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  • Title: [A research on real-time ventricular QRS classification methods for single-chip-microcomputers].
    Author: Peng L, Yang Z, Li L, Chen H, Chen E, Lin J.
    Journal: Zhongguo Yi Liao Qi Xie Za Zhi; 1997 May; 21(3):133-5, 157. PubMed ID: 11189347.
    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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