Session S32.1

Quantitative Analysis of Circadian Variation in Atrial Fibrillation Frequency

F Sandberg*, A Bollmann, D Husser, M Stridh, L Sörnmo

Lund University
Lund, Sweden

Circadian variation in atrial fibrillation (AF) frequency is explored in this paper by employing recent advances in signal processing. The motivation for this study is that the presence of circadian variation in AF frequency may reflect autonomic modulation. Once the AF frequency has been estimated and tracked by a hidden Markov model approach, the resulting trend is analyzed for the purpose of detecting and characterizing the presence of circadian variation. Three different methods are employed for this task, namely, cosinor analysis, autocorrelation, and ensemble correlation. The cosinor analysis method, in which a sinusoidal shape of the circadian variation is imposed, is employed to estimate the magnitude and phase of the circadian variation of each AF frequency trend. The autocorrelation method, which makes assumptions of the functional shape of the circadian variation, is used to detect if a circadian variation is present or not. The ensemble correlation method explores the joint variational pattern of the AF frequency trends. Ambulatory 24-hour ECG recordings were acquired from 18 patients with persistent AF and used in this study.
With cosinor analysis, the results show that the spontaneous second-to-second variation in AF frequency exceeds, by far, the variation that may be attributed to circadian. Using the autocorrelation method, circadian variation could not be detected in any of the recordings. Using the ensemble correlation method, the highest AF frequency usually occurred during the afternoon, whereas the lowest usually occurred during late night. It is concluded that no circadian variation is present in patients with persistent AF but the second-to-second variation in AF frequency is the variation that by far dominates.

(Abstract Control Number: 32)