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1.	Bachi, Lorenzo, et al. (författare) ECG Modeling for Simulation of Arrhythmias in Time-Varying Conditions 2023 Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 70:12, s. 3449-3460 Tidskriftsartikel (refereegranskat)abstract The present paper proposes an ECG simulator that advances modeling of arrhythmias and noise by introducing time-varying signal characteristics. The simulator is built around a discrete-time Markov chain model for simulating atrial and ventricular arrhythmias of particular relevance when analyzing atrial fibrillation (AF). Each state is associated with statistical information on episode duration and heartbeat characteristics. Statistical, time-varying modeling of muscle noise, motion artifacts, and the influence of respiration is introduced to increase the complexity of simulated ECGs, making the simulator well suited for data augmentation in machine learning. Modeling of how the PQ and QT intervals depend on heart rate is also introduced. The realism of simulated ECGs is assessed by three experienced doctors, showing that simulated ECGs are difficult to distinguish from real ECGs. Simulator usefulness is illustrated in terms of AF detection performance when either simulated or real ECGs are used to train a neural network for signal quality control. The results show that both types of training lead to similar performance.
2.	Barquero-Perez, Oscar, et al. (författare) On the influence of heart rate and coupling interval prematurity on heart rate turbulence 2017 Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 64:2, s. 302-309 Tidskriftsartikel (refereegranskat)abstract Objective: Heart rate turbulence (HRT) has been successfully explored for cardiac risk stratification. While HRT is known to be influenced by the heart rate (HR) and the coupling interval (CI), nonconcordant results have been reported on how the CI influences HRT. The purpose of this study is to investigate HRT changes in terms of CI and HR by means of an especially designed protocol. Methods: A dataset was acquired from 11 patients with structurally normal hearts for which CI was altered by different pacing trains and HR by isoproterenol during electrophysiological study (EPS). The protocol was designed so that, first, the effect of HR changes on HRT and, second, the combined effect of HR and CI could be explored. As a complement to the EPS dataset, a database of 24-h Holters from 61 acute myocardial infarction (AMI) patients was studied for the purpose of assessing risk. Data analysis was performed by using different nonlinear ridge regression models, and the relevance of model variables was assessed using resampling methods. The EPS subjects, with and without isoproterenol, were analyzed separately. Results: The proposed nonlinear regression models were found to account for the influence of HR and CI on HRT, both in patients undergoing EPS without isoproterenol and in low-risk AMI patients, whereas this influence was absent in high-risk AMI patients. Moreover, model coefficients related to CI were not statistically significant, p > 0.05, on EPS subjects with isoproterenol. Conclusion: The observed relationship between CI and HRT, being in agreement with the baroreflex hypothesis, was statistically significant (p < 0.05), when decoupling the effect of HR and normalizing the CI by the HR. Significance: The results of this study can help to provide new risk indicators that take into account physiological influence on HRT, as well as to model how this influence changes in different cardiac conditions.
3.	Behjat, Hamid, et al. (författare) Domain-Informed Spline Interpolation 2019 Ingår i: IEEE Transactions on Signal Processing. - 1053-587X. ; 67:15, s. 3909-3921 Tidskriftsartikel (refereegranskat)abstract Standard interpolation techniques are implicitly based on the assumption that the signal lies on a single homogeneous domain. In contrast, many naturally occurring signals lie on an inhomogeneous domain, such as brain activity associated to different brain tissue. We propose an interpolation method that instead exploits prior information about domain inhomogeneity, characterized by different, potentially overlapping, subdomains. As proof of concept, the focus is put on extending conventional shift-invariant B-spline interpolation. Given a known inhomogeneous domain, B-spline interpolation of a given order is extended to a domain-informed, shift-variant interpolation. This is done by constructing a domain-informed generating basis that satisfies stability properties. We illustrate example constructions of domain-informed generating basis and show their property in increasing the coherence between the generating basis and the given inhomogeneous domain. By advantageously exploiting domain knowledge, we demonstrate the benefit of domain-informed interpolation over standard B-spline interpolation through Monte Carlo simulations across a range of B-spline orders. We also demonstrate the feasibility of domain-informed interpolation in a neuroimaging application where the domain information is available by a complementary image contrast. The results show the benefit of incorporating domain knowledge so that an interpolant consistent to the anatomy of the brain is obtained.
4.	Ben-Moshe, Noam, et al. (författare) RawECGNet : Deep Learning Generalization for Atrial Fibrillation Detection From the Raw ECG 2024 Ingår i: IEEE Journal of Biomedical and Health Informatics. - 2168-2194. ; , s. 1-10 Tidskriftsartikel (refereegranskat)abstract Introduction Deep learning models for detecting episodes of atrial fibrillation (AF) using rhythm information in long-term ambulatory ECG recordings have shown high performance. However, the rhythm-based approach does not take advantage of the morphological information conveyed by the different ECG waveforms, particularly the f-waves. As a result, the performance of such models may be inherently limited. Methods: To address this limitation, we have developed a deep learning model, named RawECGNet, to detect episodes of AF and atrial flutter (AFl) using the raw, single-lead ECG. We compare the generalization performance of RawECGNet on two external data sets that account for distribution shifts in geography, ethnicity, and lead position. RawECGNet is further benchmarked against a state-of-the-art deep learning model, named ArNet2, which utilizes rhythm information as input. Results: Using RawECGNet, the results for the different leads in the external test sets in terms of the F1 score were 0.91–0.94 in RBDB and 0.93 in SHDB, compared to 0.89–0.91 in RBDB and 0.91 in SHDB for ArNet2. The results highlight RawECGNet as a high-performance, generalizable algorithm for detection of AF and AFl episodes, exploiting information on both rhythm and morphology.
5.	Biton, Shany, et al. (författare) Estimation of f-wave Dominant Frequency Using a Voting Scheme 2022 Ingår i: Computing in Cardiology, CinC 2022. - 9798350300970 Konferensbidrag (refereegranskat)abstract Atrial fibrillation (AF) is the most common heart arrhythmia, characterized by the presence of fibrillatory waves (f-waves) in the ECG. We introduce a voting scheme to estimate the dominant atrial frequency (DAF) of f-waves. Methods: We analysed a subset of Holter recordings obtained from the University of Virginia AF Database. 100 Holter recordings with manually annotated AF events, resulting in a total 363 AF events lasting more than 1 min. The f-waves were extracted using four different template subtraction (TS) algorithms and the DAF was estimated from the first 1-min window of each AF event. A random forest classifier was used. We hypothesized that better extraction of the f-wave meant better AF/non-AF classification using the DAF as the single input feature of the RF model. Results: Performance on the test set, expressed in terms of AF/non-AF classification, was the best when the DAF was computed computed the three best-performing extraction methods. Using these three algorithms in a voting scheme, the classifier obtained AUC=0.60 and the DAFs were mostly spread around 6 Hz, 5.66 (4.83-7.47). Conclusions: This study has two novel contributions: (1) a method for assessing the performance of f-wave extraction algorithms, and (2) a voting scheme for improved DAF estimation.
6.	Butkuviene, Monika, et al. (författare) Atrial Fibrillation Episode Patterns and Their Influence on Detection Performance 2021 Ingår i: 2021 Computing in Cardiology, CinC 2021. - 2325-8861 .- 2325-887X. - 9781665479165 ; 2021-September Konferensbidrag (refereegranskat)abstract Existing studies offer little insight on how atrial fibrillation (AF) detection performance is influenced by the properties of AF episode patterns. The aim of this study is to investigate the influence of AF burden and median AF episode length on detection performance. For this purpose, three types of AF detectors, using either information on rhythm, rhythm and morphology, or ECG segments, were investigated on 1-h simulated ECGs. Comparing AF burdens of 20% and 80% for a median episode length of 167 beats, the sensitivity of the rhythm- and morphology-based detector increases only slightly whereas the specificity drops from 99.5% to 93.3%. The corresponding figures of specificity are 99.0% and 90.6% for the rhythm-based detector; 88.1% and 70.7% for the segment-based detector. The influence of AF burden on specificity becomes even more pronounced for AF patterns with brief episodes (median episode length set to 30 beats). Therefore, patterns with briefepisodes and high AF burden imply higher demands on detection performance. Future research should focus on how well episode patterns are captured.
7.	Butkuviene, Monika, et al. (författare) Characterization of Atrial Fibrillation Episode Patterns : A Comparative Study 2024 Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 71:1, s. 106-113 Tidskriftsartikel (refereegranskat)abstract Objective: The episode patterns of paroxysmal atrial fibrillation (AF) may carry important information on disease progression and complication risk. However, existing studies offer very little insight into to what extent a quantitative characterization of AF patterns can be trusted given the errors in AF detection and various types of shutdown, i.e., poor signal quality and non-wear. This study explores the performance of AF pattern characterizing parameters in the presence of such errors. Methods: To evaluate the performance of the parameters AF aggregation and AF density, both previously proposed to characterize AF patterns, the two measures mean normalized difference and the intraclass correlation coefficient are used to describe agreement and reliability, respectively. The parameters are studied on two PhysioNet databases with annotated AF episodes, also accounting for shutdowns due to poor signal quality. Results: The agreement is similar for both parameters when computed for detector-based and annotated patterns, which is 0.80 for AF aggregation and 0.85 for AF density. On the other hand, the reliability differs substantially, with 0.96 for AF aggregation but only 0.29 for AF density. This finding suggests that AF aggregation is considerably less sensitive to detection errors. The results from comparing three strategies to handle shutdowns vary considerably, with the strategy that disregards the shutdown from the annotated pattern showing the best agreement and reliability. Conclusions: Due to its better robustness to detection errors, AF aggregation should be preferred. To further improve performance, future research should put more emphasis on AF pattern characterization.
8.	Butkuviene, Monika, et al. (författare) Considerations on Performance Evaluation of Atrial Fibrillation Detectors 2021 Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 68:11, s. 3250-3260 Tidskriftsartikel (refereegranskat)abstract Objective: A large number of atrial fibrillation (AF) detectors have been published in recent years, signifying that the comparison of detector performance plays a central role, though not always consistent. The aim of this study is to shed needed light on aspects crucial to the evaluation of detection performance. Methods: Three types of AF detector, using either information on rhythm, rhythm and morphology, or segments of ECG samples, are implemented and studied on both real and simulated ECG signals. The properties of different performance measures are investigated, for example, in relation to dataset imbalance. Results: The results show that performance can differ considerably depending on the way detector output is compared to database annotations, i.e., beat-to-beat, segment-to-segment, or episode-to-episode comparison. Moreover, depending on the type of detector, the results substantiate that physiological and technical factors, e.g., changes in ECG morphology, rate of atrial premature beats, and noise level, can have a considerable influence on performance. Conclusion: The present study demonstrates overall strengths and weaknesses of different types of detector, highlights challenges in AF detection, and proposes five recommendations on how to handle data and characterize performance.
9.	Corino, Valentina D.A., et al. (författare) Non-invasive evaluation of the effect of metoprolol on the atrioventricular node during permanent atrial fibrillation 2014. - January Ingår i: Computing in Cardiology 2014. - : Oxford University Press (OUP). - 2325-8861. - 9781479943463 - 9781479943470 ; 41, s. 889-892 Konferensbidrag (refereegranskat)abstract The aim of this study was to evaluate changes in AV nodal properties during administration of metoprolol, using a novel ECG-based method for parameter estimation. The AV nodal parameters account for the probability of an impulse not passing through the fast pathway, the absolute refractory periods of the slow and fast pathways (aRPs and aRPf), representing the functional refractory period, and related prolongation in the respective refractory periods. Twenty patients (age 71±8 years, 14 men) with permanent AF from the RATe control in Atrial Fibrillation (RATAF) database were included in this study. Recordings during baseline and metoprolol administration were analyzed. Furthermore, simulated RR series were generated mimicking metoprolol administration. During metoprolol administration, aRP was significantly prolonged in both pathways (aRPs: 342±39 vs. 408±81 ms, p<0.001; aRPf: 432±74 vs. 527±83 ms, p<0.001). Similar results were found for the simulated RR series: both aRPs and aRPf were significantly prolonged with metoprolol. The AV nodal parameters reflect expected changes after metoprolol administration, i.e., a prolongation in functional refractory period. The simulations suggest that aRP may serve as an estimate of the functional refractory period.
10.	Corino, Valentina D A, et al. (författare) Statistical modeling of atrioventricular nodal function during atrial fibrillation : An update 2013 Ingår i: BIOSIGNALS 2013 - Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing. - 9789898565365 ; , s. 25-29 Konferensbidrag (refereegranskat)abstract This paper introduces a number of advancements of our recently proposed model of atrioventricular (AV) node function during atrial fibrillation (AF). The model is defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the two AV nodal pathways, the refractory periods of these pathways, and their prolongation. In the updated model, the characterization of AV nodal pathways is made more detailed and the number of pathways is determined by the Bayesian information criterion. The performance is evaluated on ECG data acquired from twenty-five AF patients during rest and head-up tilt test. The results show that the refined AV node model provides significantly better fit than did the original model. During tilt, the AF frequency increased (6.25 ±0.58 Hz vs. 6.32 ±0.61 Hz, p < 0.05, rest vs. tilt) and the prolongation of the refractory periods decreased for both pathways (slow pathway: 0.23 ±0.20 s vs. 0.11 ±0.10 s, p < 0.001, rest vs. tilt; fast pathway: 0.24±0.31 s vs. 0.16±0.19 s, p < 0.05, rest vs. tilt). These results show that AV node characteristics can be assessed noninvasively for the purpose of quantifying changes induced by autonomic stimulation.
11.	Corino, Valentina D.A., et al. (författare) Statistical modeling of the atrioventricular node during atrial fibrillation : Data length and estimator performance 2013 Ingår i: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. - 9781457702167 ; , s. 2567-2570 Konferensbidrag (refereegranskat)abstract The atrioventricular (AV) node plays a central role during atrial fibrillation (AF). We have recently proposed a statistical AV node model defined by parameters characterizing the arrival rate of atrial impulses, the probability of an impulse choosing either one of the dual AV nodal pathways, the refractory periods of the pathways, and the prolongation of refractory periods. All model parameters are estimated from the RR series using maximum likelihood (ML) estimation, except for the mean arrival rate of atrial impulses which is estimated by the AF frequency derived from the f-waves. The aim of this study is to present a unified approach to ML estimation which also involves the shorter refractory period, thus avoiding our previous Poincaré plot analysis which becomes biased. In addition, the number of RR intervals required for accurate parameter estimation is presented. The results show that the shorter refractory period can be accurately estimated, and that the resulting estimates converge to the true values when about 500 RR intervals are available.
12.	Halvaei, Hesam, et al. (författare) Detection of Non-Sustained Supraventricular Tachycardia in Atrial Fibrillation Screening Ingår i: IEEE Journal of Translational Engineering in Health and Medicine. - 2168-2372. Tidskriftsartikel (refereegranskat)abstract Objective: Non-sustained supraventricular tachycardia (nsSVT) is associated with a higher risk of developing atrial fibrillation (AF), and, therefore, detection of nsSVT can improve AF screening efficiency. However, the detection is challenged by the lower signal quality of ECGs recorded using handheld devices and the presence of ectopic beats which may mimic the rhythm characteristics of nsSVT. Methods: The present study introduces a new nsSVT detector for use in single-lead, 30-s ECGs, based on the assumption that beats in an nsSVT episode exhibits similar morphology, implying that episodes with beats of deviating morphology, either due to ectopic beats or noise/artifacts, are excluded. A support vector machine is used to classify successive 5-beat sequences in a sliding window with respect to similar morphology. Due to the lack of adequate training data, the classifier is trained using simulated ECGs with varying signal-to-noise ratio. In a subsequent step, a set of rhythm criteria is applied to similar beat sequences to ensure that episode duration and heart rate is acceptable. Results: The performance of the proposed detector is evaluated using the StrokeStop II database, resulting in sensitivity, specificity, and positive predictive value of 84.6%, 99.4%, and 18.5%, respectively. Conclusion: The results show that a significant reduction in expert review burden (factor of 6) can be achieved using the proposed detector. Clinical and Translational Impact: The reduction in the expert review burden shows that nsSVT detection in AF screening can be made considerably more efficiently.
13.	Halvaei, Hesam, et al. (författare) Detection of Short Supraventricular Tachycardias in Single-lead ECGs Recorded Using a Handheld Device 2022 Ingår i: Computing in Cardiology, CinC 2022. - 9798350300970 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.
14.	Henriksson, Mikael, et al. (författare) Model-based Assessment of f-Wave Signal Quality in Patients with Atrial Fibrillation 2018 Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 65:11, s. 2600-2611 Tidskriftsartikel (refereegranskat)abstract Objective: The detection and analysis of atrial fibrillation (AF) in the ECG is greatly influenced by signal quality. The present study proposes and evaluates a model-based f-wave signal quality index (SQI), denoted S, for use in the QRST-cancelled ECG signal. Methods: S is computed using a harmonic f-wave model, allowing for variation in frequency and amplitude. The properties of S are evaluated on both f-waves and P-waves using 378 12-lead ECGs, 1875 single-lead ECGs, and simulated signals. Results: S decreases monotonically when noise is added to f-wave signals, even for noise which overlaps spectrally with f-waves. Moreover, S is shown to be closely associated with the accuracy of AF frequency estimation, where S>0.3 implies accurate estimation. When S is used as a measure of f-wave presence, AF detection performance improves: the sensitivity increases from 97.0% to 98.1% and the specificity increases from 97.4% to 97.8% when compared to the reference detector. Conclusion: The proposed SQI represents a novel approach to assessing f-wave signal quality, as well as to determining whether f-waves are present. Significance: The use of S improves the detection of AF and benefits the analysis of noisy ECGs.
15.	Henriksson, Mikael, et al. (författare) Modeling and Estimation of Temporal Episode Patterns in Paroxysmal Atrial Fibrillation 2021 Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 68:1, s. 319-329 Tidskriftsartikel (refereegranskat)abstract Objective: The present study proposes a model-based, statistical approach to characterizing episode patterns in paroxysmal atrial fibrillation (AF). Thanks to the rapid advancement of noninvasive monitoring technology, the proposed approach should become increasingly relevant in clinical practice. Methods: History-dependent point process modeling is employed to characterize AF episode patterns, using a novel alternating, bivariate Hawkes self-exciting model. In addition, a modified version of a recently proposed statistical model to simulate AF progression throughout a lifetime is considered, involving non-Markovian rhythm switching and survival functions. For each model, the maximum likelihood estimator is derived and used to find the model parameters from observed data. Results: Using three databases with a total of 59 long-term ECG recordings, the goodness-of-fit analysis demonstrates that the proposed alternating, bivariate Hawkes model fits SR-to-AF transitions in 40 recordings and AF-to-SR transitions in 51; the corresponding numbers for the AF model with non-Markovian rhythm switching are 40 and 11, respectively. Moreover, the results indicate that the model parameters related to AF episode clustering, i.e., aggregation of temporal AF episodes, provide information complementary to the well-known clinical parameter AF burden. Conclusion: Point process modeling provides a detailed characterization of the occurrence pattern of AF episodes that may improve the understanding of arrhythmia progression.
16.	Kontaxis, Spyridon, et al. (författare) Investigating Respiratory Rate Estimation during Paroxysmal Atrial Fibrillation Using an Improved ECG Simulation Model 2020 Ingår i: 2020 Computing in Cardiology, CinC 2020. - 2325-887X .- 2325-8861. - 9781728173825 ; 2020-September Konferensbidrag (refereegranskat)abstract The present study addresses the problem of respiratory rate estimation from ECG-derived respiration (EDR) signals during paroxysmal atrial fibrillation (AF). Novel signal-to-noise ratios between various components of the ECG including the influence of respiration, measured by QRS ensemble variance, the amplitude of fibrillatory waves (f-waves), and the QRS amplitude are introduced to characterize EDR performance. Using an improved ECG simulation model accounting for morphological variation induced by respiration, the results show that 1. the error in estimating the respiratory rate increases as a function of the time spent in AF, 2. the leads farthest away from the atria, i.e., V_{4}, V_{5}, V_{6}, exhibit the best performance due to lower f-wave amplitudes, 3. lower errors in leads with similar f-wave amplitude are due to a more pronounced respiratory influence, and 4. the respiratory influence is higher in V_{2}, V_{3}, and V_{4} compared to other precordial leads.
17.	Lazaro, Jesus, et al. (författare) Electrocardiogram derived respiration from QRS slopes : Evaluation with stress testing recordings 2013 Ingår i: 2013 Computing in Cardiology. - 9781479908844 ; 40, s. 655-658 Konferensbidrag (refereegranskat)abstract A method for respiratory rate estimation from electrocardiogram (ECG), based on variations in QRS complexes slopes, is evaluated over stress testing recordings. Besides the 12 standard, and the 3 vectorcardiogram (VCG), 2 additional leads derived from the VCG are analyzed. A total of 34 slope series were studied, 2 for each lead: slopes between the peaks of the Q and R waves, and between the peaks of the R and S waves. Respiratory rate is estimated by using a time-frequency based algorithm which can combine information from several derived respiration signals. Evaluation was performed over a database containing ECG and respiratory signals simultaneously recorded from 30 subjects spontaneously breathing during a stress test. Respiratory rate estimation is performed with information of 4 different combinations of QRS slope series. The best results in respiratory rate estimation error terms are -1.07 ± 8.86% (-11.47 ± 37.97 mHz). These results suggest that proposed methods based on QRS slopes are highly suitable for respiratory rate estimation from ECG signal, specially at very non-stationary and noise scenarios as stress test.
18.	Martin-Yebra, Alba, et al. (författare) Characterization of Atrial Fibrillation Episodes Using a Point Process Model 2020 Ingår i: 2020 11th Conference of the European Study Group on Cardiovascular Oscillations : Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020 - Computation and Modelling in Physiology: New Challenges and Opportunities, ESGCO 2020. - 9781728157511 Konferensbidrag (refereegranskat)abstract The purpose of the present study is to introduce a point process model for characterizing the pattern of atrial fibrillation (AF) episodes. A variant of the bivariate Hawkes process is proposed, accounting for clustered episodes. The model parameters are inferred by the maximum likelihood method. The goodness-of-fit analysis show that model fits the data in most of the recordings (27 out of 32). The information provided by this approach is complementary to AF burden.
19.	Martin-Yebra, Alba, et al. (författare) Model-Based Characterization of Atrial Fibrillation Episodes and its Clinical Association 2020 Ingår i: 2020 Computing in Cardiology, CinC 2020. - 2325-887X .- 2325-8861. - 9781728173825 ; 2020-September Konferensbidrag (refereegranskat)abstract Studies investigating risk factors associated with atrial fibrillation (AF) have mostly focused on AF presence and burden, disregarding the temporal distribution of AF episodes although such information can be relevant. In the present study, the alternating, bivariate Hawkes model was used to characterize paroxysmal AF episode patterns. Two parameters: the intensity ratio µ, describing the dominating rhythm (AF or non-AF) and the exponential decay ß 1, providing information on clustering, were investigated in relation to AF burden and atrial echocardiographic measurements. Both µ and ß1were weakly correlated with atrial volume (r=0.19 and r=0.34, respectively), whereas µ was correlated with atrial strain (r=-0.74, p=0.1) and AF burden (r=0.68, p=0.05). Weak correlation between ß1 and AF burden was found (r=0.29). Atrial structural remodeling is associated with changes in AF characteristics, often manifested as episodes of increasing duration, thus µ may reflect the degree of atrial electrical and structural remodeling. Moreover, clustering information (ß1) is complementary information to AF burden, which may be useful for understanding arrhythmia progression and risk assessment of ischemic stroke.
20.	Martin-Yebra, Alba, et al. (författare) QT interval Adaptation to Heart Rate Changes in Atrial Fibrillation as a Predictor of Sudden Cardiac Death 2022 Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 69:10, s. 3109-3118 Tidskriftsartikel (refereegranskat)abstract Objective: The clinical significance of QT interval adaptation to heart rate changes has been poorly investigated in atrial fibrillation (AF), since QT delineation in the presence of f-waves is challenging. Therefore, the objective of the present study is to investigate new techniques for QT adaptation estimation in permanent AF. Methods: A multilead strategy based on generalized periodic component analysis is proposed for QT delineation, involving a spatial, linear transformation which emphasizes Twave periodicity and attenuates f-waves. QT adaptation is modeled by a linear, time-invariant filter, whose impulse response describes the dependence between the current QT interval and the preceding RR intervals, followed by a memoryless, possibly nonlinear, function. The QT adaptation time lag is determined from the estimated impulse response. Results: Using simulated ECGs in permanent AF, the transformed lead was found to offer more accurate QT delineation and time lag estimation than did the original ECG leads for a wide range of f-wave amplitudes (the time lag estimation error was found to be -0.2+/-0.6 s for SNR = 12 dB). In a population with chronic heart failure and permanent AF, the time lag estimated from the transformed lead was found to have the strongest, statistically significant association with sudden cardiac death (SCD) (hazard ratio = 3.49), whereas none of the original, orthogonal leads had any such association. Conclusions: Periodic component analysis provides more accurate QT delineation and improves time lag estimation in AF. A prolonged adaptation time of the QT interval to heart rate changes is associated with a high risk for SCD. Significance: This study demonstrates that SCD risk markers, originally developed for sinus rhythm, can also be used in AF, provided that Twave periodicity is emphasized. The time lag is a potentially useful marker for identifying patients at high risk for SCD, guiding clinicians in adopting effective therapeutic decisions.
21.	Perez, Cristina, et al. (författare) Evaluation of a QT Adaptation Time Estimator for ECG Exercise Stress Test in Controlled Simulation 2023 Ingår i: Computing in Cardiology, CinC 2023. - 2325-887X .- 2325-8861. - 9798350382525 Konferensbidrag (refereegranskat)abstract Slowed adaptation of the QT interval to sudden abrupt heart rate (HR) changes has been identified as a marker of ventricular arrhythmic risk. However, abrupt HR changes are difficult to induce in patients. Quantifying the QT adaptation time in gradual HR changes, as observed in ECGs recording during an exercise stress test, has been recently proposed. The time lag between the QT series and an instantaneous memoryless HR-dependent QT series along stress test was computed as QT memory. Here, this method was evaluated in a control scenario using simulated exercise stress test ECG signals presenting different QT adaptation times. The method robustness was studied by contaminating the ECGs with muscular noise (MN) signals with different Signal-to-Noise ratio (SNR) values, either synthetic or extracted from real recordings. We found that delineation of the T-wave end point in the first transformed lead from Periodic Component Analysis offers the best performance for low SNR. Moreover, we confirmed that the estimator provides an unbiased estimate of the QT memory introduced in the simulations for the studied range of SNR values (25 to 50 dB).
22.	Petrenas, Andrius, et al. (författare) A noise-adaptive method for detection of brief episodes of paroxysmal atrial fibrillation 2013 Ingår i: 2013 Computing in Cardiology. - 9781479908844 ; 40, s. 739-742 Konferensbidrag (refereegranskat)abstract The aim of this work is to develop a method for detection of brief episode paroxysmal atrial fibrillation (PAF). The proposed method utilizes four different features: RR interval irregularity, absence of P waves, presence of f-waves and noise level. The obtained features are applied to the Mamdani-type fuzzy inference method for decisionmaking. The performance was evaluated on one hundred 90 s long surrogate ECG signals with brief PAF episodes (5-30 beats). The robustness to noise in ECGs where noise level in each set is incremented in steps of 0.01 mV from 0 to 0.2 mV was examined as well. When compared to the coefficient of sample entropy, our method showed considerably better performance for low and moderate noise levels (< 0.06 mV) with an area under the receiver operating characteristic curve of 0.9 and 0.94, respectively. Similar performance is expected for higher noise levels as atrial activity is less used in the detection process. Finally, the results suggest that our method is more robust to false alarms due to ectopic beats or other irregular rhythms than the method under comparison.
23.	Petrenas, Andrius, et al. (författare) Reservoir computing for extraction of low amplitude atrial activity in atrial fibrillation 2012 Ingår i: 2012 Computing in Cardiology. - 9781467320740 ; 39, s. 13-16 Konferensbidrag (refereegranskat)abstract A novel method for QRST cancellation during atrial fibrillation (AF) is introduced for use in recordings with two or more leads. The method is based on an echo state neural network (ESN) which estimates the time-varying, nonlinear transfer function between two leads, one lead with atrial activity and another lead without, for the purpose of canceling ventricular activity. The performance is evaluated on ECG signals, with simulated f-waves of low amplitude added, by determining the root mean square error P between the true f-wave signal and the estimated signal, as well as by evaluating the dominant AF frequency. When compared to average beat subtraction (ABS), being the most widely used method for QRST cancellation, the performance is found to be significantly better with equal to mean and standard deviation of PESN 24.8±7.3 and PABS 34.2±17.9 μV (p < 0.001). The novel method is particularly well-suited for implementation in mobile health systems where monitoring of AF during extended time periods is of interest.
24.	Plusciauskaite, Vilma, et al. (författare) Detection of Pre-and Post-Trigger Atrial Fibrillation in Long-Term Photoplethysmogram Signals Acquired in Free-Living 2023 Ingår i: Computing in Cardiology, CinC 2023. - 9798350382525 Konferensbidrag (refereegranskat)abstract Modifiable factors, such as alcohol or physical exertion, may trigger atrial fibrillation (AF) episodes. Identifying and eliminating these triggers can lead to effective strategies which reduce risk of AF recurrence. This study aims to evaluate pre-and post-trigger AF in long-term photo-plethysmogram (PPG) signals obtained during daily living from patients with paroxysmal AF. Thirty-seven patients were instructed to wear a wrist-worn device for a week. They were also asked to log suspected triggers using a smartphone app. Of these patients, 15 experienced AF episodes, resulting in an average AF burden of 0.15. The results indicate that longer post-trigger analysis time intervals resulted in better performance of PPG-based AF detection. The sensitivity was highest for the 16-h post-trigger interval (0.76) and lowest for the 4-h interval (0.43). In contrast, the specificity slightly decreased with an increasing longer post-trigger analysis time interval, being 0.98 and 0.95 for the 4-h and 16-h intervals, respectively. The PPG-based post-trigger AF burden was approximately half of that determined by the annotated ECG-based AF pattern. The study suggests that long-term PPG-based monitoring is a suitable alternative for detecting post-trigger AF instead of ECG-based. However, the accuracy of AF burden estimation using PPG-based technology still calls for improvement.
25.	Plusciauskaite, Vilma, et al. (författare) Modeling of the Effect of Alcohol on Episode Patterns in Atrial Fibrillation 2022 Ingår i: 2022 Computing in Cardiology, CinC 2022. - 2325-8861 .- 2325-887X. - 9798350300970 ; 2022-September Konferensbidrag (refereegranskat)abstract Growing evidence shows that alcohol triggers paroxysmal atrial fibrillation (PAF) in some patients. How-ever, there is a lack of methods for assessing the causality between triggers and atrial fibrillation (AF) episodes. Accordingly, this work aims to develop an approach to episode modeling under the influence of alcohol for the purpose of evaluating causality assessment methods. The alternating, bivariate Hawkes model is used to produce episode patterns, where the conditional intensity function λ1(t) defines the transitions from sinus rhythm (SR) to AF. The effect of alcohol consumption is characterized by a body reactivity function, defined by the base intensity μ1(t), which alters λ1(t). Different AF episode patterns were modeled for alcohol units ranging from 0 to 15. The mean AF burden without alcohol was 17.2%, which doubled with 9 alcohol units; the number of AF episodes doubled from 12.9 with 8 alcohol units. The aggregation of AF episodes tended to decrease after 6 alcohol units. The proposed model of alcohol-affected PAF patterns may be useful for assessing the methods for evaluation of causality between triggers and PAF occurrence.
26.	Sandberg, Frida, et al. (författare) Drug effect evaluation during permanent atrial fibrillation using an AV-node model 2013 Ingår i: Computing in Cardiology 2013, CinC 2013. - 9781479908844 ; 40, s. 1243-1246 Konferensbidrag (refereegranskat)abstract The purpose of the present study is to evaluate the effect of rate control drugs on the AV node characteristics during atrial fibrillation (AF) using a model-based approach. A statistical model of the AV nodal function is employed, defined by parameters which characterize the arrival rate of atrial impulses, the refractoriness of the fast and the slow AV-nodal pathway and the probability of atrial impulse to pass through either of the two pathways. The RATAF (RATe control in Atrial Fibrillation) study database consists of recordings from 60 patients with permanent AF at baseline and on treatment with metoprolol, verapamil, diltiazem and carvedilol, respectively. The resulting model parameter estimates indicate that the refractory period of the slow pathway as well as that of the fast pathway increased significantly during treatment with all four drugs. The results suggest that the proposed AV-node model can be used for non-invasive evaluation of the effect of rate control drugs.
27.	Sandberg, Frida, et al. (författare) Prediction of intradialytic hypotension using PPG and ECG 2013 Ingår i: 2013 Computing in Cardiology. - 9781479908844 ; 40, s. 1227-1230 Konferensbidrag (refereegranskat)abstract Intradialytic hypotension (IDH) is the most common complication during hemodialysis; early prediction and prevention of IDH would dramatically improve the living conditions for patients with end stage renal disease. A recently published study suggests that a decrease in the envelope of the photoplethysmograpy (PPG) signal can be used for predicting acute symptomatic IDH. In the present study, the PPG based method is extended by introducing a patient dependent detection threshold, which involves information on heart rate variability (HRV) and heart rate turbulence (HRT) from the current dialysis session. This is motivated since several studies have found significant differences in HRV and HRT between hypotension-prone and hypotension-resistant patients. Recordings from 15 patients during 38 hemodialysis sessions were used to evaluate the method. Symptomatic IDH was correctly predicted in 9 out of 14 cases, while 5 out of 24 cases were falsely predicted. The performance was better for acute symptomatic IDH, 5 out of 5 cases were correctly predicted. The present method represents a novel approach to combining information derived from ECG and PPG signals.
28.	Simaityte, Monika, et al. (författare) Quantitative Evaluation of Temporal Episode Patterns in Paroxysmal Atrial Fibrillation 2018 Ingår i: Computing in Cardiology Conference, CinC 2018. - 9781728109589 ; 45 Konferensbidrag (refereegranskat)abstract Flow velocity in left atrial appendage decreases when paroxysmal atrial fibrillation (PAF) progresses to longer episodes, suggesting that the temporal PAF episode pattern may be related to risk of thrombus formation. This study investigates the feasibility of discriminating episode patterns based on two descriptors: the aggregation characterizes the temporal distribution of PAF episodes, whereas the Gini coefficient characterizes differences in episode duration. The descriptors were studied on three PhysioNet databases with annotated PAF episodes, resulting in a total of 102 recordings. Three types of patterns were defined: congregation of several episodes in a single and multiple clusters, and episodes dispersed over the entire monitoring period. The results show that the aggregation descriptor achieves large values for patterns with a single and multiple clusters (0.76± 0.07 and 0.60± 0.08, respectively). In contrast, much lower values are obtained for dispersed episode patterns (0.10± 0.05). The Gini coefficient is better suited for discriminating among the patterns with high PAF burden and, therefore, represents a descriptor which is complementary to aggregation. Both descriptors may have relevance when studying the relationship between episode pattern and the risk of thrombus formation.
29.	Sornmo, Leif, et al. (författare) Spectral Analysis of Heart Rate Variability in Time-Varying Conditions and in the Presence of Confounding Factors 2022 Ingår i: IEEE Reviews in Biomedical Engineering. - 1937-3333. ; , s. 1-21 Tidskriftsartikel (refereegranskat)abstract The tools for spectrally analyzing heart rate variability (HRV) has in recent years grown considerably, with emphasis on the handling of time-varying conditions and confounding factors. Time–frequency analysis holds since long an important position in HRV analysis, however, this technique cannot alone handle a mean heart rate or a respiratory frequency which vary over time. Overlapping frequency bands represents another critical condition which needs to be dealt with to produce accurate spectral measurements. The present survey offers a comprehensive account of techniques designed to handle such conditions and factors by providing a brief description of the main principles of the different methods. Several methods derive from a mathematical/statistical model, suggesting that the model can be used to simulate data used for performance evaluation. The inclusion of a respiratory signal, whether measured or derived, is another feature of many recent methods, e.g., used to guide the decomposition of the HRV signal so that signals related as well as unrelated to respiration can be analyzed. It is concluded that the development of new approaches to handling time-varying scenarios are warranted, as is benchmarking of performance evaluated in technical as well as in physiological/clinical terms.
30.	Vraka, Aikaterini, et al. (författare) Alternative Time-Domain P-wave Analysis for Precise Information on Substrate Alteration after Pulmonary Vein Isolation for Atrial Fibrillation 2021 Ingår i: 2021 9th E-Health and Bioengineering Conference, EHB 2021. - 9781665440004 Konferensbidrag (refereegranskat)abstract While P-wave duration (PWD) is primarily employed to observe the atrial substrate alterations after pulmonary vein isolation (PVI) on atrial fibrillation (AF) patients, the acquired information corresponds to the entire atria. Left (LA) and right atrium (RA), though, may be differently affected by PVI, implying the need for different after-PVI handling. In order to clarify this assumption, five-minute lead II recordings from 29 paroxysmal AF patients undergoing first-ever PVI were recruited before and after PVI. PWD was analyzed integrally and in parts, with the first part (PWD1) from the onset to the peak corresponding to RA and the second part (PWD2) to LA depolarization. Time from P-wave onset or offset to the R peak were also calculated (Pon - R and Poff - R, respectively). Normalization (N) to mitigate heart-rate effect was applied. Results before and after PVI were compared with Mann-Whitney U-test (MWU). Median values and variations due to PVI were calculated for all features and compared between PWD and the remaining features via Pearson correlation. After PVI, PWD (-9.84%, p = 0.0085, N: - 17.96%, p = 0.0442) and PWD2 (-22.03%, p = 0.0250, N: - 27.77%, p = 0.0268) were significantly decreased. PWD1 did not shorten significantly (up to -8.96%, p > 0.05 at either cases). PWD - PWD1 (ρ > 74.5%, p < 0.0001) showed higher correlation than PWD - PWD2 (ρ > 41.9%, p < 0.0001) in before and after PVI analysis but not for PVI-related variation (ρPWD-PWD1 = 54.0%, p = 0.0114 and ρPWD-PWD2 = 61.4%, p = 0.0031). While RA depolarization time is more in line with PWD analysis, the effect of PVI in PWD is more coherent with LA's findings. Additionally, PWD shortening is only observed in the LA. Therefore, LA is crucial for the assessment of the atrial substrate alteration after PVI and its analysis should be considered by future studies.
31.	Vraka, Aikaterini, et al. (författare) The P-Wave Time-Domain Significant Features to Evaluate Substrate Modification After Catheter Ablation of Paroxysmal Atrial Fibrillation 2022 Ingår i: 2022 Computing in Cardiology, CinC 2022. - 2325-887X .- 2325-8861. - 9798350300970 ; 2022-September Konferensbidrag (refereegranskat)abstract The outcome of catheter ablation (CA) of atrial fibrillation (AF) is vastly analyzed by the entire P-wave duration (PWD). However, the first and second P-wave parts, corresponding to right (RA) and left atrial (LA) wavefront propagation, may be unequally modified. Five-minute lead II recordings before and after the first-ever CA of 40 parox-ysmal AF patients were analyzed and P-wave features were calculated: PWDon-off of the entire P-wave and each P-wave part (RA:PWDon-peak, LA:PWDpeak-off) and the time from P-wave onset or offset to the R-peak (PWDon-R and PWDoff-R, respectively). Heart-rate (HR) adjustment (HRA) mitigated the HR fluctuations. Prelpost-CA comparison was performed with Mann-Whitney U-test and median values were calculated. Pearson's correlation was calculated between PWD and the remaining features. The effect of CA with (Δ: -17.96%) or without HRA (Δ: -9.84%) was significant at the entire PWDon-off and at the PWDpeak-off(HRA:Δ: -27.77%, no HRA: Δ: -22.03%). PWDon-off showed a stronger correlation with RA than LA(ρmax=0.805 vs ρmax=0.541). P-wave features corresponding to RA are more strongly related to the entire P-wave. Nevertheless, only the P-wave part associated with LA is significantly affected by CA. That being so, studies are encouraged to incorporate part-time P-wave analysis.

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