Time-frequency analysis for early classification of persistent and long-standing persistent atrial fibrillation

摘要

This study aimed to assess an early classification of persistent and long-standing persistent atrial fibrillation patients by means of the time-frequency analysis of the surface ECG, which would allow electrophysiologists to choose the most suitable therapeutic approach to treat this arrhythmia. 140 consecutive unselected patients suffering from atrial fibrillation conformed the study population (84 persistent and 56 long-standing persistent). After ventricular activity cancellation, time-frequency analysis of the atrial activity was performed. Then, the study of phase variations along time for those frequency bands where the average power of atrial activity is concentrated, together with the mean distance between R peaks determined to be significative to allow early classification. Classification was performed with a Support Vector Machine trained with 20 ECGs (10 corresponding to persistent and 10 to long-standing persistent AF). Classification results were: Accuracy = 74.16%, Sensitivity = 71.72%, Specificity = 78.26%. These results would provide electrophysiologists a tool to classify persistent AF patients, in order to choose the most suitable treatment in each case.