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Träfflista för sökning "WFRF:(Sörnmo Leif) srt2:(2020-2024)"

Sökning: WFRF:(Sörnmo Leif) > (2020-2024)

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1.
  • Halvaei, Hesam, et al. (författare)
  • False Alarm Reduction in Atrial Fibrillation Screening
  • 2021
  • Ingår i: 2020 Computing in Cardiology. - 9781728111056 - 9781728173825
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • Early detection of AF is essential and emphasizes the significance of AF screening. However, AF detection in screening ECGs, usually recorded by handheld and portable devices, is limited because of their high susceptibility to noise. In this study, the feasibility of applying a machine learning-based quality control stage, inserted between the QRS detector and AF detector blocks, is investigated with the aim to improve AF detection. A convolutional neural network was trained to classify the detections into either true or false. False detections were excluded and an updated series of QRS complexes was fed to the AF detector. The results show that the convolutional neural network-based quality control reduces the number of false alarms by 24.8% at the cost of 1.9% decrease in sensitivity compared to AF detection without any quality control.
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2.
  • Halvaei, Hesam, et al. (författare)
  • Identification of Transient Noise to Reduce False Detections in Screening for Atrial Fibrillation
  • 2021
  • Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 12
  • Tidskriftsartikel (refereegranskat)abstract
    • Screening for atrial fibrillation (AF) with a handheld device for recording the ECG is becoming increasingly popular. The poorer signal quality of such ECGs may lead to false detection of AF, often caused by transient noise. Consequently, the need for expert review in AF screening can become extensive. A convolutional neural network (CNN) is proposed for transient noise identification in AF detection. The network is trained using the events produced by a QRS detector, classified into either true beat detections or false detections. The CNN and a low-complexity AF detector are trained and tested using the StrokeStop I database, containing 30-s ECGs from mass screening for AF in the elderly population. Performance evaluation of the CNN-based quality control using a subset of the database resulted in sensitivity, specificity, and accuracy of 96.4, 96.9, and 96.9%, respectively. By inserting the CNN before the AF detector, the false AF detections were reduced by 22.5% without any loss in sensitivity. The results show that the number of recordings calling for expert review can be significantly reduced thanks to the identification of transient noise. The reduction of false AF detections is directly linked to the time and cost spent on expert review.
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3.
  • Halvaei, Hesam, et al. (författare)
  • Signal quality assessment of a novel ecg electrode for motion artifact reduction
  • 2021
  • Ingår i: Sensors. - : MDPI AG. - 1424-8220. ; 21:16
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: The presence of noise is problematic in the analysis and interpretation of the ECG, especially in ambulatory monitoring. Restricting the analysis to high-quality signal segments only comes with the risk of excluding significant arrhythmia episodes. Therefore, the development of novel electrode technology, robust to noise, continues to be warranted. Methods: The signal quality of a novel wet ECG electrode (Piotrode) is assessed and compared to a commercially available, commonly used electrode (Ambu). The assessment involves indices of QRS detection and atrial fibrillation detection performance, as well as signal quality indices (ensemble standard deviation and time–frequency repeatability), computed from ECGs recorded simultaneously from 20 healthy subjects performing everyday activities. Results: The QRS detection performance using the Piotrode was considerably better than when using the Ambu, especially for running but also for lighter activities. The two signal quality indices demonstrated similar trends: the gap in quality became increasingly larger as the subjects became increasingly more active. Conclusions: The novel wet ECG electrode produces signals with less motion artifacts, thereby offering the potential to reduce the review burden, and accordingly the cost, associated with ambulatory monitoring.
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4.
  • Henriksson, Mikael, et al. (författare)
  • Short-term reproducibility of parameters characterizing atrial fibrillatory waves
  • 2020
  • Ingår i: Computers in Biology and Medicine. - : Elsevier BV. - 0010-4825. ; 117
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: To study reproducibility of f-wave parameters in terms of inter- and intrapatient variation. Approach: Five parameters are investigated: dominant atrial frequency (DAF), f-wave amplitude, phase dispersion, spectral organization, and spatiotemporal variability. For each parameter, the variance ratio R, defined as the ratio between inter- and intrapatient variance, is computed; a larger R corresponds to better stability and reproducibility. The study population consists of 20 high-quality ECGs recorded from patients with atrial fibrillation (11/9 paroxysmal/persistent). Main results: The well-established parameters DAF and f-wave amplitude were associated with considerably larger R-values (13.1 and 21.0, respectively) than phase dispersion (2.4), spectral organization (2.4), andspatiotemporal variability (2.7). The use of an adaptive harmonic frequency tracker to estimate the DAF resulted in a larger R (13.1) than did block-based maximum likelihood estimation (6.3). Significance: This study demonstrates a noticeable difference in reproducibility among f-wave parameters, a resultwhich should be taken into account when performing f-wave analysis.
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5.
  • Holmer, Mattias, et al. (författare)
  • Detection of Needle Dislodgement Using Extracorporeal Pressure Signals : A Feasibility Study
  • 2020
  • Ingår i: ASAIO Journal. - 1538-943X. ; 66:4, s. 454-462
  • Tidskriftsartikel (refereegranskat)abstract
    • Venous needle dislodgement (VND) during dialysis is a rarely occurring adverse event, which becomes life-threatening if not handled promptly. Because the standard venous pressure alarm, implemented in most dialysis machines, has low sensitivity, a novel approach using extracted cardiac information to detect needle dislodgement is proposed. Four features are extracted from the arterial and venous pressure signals of the dialysis machine, characterizing the mean venous pressure, the venous cardiac pulse pressure, the time delay, and the correlation between the two pressure signals. The features serve as input to a support vector machine (SVM), which determines whether dislodgement has occurred. The SVM is first trained on a set of laboratory data, and then tested on another set of laboratory data as well as on a small data set from clinical hemodialysis sessions. The results show that dislodgement can be detected after 12-17 s, corresponding to 24-143 ml blood loss. The standard venous pressure alarm used in clinical routine only detects 50% of the VNDs, whereas the novel method detects all VNDs and has a false alarm rate of 0.12 per hour, provided that the amplitude of the extracted cardiac pressure signal exceeds 1 mmHg. The results are promising; however, the method needs to be tested on a larger set of clinical data to better establish its performance.
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6.
  • Isasi, Iraia, et al. (författare)
  • Restoration of the electrocardiogram during mechanical cardiopulmonary resuscitation
  • 2020
  • Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 41:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: An artefact-free electrocardiogram (ECG) is essential during cardiac arrest to decide therapy such as defibrillation. Mechanical cardiopulmonary resuscitation (CPR) devices cause movement artefacts that alter the ECG. This study analyzes the effectiveness of mechanical CPR artefact suppression filters to restore clinically relevant ECG information. Approach: In total, 495 10 s ECGs were used, of which 165 were in ventricular fibrillation (VF), 165 in organized rhythms (OR) and 165 contained mechanical CPR artefacts recorded during asystole. CPR artefacts and rhythms were mixed at controlled signal-to-noise ratios (SNRs), ranging from –20 dB to 10 dB. Mechanical artefacts were removed using least mean squares (LMS), recursive least squares (RLS) and Kalman filters. Performance was evaluated by comparing the clean and the restored ECGs in terms of restored SNR, correlation-based similarity measures, and clinically relevant features: QRS detection performance for OR, and dominant frequency, mean amplitude and waveform irregularity for VF. For each filter, a shock/no-shock support vector machine algorithm based on multiresolution analysis of the restored ECG was designed, and evaluated in terms of sensitivity (Se) and specificity (Sp). Main results: The RLS filter produced the largest correlation coefficient (0.80), the largest average increase in SNR (9.5 dB), and the best QRS detection performance. The LMS filter best restored VF with errors of 10.3% in dominant frequency, 18.1% in amplitude and 11.8% in waveform irregularity. The Se/Sp of the diagnosis of the restored ECG were 95.1/94.5% using the RLS filter and 97.0/91.4% using the LMS filter. Significance: Suitable filter configurations to restore ECG waveforms during mechanical CPR have been determined, allowing reliable clinical decisions without interrupting mechanical CPR therapy.
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7.
  • Johnson, Linda S., et al. (författare)
  • Can 24 h of ambulatory ECG be used to triage patients to extended monitoring?
  • 2023
  • Ingår i: Annals of Noninvasive Electrocardiology. - 1082-720X. ; 28:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Access to long-term ambulatory recording to detect atrial fibrillation (AF) is limited for economical and practical reasons. We aimed to determine whether 24 h ECG (24hECG) data can predict AF detection on extended cardiac monitoring. Methods: We included all US patients from 2020, aged 17–100 years, who were monitored for 2–30 days using the PocketECG device (MEDICALgorithmics), without AF ≥30 s on the first day (n = 18,220, mean age 64.4 years, 42.4% male). The population was randomly split into equal training and testing datasets. A Lasso model was used to predict AF episodes ≥30 s occurring on days 2–30. Results: The final model included maximum heart rate, number of premature atrial complexes (PACs), fastest rate during PAC couplets and triplets, fastest rate during premature ventricular couplets and number of ventricular tachycardia runs ≥4 beats, and had good discrimination (ROC statistic 0.7497, 95% CI 0.7336–0.7659) in the testing dataset. Inclusion of age and sex did not improve discrimination. A model based only on age and sex had substantially poorer discrimination, ROC statistic 0.6542 (95% CI 0.6364–0.6720). The prevalence of observed AF in the testing dataset increased by quintile of predicted risk: 0.4% in Q1, 2.7% in Q2, 6.2% in Q3, 11.4% in Q4, and 15.9% in Q5. In Q1, the negative predictive value for AF was 99.6%. Conclusion: By using 24hECG data, long-term monitoring for AF can safely be avoided in 20% of an unselected patient population whereas an overall risk of 9% in the remaining 80% of the population warrants repeated or extended monitoring.
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8.
  • Lázaro, Jesús, et al. (författare)
  • ECG-Derived Respiratory Rate in Atrial Fibrillation
  • 2020
  • Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 67:3, s. 905-914
  • 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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9.
  • Mihandoost, Sara, et al. (författare)
  • A comparative study of the performance of methods for f-wave extraction
  • 2022
  • Ingår i: Physiological Measurement. - : IOP Publishing. - 0967-3334 .- 1361-6579. ; 43:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective. This study proposes a novel technique for atrial fibrillatory waves (f-waves) extraction and investigates the performance of the proposed method comparing with different f-wave extraction methods. Approach. We propose a novel technique combining a periodic component analysis (PiCA) and echo state network (ESN) for f-waves extraction, denoted PiCA-ESN. PiCA-ESN benefits from the advantages of using both source separation and nonlinear adaptive filtering. PiCA-ESN is evaluated by comparing with other state-of-the-art approaches, which include template subtraction technique based on principal component analysis, spatiotemporal cancellation, nonlinear adaptive filtering using an echo state neural network, and a source separation technique based on PiCA. Quality assessment is performed on a recently published reference database including a large number of simulated ECG signals in atrial fibrillation (AF). The performance of the f-wave extraction methods is evaluated in terms of signal quality metrics (SNR, ΔSNR) and robustness of f-wave features. Main results. The proposed method offers the best signal quality performance, with a ΔSNR of approximately 22 dB across all 8 sets of the reference database, as well as the most robust extraction of f-wave features, with 75% of all estimates of dominant atrial frequency well below 1 Hz.
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10.
  • Pluščiauskaitė, Vilma, et al. (författare)
  • An objective approach to identifying individual atrial fibrillation triggers : A simulation study
  • 2024
  • Ingår i: Biomedical Signal Processing and Control. - 1746-8094. ; 87
  • Tidskriftsartikel (refereegranskat)abstract
    • Background and Objective: Growing evidence shows that certain acute exposures, especially alcohol, may trigger episodes of paroxysmal atrial fibrillation (AF). However, there is a lack of methods for assessing the relation between triggers and AF episodes in individual patients. The present paper proposes an approach to identifying AF triggers based on the assumption that the post-trigger AF burden is larger than the pre-trigger AF burden during the analysis time interval. Method: For the purpose of identification, a measure of relational strength between pre- and post-trigger burden is introduced, accounting for the cumulative effect of the triggers contained in the observation interval. The proposed approach is explored for different types of AF episode pattern, generated using the alternating, bivariate Hawkes model, whose conditional intensity function is designed to account for the effect of alcohol. In total, 7200 different AF patterns were generated for different numbers of AF triggers and alcohol units. Results: The simulation study demonstrates that, depending on the pattern type, the relational strength increases 3–6 times with alcohol consumption in comparison with no consumption. Conclusions: The proposed approach to identifying triggers in individual patients with paroxysmal AF should facilitate the implementation of longitudinal studies for the objective assessment of trigger effect on AF occurrence.
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