Automatic Identification of Atrial Fibrillation by Spectral Analysis of Fibrillatory Waves

A heart affected by atrial fibrillation (AF) presents atrial cells that depolarize in many sites, generating a chaotic electrical activity. On the electrocardiogram (ECG), this activity reflects in the appearance of fibrillatory (F) waves, consisting of low-amplitude oscillations at 4-10 Hz. Aim of the present study is to propose an automatic AF identification method based on F-wave frequency analysis in 10 s ECGs. To this aim, 10 s ECG from 90 healthy subjects (HSs) and 50 AF patients (AFPs) were considered. ECGs were processed by the segmented beat modulation method to reduce components in the F-wave band. Then, the power spectral density (PSD) was computed and the F-wave frequency ratio (FWFR), defined as the ratio between the spectral area in the F-wave frequency band and the total spectral area, was computed. FWFR ability to discriminate AFPs from HSs was evaluated by analyzing the area under the curve (AUC) of the receiver operating characteristic, and by computation of sensitivity, specificity and accuracy. FWFR values were higher in AFPs than in HSs (P<10-11). AUC was at least 85%, whereas sensitivity, specificity and accuracy were at least 84%, 69% and 81%, respectively. In conclusion, F-wave frequency evaluation by FWFR represents a promising clinical tool to automatically identify AF.