scholarly journals A Wavelet-Based Method for Non-Invasive Dominant Frequency Detection in Atrial Fibrillation

2020 ◽  
Author(s):  
Victor Gonçalves Marques ◽  
Miguel Rodrigo ◽  
Maria de la Salud Guillem Sánchez ◽  
João Salinet
Keyword(s):  
Atrial Fibrillation ◽  
Dominant Frequency ◽  
Non Invasive ◽  
Frequency Detection

scholarly journals Systematic differences of non-invasive dominant frequency estimation compared to invasive dominant frequency estimation in atrial fibrillation

2019 ◽  
Vol 104 ◽  
pp. 299-309 ◽  
Author(s):  
Frederique J. Vanheusden ◽  
Gavin S. Chu ◽  
Xin Li ◽  
João Salinet ◽  
Tiago P. Almeida ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Frequency Estimation ◽  
Dominant Frequency ◽  
Non Invasive

scholarly journals Non-invasive Spatial Mapping of Frequencies in Atrial Fibrillation: Correlation With Contact Mapping

2021 ◽  
Vol 11 ◽  
Author(s):  
Miguel Rodrigo ◽  
Kian Waddell ◽  
Sarah Magee ◽  
Albert J. Rogers ◽  
Mahmood Alhusseini ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Dominant Frequency ◽  
Electrocardiographic Imaging ◽  
Distribution Maps ◽  
Contact Mapping ◽  
Non Invasive ◽  
Df Analysis ◽  
Ablation Success ◽  
Atrial Activation ◽  
Activation Rates

Introduction: Regional differences in activation rates may contribute to the electrical substrates that maintain atrial fibrillation (AF), and estimating them non-invasively may help guide ablation or select anti-arrhythmic medications. We tested whether non-invasive assessment of regional AF rate accurately represents intracardiac recordings.Methods: In 47 patients with AF (27 persistent, age 63 ± 13 years) we performed 57-lead non-invasive Electrocardiographic Imaging (ECGI) in AF, simultaneously with 64-pole intracardiac signals of both atria. ECGI was reconstructed by Tikhonov regularization. We constructed personalized 3D AF rate distribution maps by Dominant Frequency (DF) analysis from intracardiac and non-invasive recordings.Results: Raw intracardiac and non-invasive DF differed substantially, by 0.54 Hz [0.13 – 1.37] across bi-atrial regions (R2 = 0.11). Filtering by high spectral organization reduced this difference to 0.10 Hz (cycle length difference of 1 – 11 ms) [0.03 – 0.42] for patient-level comparisons (R2 = 0.62), and 0.19 Hz [0.03 – 0.59] and 0.20 Hz [0.04 – 0.61] for median and highest DF, respectively. Non-invasive and highest DF predicted acute ablation success (p = 0.04).Conclusion: Non-invasive estimation of atrial activation rates is feasible and, when filtered by high spectral organization, provide a moderate estimate of intracardiac recording rates in AF. Non-invasive technology could be an effective tool to identify patients who may respond to AF ablation for personalized therapy.

Reliable detection of atrial fibrillation with a medical wearable under inpatient conditions (CoMMoD-A-fib)

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Jacobsen ◽  
T.A Dembek ◽  
A.P Ziakos ◽  
G Kobbe ◽  
M Kollmann ◽  
...  
Keyword(s):  
Neural Network ◽  
Atrial Fibrillation ◽  
Deep Neural Network ◽  
Sampling Rate ◽  
Public Institution ◽  
Funding Source ◽  
Upper Arm ◽  
Recording Time ◽  
Reduced Ejection Fraction ◽  
Non Invasive

Abstract Background Atrial fibrillation (A-fib) is the most common arrhythmia; however, detection of A-fib is a challenge due to irregular occurrence. Purpose Evaluating feasibility and performance of a non-invasive medical wearable for detection of A-fib. Methods In the CoMMoD-A-fib trial admitted patients with a high risk for A-fib carried the wearable and an ECG Holter (control) in parallel over a period of 24 hours under not physically restricted conditions. The wearable with a tight-fit upper arm band employs a photoplethysmography (PPG) technology enabling a high sampling rate. Different algorithms (including a deep neural network) were applied to 5 min PPG datasets for detection of A-fib. Proportion of monitoring time automatically interpretable by algorithms (= interpretable time) was analyzed for influencing factors. Results In 102 inpatients (age 71.0±11.9 years; 52% male) 2306 hours of parallel recording time could be obtained; 1781 hours (77.2%) of these were automatically interpretable by an algorithm analyzing PPG derived intervals. Detection of A-Fib was possible with a sensitivity of 92.7% and specificity of 92.4% (AUC 0.96). Also during physical activity, detection of A-fib was sufficiently possible (sensitivity 90.1% and specificity 91.2%). Usage of the deep neural network improved detection of A-fib further (sensitivity 95.4% and specificity 96.2%). A higher prevalence of heart failure with reduced ejection fraction was observed in patients with a low interpretable time (p=0.080). Conclusion Detection of A-fib by means of an upper arm non-invasive medical wearable with a high resolution is reliably possible under inpatient conditions. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Internal grant program (PhD and Dr. rer. nat. Program Biomedicine) of the Faculty of Health at Witten/Herdecke University, Germany. HELIOS Kliniken GmbH (Grant-ID 047476), Germany

scholarly journals NON-INVASIVE TRACKING OF ATRIAL FIBRILLATION PREDICTS ACUTE TERMINATION BY ABLATION

2021 ◽  
Vol 77 (18) ◽  
pp. 280
Author(s):  
Miguel Rodrigo ◽  
Tina Baykaner ◽  
Wouter-Jan Rappel ◽  
Sanjiv Narayan
Keyword(s):  
Atrial Fibrillation ◽  
Non Invasive

scholarly journals Non-invasive mid-term ECG monitoring for the detection of atrial fibrillation in an outpatient population

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J Cai ◽  
K.K Yeo ◽  
P Wong ◽  
C.K Ching
Keyword(s):  
Atrial Fibrillation ◽  
Public Institution ◽  
First Episode ◽  
Prior History ◽  
Funding Source ◽  
Monitoring Device ◽  
Ecg Monitoring ◽  
Non Invasive ◽  
Increased Risk ◽  
The Mean

Abstract Background Atrial fibrillation (AF) is a common arrhythmia with significant morbidity due to an increased risk of ischemic stroke. Outpatient electrocardiogram (ECG) monitoring is an integral part of the diagnosis of AF. Conventional 24 hour Holter monitoring can be cumbersome and often fails to diagnose patients with paroxysmal AF. Spyder ECG is a non-invasive ECG monitoring device that allows wireless transmission of ECG information for analysis. It is small and comfortable, allowing for easy application for the screening and detection of AF over a mid-term duration. Purpose This study aims to evaluate the incidence of AF in patients with no prior AF and CHADsVASC score of at least 1 with the use of the Spyder ECG mid-term ECG monitoring device. Methods Patients aged 21 to 85 years old with no prior history of AF and CHADsVASC score of at least 1 were recruited from outpatient clinics of 3 large tertiary hospitals in Singapore from December 2016 to April 2019. Patients wore the Spyder ECG device for up to 2 weeks, during which continuous ECG information was uploaded onto a central cloud database and analysed. Results There were 363 patients recruited. The mean age was 61±10.0 years and 65.1% were male. There were 80.3% Chinese, 11.6% Malay, 7.5% Indian and 20.6% of other races. 68.3% of the patients were non-smokers and 74.0% of them were non-alcohol drinkers. The mean BMI of 25.5±4.7 kg/m2. The patient population had significant co-morbidities. 76.3% of the patients had hypertension, 69.4% of them had hyperlipidemia and 40.5% of them had diabetes mellitus. 10.0% of them had congestive cardiac failure and 56.7% had ischaemic heart disease. 11.3% of patients had a previous stroke and 20.4% had a prior myocardial infarction. 7.8% of the patients had asthma, 5.8% of them had thyroid disease and 9.9% of them had chronic kidney disease. They were monitored for a mean of 5.4±2.9 days each. There were 15 (4.1%) patients in whom AF was detected. The patients with AF wore the device for a mean of 5.7±2.0 SD days. The mean burden of AF was 9.0% of monitored time. 46.7% of the patients with AF had detection of AF on the first day, 26.7% on the second day, 13.3% on the third day and 13.3% on the seventh day. The mean duration of the first episode of AF was 251±325 minutes. 7 out of 15 (46.7%) of patients had first episodes of AF lasting less than 10 minutes. Conclusion Continuous mid-term ECG monitoring was able to detect AF in 15 (4.1%) of a population of 363 patients with no prior AF and CHADsVASC score of at least one, monitored for a mean of 5.4 days. Most episodes (53.3%) of AF were detected after the first day of ECG monitoring. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Duke-NUS Medical School Singapore

Abstract 14839: High-resolution Spatiotemporal Changes in Dominant Frequency and Structural Organization During Persistent Atrial Fibrillation

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Terrence Pong ◽  
Joy Aparicio Valenzuela ◽  
Kevin J Cyr ◽  
Cody Carlton ◽  
Sasank Sakhamuri ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
High Resolution ◽  
Structural Organization ◽  
Porcine Model ◽  
Dominant Frequency ◽  
Patient Specific ◽  
Structural Remodeling ◽  
Atrial Activity ◽  
Spatiotemporal Changes ◽  
Mapping Arrays

Introduction: Spatiotemporal differences in atrial activity are thought to contribute to the maintenance of atrial fibrillation (AF). While recent evidence has identified changes in dominant frequency (DF) during the transition from paroxysmal to persistent AF, little is known about the frequency characteristics of the epicardium during this transition. The purpose of this study was to perform high-resolution mapping of the atrial epicardium and to characterize changes in frequency activity and structural organization during the transition from paroxysmal to persistent AF. Hypothesis: In a porcine model of persistent AF, we tested the hypothesis that the epicardium undergoes spatiotemporal changes in atrial activity and structural organization during persistent AF. Methods: Paroxysmal and persistent AF was induced in adult Yorkshire swine by atrial tachypacing. Atrial morphology was segmented from magnetic resonance imaging and high-resolution patient-specific flexible mapping arrays were 3D printed to match the epicardial contours of the atria. Epicardial activation and DF mapping was performed in four paroxysmal and four persistent AF animals using personalized mapping arrays. Histological analysis was performed to determine structural differences between paroxysmal and persistent AF. Results: The left atrial epicardium was associated with a significant increase in DF between paroxysmal and persistent AF (6.5 ± 0.2 vs. 7.4 ± 0.5 Hz, P = 0.03). High-resolution spatiotemporal mapping identified organized clusters of DF during paroxysmal AF which were lost during persistent AF. The development of persistent AF led to structural remodeling with increased atrial epicardial fibrosis. The organization index (OI) significantly decreased during persistent AF in both the left atria (0.3 ± 0.03 vs. 0.2 ± 0.03, P = 0.01) and right atria (0.33 ± 0.04 vs. 0.23 ± 0.02, P = 0.02). Conclusions: In the porcine model of persistent AF, the epicardium undergoes structural remodeling with increased epicardial fibrosis, reflected by changes in atrial organization index and dominant frequency.

Sign in / Sign up

Export Citation Format

Share Document