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Real-time Atrial Fibrillation Detection Using Artificial Neural Network on a Wearable Electrocardiogram

Aulia A. Iskandar, Klaus Schilling
2019 ICONIET PROCEEDING  
An embedded device worn on the chest can be used to perform a real-time data acquisition and processing of the electrocardiogram, that consists of a 1-lead ECG, an ARM processor, a Bluetooth module, an  ...  We are able to perform a pre-diagnosis of atrial fibrillation, that is one of the common arrhythmias, from 41 recorded training samples (Physionet MIT/BIH AFDB and NSRDB) and 6 healthy subjects as test  ...  Acknowledgement The author would like to thank all the subject's ECG data that was used in this research.  ... 
doi:10.33555/iconiet.v2i3.26 fatcat:rlk3cvnokrflde5h46degvhe3i

Automated real-time atrial fibrillation detection on a wearable wireless sensor platform

F. Rincon, P. R. Grassi, N. Khaled, D. Atienza, D. Sciuto
2012 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
raw signal to a central coordinator (e.g., smartphone or laptop) for its ulterior processing.  ...  This paper presents an automated real-time atrial fibrillation (AF) detection approach that relies on the observation of two characteristic irregularities of AF episodes in the electrocardiogram (ECG)  ...  REAL-TIME EMBEDDED AF DETECTION Our target WBSN node is the Shimmer TM [8] , a small, lowpower commercial wireless sensor platform for noninvasive biomedical research.  ... 
doi:10.1109/embc.2012.6346465 pmid:23366426 dblp:conf/embc/RinconGKAS12 fatcat:mmb23icrijaubf33anzajr7nke

Mobile and E-Healthcare: Recent Trends and Future Directions

Rahul K Kher
2016 Journal of Health & Medical Economics  
In the past decade, wearable sensors and devices have evolved as key technological objects which have dramatically revolutionized the next generation healthcare solutions.  ...  Ambulatory and long-term health monitoring for elderly people is another aspect, particularly for countries like China and Japan where population aging is increasing.  ...  [60] have proposed an intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation.  ... 
doi:10.21767/2471-9927.100010 fatcat:qoil33b42vgsnffhuu3hhbog3a

Ambulatory Health Monitoring System Using Wireless Sensors Node

Mohamed Fezari, Rachad Rasras, Ibrahiem M. M. El Emary
2015 Procedia Computer Science  
It can also be used to control patients or athletic person over a long period. The system reads, stores and analyses the heart beat rate signals, body temperature repetitively in real-time.  ...  The paper focus on: how we implemented algorithms to analyze heart beat rate signals in real-time, how to fusion data of different sensors mainly here temperature and blood pressure and to transmit the  ...  Acknowledgments We are grateful to members of laboratory of automatic and signals (LASA) at Annaba University for their contribution in the development of this work. And some colleagues from KAU  ... 
doi:10.1016/j.procs.2015.09.082 fatcat:c2pdrk6rvjaytp6kehjf2unkaa

Photoplethysmography based atrial fibrillation detection: a review

Tania Pereira, Nate Tran, Kais Gadhoumi, Michele M. Pelter, Duc H. Do, Randall J. Lee, Rene Colorado, Karl Meisel, Xiao Hu
2020 npj Digital Medicine  
Atrial fibrillation (AF) is a cardiac rhythm disorder associated with increased morbidity and mortality.  ...  A thorough account of the signal processing, machine learning, and deep learning approaches used in these studies is presented, followed by a discussion of their limitations and challenges towards clinical  ...  INTRODUCTION Atrial fibrillation (AF) is an abnormal cardiac rhythm characterized by a disorganized atrial activity.  ... 
doi:10.1038/s41746-019-0207-9 pmid:31934647 pmcid:PMC6954115 fatcat:zaqjc27navgsdpfgqj5b3cyk6i

Wearable Intelligent System for the Diagnosis of Cardiac Diseases Working in Real Time and with Low Energy Cost

Olga Valenzuela, Beatriz Prieto, Elvira Delgado-Marquez, Hector Pomares, Ignacio Rojas
2018 Proceedings (MDPI)  
In this paper we used samples of electrocardiograms of MIT-related database with ten types of pathologies and a rate corresponding to normal (healthy patient), which are processed and used for extraction  ...  The electrocardiogram is an important source of information for identifying these conditions, therefore, becomes necessary to seek an advanced system of diagnosis based on these signals.  ...  of physical activity of a patient (therefore working in real time) using sensors and advanced processing, as a wearable system.  ... 
doi:10.3390/proceedings2190513 fatcat:zxsqv7e6lzgjjnjprolwx4sjyu

Deep learning-based ambient assisted living for self-management of cardiovascular conditions

Maria Ahmed Qureshi, Kashif Naseer Qureshi, Gwanggil Jeon, Francesco Piccialli
2021 Neural computing & applications (Print)  
For each theme, a detailed investigation shows (1) how these new technologies are nowadays integrated into diagnostic systems and (2) how new technologies like IoT sensors, cloud models, machine and deep  ...  Preferred reporting items for systematic reviews and meta-analyses technique are used to answer the research questions.  ...  [48] focused on the use of wearable home-based monitoring devices for the earlier detection of cardiovascular episodes such as atrial fibrillation to provide opportunities for effective and economical  ... 
doi:10.1007/s00521-020-05678-w fatcat:fkabjm33xza2ncgq6ecu2qifaq

An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks

Jaime A. Rincon, Solanye Guerra-Ojeda, Carlos Carrascosa, Vicente Julian
2020 Sensors  
Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms.  ...  The performance of the proposed system is evaluated on a dataset of 8.528 short single-lead ECG records using two merge MobileNet networks that classify data with an accuracy of 90% for atrial fibrillation  ...  The sensor nodes monitor and analyse the ECG signals to efficiently process the data of the cardiac patients, however the response time of the LCHM is longer which reduces the performance.  ... 
doi:10.3390/s20247353 pmid:33371514 fatcat:tz4eae22sngadhvtvc7edl2vy4

Windows Into Human Health Through Wearables Data Analytics

Daniel Witt, Ryan Kellogg, Michael Snyder, Jessilyn Dunn
2019 Current Opinion in Biomedical Engineering  
Wearable sensors (wearables) have been commonly integrated into a wide variety of commercial products and are increasingly being used to collect and process raw physiological parameters into salient digital  ...  Much of the current and future utility of wearables lies in the signal processing steps and algorithms used to analyze large volumes of data.  ...  [113] Approaching fall detection using wearable sensors has often proven to be most practical for real-world applications and less prone to signal error. [34] Özdemir et al. studied falls with six wearable  ... 
doi:10.1016/j.cobme.2019.01.001 pmid:31832566 pmcid:PMC6907085 fatcat:jjwpn77kz5dynmy4ydqvbehfsu

A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis

A. Pantelopoulos, N.G. Bourbakis
2010 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
An emphasis is given to multiparameter physiological sensing system designs, providing reliable vital signs measurements and incorporating real-time decision support for early detection of symptoms or  ...  These systems can comprise various types of small physiological sensors, transmission modules and processing capabilities, and can thus facilitate low-cost wearable unobtrusive solutions for continuous  ...  identify atrial fibrillation episodes and atrial and ventricular ectopic beats.  ... 
doi:10.1109/tsmcc.2009.2032660 fatcat:t4vbxxar55bxfogn7fjz6aq36i

Ultra-Low Power Design of Wearable Cardiac Monitoring Systems

Rubén Braojos, Hossein Mamaghanian, Alair Dias Junior, Giovanni Ansaloni, David Atienza, Francisco J. Rincón, Srinivasan Murali
2014 Proceedings of the The 51st Annual Design Automation Conference on Design Automation Conference - DAC '14  
This paper presents the system-level architecture of novel ultra-low power wireless body sensor nodes (WBSNs) for real-time cardiac monitoring and analysis, and discusses the main design challenges of  ...  This wearable system allows a wide range of applications, including multi-lead ECG arrhythmia detection and autonomous sleep monitoring for critical scenarios, such as monitoring of the sleep state of  ...  In addition, similar results have been obtained for applications performing a diagnosis at a higher level of abstraction, such as Atrial Fibrillation (AF) detection [25] .  ... 
doi:10.1145/2593069.2596691 dblp:conf/dac/BraojosMJAARM14 fatcat:zdqq2o7nljfvhojjiwx6cpqc2e

Ultra-low power design of wearable cardiac monitoring systems

Ruben Braojos, Hossein Mamaghanian, Alair Dias, Giovanni Ansaloni, David Atienza, Francisco J. Rincon, Srinivasan Murali
2014 2014 51st ACM/EDAC/IEEE Design Automation Conference (DAC)  
This paper presents the system-level architecture of novel ultra-low power wireless body sensor nodes (WBSNs) for real-time cardiac monitoring and analysis, and discusses the main design challenges of  ...  This wearable system allows a wide range of applications, including multi-lead ECG arrhythmia detection and autonomous sleep monitoring for critical scenarios, such as monitoring of the sleep state of  ...  In addition, similar results have been obtained for applications performing a diagnosis at a higher level of abstraction, such as Atrial Fibrillation (AF) detection [25] .  ... 
doi:10.1109/dac.2014.6881344 fatcat:lkcvwv537fdirkv3yevfob247q

A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications

Jin-Woo Jeong, Woochan Lee, Young-Joon Kim
2021 Sensors  
This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring.  ...  In this paper, we present a wireless physiological signal acquisition device and a smartphone-based software platform for real-time data processing and monitor and cloud server access for everyday ECG/  ...  In this study, a wearable continuous ECG and EMG monitoring system for real-time detection is proposed.  ... 
doi:10.3390/s22010104 pmid:35009644 pmcid:PMC8747365 fatcat:czgr4couevenppy5mpi6svs42m

An Open-Access Arrhythmia Database of Wearable Electrocardiogram

Qin Shen, Hongxiang Gao, Yuwen Li, Qi Sun, Minglong Chen, Jianqing Li, Chengyu Liu
2020 Journal of Medical and Biological Engineering  
Therefore, a database for arrhythmia detection was planned to construct.  ...  Methods Collaborating with hospital, this study presents a bipolar limb two-lead wearable device by collecting a large amount of real-time data and giving rise to readily available ECG databases.  ...  Therefore, wearable real-time ECG for long-term monitoring has potential to be the most useful non-invasive device for assessing cardiac health.  ... 
doi:10.1007/s40846-020-00554-3 fatcat:olgdm272anfzzja2yl56dvu6su

DeepBeat: A multi-task deep learning approach to assess signal quality and arrhythmia detection in wearable devices [article]

Jessica Torres Soto, Euan Ashley
2020 arXiv   pre-print
Here, we develop a multi-task deep learning method to assess signal quality and arrhythmia event detection in wearable photoplethysmography devices for real-time detection of atrial fibrillation (AF).  ...  In conclusion, though a combination of simulation and transfer learning and we develop and apply a multitask architecture to the problem of AF detection from wearable wrist sensors demonstrating high levels  ...  JTS, and EAA drafted and critically revised the manuscript for important intellectual content.  ... 
arXiv:2001.00155v2 fatcat:72t3hchzunbt5jvzemgaw6sfe4
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