A system for automated analysis of RR-series applied to identification of patients with neurocardiogenic syncope

摘要

Deals with an adaptable software system for heart rate variability (HRV) analysis and its application to the clinical problem of neurocardiogenic syncope. Features here calculated from 24h-Holter recordings of 17 patients and 15 control probands. The best discrimination results (88% sensitivity, 73% specificity) between the two groups are achieved by combination of the standard deviation of intervals between normal beats (SDNN) and the standard deviation of Haar-wavelet coefficients (/spl sigma//sub WAV/) for scale 10 using a first order polynomial classifier. The prominent key features of the developed software system are discussed.