörnmo,Pablo Laguna +1 more
TL;DR: Chapter 1.
Book
Advanced Methods And Tools for ECG Data Analysis
TL;DR: The ECG and Its Contaminants, Visualization Methods, Knowledge Management and Emerging Methods, and Supervised and Unsupervised Classification.
Journal ArticleDOI
Automatic detection of wave boundaries in multilead ECG signals: validation with the CSE database
TL;DR: An algorithm for automatically locating the waveform boundaries (the onsets and ends of P, QRS, and T waves) in multilead ECG signals (the 12 standard leads and the orthogonal XYZ leads) achieves better agreement with manual measurements of the T-wave end and of interval values.
Journal ArticleDOI
A History of the origin, evolution, and impact of electrocardiography
W. Bruce Fye,W. Bruce Fye +1 more
TL;DR: The origins and development of electrocardiography are summarized and its role in defining cardiology as a specialty is addressed and it is addressed how this information helps physicians diagnose various forms of heart disease.
Journal ArticleDOI
Computational techniques for ECG analysis and interpretation in light of their contribution to medical advances
TL;DR: The computational methods reported in this review are a strong asset for medical discoveries and their translation to the clinical world may lead to promising advances.