Balasundaram K, Masse S, Nair K, Farid T, Nanthakumar K, Umapathy K
Ryerson University.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:969-72. doi: 10.1109/IEMBS.2011.6090219.
Ventricular arrhythmias arise from abnormal electrical activity of the lower chambers (ventricles) of the heart. Ventricular tachycardia (VT) and ventricular fibrillation (VF) are the two major subclasses of ventricular arrhythmias. While VT has treatment options that can be performed in catheterization labs, VF is a lethal cardiac arrhythmia, often when detected the patient receives an implantable defibrillator which restores the normal heart rhythm by the application of electric shocks whenever VF is detected. The classification of these two subclasses are important in making a decision on the therapy performed. As in the case of all real world process the boundary between VT and VF is ill defined which might lead to many of the patients experiencing arrhythmias in the overlap zone (that might be predominately VT) to receive shocks by the an implantable defibrillator. There may also be a small population of patients who could be treated with anti-arrhythmic drugs or catheterization procedure if they can be diagnosed to suffer from predominately VT after objectively analyzing their intracardiac electrogram data obtained from implantable defibrillator. The proposed work attempts to arrive at a quantifiable way to scale the ventricular arrhythmias into VT, VF, and the overlap zone arrhythmias as VT-VF candidates using features extracted from the wavelet analysis of surface electrograms. This might eventually lead to an objective way of analyzing arrhythmias in the overlap zone and computing their degree of affinity towards VT or VF. A database of 24 human ventricular arrhythmia tracings obtained from the MIT-BIH arrhythmia database was analyzed and wavelet-based features that demonstrated discrimination between the VT, VF, and VT-VF groups were extracted. An overall accuracy of 75% in classifying the ventricular arrhythmias into 3 groups was achieved.
室性心律失常源于心脏下腔（心室）的异常电活动。室性心动过速（VT）和心室颤动（VF）是室性心律失常的两个主要子类。虽然VT有可在导管实验室进行的治疗选择，但VF是一种致命的心律失常，通常在检测到VF时，患者会植入除颤器，一旦检测到VF，除颤器就会通过施加电击来恢复正常心律。这两个子类的分类对于决定所实施的治疗很重要。与所有现实世界的过程一样，VT和VF之间的界限定义不明确，这可能导致许多在重叠区域（可能主要是VT）出现心律失常的患者接受植入式除颤器的电击。也可能有一小部分患者，如果在客观分析从植入式除颤器获得的心内电图数据后被诊断主要患有VT，他们可以用抗心律失常药物或导管手术进行治疗。所提出的工作试图找到一种可量化的方法，利用从表面心电图的小波分析中提取的特征，将室性心律失常分为VT、VF以及作为VT-VF候选的重叠区域心律失常。这最终可能会导致一种客观的方法来分析重叠区域的心律失常，并计算它们对VT或VF的亲和程度。分析了从麻省理工学院 - 贝斯以色列女执事医疗中心心律失常数据库获得的24份人类室性心律失常心电图记录，并提取了能够区分VT、VF和VT-VF组的基于小波的特征。在将室性心律失常分为3组时，总体准确率达到了75%。
