首页> 外文会议>2013 3rd International Conference on Computer, Control amp; Communication >Novel algorithm for analysis and classification of atrio-ventricular nodal re-entry tachycardia (AVNRT) using intracardiac electrograms
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Novel algorithm for analysis and classification of atrio-ventricular nodal re-entry tachycardia (AVNRT) using intracardiac electrograms

机译:使用心内电图分析和分类房室结再入性心动过速(AVNRT)的新算法

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摘要

Cardiac Electrophysiology (EP) is an established clinical technique for the examination and handling of cardiac rhythm disorders especially arrhythmias since past couple of years. Among several types of arrhythmias, Atrioventricular Nodal Reentrant Tachycardia (AVNRT) is one of the most common arrhythmia seen in the EP Lab. AVNRT is detected in EP Lab by inducing tachycardia in the patient and then by looking on monitor screen and manually evaluating its key features from recorded intra cardiac data which can indicate AVNRT presence and all this process consumes precious time of the Electrophysiologist. The proposed algorithm uses the intracardiac data and by using signal processing, it extracts the AVNRT related features which are used by the classifier for the detection of AVNRT This will save the time of manual calculations by Electrophysiologist. More than 20 patient data was used to test the algorithm for feature extraction part which shows precision between 92.8% and 96.5%. Among these 20 patients 4 belong to AVNRT and they are classified by the classifier to AVNRT successfully.
机译:心脏电生理学(EP)是过去几年来检查和处理心律失常(尤其是心律不齐)的一项成熟临床技术。在几种类型的心律不齐中,房室结折返性心动过速(AVNRT)是EP实验室中最常见的心律不齐之一。在EP实验室中,通过诱发患者心动过速,然后在监护仪屏幕上查看并从记录的心脏内数据手动评估其关键特征(可指示AVNRT的存在)来检测AVNRT,所有这些过程均耗费了电生理学家的宝贵时间。所提出的算法利用心内数据并通过信号处理提取与AVNRT相关的特征,分类器将这些特征用于检测AVNRT,这将节省电生理学家的手动计算时间。使用了20多个患者数据来测试特征提取部分的算法,该算法显示出92.8%至96.5%的精度。在这20位患者中,有4位属于AVNRT,并且已通过分类器成功分类为AVNRT。

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