Tooley M A, Davies D W, Nathan A W, Camm A J
Department of Medical Electronics, St. Bartholomew's Hospital, London, United Kingdom.
Pacing Clin Electrophysiol. 1991 Feb;14(2 Pt 2):337-40. doi: 10.1111/j.1540-8159.1991.tb05117.x.
New implantable devices are now available that can offer different therapies for different arrhythmias but they need a method of discriminating between these rhythms. Heart rate analysis is predominantly used to discern between sinus rhythm (SR) and pathological tachycardias but this may be of limited value when the rates of the rhythms are similar. An enhanced form of Gradient Pattern Detection (GPD) has been developed using an 8-bit microcomputer that can distinguish between SR and up to three other arrhythmias in real time. This is a method based on electrogram morphology where each rhythm's specific electrogram is classified by a sequence of gradient 'zones'. The microprocessor of the computer is of similar processing power to ones used in current pacemakers. Five patients with multiple arrhythmias were studied. Four had ventricular tachycardia (VT) and one had three conduction patterns during supraventricular tachycardia (SVT). Bipolar endocardial right ventricular electrograms were recorded during SR and tachycardia in all patients. The computer would first 'learn' about each different rhythm by a semi-automatic means. Once all the rhythms were learned the program would enter the GPD analysis phase. The computer would output a series of real-time rhythm specific marker codes onto a chart recorder as it recognized each rhythm. Sixteen different arrhythmias (13 VT, 3 SVT) were examined for this study. All rhythms (including SR) were distinguished from each other except in the case of one patient with six VTs where two VTs had identical shapes and therefore could not be detected apart. The method would be a useful addition to heart rate analysis for future generations of microprocessor assisted pacemakers.
现在有了新型可植入设备，它们能够针对不同的心律失常提供不同的治疗方法，但需要一种区分这些心律的方法。心率分析主要用于辨别窦性心律（SR）和病理性心动过速，但当心律速率相似时，其价值可能有限。利用8位微型计算机开发了一种增强型梯度模式检测（GPD），它能够实时区分SR和其他三种心律失常。这是一种基于心电图形态学的方法，每种心律的特定心电图通过一系列梯度“区域”进行分类。该计算机的微处理器处理能力与当前起搏器中使用的微处理器相似。对五名患有多种心律失常的患者进行了研究。四名患者患有室性心动过速（VT），一名患者在室上性心动过速（SVT）期间有三种传导模式。在所有患者的SR和心动过速期间记录双极心内膜右心室心电图。计算机首先会通过半自动方式“学习”每种不同的心律。一旦学习了所有心律，程序就会进入GPD分析阶段。计算机在识别每种心律时，会将一系列实时心律特定标记代码输出到图表记录器上。本研究检查了16种不同的心律失常（13种VT，3种SVT）。除了一名患有六种VT的患者中两种VT形状相同因而无法区分外，所有心律（包括SR）都能相互区分。对于未来几代微处理器辅助起搏器而言，该方法将是心率分析的有益补充。
