A Cloud-Based Machine Learning Approach to Reduce Noise in ECG Arrhythmias for Smart Healthcare Services
ECG (electrocardiogram) identifies and traces targets and is commonly employed in cardiac disease detection. It is necessary for monitoring precise target trajectories. Estimations of ECG are nonlinear as the parameters TDEs (time delays) and Doppler shifts are computed on receipt of echoes where EK...
Main Authors: | Alsanie, W.F (Author), Altamirano, G.C (Author), Asakipaam, S.A (Author), Gago, D.O (Author), Jain, P. (Author), Rizwan, A. (Author), Sandoval Núñez, R.A (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
NLM (Medline)
2022
|
Online Access: | View Fulltext in Publisher |
Similar Items
-
Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition
by: Kang-Ming Chang
Published: (2010-06-01) -
One-Dimensional CNN Approach for ECG Arrhythmia Analysis in Fog-Cloud Environments
by: Omar Cheikhrouhou, et al.
Published: (2021-01-01) -
Arrhythmia Evaluation in Wearable ECG Devices
by: Muammar Sadrawi, et al.
Published: (2017-10-01) -
Minor ECG Change and Fatal Arrhythmias
by: Yoshifusa Aizawa, MD
Published: (2009-01-01) -
The ECG features detection and arrhythmia classification system
by: Shao-Yung Yen, et al.
Published: (2007)