Spectral analysis of chronic atrial fibrillation and its relation to minimal defibrillation energy.
The average rate of fibrillatory activity may reflect the global activation pattern of AF. Electrical cardioversion is the most effective method of converting chronic AF to sinus rhythm. The aim of this study was to investigate the relation between the minimal defibrillation energy requirement and the dominant frequency of chronic AF. Twenty-nine patients with chronic AF (mean duration 57.9 +/- 7.7 months) underwent external electrical cardioversion. Before cardioversion, the frequency content of the 60-second AF in ECG lead V1 was quantified using digital signal processing. After band-pass filtering, QRST complexes were cancelled using a recursive lease squares algorithm. The resulting fibrillatory baseline signal was subjected to fast Fourier transform and was displayed as a power spectrum. The dominant AF frequency was found to range from 4.9 to 8.7 Hz (mean 6.7 +/- 0.9 Hz). Twenty-six patients had successful conversion of AF to sinus rhythm without immediate recurrence. There was a positive correlation between the minimal defibrillation energy and the dominant frequency of chronic AF (rho = 0.414, P = 0.035). Thus, power spectral analysis of AF using the surface ECG is feasible and may be useful in predicting the minimal shock energy required for successful cardioversion of chronic AF.
Tai
Ching-Tai
CT
Division of Cardiology, Department of Medicine, National Yang-Ming University School of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan, R.O.C. cttai@vghtpe.gov.tw
Chen
Shih-Ann
SA
Liu
Ann-Shin
AS
Yu
Wen-Chung
WC
Ding
Yu-An
YA
Chang
Mau-Song
MS
Kao
Tsair
T
D000368:Aged; D000465:Algorithms; D001281:Atrial Fibrillation / Q000503:physiopathology* / Q000517:prevention & control*; D002908:Chronic Disease; D004554:Electric Countershock; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D012815:Signal Processing, Computer-Assisted