Session P79.3

Poincaré Plots of Time-Frequency Parameters Applied to the Prediction of Atrial Fibrillation Termination

C Vayá*, JJ Rieta, J Mateo, C Sánchez

Universidad de Castilla-La Mancha
Cuenca, Spain

Atrial Fibrillation (AF) episodes are commonly encountered in the daily clinical practice and cardiologists have often to face the difficulty of classifying between terminating and non-terminating AF episodes. Given that in these critical situations a decision must be made with the utmost urgency, it would be desirable to have a visualization tool of easy interpretation that could provide a fast and reliable prediction of AF episode evolution. In this essay, a method based on Poincaré plots and time-frequency analysis is presented as a new technique of AF diagnosis.
The database of this work consisted of thirty ECG recordings that were properly annotated as terminating or non-terminating AF episodes. The spectrograms of the atrial activity (AA) extracted from the ECGs were computed using 4096 points Fast Fourier Transform (FFT), 97% overlap and Hamming windowing. Then the sequences consisting of main peak frequencies (fp1), second largest peaks (fp2), and amplitudes at this frequencies (A1 and A2) were constructed. Finally, the Poincaré plots of these sequences were visualized and analyzed.
The visual inspection of Poincaré plots of fp1 showed that both terminating and non-terminating episodes presented lineal discontinuous clustering along the diagonal of the graph. Nonetheless, in the case of non-terminating episodes clusters were concentrated close to the top right-hand corner of the graph. On the contrary, clusters were situated close to the bottom left-hand corner of the graph in the case of terminating episodes. Specifically, when a cursor was located at the place determined by the frequency of 5.5 Hz as a graphical threshold, the subdivision of the graph allowed us to classify 80 % of episodes correctly. In the rest of parameters we could not fix any threshold so that the percentage of correct classifications exceeded 50%, and therefore they were considered to be irrelevant to the characterization of AF. To sum up, the Poincaré plots can be used as a reliable practical tool in predicting the evolution of AF when the parameter fp1 is considered, what is consistent with the mainly decreasing evolution of fp in terminating AF episodes.

(Abstract Control Number: 65)