A Wearable Electrocardiogram Telemonitoring System for Atrial Fibrillation Detection

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.

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

Sensors ◽

10.3390/s21113814 ◽

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.

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

The Siberian Journal of Clinical and Experimental Medicine ◽

10.29001/2073-8552-2021-36-3-166-172 ◽

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.

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Design of Portable Electrocardiograph Monitoring System

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2021.65.3.030403 ◽

2020 ◽

Author(s):

Jia Hua-Ping ◽

Zhao Jun-Long ◽

Liu Jun

Keyword(s):

Real Time ◽

Monitoring System ◽

Data Storage ◽

P Wave ◽

Ecg Monitoring ◽

The Public ◽

Ecg Signals ◽

Early Warning Mechanism ◽

Timely Treatment ◽

Ecg Data

Cardiovascular disease is one of the major diseases that threaten the human health. But the existing electrocardiograph (ECG) monitoring system has many limitations in practical application. In order to monitor ECG in real time, a portable ECG monitoring system based on the Android platform is developed to meet the needs of the public. The system uses BMD101 ECG chip to collect and process ECG signals in the Android system, where data storage and waveform display of ECG data can be realized. The Bluetooth HC-07 module is used for ECG data transmission. The abnormal ECG can be judged by P wave, QRS bandwidth, and RR interval. If abnormal ECG is found, an early warning mechanism will be activated to locate the user’s location in real time and send preset short messages, so that the user can get timely treatment, avoiding dangerous occurrence. The monitoring system is convenient and portable, which brings great convenie to the life of ordinary cardiovascular users.

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Relevance of supraventricular runs detected after cerebral ischemia

Neurology ◽

10.1212/wnl.0000000000004487 ◽

2017 ◽

Vol 89 (15) ◽

pp. 1545-1552 ◽

Cited By ~ 8

Author(s):

Mark Weber-Krüger ◽

Constanze Lutz ◽

Antonia Zapf ◽

Raoul Stahrenberg ◽

Joachim Seegers ◽

...

Keyword(s):

Atrial Fibrillation ◽

Cerebral Ischemia ◽

Ecg Monitoring ◽

Holter Ecg ◽

Acute Cerebral Ischemia ◽

Temporal Phenomenon ◽

Long Term Follow Up ◽

Recurrent Strokes

Objective:Prolonged ECG monitoring after stroke frequently reveals short paroxysmal atrial fibrillation (pAF) and supraventricular (SV) runs. The minimal duration of atrial fibrillation (AF) required to induce cardioembolism, the relevance of SV runs, and whether short pAF results from cerebral damage itself are currently being debated. We aimed to study the relevance of SV runs and short pAF detected by prolonged Holter ECG after cerebral ischemia during long-term follow-up.Methods:Analysis is from the prospective Find-AF trial (ISRCTN46104198). We included patients with acute cerebral ischemia. Those without AF on admission received 7-day Holter ECG monitoring. We differentiated patients with AF on admission (AF-adm), with pAF (>30 seconds), with SV runs (>5 beats but <30 seconds in a 24-hour ECG interval), and without SV runs (controls). During follow-up, those with baseline pAF received another 7-day Holter ECG to examine AF persistence.Results:A total of 254 of 281 initially included patients were analyzed (mean age 70.0 years, 45.3% female). Forty-three (16.9%) had AF-adm. A total of 211 received 7-day Holter ECG monitoring: 27 (12.8%) had pAF, 67 (31.8%) had SV runs, and 117 (55.5%) were controls. During a mean 3.7 years of follow-up, the SV runs group had more recurrent strokes (p = 0.04) and showed numerically more novel AF (12% vs 5%, p = 0.09) than the controls. Seventy-five percent of the patients with manifest pAF detected after cerebral ischemia still had AF during follow-up (50% paroxysmal, 50% persisting/permanent).Conclusions:Patients with cerebral ischemia and SV runs had more recurrent strokes and numerically more novel AF during follow-up and could benefit from further prolonged ECG monitoring. pAF detected after stroke is not a temporal phenomenon.

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Design and Implementation of a Low Cost Wireless Ambulatory ECG Monitoring System for Deployment in Rural Communities

International Journal of Online and Biomedical Engineering (iJOE) ◽

10.3991/ijoe.v15i15.11860 ◽

2019 ◽

Vol 15 (15) ◽

pp. 57

Author(s):

Hassan Ali ◽

Ben Ernest Villaneouva ◽

Raziq Yaqub

Keyword(s):

Rural Communities ◽

Real Time ◽

Monitoring System ◽

Low Cost ◽

Ecg Monitoring ◽

Ecg Signals ◽

Design And Implementation ◽

Ambulatory Ecg ◽

Ambulatory Ecg Monitoring ◽

Ecg Data

Due to the rising number of heart patients and the apparent need for more robust electrocardiogram (ECG) monitoring of these patients, hospitals are increasingly investing in typical cloud technology or centralized hospital server based remote ECG monitoring systems. However, the deployment these systems in rural communities is limited due to the high cost factor. To counter this challenge, in this paper, we focus on the design and implementation of a low cost real time wireless ambulatory ECG monitoring system. The detected ECG signals are first filtered and amplified and then digitally converted by a microcontroller. The digitized ECG signals are then sent over a ZigBee wireless link to a gateway personal computer (PC) at patient’s premises. The received ECG data from the ZigBee connection is displayed in real time via the National Instruments (NI) Laboratory Virtual Instrument Engineering Workbench (LabVIEW) user interface on the PC for instant personalized evaluation of the ECG data. The ECG data can be saved on the PC and sent via email to a remote cardiologist or a clinician. Additionally, the gateway PC at patient’s end acts as web server for sharing patient’s data over the Internet. The remote off-site physician (medical staff in a hospital) can use a web browser on a PC, laptop or a mobile phone with Internet connection to access patient’s real time ECG trace for monitoring, expert review and diagnosis. It is shown that the system prototype allows users to acquire reliable ECG signals effectively and simply. The proposed ambulatory ECG system offers an alternative low cost deployment strategy and is especially suited for remote cardiac monitoring of patients in rural communities.

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Development of Software-as-a-Service Cloud Computing Architecture for Manufacturing Management Systems Based on Virtual COM Port Driver Technology

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.479-480.1023 ◽

2013 ◽

Vol 479-480 ◽

pp. 1023-1026 ◽

Cited By ~ 4

Author(s):

Shang Liang Chen ◽

Hsuan Pei Wang ◽

Yun Yao Chen ◽

Chiang Hsu

Keyword(s):

Information Integration ◽

Manufacturing System ◽

Cloud Manufacturing ◽

Innovative Technology ◽

Cloud Infrastructure ◽

Web Browser ◽

Manufacturing Management ◽

Cloud Server ◽

The Web

This study proposes an innovative technology of Virtual COM Port Driver applied to the SaaS cloud manufacturing system, so that user can only via a web browser to complete all operations of system. Flexibility of the system extensions, and support manufacturing enterprise use other communications equipment at work, for example RFID products, GPS receiver. Information integration, solve each computer to be fitted Middleware to read native components and retrieve information for the inconvenience. This study proposes five-layer model of cloud manufacturing system, and through the virtualization web server to achieve cloud infrastructure layer. In particular, the Virtual Com Port Driver is deployed in the cloud infrastructure layer and middleware layer, and the signal device layer can communicate directly to the cloud infrastructure layer via the web browser. Through a case study, to implement the Virtual COM Port Driver technology to verify the cloud server can capture the local COM port successfully only via the web browser and integrate the information further.

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Anticipating Atrial Fibrillation Signal Using Efficient Algorithm

International Journal of Online and Biomedical Engineering (iJOE) ◽

10.3991/ijoe.v17i02.19183 ◽

2021 ◽

Vol 17 (02) ◽

pp. 106

Author(s):

Mohand Lokman Ahmad Al-dabag ◽

Haider Th. Salim ALRikabi ◽

Raid Rafi Omar Al-Nima

Keyword(s):

Atrial Fibrillation ◽

Computational Cost ◽

Extraction Methods ◽

Support Vector ◽

Ecg Signal ◽

Heart Problem ◽

Ecg Signals ◽

The Right ◽

Electrocardiogram Ecg ◽

Low Computational Cost

One of the common types of arrhythmia is Atrial Fibrillation (AF), it may cause death to patients. Correct diagnosing of heart problem through examining the Electrocardiogram (ECG) signal will lead to prescribe the right treatment for a patient. This study proposes a system that distinguishes between the normal and AF ECG signals. First, this work provides a novel algorithm for segmenting the ECG signal for extracting a single heartbeat. The algorithm utilizes low computational cost techniques to segment the ECG signal. Then, useful pre-processing and feature extraction methods are suggested. Two classifiers, Support Vector Machine (SVM) and Multilayer Perceptron (MLP), are separately used to evaluate the two proposed algorithms. The performance of the last proposed method with the two classifiers (SVM and MLP) show an improvement of about (19% and 17%, respectively) after using the proposed segmentation method so it became 96.2% and 97.5%, respectively.

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

Sensors ◽

10.3390/s21186036 ◽

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.

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A Long-Term, Portable ECG Patch Monitor Based on Flexible Dry Electrode

10.21203/rs.3.rs-1223238/v1 ◽

2022 ◽

Author(s):

Hao Chu ◽

Chenxi Yang ◽

Yantao Xing ◽

Jianqing Li ◽

Chengyu Liu

Keyword(s):

Electrode Impedance ◽

Ecg Monitoring ◽

High Quality ◽

Ecg Signals ◽

Skin Electrode ◽

Rr Interval ◽

Dry Electrodes ◽

Dry Electrode ◽

And Storage

Abstract PurposeLong-term electrocardiogram (ECG) monitoring is an essential approach for the early diagnosis of cardiovascular diseases. Flexible dry electrodes that contains electrolyte without water could be a potential substitution of wet electrodes for long-term ECG monitoring. Therefore, this paper developes a long-term, portable ECG patch based on flexible dry electrodes, namely SEUECG-100.MethodA device consists of analog-front-end acquisition, data acquisition, and storage modules is developed and tested. An impedance test was conducted to compare the skin-electrode impedance of the flexible dry electrode and the Ag/AgCl wet electrode. The ECG signals were simutanously collected from the same subject using the SEUECG-100 and Shimmer device , which were then compared and analyzed from the perspective of ECG morphology, RR interval, and signal quality indices (SQI).ResultsThe experimental results reveal that the flexible dry electrode has the characteristics of low skin-electrode impedance. SEUECG-100 could collect high-quality ECG signals. The ECG signals collected by the two devices have a high RR interval correlation (r=0.999). SQI results show that SEUECG-100 is better than the Shimmer device in overcoming baseline drift. Long-term ECG acquisition and storage experiments show that SEUECG-100 could collect ECG signals with good stability and high reliability.ConclusionThe implementation of the proposed system design with dry electrodes could can effectively record long-term ECG monitoring with high quality in comparison to systems with wet electrodes from both impedance characteristics and signal morphology aspects.

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The Significance of Detective Arrhythmia by Using the Long- Term Ecg Monitoring in the Elderly “so Called” Healthy People: A Screening Study

10.21203/rs.3.rs-1056296/v1 ◽

2021 ◽

Author(s):

Rongsheng Xie ◽

Siting Hong ◽

Guoliang Gao ◽

Jiaoyue Zhong ◽

Lixin Geng ◽

...

Keyword(s):

Atrial Fibrillation ◽

Atrioventricular Block ◽

Previous History ◽

The Elderly ◽

Healthy People ◽

Ecg Monitoring ◽

Adhesive Patch ◽

Screening Study ◽

History Of

Abstract BackgroundArrhythmias are potential harmful diseases to human beings, especially atrial fibrillation and ventricular arrhythmia, for causing serious consequences such as acute stroke or even sudden cardiac death. Recently the screening of asymptomatic atrial fibrillation by using the long-term ECG monitoring has been widely noticed. The study is to evaluate the significance of detective arrhythmia by using the long-term ECG monitoring in the elderly “so called” healthy people who never have the symptoms of palpitation, short breath or deny previous history of arrhythmia.MethodsWe enrolled a screening study of 1056 participants who were the elderly “so called” healthy people and ready to have a healthy examination from three different communities. They all underwent a long-term ECG monitoring（an adhesive patch）to evaluate cardiac arrhythmia. Inclusion criterias were 1) without any symptoms, 2) age ≥55, and 3) denying previous history of arrhythmia. We excluded patients with prior arrhythmias and who carried the patch for less than one day due to various factors. Then we compared the detected arrhythmia events in the first 24 hours and the total wearing time. ResultsOut of 1056 participants (69.8±12.0 years, 620 males), supraventricular tachycardia (SVT) was present in 538 subjects (44% VS 54%, 24 hours VS after 24 hours, P>0.05), atrial fibrillation (AF) was detected in 69 subjects (75% VS 25%, 24 hours VS after 24 hours, P<0.001), second degree type II atrioventricular block/third degree atrioventricular block (AVB) and sinus arrest were detected in 9 subjects(22% VS 78%, 24 hours VS after 24 hours, P<0.001),ventricular tachycardia was detected in 29 subjects (31% VS 69%, 24 hours VS after 24 hours, P<0.001). The adhesive patch monitor detected 32.10%（339/1056）arrhythmia events over the first 24 hours compared with arrhythmia events over the total wearing time of the devices, 61.08%（645/1056）(P<0.001). ConclusionsThe long-term adhesive patch monitor (APM) can improve the diagnosis of conceal arrhythmias which have high risks for life quality and lifespan in the elderly “so called ” healthy people, and the diagnostic advantage in bradycardia and ventricular arrhythmias are more obvious.

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