Automatic p wave analysis over 24 hours in patients with paroxysmal or persistent atrial fibrillation.
BACKGROUND
Patients with atrial fibrillation (AF) often exhibit abnormalities of P wave morphology during sinus rhythm. We examined a novel method for automatic P wave analysis in the 24-hour-Holter-ECG of 60 patients with paroxysmal or persistent AF and 12 healthy subjects.


METHODS
Recorded ECG signals were transferred to the analysis program where 5-10 P and R waves were manually marked. A wavelet transform performed a time-frequency decomposition to train neural networks. Afterwards, the detected P waves were described using a Gauss function optimized to fit the individual morphology and providing amplitude and duration at half P wave height.


RESULTS
>96% of P waves were detected, 47.4 +/- 20.7% successfully analyzed afterwards. In the patient population, the mean amplitude was 0.073 +/- 0.028 mV (mean variance 0.020 +/- 0.008 mV(2)), the mean duration at half height 23.5 +/- 2.7 ms (mean variance 4.2 +/- 1.6 ms(2)). In the control group, the mean amplitude (0.105 +/- 0.020 ms) was significantly higher (P < 0.0005), the mean variance of duration at half height (2.9 +/- 0.6 ms(2)) significantly lower (P < 0.0085).


CONCLUSIONS
This method shows promise for identification of triggering factors of AF.
Bitzen
Alexander
A
Department of Medicine--Cardiology, University of Bonn, Bonn, Germany. alexander.bitzen@ukb.uni-bonn.de
Sternickel
Karsten
K
Lewalter
Thorsten
T
Schwab
Jörg Otto
JO
Yang
Alexander
A
Schrickel
Jan Wilko
JW
Linhart
Markus
M
Wolpert
Christian
C
Jung
Werner
W
David
Peter
P
Lüderitz
Berndt
B
Nickenig
Georg
G
Lickfett
Lars
L
D001281:Atrial Fibrillation / Q000503:physiopathology*; D016022:Case-Control Studies; D015716:Electrocardiography, Ambulatory; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012815:Signal Processing, Computer-Assisted; D018709:Statistics, Nonparametric; D013997:Time Factors