Couceiro R, Carvalho P, Henriques J, Antunes M
Centre for Informatics and Systems, University of Coimbra, Coimbra, Portugal.
Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:1087-91. doi: 10.1109/IEMBS.2008.4649349.
Premature Ventricular Contractions (PVC) are a cardiac arrhythmia that can be associated with an increased risk of adverse cardiac events such as ventricular arrhythmias and sudden death. Therefore, the characterization of this arrhythmia becomes crucial in the early diagnosis and prevention of possible life threatening cardiac diseases. In this paper a new approach for automatic detection of PVCs is presented, based on morphological derivatives and information theory techniques. Using these approaches a set of patient invariant features is introduced. Sensibility and specificity results (respectively, 96.35% and 99.15%) show the potential of the algorithm when applied to the MIT-BIH Arrhythmia database.
室性早搏(PVC)是一种心律失常,可能与室性心律失常和猝死等不良心脏事件风险增加有关。因此,这种心律失常的特征描述对于早期诊断和预防可能危及生命的心脏疾病至关重要。本文提出了一种基于形态学导数和信息论技术自动检测室性早搏的新方法。利用这些方法引入了一组患者不变特征。敏感性和特异性结果(分别为96.35%和99.15%)表明该算法应用于麻省理工学院-贝斯以色列女执事医疗中心心律失常数据库时的潜力。