Real-time discrimination of ventricular tachyarrhythmia with Fourier-transform neural network

We have developed a method to discriminate life-threatening ventricular arr hythmias by observing the QRS complex of the electrocardiogram (ECG) in eac h heartbeat. Changes in QRS complexes due to rhythm origination and conduct ion path were observed with the Fourier transform, and three kinds of rhyth ms were discriminated by a neural network. In this paper, the potential of our method for clinical uses and real-time detection was examined using hum an surface ECG's and intracardiac electrograms (EGM's), The method achieved high sensitivity and specificity (greater than or equal to 0.98) in discri mination of supraventricular rhythms from ventricular ones, We also present a hardware implementation of the algorithm on a commercial single-chip CPU .