Comprehensive scheme for detection of ventricular fibrillation for implantable cardioverter defibrillators.
Implantable cardioverter defibrillators (ICDs) detect and defibrillate ventricular fibrillation (VF) and ventricular tachycardia (VT). Other therapies which use less energy are also available to terminate VT. Previous studies have shown that ICD rate schemes often misdiagnose VT as VF. In this study, an improved VF classification scheme was designed and tested, which employs the classic rate criteria plus paired signal concordance (PSC); PSC uniquely detects VF where VT and VF rates overlap (220-340 ms). Two signals from a bipolar pair (1 cm) recorded in a unipolar sense exhibit similar signal shape for concordant rhythms, such as sinus rhythm and VT, and disconcordance for VF. Once the rate criterion is met, PSC is measured by the peak normalized cross-correlation coefficient calculated over the depolarization. Variability, measured by a modified range, determined the contextual diagnosis over a passage. Sinus rhythm (20), VT (12), VF (22), atrial fibrillation (10), sinus rhythm with ventricular premature depolarizations (7), and polymorphic VT (4) passages were recorded from 38 patients. Rate-PSC was tested with unfiltered, digitized signals (1-500 Hz, 1,000 samples per second) and with filtered, downsampled signals (1-50 Hz, 100 samples per second). Sensitivity values, or percentage of correct VF detection, and specificity values, or detection of all other rhythms, were generated and compared with simulations of three commercial ICDs programmed to similar settings as rate-PSC and to nominal settings. The sensitivity values for rate-PSC with unfiltered and with filtered signals and for ICDs with 220 ms and with nominal settings were 100%, 100%, 48-80%, and 100%, respectively; the corresponding specificity values were 95%, 83%, 93%, and 7-13%, respectively. It was concluded that the rate-PSC scheme was able to reliably separate VF from other rhythms, even rhythms that have a variable morphology or variable rate. With the confidence of accurate VF detection, use of low-energy therapies for non-VF rhythms will increase device longevity and enhance patient comfort.
Caswell
S A
SA
Department of Electrical Engineering and Computer Science, University of Michigan and Michigan Heart and Vascular Institute, Ann Arbor, USA.
Jenkins
J M
JM
DiCarlo
L A
LA
D003198:Computer Simulation; D017147:Defibrillators, Implantable; D003937:Diagnosis, Differential; D004562:Electrocardiography; D006801:Humans; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D017180:Tachycardia, Ventricular / Q000175:diagnosis; D014693:Ventricular Fibrillation / Q000175:diagnosis* / Q000628:therapy*