Journal ArticleDOI
Bottom-up approach to the ECG pattern-recognition problem
Panos Trahanias,E. Skordalakis +1 more
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A bottom-up approach to the recognition problem in ECG waveforms is presented in the paper and the peak patterns and the segment patterns are considered primitive (nondecomposable) patterns.Abstract:
A bottom-up approach to the recognition problem in ECG waveforms is presented in the paper. This approach is based on the assumption that ECG waveforms are composite entities that can be decomposed into other simpler entities, these into other simpler ones etc., until peak patterns and segment paterrns are obtained. The peak patterns and the segment patterns are considered primitive (nondecomposable) patterns. The recognition is achieved by first recognising the primitive patterns and then recognising the (higher) ECG patterns using a bottom-up procedure.read more
Citations
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QRS detection using K-Nearest Neighbor algorithm (KNN) and evaluation on standard ECG databases
TL;DR: The proposed K-Nearest Neighbor (KNN) algorithm as a classifier for detection of QRS-complex in ECG is evaluated on two manually annotated standard databases such as CSE and MIT-BIH Arrhythmia database and clearly establishes KNN algorithm for reliable and accurateQRS-detection.
Journal ArticleDOI
An approach to QRS complex detection using mathematical morphology
TL;DR: An approach to QRS complex detection based on mathematical morphology is presented, which works as a peak-valley extractor and it is controlled by the shape of the structuring element, resulting in very fast execution times.
Journal ArticleDOI
ANN-based QRS-complex analysis of ECG.
TL;DR: This work uses the learn and generalize approach of an artificial neural network (ANN) for the detection of QRS complexes in either a normal or an abnormal ECG and its analysis, which is found to be in agreement with visual measurements carried out by medical experts.
Journal ArticleDOI
Self-organizing QRS-wave recognition in ECG using neural networks
TL;DR: The author has developed a self-organizing QRS-wave recognition system for electrocardiograms (ECGs) using neural networks and an ART2 (adaptive resonance theory) network was employed.
Journal ArticleDOI
Ranking of pattern recognition parameters for premature ventricular contractions classification by neural networks.
TL;DR: The study shows that simultaneous analysis of two ECG channels yields better accuracy compared to using a single channel: the improvement is 0.1% in the classification of N beats and 4.5% for PVC beats.
References
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Journal ArticleDOI
A Real-Time QRS Detection Algorithm
Jiapu Pan,Willis J. Tompkins +1 more
TL;DR: A real-time algorithm that reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width of ECG signals and automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate.
Journal ArticleDOI
Software QRS detection in ambulatory monitoring--a review.
Olle Pahlm,Leif Sörnmo +1 more
TL;DR: This review asserts that most one-channel QRS detectors described in the literature can be considered as having the same basic structure and a discussion of some of the current detection schemes is presented.
Journal ArticleDOI
Delineation of the QRS complex using the envelope of the e.c.g.
M. E. Nygårds,Leif Sörnmo +1 more
TL;DR: A new algorithm for QRS delineation has been developed and the stability of the method is demonstrated for transitions between different waveform morphologies.
Journal ArticleDOI
A robust-digital QRS-detection algorithm for arrhythmia monitoring
Adriaan Ligtenberg,Murat Kunt +1 more
TL;DR: In this paper a new robust single lead QRS-detection algorithm is presented, allowing real-time applications and results are presented.