Abstract
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.
| Original language | English (US) |
|---|---|
| Article number | 6657784 |
| Pages (from-to) | 273-278 |
| Number of pages | 6 |
| Journal | IEEE Transactions on Biomedical Engineering |
| Volume | 61 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 1 2014 |
| Externally published | Yes |
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Keywords
- Biomedical signal processing
- cardiology
- electrocardiography
- fibrillation
ASJC Scopus subject areas
- Biomedical Engineering
Cite this
Iterative method to detect atrial activations and measure cycle length from electrograms during atrial fibrillation. / Ng, Jason; Sehgal, Vinod; Ng, Justin K.; Gordon, David; Goldberger, Jeffrey.
In: IEEE Transactions on Biomedical Engineering, Vol. 61, No. 2, 6657784, 01.02.2014, p. 273-278.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Iterative method to detect atrial activations and measure cycle length from electrograms during atrial fibrillation
AU - Ng, Jason
AU - Sehgal, Vinod
AU - Ng, Justin K.
AU - Gordon, David
AU - Goldberger, Jeffrey
PY - 2014/2/1
Y1 - 2014/2/1
N2 - 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.
AB - 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.
KW - Biomedical signal processing
KW - cardiology
KW - electrocardiography
KW - fibrillation
UR - http://www.scopus.com/inward/record.url?scp=84893221249&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893221249&partnerID=8YFLogxK
U2 - 10.1109/TBME.2013.2290003
DO - 10.1109/TBME.2013.2290003
M3 - Article
C2 - 24216630
AN - SCOPUS:84893221249
VL - 61
SP - 273
EP - 278
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
SN - 0018-9294
IS - 2
M1 - 6657784
ER -