Four Digital Algorithms for Activation Detection from Unipolar Epicardial Electrograms

The reproducibility of activation detection by each of four algorithms used to calculate maximum derivatives was tested on two sequential paced beats of right ventricular unipolar epicardial electrograms which represented either local activation of the right ventricle alone or synchronous activation of both ventricles. The methods were evaluated by comparing the shape of the two beats aligned on their selected activation times, i.e., the time at which the maximum negative deflection occurred, the differences in activation intervals for the two beats, and the effect on the activation time of superimposing distant events on local activation. The 17-point second-order data fit algorithm performed slightly better than the first-order difference, three-point Lagrange derivative, and five-point second-order data fit algorithms except that activation time selection by the 17-point technique was slightly, but significantly, delayed by the superposition of distant potentials. The 17-point second-order data fit technique is therefore recommended for use in detecting activation unless computation time is a major consideration. In that case, the five-point second-order data fit technique, which uses only four data values for each computation, can be used with only slight decreases in accuracy.