A new detection algorithm for implantable cardioverter defibrillator

One of the most important subsystems of implantable cardioverter defibrillator (ICD) is the sensing stage, since it determines the sensitivity and specificity of the device to detect the heart rate and the underlying arrhythmia. This paper aims to investigate a new detection algorithm for ICD, which operates fully automatically. The algorithm ARGUS was implemented as a computer model and tested with intracardiac electrograms recorded (band-pass: 0.05 to 500 Hz; sampling rate: 1-4 kHz) under different rhythm condition like sinus rhythm (n = 18), atrial tachycardia (n = 16), and ventricular tachycardia as well as fibrillation (n = 139) during electrophysiological tests or ICD implantation. The results of the tests were visually inspected on a beat-to-beat basis. In total 31,934 events were classified by the algorithm (18,758 as long intervals (LI) with cycle length > 300 ms; 13,176 as short intervals (SI)). 195 out of the 13,176 SI and 572 out of 18,758 LI were incorrectly classified (SI: 1.48%; LI: 3.05%). In conclusion the new algorithm yield high sensitivity (99.9%) and specificity (97.0%) as known from conventional ICD algorithms but need no manual adjustments.