Journal ArticleDOI
The impact of the MIT-BIH Arrhythmia Database
George B. Moody,Roger G. Mark +1 more
TLDR
The history of the database, its contents, what is learned about database design and construction, and some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database are reviewed.Abstract:
The MIT-BIH Arrhythmia Database was the first generally available set of standard test material for evaluation of arrhythmia detectors, and it has been used for that purpose as well as for basic research into cardiac dynamics at about 500 sites worldwide since 1980. It has lived a far longer life than any of its creators ever expected. Together with the American Heart Association Database, it played an interesting role in stimulating manufacturers of arrhythmia analyzers to compete on the basis of objectively measurable performance, and much of the current appreciation of the value of common databases, both for basic research and for medical device development and evaluation, can be attributed to this experience. In this article, we briefly review the history of the database, describe its contents, discuss what we have learned about database design and construction, and take a look at some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database.read more
Citations
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Journal ArticleDOI
Automated Atrial Fibrillation Detection using a Hybrid CNN-LSTM Network on Imbalanced ECG Datasets
Georgios Petmezas,K. Haris,Leandros Stefanopoulos,Vassilis Kilintzis,Andreas Tzavelis,John A. Rogers,Aggelos K. Katsaggelos,Nicos Maglaveras,Nicos Maglaveras +8 more
TL;DR: A novel hybrid neural model utilizing focal loss, an improved version of cross-entropy loss, to deal with training data imbalance is proposed, which can aid clinicians to detect common atrial fibrillation in real-time on routine screening ECG.
Journal ArticleDOI
A Level-Crossing Based QRS-Detection Algorithm for Wearable ECG Sensors
TL;DR: An asynchronous analog-to-information conversion system is introduced for measuring the RR intervals of the electrocardiogram (ECG) signals and it contains a modified level-crossing analog- to-digital converter and a novel algorithm for detecting the R-peaks from the level-Crossing sampled data in a compressed volume of data.
Proceedings ArticleDOI
BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series
TL;DR: Experiments show that BeatGAN accurately and efficiently detects anomalous beats in ECG time series, and routes doctors’ attention to anomalous time ticks, achieving accuracy of nearly 0.95 AUC, and very fast inference (2.6 ms per beat).
Journal ArticleDOI
Individual identification via electrocardiogram analysis
TL;DR: A survey of the techniques used so far in ECG-based human identification is provided, providing a unifying framework to appreciate previous studies and, hopefully, guide future research.
Journal ArticleDOI
Novel genetic ensembles of classifiers applied to myocardium dysfunction recognition based on ECG signals
TL;DR: The best genetic ensemble of classifiers optimized by sets, obtained a classification sensitivity of 17 heart disorders (classes) at a level of 91.40% against the background of the current scientific literature.
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