| 1. |
- Bacevicius, Justinas, et al.
(författare)
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Six-lead electrocardiography compared to single-lead electrocardiography and photoplethysmography of a wrist-worn device for atrial fibrillation detection controlled by premature atrial or ventricular contractions : six is smarter than one
- 2023
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Ingår i: Frontiers in Cardiovascular Medicine. - 2297-055X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: Smartwatches are commonly capable to record a lead-I-like electrocardiogram (ECG) and perform a photoplethysmography (PPG)-based atrial fibrillation (AF) detection. Wearable technologies repeatedly face the challenge of frequent premature beats, particularly in target populations for screening of AF. Objective: To investigate the potential diagnostic benefit of six-lead ECG compared to single-lead ECG and PPG-based algorithm for AF detection of the wrist-worn device. Methods and results: From the database of DoubleCheck-AF 249 adults were enrolled in AF group (n = 121) or control group of SR with frequent premature ventricular (PVCs) or atrial (PACs) contractions (n = 128). Cardiac rhythm was monitored using a wrist-worn device capable of recording continuous PPG and simultaneous intermittent six-lead standard-limb-like ECG. To display a single-lead ECG, the six-lead ECGs were trimmed to lead-I-like ECGs. Two diagnosis-blinded cardiologists evaluated reference, six-lead and single-lead ECGs as “AF”, “SR”, or “Cannot be concluded”. AF detection based on six-lead ECG, single-lead ECG, and PPG yielded a sensitivity of 99.2%, 95.7%, and 94.2%, respectively. The higher number of premature beats per minute was associated with false positive outcomes of single-lead ECG (18.80 vs. 5.40 beats/min, P < 0.01), six-lead ECG (64.3 vs. 5.8 beats/min, P = 0.018), and PPG-based detector (13.20 vs. 5.60 beats/min, P = 0.05). Single-lead ECG required 3.4 times fewer extrasystoles than six-lead ECG to result in a false positive outcome. In a control subgroup of PACs, the specificity of six-lead ECG, single-lead ECG, and PPG dropped to 95%, 83.8%, and 90%, respectively. The diagnostic value of single-lead ECG (AUC 0.898) was inferior to six-lead ECG (AUC 0.971) and PPG-based detector (AUC 0.921). In a control subgroup of PVCs, the specificity of six-lead ECG, single-lead ECG, and PPG was 100%, 96.4%, and 96.6%, respectively. The diagnostic value of single-lead ECG (AUC 0.961) was inferior to six-lead ECG (AUC 0.996) and non-inferior to PPG-based detector (AUC 0.954). Conclusions: A six-lead wearable-recorded ECG demonstrated the superior diagnostic value of AF detection compared to a single-lead ECG and PPG-based AF detection. The risk of type I error due to the widespread use of smartwatch-enabled single-lead ECGs in populations with frequent premature beats is significant.
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| 2. |
- Bachi, Lorenzo, et al.
(författare)
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ECG Modeling for Simulation of Arrhythmias in Time-Varying Conditions
- 2023
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Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 70:12, s. 3449-3460
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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.
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| 3. |
- Butkuviene, Monika, et al.
(författare)
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Atrial Fibrillation Episode Patterns and Their Influence on Detection Performance
- 2021
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Ingår i: 2021 Computing in Cardiology, CinC 2021. - 2325-887X .- 2325-8861. - 9781665479165 ; 2021-September
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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.
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| 4. |
- Butkuviene, Monika, et al.
(författare)
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Characterization of Atrial Fibrillation Episode Patterns : A Comparative Study
- 2024
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Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 71:1, s. 106-113
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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.
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| 5. |
- Butkuviene, Monika, et al.
(författare)
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Considerations on Performance Evaluation of Atrial Fibrillation Detectors
- 2021
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Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 68:11, s. 3250-3260
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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.
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| 6. |
- Henriksson, Mikael, et al.
(författare)
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Model-based Assessment of f-Wave Signal Quality in Patients with Atrial Fibrillation
- 2018
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Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 65:11, s. 2600-2611
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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.
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| 7. |
- Henriksson, Mikael, et al.
(författare)
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Modeling and Estimation of Temporal Episode Patterns in Paroxysmal Atrial Fibrillation
- 2021
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Ingår i: IEEE Transactions on Biomedical Engineering. - 0018-9294. ; 68:1, s. 319-329
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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.
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| 8. |
- Henriksson, Mikael, et al.
(författare)
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Signal quality assessment of f-waves in atrial fibrillation
- 2017
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Ingår i: 2017 Computing in Cardiology (CinC). - 2325-8861. - 9781538645550 - 9781538666302
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Konferensbidrag (refereegranskat)abstract
- Ambulatory ECG recordings are frequently corrupted by artifacts caused by, e.g., muscle activity or moving electrodes, which complicates the analysis of f-waves and motivates signal quality assessment to improve the reliability of f-wave analysis. Although many methods have been developed for assessing the quality of ECG signals in general, no method deals specifically with f-waves. This study proposes a novel signal quality index (SQI), using a modelbased approach for assessment of f-wave signal quality. To evaluate the performance of the SQI, 189 5-s recordings of f-waves from AF patients are studied, as is the same number of recordings with motion artifacts and electrode movements taken from the MIT-BIH Noise Stress Test Database. The signal quality index is capable of discriminating between f-waves and noisy recordings with an accuracy of 98%. The results suggest that the proposed signal quality index correctly identifies noisy recordings, and can be used to improve the reliability of f-wave analysis.
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| 9. |
- Janusauskas, Arturas, et al.
(författare)
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Detection of Hearing Loss in Audiological Frequencies from Transient Evoked Otoacoustic Emissions
- 2010
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Ingår i: Informatica. - 0868-4952. ; 21:2, s. 191-204
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Tidskriftsartikel (refereegranskat)abstract
- Transient evoked otoacoustic emissions (TEOAEs) have been analyzed for objective assessment of hearing function and monitoring of the influence of noise exposure and ototoxic drugs. This paper presents a novel application of the Hilbert-Huang transform (HHT) for detection and time-frequency mapping of TEOAEs. Since the HHT does not distinguish between signal and noise, it is combined with ensemble correlation in order to extract signal information in intervals with correlated activity. High resolution time-frequency mapping could predict 30 dB(HL), or higher hearing loss, at different audiological frequencies in 63-90% of the cases and normal hearing in 75-90% of the cases. The proposed method offers TEOAE time-frequency mapping by constraining the analysis to regions with high signal-to-noise ratios. The results suggest that the HI-IT is suitable for hearing loss detection at individual frequencies and characterization of the fine structures of TEOAEs.
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| 10. |
- Kontaxis, Spyridon, et al.
(författare)
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Investigating Respiratory Rate Estimation during Paroxysmal Atrial Fibrillation Using an Improved ECG Simulation Model
- 2020
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Ingår i: 2020 Computing in Cardiology, CinC 2020. - 2325-887X .- 2325-8861. - 9781728173825 ; 2020-September
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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.
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