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Novel algorithm for analysis and classification of atrio-ventricular nodal re-entry tachycardia (AVNRT) using intracardiac electrograms

机译:用心内电子图谱分析和分类Atrio-anyriculardal重新进入心动过速(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(EP)是用于检查既定的临床技术和操作心律紊乱的,因为过去几年尤其是心律不齐。在几种类型的心律失常,房室结折返性心动过速(AVNRT)是在EP实验室看到的最常见的心律失常之一。 AVNRT在EP实验室通过在患者中诱导的心动过速,然后通过观察监视器屏幕上,并手动从记录帧内心脏数据可指示AVNRT存在和电生理学家的所有此过程消耗宝贵的时间评价其关键特征检测。所提出的算法使用心内数据,并通过使用信号处理,它提取其用于由所述分类器用于检测AVNRT这将节省由电生理学家手工计算的时间的AVNRT相关的功能。超过20个患者数据被用来测试对特征提取部分中的算法,该算法92.8%和96.5%之间显示精度。其中20名患者4属于AVNRT和它们被分类归入成功对AVNRT。

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