Session S33.1

Heart Rate Turbulence Detection Using Mean Shape Information

D Smith*, K Solem, P Laguna, JP Martínez, L Sörnmo

Lund University
Lund, Sweden

Heart rate turbulence (HRT) refers to a short-term fluctuation in heart rate triggered by a single ventricular ectopic beat (VEB) which in normal subjects compensates for the VEB-induced drop in blood pressure by an accelerated sinus rate. Blunted or entirely missing turbulence reflects autonomic dysfunction and is associated with various conditions. In this study, we propose a generalized likelihood ratio test (GLRT) statistic for detection of HRT based on a linear signal model. The new test statistic, which expands our previous original detector, takes a priori information regarding HRT shape into account. The detector structure is based on the extended integral pulse frequency modulation model which accounts for the presence of ectopic beats and HRT. The spectral relationship between heart rate variability (HRV) and HRT is investigated for the purpose of modeling HRV “noise” present during the turbulence period, the results suggesting that the white noise assumption is feasible to pursue. The performance was studied for both simulated data and real data consisting of 5764 beat tachograms containing HRT and 26577 without HRT obtained from the Long-Term ST database. The results show that the new detector is superior to the original one as well as to the commonly used parameter turbulence slope (TS) on both types of data. Averaging 10 ventricular ectopic beats, the estimated detection probabilities of the new detector, the original detector, and TS were found to be 0.83, 0.35, and 0.41, respectively, when the false alarm probability was held fixed at 0.1.

(Abstract Control Number: 136)