Research Progress of ECG Monitoring Equipment and Algorithms Based on Polymer Materials

Research Progress of ECG Monitoring Equipment and Algorithms Based on Polymer Materials

Heart diseases such as myocardial ischemia (MI) are the main causes of human death. The prediction of MI and arrhythmia is an effective method for the early detection, diagnosis, and treatment of heart disease. For the rapid detection of arrhythmia and myocardial ischemia, the electrocardiogram (ECG...

Full description

Bibliographic Details
Main Authors:	Lvheng Zhang, Jihong Liu
Format:	Article
Language:	English
Published:	MDPI AG 2021-10-01
Series:	Micromachines
Subjects:	arrhythmias polymer materials deep learning electrocardiogram generative adversarial networks myocardial ischemia
Online Access:	https://www.mdpi.com/2072-666X/12/11/1282

Similar Items

An Ominous ECG
by: Danqiong Zhu, MD, et al.
Published: (2023-10-01)

ProEGAN-MS: A Progressive Growing Generative Adversarial Networks for Electrocardiogram Generation
by: Haixu Yang, et al.
Published: (2021-01-01)

Evaluation of 12-lead electrocardiogram at 0.55T for improved cardiac monitoring in magnetic resonance imaging
by: Aravindan Kolandaivelu, et al.
Published: (2024-01-01)

Deep Learning Autoencoder Study on ECG Signals
by: Dandi Mochamad Reza, et al.
Published: (2023-12-01)

ECG analysis of ventricular fibrillation dynamics reflects ischaemic progression subject to variability in patient anatomy and electrode location
by: Hector Martinez-Navarro, et al.
Published: (2024-11-01)

Development and Validation of a Real-Time Service Model for Noise Removal and Arrhythmia Classification Using Electrocardiogram Signals
by: Yeonjae Park, et al.
Published: (2024-08-01)

Validation of Adhesive Single-Lead ECG Device Compared with Holter Monitoring among Non-Atrial Fibrillation Patients
by: Soonil Kwon, et al.
Published: (2021-04-01)

Classifying Cardiac Arrhythmia from ECG Signal Using 1D CNN Deep Learning Model
by: Adel A. Ahmed, et al.
Published: (2023-01-01)

CardioGPT: An ECG Interpretation Generation Model
by: Guohua Fu, et al.
Published: (2024-01-01)

An Innovative Approach for the Prediction of Future Arrhythmia through T-wave Alternans on Surface Electrocardiogram (ECG)
by: Ali Farhan, et al.
Published: (2023-12-01)

ECG Recurrence Plot-Based Arrhythmia Classification Using Two-Dimensional Deep Residual CNN Features
by: Bhekumuzi M. Mathunjwa, et al.
Published: (2022-02-01)

Detection of multi-class arrhythmia using heuristic and deep neural network on edge device
by: Arief Kurniawan, et al.
Published: (2023-11-01)

Computer Modeling of the Heart for ECG Interpretation—A Review
by: Olaf Dössel, et al.
Published: (2021-07-01)

ECG Arrhythmias Detection Using Auxiliary Classifier Generative Adversarial Network and Residual Network
by: Pu Wang, et al.
Published: (2019-01-01)

Electrocardiography in the Supraventricular cardiac arrythmias
by: Claudia Liliana Sanabria Peña, et al.
Published: (1998-08-01)

Analysis of the Prevalence of Ventricular Late Potentials in the Late Phase of Myocardial Infarction Based on the Site of Infarction
by: P. R. Benchimol-Barbosa, et al.
Published: (2002-04-01)

A novel method of swin transformer with time-frequency characteristics for ECG-based arrhythmia detection
by: Siyuan Chen, et al.
Published: (2024-06-01)

An interpretable electrocardiogram-based model for predicting arrhythmia and ischemia in cardiovascular disease
by: Tanjila Alam Sathi, et al.
Published: (2024-12-01)

IMPLEMENTATION OF AN ARTIFICIAL INTELLIGENCE-BASED ECG ACQUISITION SYSTEM FOR THE DETECTION OF CARDIAC ABNORMALITIES
by: Achraf Benba, et al.
Published: (2023-03-01)

ECG – implantable loop recorder
by: Sok-Sithikun Bun, et al.
Published: (2021-09-01)

A GENERATIVE MODEL FOR DEEP FAKE AUGMENTATION OF PHONOCARDIOGRAM AND ELECTROCARDIOGRAM SIGNALS USING LSGAN AND CYCLE GAN
by: Swarajya Madhuri Rayavarapu, et al.
Published: (2023-12-01)

Efficient Learning of Healthcare Data from IoT Devices by Edge Convolution Neural Networks
by: Yan He, et al.
Published: (2020-12-01)

LDCNN: A new arrhythmia detection technique with ECG signals using a linear deep convolutional neural network
by: Ali Bayani, et al.
Published: (2024-09-01)

The impact of hospital-based cardiac rehabilitation on signal average ECG parameters of the heart after myocardial infarction
by: Mohammadvahid Jorat, et al.
Published: (2015-01-01)

Complementary Photoplethysmogram Synthesis From Electrocardiogram Using Generative Adversarial Network
by: Heean Shin, et al.
Published: (2021-01-01)

ECG Arrhythmia Classification based on Convolutional Autoencoders and Transfer Learning
by: Rasool Muayad Obaidi, et al.
Published: (2022-09-01)

Standard ECG in Brugada Syndrome as a Marker of Prognosis: From Risk Stratification to Pathophysiological Insights
by: Francesco Vitali, et al.
Published: (2021-05-01)

Does hypoglycemia cause cardiovascular events?
by: Sandeep Chopra, et al.
Published: (2012-01-01)

Effect of different doses of oxytocin on cardiac electrophysiology and arrhythmias induced by ischemia
by: Fariba Houshmand, et al.
Published: (2017-01-01)

A Hybrid Deep CNN Model for Abnormal Arrhythmia Detection Based on Cardiac ECG Signal
by: Amin Ullah, et al.
Published: (2021-02-01)

New ECG Algorithm for the Prediction of Culprit Vessel in Acute Myocardial Infarction Involving Lateral Part of the Ventricle: Ilkay Classification
by: Sarıçam E, et al.
Published: (2023-06-01)

Fetal Arrhythmia Detection Based on Labeling Considering Heartbeat Interval
by: Sara Nakatani, et al.
Published: (2022-12-01)

Ambulatory Smartwatch ECG Monitoring among Patients Undergoing Transcatheter Aortic Valve Replacement Early after Discharge: An Observational Study
by: Yi Zhang, et al.
Published: (2023-01-01)

ECG Wave-Maven: Self-Assessment Program for Students and Clinicians (Out of Print)
by: Ary Goldberger
Published: (2006-06-01)

The ECG Characteristics of Patients With Isolated Hypomagnesemia
by: Yiheng Yang, et al.
Published: (2021-01-01)

A Review of Shockable Arrhythmia Detection of ECG Signals Using Machine and Deep Learning Techniques
by: Kavya Lakkakula, et al.
Published: (2024-09-01)

Synthesis of Multimodal Cardiological Signals Using a Conditional Wasserstein Generative Adversarial Network
by: Ioana Cretu, et al.
Published: (2024-01-01)

Comparing Classical Machine Learning and Deep Learning for Classification of Arrhythmia from ECG Signals
by: Marija Bikova, et al.
Published: (2023-11-01)

The effects of ATP-dependent potassium channel opener; pinacidil, and blocker; glibenclamide, on the ischemia induced arrhythmia in partial and complete ligation of coronary artery in rats
by: Selçuk Yaşar, et al.
Published: (2015-02-01)

Deep Learning-Based ECG Arrhythmia Classification: A Systematic Review
by: Qiao Xiao, et al.
Published: (2023-04-01)