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
.