An APN model for Arrhythmic beat classification | Zendy

HsiuSen Chiang | Zendy; DongHer Shih | Zendy; Binshan Lin | Zendy; MingHung Shih | Zendy

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An APN model for Arrhythmic beat classification

Author(s) -

HsiuSen Chiang,

DongHer Shih,

Binshan Lin,

MingHung Shih

Publication year - 2014

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btu101

Subject(s) - computer science , petri net , cardiac arrhythmia , beat (acoustics) , identification (biology) , rhythm , artificial intelligence , heart rhythm , pattern recognition (psychology) , atrial fibrillation , medicine , algorithm , physics , botany , acoustics , biology

Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately fatal or cause irreparable damage to the heart sustained over long periods of time. Therefore, the ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this article, classification by using associative Petri net (APN) for personalized ECG-arrhythmia-pattern identification is proposed for the first time in literature.

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