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Abstract-Cardiac cycle dynamics reflect underlying physiological changes that could predict imminent arrhythmias but are obscured by high complexity, nonstationarity, and large interindividual differences. To overcome these problems, we developed an adaptive technique, referred to as the modified Karhunen-Loeve transform (MKLT), that identifies an individual characteristic ("core") pattern of cardiac cycles and then tracks the changes in the pattern by projecting the signal onto characteristic eigenvectors. We hypothesized that disturbances in the core pattern, indicating progressive destabilization of cardiac rhythm, would predict the onset of spontaneous sustained ventricular tachyarrhythmias (VTAs) better than previously reported methods. We analyzed serial ambulatory ECGs recorded in 57 patients at the time of VTA and non-VTA 24-hour periods. The disturbances in the pattern were found in 82% of the recordings before the onset of impending VTA, and their dimensionality, defined as the number of unstable orthogonal projections, increased gradually several hours before the onset. MKLT provided greater sensitivity and specificity (70% and 93%) compared with the best traditional method (68% and 67%, respectively). We present a theoretical analysis of MKLT and describe the effects of ectopy and slow changes in cardiac cycles on the disturbances in the pattern. We conclude that MKLT provides greater predictive accuracy than previously reported methods. The improvement is due to the use of individual patterns as a reference for tracking the changes. Because this approach is independent of the group reference values or the underlying clinical context, it should have substantial potential for predicting other forms of arrhythmic events in other populations. Key Words: ventricular arrhythmias Ⅲ cardiac cycle dynamics Ⅲ orthogonal decomposition A lthough substantial progress has been made in the understanding of arrhythmia mechanisms and identification of individuals at risk, short-term prediction of the timing of onset of sustained ventricular tachyarrhythmias (VTAs) has lagged, delaying development of preventive treatments. 1 Because autonomic activity is thought to be an important trigger of VTA and because cardiac cycle lengths (CCLs) are modulated by autonomic tone, it has been assumed that the analysis of the changes in CCL could predict the timing as well as the triggers of VTA. 2 This has been confirmed by studies that demonstrated heart rate increase before the VTA onset in many patients. [2][3][4][5] However, the change in heart rate before the onset of VTA is usually small and indistinguishable from random daily variations. 2,6 Descriptors of heart rate variability proved useful in general risk assessment but failed to predict the timing of VTA. 5,7 Probable reasons for the failure include the high complexity of the interacting physiological influences and violation of the statistical assumptions that underlie traditional techniques. 8 In addition, the attempts to summarize highly nonstationary and indivi...

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