scholarly journals Recent Research for Unobtrusive Atrial Fibrillation Detection Methods Based on Cardiac Dynamics Signals: A Survey

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3814
Author(s):  
Fangfang Jiang ◽  
Yihan Zhou ◽  
Tianyi Ling ◽  
Yanbing Zhang ◽  
Ziyu Zhu
Keyword(s):  
Atrial Fibrillation ◽  
Detection Methods ◽  
Ecg Signals ◽  
Non Invasive ◽  
Cardiac Dynamics ◽  
Feature Extraction And Selection ◽  
Future Work ◽  
Electrocardiogram Ecg ◽  
Term Monitoring

Atrial fibrillation (AF) is the most common cardiac arrhythmia. It tends to cause multiple cardiac conditions, such as cerebral artery blockage, stroke, and heart failure. The morbidity and mortality of AF have been progressively increasing over the past few decades, which has raised widespread concern about unobtrusive AF detection in routine life. The up-to-date non-invasive AF detection methods include electrocardiogram (ECG) signals and cardiac dynamics signals, such as the ballistocardiogram (BCG) signal, the seismocardiogram (SCG) signal and the photoplethysmogram (PPG) signal. Cardiac dynamics signals can be collected by cushions, mattresses, fabrics, or even cameras, which is more suitable for long-term monitoring. Therefore, methods for AF detection by cardiac dynamics signals bring about extensive attention for recent research. This paper reviews the current unobtrusive AF detection methods based on the three cardiac dynamics signals, summarized as data acquisition and preprocessing, feature extraction and selection, classification and diagnosis. In addition, the drawbacks and limitations of the existing methods are analyzed, and the challenges in future work are discussed.

scholarly journals A Wearable Electrocardiogram Telemonitoring System for Atrial Fibrillation Detection

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 606 ◽  
Author(s):  
Minggang Shao ◽  
Zhuhuang Zhou ◽  
Guangyu Bin ◽  
Yanping Bai ◽  
Shuicai Wu
Keyword(s):  
Atrial Fibrillation ◽  
Ecg Monitoring ◽  
Web Browser ◽  
Ecg Signals ◽  
Cloud Server ◽  
Android App ◽  
Electrocardiogram Ecg ◽  
The Web ◽  
Ecg Data

In this paper we proposed a wearable electrocardiogram (ECG) telemonitoring system for atrial fibrillation (AF) detection based on a smartphone and cloud computing. A wearable ECG patch was designed to collect ECG signals and send the signals to an Android smartphone via Bluetooth. An Android APP was developed to display the ECG waveforms in real time and transmit every 30 s ECG data to a remote cloud server. A machine learning (CatBoost)-based ECG classification method was proposed to detect AF in the cloud server. In case of detected AF, the cloud server pushed the ECG data and classification results to the web browser of a doctor. Finally, the Android APP displayed the doctor’s diagnosis for the ECG signals. Experimental results showed the proposed CatBoost classifier trained with 17 selected features achieved an overall F1 score of 0.92 on the test set (n = 7270). The proposed wearable ECG monitoring system may potentially be useful for long-term ECG telemonitoring for AF detection.

scholarly journals Anytime ECG Monitoring through the Use of a Low-Cost, User-Friendly, Wearable Device

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6036
Author(s):  
Vincenzo Randazzo ◽  
Jacopo Ferretti ◽  
Eros Pasero
Keyword(s):  
Atrial Fibrillation ◽  
Low Cost ◽  
Portable Devices ◽  
Cardiac Health ◽  
Non Invasive ◽  
Key Factor ◽  
User Friendly ◽  
Electrocardiogram Ecg

Every year cardiovascular diseases kill the highest number of people worldwide. Among these, pathologies characterized by sporadic symptoms, such as atrial fibrillation, are difficult to be detected as state-of-the-art solutions, e.g., 12-leads electrocardiogram (ECG) or Holter devices, often fail to tackle these kinds of pathologies. Many portable devices have already been proposed, both in literature and in the market. Unfortunately, they all miss relevant features: they are either not wearable or wireless and their usage over a long-term period is often unsuitable. In addition, the quality of recordings is another key factor to perform reliable diagnosis. The ECG WATCH is a device designed for targeting all these issues. It is inexpensive, wearable (size of a watch), and can be used without the need for any medical expertise about positioning or usage. It is non-invasive, it records single-lead ECG in just 10 s, anytime, anywhere, without the need to physically travel to hospitals or cardiologists. It can acquire any of the three peripheral leads; results can be shared with physicians by simply tapping a smartphone app. The ECG WATCH quality has been tested on 30 people and has successfully compared with an electrocardiograph and an ECG simulator, both certified. The app embeds an algorithm for automatically detecting atrial fibrillation, which has been successfully tested with an official ECG simulator on different severity of atrial fibrillation. In this sense, the ECG WATCH is a promising device for anytime cardiac health monitoring.

scholarly journals The experience of using non-invasive long-term ECG monitoring in patients with various cardiac arrhythmias

2021 ◽  
Vol 36 (3) ◽  
pp. 166-172
Author(s):  
E. A. Archakov ◽  
R. E. Batalov ◽  
S. Y. Usenkov ◽  
S. V. Popov
Keyword(s):  
Atrial Fibrillation ◽  
Cardiac Arrhythmias ◽  
Ecg Monitoring ◽  
Non Invasive ◽  
Electrocardiogram Ecg ◽  
Clinical Cases

The article describes clinical cases demonstrating the advantages of non-invasive long-term electrocardiogram (ECG) monitoring allowing to detect asymptomatic atrial fibrillation (AF) and transient atrioventricular (AV) and sinoatrial (SA) blocks.

scholarly journals Advanced P Wave Detection in Ecg Signals During Pathology: Evaluation in Different Arrhythmia Contexts

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Lucie Maršánová ◽  
Andrea Němcová ◽  
Radovan Smíšek ◽  
Martin Vítek ◽  
Lukáš Smital
Keyword(s):  
Automated Analysis ◽  
P Wave ◽  
Algorithm Performance ◽  
Ecg Signals ◽  
Wave Detection ◽  
Pathological Conditions ◽  
Novel Method ◽  
Electrocardiogram Ecg ◽  
Term Monitoring

AbstractReliable P wave detection is necessary for accurate and automatic electrocardiogram (ECG) analysis. Currently, methods for P wave detection in physiological conditions are well-described and efficient. However, methods for P wave detection during pathology are not generally found in the literature, or their performance is insufficient. This work introduces a novel method, based on a phasor transform, as well as innovative rules that improve P wave detection during pathology. These rules are based on the extraction of a heartbeats’ morphological features and knowledge of heart manifestation during both physiological and pathological conditions. To properly evaluate the performance of the proposed algorithm in pathological conditions, a standard database with a sufficient number of reference P wave positions is needed. However, such a database did not exist. Thus, ECG experts annotated 12 chosen pathological records from the MIT-BIH Arrhythmia Database. These annotations are publicly available via Physionet. The algorithm performance was also validated using physiological records from the MIT-BIH Arrhythmia and QT databases. The results for physiological signals were Se = 98.42% and PP = 99.98%, which is comparable to other methods. For pathological signals, the proposed method reached Se = 96.40% and PP = 85.84%, which greatly outperforms other methods. This improvement represents a huge step towards fully automated analysis systems being respected by ECG experts. These systems are necessary, particularly in the area of long-term monitoring.

scholarly journals Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elisa Mejía-Mejía ◽  
James M. May ◽  
Mohamed Elgendi ◽  
Panayiotis A. Kyriacou
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Pulse Transit Time ◽  
Pulse Rate Variability ◽  
Physiological Factors ◽  
Ecg Signals ◽  
Non Invasive ◽  
Electrocardiogram Ecg

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

First clinical experience with the wearable cardiac rhythm long-term monitoring cardioskin device

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
P Guedeney ◽  
J Silvain ◽  
F Hidden-Lucet ◽  
C Maupain ◽  
S Dinanian ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Clinical Practice ◽  
Cardiac Rhythm ◽  
Cardiac Monitoring ◽  
Funding Source ◽  
Single Center ◽  
Long Term Monitoring ◽  
Monitoring Devices ◽  
Term Monitoring

Abstract Background There are only limited options for long-term cardiac monitoring devices readily available in clinical practice for outpatients. Holter monitoring devices are limited by the uncomfort of wires and patches, the small number of leads for analysis, the quality of recordings or the monitoring duration while insertable cardiac monitors are costly and exposed to potential local complication. Purpose To describe a single center experience with a novel wearable device for cardiac rhythm monitoring. Methods The Cardioskin™ system is a patch-free, wire-free, wearable device with rechargeable batteries that provides a high quality 15-lead electrocardiogram monitoring over 1 month (Figure 1). Data are sent using a mobile application downloaded in the patient smartphone to a central Corelab where they can be interpreted by an expert and/or the prescribing physician. An alarm signal is readily available within the Cardioskin™ device, to allow patients to indicate the presence of symptoms. In this single center retrospective registry, we provide a first report of the use of this novel device in real world practice, with indication and duration of cardiac monitoring left at the physicans “discretion”. Results From January 2019 to December 2019, the Cardioskin™ system was prescribed in 60 patients for an overall median duration of 26.5 (14–32) days. The mean age of the patients was 45±12.2 years and 24 (40%) were male. Indications for cardiac monitoring were post-Stroke, palpitation, syncope and cardiomyopathy assessment in 56%, 30%, 7% and 7% of the cases, respectively. A sustained (>30 seconds) supraventricular tachycardia was detected in 4 cases, including one case of atrial fibrillation, two case of atrial tachycardia and on case of junctional tachycardia. Unsustained ventricular tachycardia and atrial fibrillation burst were detected in another 2 cases (Figure 1). There was no reported case of skin irritation by the Cardioskin™ system or abrupt interruption of the monitoring by the patients. Conclusion The Cardioskin™ system is a novel, discreet and comfortable cardiac rhythm wearable long-term monitoring device which can be used in clinical practice for broad diagnostic indications. Figure 1. Cardioskin system Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): ACTION coeur

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.

scholarly journals Atrial Fibrillation in Hypertrophic Cardiomyopathy

2021 ◽  
Vol 11 (3) ◽  
pp. 173-185
Author(s):  
G. A. Ignatenko ◽  
G. G. Taradin ◽  
N. T. Vatutin ◽  
A. A. Kaluga ◽  
Yu. D. Kostyamin
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Radiofrequency Ablation ◽  
Hypertrophic Cardiomyopathy ◽  
Sinus Rhythm ◽  
Antiarrhythmic Drugs ◽  
Contemporary Literature ◽  
Clinical Manifestations ◽  
Detection Methods

The current information about features of atrial fibrillation in patients with hypertrophic cardiomyopathy is presented in this review. The data about prevalence, pathogenesis and its various complications in these patients are disclosed. The article contains updated clinical recommendations of authoritative medical societies on the discussing problem. There is detailed discussion of risk factors of atrial fibrillation onset in setting of hypertrophic cardiomyopathy with demonstration of results of different studies concerning to investigation of relationship between risk factors and probability of the arrhythmia development. There is description of detection methods, clinical manifestations, and the course of atrial fibrillation in patients with hypertrophic cardiomyopathy. The contemporary literature data are presented regarding to the management of patients with atrial fibrillation with use of anticoagulants, antiarrhythmic drugs, indications for performing of radiofrequency ablation and results of studies concerning long-term efficacy of such procedure are demonstrated. The discussion on the management of the patients in cases of sinus rhythm restoration or maintenance failure is described.

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