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Novel Algorithm for Analysis and Classification of Atrioventricular Nodal Re-entry Tachycardia (AVNRT) Using IntraCardiac ElectroGrams

机译:用心内电子图谱分析和分类分析和分类算法,intrioventriculary核心再进入心动图(AVNRT)

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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. A VNRT 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 A VNRT related features which are used by the classifier for the detection of A VNRT. 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 A VNRT and they are classified by the classifier to A VNRT successfully.
机译:心脏电生理学(EP)是一种既定的临床技术,用于检查和处理心律疾病,尤其是过去几年以来的心律失常。在几种类型的心律失常中,房室性核心释放性心动过速(AVNRT)是EP实验室中最常见的心律失常之一。通过在患者中诱导心动过速,然后通过查找监视器屏幕并手动评估其关键特征,从记录的内部心脏数据中观察,可以指示AVNRT存在,并且所有这些过程消耗电生理学家的宝贵时间。所提出的算法使用Intracardiac数据并通过使用信号处理,提取由分类器使用的VNRT相关特征来检测VNRT。这将通过电生理学家省流动计算的时间。超过20名患者数据用于测试特征提取部分的算法,显示精度为92.8%和96.5%。在这20例患者中,4属于VNRT,它们被分类器成功分类为VNRT。

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