Da. Igel et Bl. Wilkoff, AUTOMATED VENTRICULAR TACHYARRHYTHMIA RECOGNITION - A COMBINATION OF CYCLE LENGTH AND NONLINEAR DYNAMICS MEASUREMENTS, Journal of cardiovascular electrophysiology, 8(4), 1997, pp. 388-397
Introduction: Cardiac monitoring devices such as external cardioverter
defibrillators and ICU computerized ECC monitoring systems sense indi
vidual QRS complexes to detect and subclassify ventricular tachyarrhyt
hmias, Many algorithms that evaluate ECG morphology mark individual QR
S complexes so that specific waveform characteristics can be measured,
QRS sensors miss a percentage of electrogram events, especially durin
g fibrillatory rhythms; thus, a morphology algorithm that helps subcla
ssify arrhythmias without marking individual electrogram events may be
more robust and improve arrhythmia detection accuracy. Methods and Re
sults: Four nonlinear dynamics calculations were evaluated for detecti
ng ventricular tachyarrhythmias and for subclassifying monomorphic ven
tricular tachycardia (MVT) and polymorphic ventricular tachycardia (PV
T), Five-second epochs of normal (NML, n = 48), MVT (n = 58), and PVT
(n = 75) rhythms were presented to a statistical discriminant function
based on cycle length (CL), and its performance was compared to two o
ther discriminant functions, one consisting of the nonlinear dynamics
calculations and one consisting of a combination of all variables, The
discriminant function based on nonlinear dynamics calculations and CL
detected 100% of the ventricular tachyarrhythmias, and subclassified
more (P < 0.001) MVT and PVT arrhythmias (90 %) than that based on CL
alone (71 %). Conclusions: The nonlinear dynamics measurements used in
this study significantly increased the subclassification accuracy of
the CL-based discriminant function, and they were calculated from ECG
signals without marking individual QRS complexes, Therefore, arrhythmi
a detectors that use nonlinear dynamics measurements may commit fewer
classification errors due to QRS undersensing and aid therapy decision
s when circumstances suggest that QRS sensing is inaccurate.