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PubMed · 11189347

[A research on real-time ventricular QRS classification methods for single-chip-microcomputers].

L Peng·Z Yang·L Li·H Chen·E Chen·J Lin
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Abstract

Ventricular QRS classification is key technique of ventricular arrhythmias detection in single-chip-microcomputer based dynamic electrocardiogram real-time analyser. This paper adopts morphological feature vector including QRS amplitude, interval information to reveal QRS morphology. After studying the distribution of QRS morphology feature vector of MIT/BIH DB ventricular arrhythmia files, we use morphological feature vector cluster to classify multi-morphology QRS. Based on the method, morphological feature parameters changing method which is suitable to catch occasional ventricular arrhythmias is presented. Clinical experiments verify missed ventricular arrhythmia is less than 1% by this method.

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Arrhythmias, CardiacCluster AnalysisElectrocardiography, AmbulatoryHumansMathematicsMicrocomputersEnglish AbstractJournal Article

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BibTeXRIS

L Peng, Z Yang, L Li, H Chen, E Chen, J Lin. 1997. [A research on real-time ventricular QRS classification methods for single-chip-microcomputers].. https://pubmed.ncbi.nlm.nih.gov/11189347/

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