Automatic analysis of cardiac repolarization morphology using Gaussian mesa function modeling

Abstract A novel fully automated method for wave identification and extraction from electrocardiogram (ECG) waveforms is presented. This approach implements the combined use of a new machine-learning algorithm and of specified parameterized functions called Gaussian mesa functions (GMFs). Individual...

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Veröffentlicht in:	Journal of electrocardiology 2008-11, Vol.41 (6), p.588-594
Hauptverfasser:	Badilini, Fabio, PhD, Vaglio, Martino, MS, Dubois, Rémi, PhD, Roussel, Pierre, PhD, Sarapa, Nenad, MD, Denjoy, Isabelle, MD, Extramiana, Fabrice, MD, Maison-Blanche, Pierre, MD
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Arrhythmias, Cardiac - diagnosis Artificial Intelligence Cardiovascular Diagnosis, Computer-Assisted - methods ECG modeling Electrocardiography - methods Humans Models, Cardiovascular Models, Statistical Normal Distribution Pattern Recognition, Automated - methods Repolarization Reproducibility of Results Sensitivity and Specificity
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