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A dynamical model for generating synthetic electrocardiogram signals
TLDR
A dynamical model based on three coupled ordinary differential equations is introduced which is capable of generating realistic synthetic electrocardiogram (ECG) signals. Expand
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Advanced Methods And Tools for ECG Data Analysis
Preface. Introduction. Mathematical Characterization of the ECG and Its Contaminants. Filtering, Compression, Decompression, and Interpolation. Feature Extraction. Supervised and UnsupervisedExpand
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AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017
TLDR
The PhysioNet/Computing in Cardiology (CinC) Challenge 2017 focused on differentiating AF from noise, normal or other rhythms in short term (from 9–61 s) ECG recordings performed by patients. Expand
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An open access database for the evaluation of heart sound algorithms.
In the past few decades, analysis of heart sound signals (i.e. the phonocardiogram or PCG), especially for automated heart sound segmentation and classification, has been widely studied and has beenExpand
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A Nonlinear Bayesian Filtering Framework for ECG Denoising
TLDR
In this paper, a nonlinear Bayesian filtering framework is proposed for the filtering of single channel noisy electrocardiogram (ECG) recordings. Expand
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The PhysioNet/Computing in Cardiology Challenge 2015: Reducing false arrhythmia alarms in the ICU
TLDR
The 2015 PhysioNet/Computing in Cardiology Challenge provides a set of 1,250 multi-parameter data segments associated with critical arrhythmia alarms, and challenges the general research community to address the issue of false alarm suppression using all available signals. Expand
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Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019
Supplemental Digital Content is available in the text. Objectives: Sepsis is a major public health concern with significant morbidity, mortality, and healthcare expenses. Early detection andExpand
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Logistic Regression-HSMM-Based Heart Sound Segmentation
TLDR
The identification of the exact positions of the first and second heart sounds within a phonocardiogram (PCG), or heart sound segmentation, is an essential step in the automatic analysis of heart sound recordings, allowing for the classification of pathological events. Expand
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Automated de-identification of free-text medical records
TLDR
We describe an automated Perl-based de-identification software package that is generally usable on most free-text medical records, e.g., nursing notes, discharge summaries, X-ray reports, etc. Expand
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A Review of Fetal ECG Signal Processing; Issues and Promising Directions.
The field of electrocardiography has been in existence for over a century, yet despite significant advances in adult clinical electrocardiography, signal processing techniques and fast digitalExpand
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