Iterative Method to Detect Atrial Activations and Measure Cycle Length From Electrograms During Atrial Fibrillation

Atrial fibrillation (AF) electrograms are characterized by varying morphologies, amplitudes, and cycle lengths (CLs), presenting a challenge for automated detection of individual activations and the activation rate. In this study, we evaluate an algorithm to detect activations and measure CLs from A...

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Vydáno v:IEEE transactions on biomedical engineering Ročník 61; číslo 2; s. 273 - 278
Hlavní autoři: Ng, Jason, Sehgal, Vinod, Ng, Justin K., Gordon, David, Goldberger, Jeffrey J.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.02.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithm design and analysis
Algorithms
Approximation algorithms
Atrial Fibrillation - physiopathology
Biomedical signal processing
cardiology
Educational institutions
electrocardiography
Electrocardiography - methods
Electronic mail
Estimation
Female
fibrillation
Heart - physiopathology
Humans
Male
Manuals
Middle Aged
Models, Statistical
Signal Processing, Computer-Assisted
ISSN:0018-9294, 1558-2531, 1558-2531
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Shrnutí:Atrial fibrillation (AF) electrograms are characterized by varying morphologies, amplitudes, and cycle lengths (CLs), presenting a challenge for automated detection of individual activations and the activation rate. In this study, we evaluate an algorithm to detect activations and measure CLs from AF electrograms. This algorithm iteratively adjusts the detection threshold level until the mean CL converges with the median CL to detect all individual activations. A total of 291 AF electrogram recordings from 13 patients (11 male, 58 ± 10 years old) undergoing AF ablation were obtained. Using manual markings by two independent reviewers as the standard, we compared the cycle length iteration algorithm with a fixed threshold algorithm and dominant frequency (DF) for the estimation of CL. At segment lengths of 10 s, when comparing the algorithm detected to the manually detected activation, the undersensing, oversensing, and total discrepancy rates were 2.4%, 4.6%, and 7.0%, respectively, and with absolute differences in mean and median CLs were 7.9 ± 9.6 ms and 5.6 ± 6.8 ms, respectively. These results outperformed DF and fixed threshold-based measurements. This robust method can be used for CL measurements in either real-time and offline settings and may be useful in the mapping of AF.
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ISSN:0018-9294
1558-2531
1558-2531
DOI:10.1109/TBME.2013.2290003