Throne R D
Department of Electrical Engineering, Lincoln, NE 68588-0511.
Biomed Sci Instrum. 1994;30:15-20.
Computing a correlation coefficient between a stored template of a normal beat and subsequent beats is a widely used indicator of changes in electrogram morphology. While effective, this method is quite computationally demanding, particularly for use in implantable devices with limited available power. We investigated methods for computing a normalized autocorrelation as efficient template matching alternatives to the correlation coefficient. These four algorithms, polarity incidence (PI), hybrid sign (HS), modified hybrid sign (MHS), and relative magnitude (RM) are compared with the correlation coefficient (CC) for detecting changes in intraventricular electrogram morphology. We sought to determine the number of instances in which 75% (or 90%) of a patient's sinus rhythm beats could be distinguished from 75% (or 90%) of the patient's ventricular tachycardia beats at the 95% confidence level in 30 patients. The relative magnitude method performs nearly as well as the correlation coefficient in nearly every case but requires only 3 multiplies per application. Hence the relative magnitude algorithm may be more appropriate for implantable devices.
计算正常心搏的存储模板与后续心搏之间的相关系数，是一种广泛用于检测心电图形态变化的指标。虽然这种方法有效，但计算量很大，特别是在可用功率有限的植入式设备中使用时。我们研究了计算归一化自相关的方法，作为相关系数的高效模板匹配替代方法。将极性发生率（PI）、混合符号（HS）、改进混合符号（MHS）和相对幅值（RM）这四种算法与相关系数（CC）进行比较，以检测心室内电图形态的变化。我们试图确定在30名患者中，在95%置信水平下，75%（或90%）的患者窦性心律心搏能够与75%（或90%）的患者室性心动过速心搏区分开的实例数量。相对幅值法在几乎所有情况下的表现都与相关系数相近，但每次应用仅需3次乘法运算。因此，相对幅值算法可能更适合植入式设备。
