| 1. |
- Halvaei, Hesam, et al.
(författare)
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Detection of Short Supraventricular Tachycardias in Single-lead ECGs Recorded Using a Handheld Device
- 2022
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Ingår i: Computing in Cardiology, CinC 2022. - 9798350300970
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Konferensbidrag (refereegranskat)abstract
- Short supraventricular tachycardias (S-SVTs) have been associated with a higher risk of developing atrial fibrillation (AF). Hence, identification of participants with such arrhythmias may increase the yield of AF screening. However, the lower signal quality of ECGs recorded using handheld screening devices challenges the detection of S-SVT. In the present work, a new method for detection of S-SVT is presented, which is based on the requirement on morphologic similarity between the detected beats. Specifically, any episode with a sequence of beats of similar morphology is considered as an S-SVT candidate while any episode with detections of different morphology, either due to signal disturbances or aberrant ectopic beats, is excluded. For this purpose, a support vector machine (SVM) was trained and validated, using a simulated ECG database, to classify an episode as either consisting of beats of similar or non-similar morphologies. Episodes identified as S-SVT candidates are subject to two further rhythm criteria in order to confirm the presence of an S-SVT. The performance of the S-SVT detector is evaluated using a subset of the StrokeStop I database (305 S-SVT out of 8258), resulting in a sensitivity, specificity, and positive predictive value of 88.8%, 92.0%, and 29.9%, respectively. In conclusion, the results suggest that the detection of S-SVT in AF screening can be done at an acceptable balance between sensitivity and positive predictive value.
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| 2. |
- Lázaro, Jesús, et al.
(författare)
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ECG-Derived Respiratory Rate in Atrial Fibrillation
- 2020
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Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 67:3, s. 905-914
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The present study addresses the problem of estimating the respiratory rate from the mor- phological ECG variations in the presence of atrial fibrilla- tory waves (f-waves). The significance of performing f-wave suppression before respiratory rate estimation is investi- gated. Methods: The performance of a novel approach to ECG-derived respiration, named “slope range” (SR) and de- signed particularly for operation in atrial fibrillation (AF), is compared to that of two well-known methods based on ei- ther R-wave angle (RA) or QRS loop rotation angle (LA). A novel rule is proposed for spectral peak selection in respira- tory rate estimation. The suppression of f-waves is accom- plished using signal- and noise-dependent QRS weighted averaging. The performance evaluation embraces real as well as simulated ECG signals acquired from patients with persistent AF; the estimation error of the respiratory rate is determined for both types of signals. Results: Using real ECG signals and reference respiratory signals, rate estima- tion without f-wave suppression resulted in a median error of 0.015 ± 0.021 Hz and 0.019 ± 0.025 Hz for SR and RA, respectively, whereas LA with f-wave suppression resulted in 0.034 ± 0.039 Hz. Using simulated signals, the results also demonstrate that f-wave suppression is superfluous for SR and RA, whereas it is essential for LA. Conclusion: The results show that SR offers the best performance as well as computational simplicity since f-wave suppression is not needed. Significance: The respiratory rate can be robustly estimated from the ECG in the presence of AF.
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| 3. |
- Saiz-Vivó, Javier, et al.
(författare)
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Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
- 2023
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Ingår i: Medical and Biological Engineering and Computing. - : Springer Science and Business Media LLC. - 0140-0118 .- 1741-0444. ; 61:2, s. 317-327
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Tidskriftsartikel (refereegranskat)abstract
- Methods for characterization of atrial fibrillation (AF) episode patterns have been introduced without establishing clinical significance. This study investigates, for the first time, whether post-ablation recurrence of AF can be predicted by evaluating episode patterns. The dataset comprises of 54 patients (age 56 ± 11 years; 67% men), with an implantable cardiac monitor, before undergoing the first AF catheter ablation. Two parameters of the alternating bivariate Hawkes model were used to characterize the pattern: AF dominance during the monitoring period (log(mu)) and temporal aggregation of episodes (beta1). Moreover, AF burden and AF density, a parameter characterizing aggregation of AF burden, were studied. The four parameters were computed from an average of 29 AF episodes before ablation. The risk of AF recurrence after catheter ablation using the Hawkes parameters log(mu) and beta1, AF burden, and AF density was evaluated. While the combination of AF burden and AF density is related to a non-significant hazard ratio, the combination of log(mu) and beta1 is related to a hazard ratio of 1.95 (1.03–3.70; p < 0.05). The Hawkes parameters showed increased risk of AF recurrence within 1 year after the procedure for patients with high AF dominance and high episode aggregation and may be used for pre-ablation risk assessment.
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| 4. |
- Saiz-Vivo, Javier, et al.
(författare)
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Atrial Fibrillatory Rate Characterization Extracted from Implanted Cardiac Monitor Data
- 2021
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Ingår i: 2021 Computing in Cardiology, CinC 2021. - 2325-8861 .- 2325-887X. - 9781665479165 ; 48
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Konferensbidrag (refereegranskat)abstract
- The aim of this study is to characterize atrial fibrillatory rate (AFR) extracted from a cohort of continuously monitored atrial fibrillation (AF) patients as function of episode duration and onset time. The f-wave signal used to compute the AFR was extracted from a single lead ECG strip of the AF episodes stored in an Implantable Cardiac Monitor (ICM) in a cohort of 99 patients. The f-wave signals were obtained from 1400 AF episodes using a spatiotemporal QRST cancellation process and the AFR was estimated as the fundamental frequency of a model fitted to the extracted f-waves. We studied the relationship between AFR and episode duration and episode onset time, respectively. AFR (median (interquartile range)) was significantly lower (p-value<0.05) in short episodes (<20 min) (5.15 (0.66) Hz) than in longer episodes (5.30 (0.74) Hz). AFR was significantly higher for episodes with onset time at night (00-06) (5.34 (0.82) Hz) than for episodes with onset during the day (10-20) (5.21 (0.70) Hz). Significant differences were also found between the relative AFR (ratio between the AFR and the average AFR of the patient) and episode duration (Short: 99.2 (9.3) %; Long: 100.0 (8.9) %). Data extracted from ICMs shows that that nighttime AF onset and longer duration AF episodes are more common in patients with higher AFR.
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| 5. |
- Saiz-Vivo, Javier, et al.
(författare)
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Heart rate characteristic based modelling of atrial fibrillatory rate using implanted cardiac monitor data
- 2023
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Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 44:3
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: The objective of the present study is to investigate the feasibility of using heart rate characteristics to estimate atrial fibrillatory rate (AFR) in a cohort of atrial fibrillation (AF) patients continuously monitored with an implantable cardiac monitor (ICM). We will use a mixed model approach to investigate population effect and patient specific effects of heart rate characteristics on AFR, and will correct for the effect of previous ablations, episode duration, and onset date and time.APPROACH: The f-wave signals, from which AFR is estimated, were extracted using a QRST cancellation process of the AF episodes in a cohort of 99 patients (67% male; 57±12 years) monitored for 9.2(0.2-24.3) months as median(min-max). The AFR from 2453 f-wave signals included in the analysis was estimated using a model-based approach. The association between AFR and heart rate characteristics, prior ablations, and episode-related features were modelled using fixed-effect and mixed-effect modelling approaches.MAIN RESULTS: The mixed-effect models had a better fit to the data than fixed-effect models showing higher coefficients of determination (R2=0.49 vs R2=0.04) when relating the variations of AFR to the heart rate features. However, when correcting for the other factors, the mixed-effect model showed the best fit (R2=0.56). AFR was found to be significantly affected by previous catheter ablations (p<0.05), episode duration (p<0.05), and irregularity of the RR interval series (p<0.05).SIGNIFICANCE: Mixed-effect models are more suitable for AFR modelling. AFR was shown to be faster in episodes with longer duration, less organized RR intervals and after several ablation procedures.
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