Applications of machine learning in ambulatory ECG

J Xue, L Yu - Hearts, 2021 - mdpi.com
Simple Summary The ambulatory ECG (AECG) is an important diagnostic tool for many
heart electrophysiology-related cases. This review covers some key Ambulatory ECG …

An effective LSTM recurrent network to detect arrhythmia on imbalanced ECG dataset

J Gao, H Zhang, P Lu, Z Wang - Journal of healthcare …, 2019 - Wiley Online Library
To reduce the high mortality rate from cardiovascular disease (CVD), the electrocardiogram
(ECG) beat plays a significant role in computer‐aided arrhythmia diagnosis systems …

Bias‐Free Cardiac Monitoring Capsule

X Qu, S Cheng, Y Liu, Y Hu, Y Shan, R Luo… - Advanced …, 2024 - Wiley Online Library
Cardiovascular disease (CVD) remains the leading cause of death worldwide. Patients often
fail to recognize the early signs of CVDs, which display irregularities in cardiac contractility …

Machine learning-data mining integrated approach for premature ventricular contraction prediction

Q Mastoi, MS Memon, A Lakhan… - Neural Computing and …, 2021 - Springer
Cardiac arrhythmias impose a significant burden on the healthcare environment due to the
increasing ratio of mortality worldwide. Arrhythmia and abnormal ECG heartbeat are the …

Automatic arrhythmia recognition from electrocardiogram signals using different feature methods with long short-term memory network model

SK Pandey, RR Janghel - Signal, Image and Video Processing, 2020 - Springer
The high mortality rate that has been prevailing among cardiac patients can be reduced to
some extent through early detection of the heart-related diseases which can be done with …

Automatic premature ventricular contraction detection using deep metric learning and KNN

J Yu, X Wang, X Chen, J Guo - Biosensors, 2021 - mdpi.com
Premature ventricular contractions (PVCs), common in the general and patient population,
are irregular heartbeats that indicate potential heart diseases. Clinically, long-term …

Diagnostic validation of smart wearable device embedded with single-lead electrocardiogram for arrhythmia detection

Y Niu, H Wang, H Wang, H Zhang, Z Jin… - Digital Health, 2023 - journals.sagepub.com
Objective To validate a single-lead electrocardiogram algorithm for identifying atrial
fibrillation, atrial premature beats, ventricular premature beats, and sinus rhythm. Methods A …

[PDF][PDF] 基于小波分解和1D-GoogLeNet 的心律失常检测

杨淑莹, 桂彬彬, 陈胜勇 - 电子与信息学报, 2021 - jeit.ac.cn
心电图(ECG) 信号的准确分类对于心脏病的自动诊断非常重要. 为了实现对心律失常的智能分类
, 该文提出一种基于小波分解和1D-GoogLeNet 的精确分类方法. 在该方法中, 利用Db6 …

A fully automatic model for premature ventricular heartbeat arrhythmia classification using the internet of medical things

A Shaikh, MS Al Reshan, A Sulaiman… - … Signal Processing and …, 2023 - Elsevier
Cardiac arrhythmias are one of the leading causes of increased mortality worldwide and
place a heavy burden on the medical environment. Premature ventricular contraction is the …

Heart arrhythmia detection and classification: A comparative study using deep learning models

A Arora, A Taneja, J Hemanth - Iranian Journal of Science and Technology …, 2023 - Springer
The irregular functioning of heartbeats known as “Heart Arrhythmia” may lead to heart
palpitations, blood clots, and even a heart stroke. The ECG test is one of the primary clinical …