scholarly journals Central tendency measure and wavelet transform combined in the non-invasive analysis of atrial fibrillation recordings

2012 ◽  
Vol 11 (1) ◽  
pp. 46 ◽  
Author(s):  
Raúl Alcaraz ◽  
José Rieta
Keyword(s):  
Atrial Fibrillation ◽  
Wavelet Transform ◽  
Central Tendency ◽  
Central Tendency Measure ◽  
Non Invasive

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

scholarly journals Predictors of Occult Paroxysmal Atrial Fibrillation in Cryptogenic Strokes Detected by Long-Term Noninvasive Cardiac Monitoring

2011 ◽  
Vol 2011 ◽  
pp. 1-5 ◽  
Author(s):  
Archit Bhatt ◽  
Arshad Majid ◽  
Anmar Razak ◽  
Mounzer Kassab ◽  
Syed Hussain ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Paroxysmal Atrial Fibrillation ◽  
Cryptogenic Stroke ◽  
Cardiac Monitoring ◽  
High Signal ◽  
Detection Rates ◽  
Non Invasive ◽  
Patient Reported ◽  
Premature Beats

Background and Purpose. Paroxysmal Atrial fibrillation/Flutter (PAF) detection rates in cryptogenic strokes have been variable. We sought to determine the percentage of patients with cryptogenic stroke who had PAF on prolonged non-invasive cardiac monitoring.Methods and Results. Sixty-two consecutive patients with stroke and TIA in a single center with a mean age of 61 (+/− 14) years were analyzed. PAF was detected in 15 (24%) patients. Only one patient reported symptoms of shortness of breath during the episode of PAF while on monitoring, and 71 (97%) of these 73 episodes were asymptomatic. A regression analysis revealed that the presence of PVCs (ventricular premature beats) lasting more than 2 minutes (OR 6.3, 95% CI, 1.11–18.92;P=.042) and strokes (high signal on Diffusion Weighted Imaging) (OR 4.3, 95% CI, 5–36.3;P=.041) predicted PAF. Patients with multiple DWI signals were more likely than solitary signals to have PAF (OR 11.1, 95% CI, 2.5–48.5,P<.01).Conclusion. Occult PAF is common in cryptogenic strokes, and is often asymptomatic. Our data suggests that up to one in five patients with suspected cryptogenic strokes and TIAs have PAF, especially if they have PVCs and multiple high DWI signals on MRI.

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