Review of noise removal techniques in ECG signals
An electrocardiogram (ECG) records the electrical signal from the heart to check for different
heart conditions, but it is susceptible to noises. ECG signal denoising is a major pre …
heart conditions, but it is susceptible to noises. ECG signal denoising is a major pre …
[HTML][HTML] Comprehensive survey of computational ECG analysis: Databases, methods and applications
E Merdjanovska, A Rashkovska - Expert Systems with Applications, 2022 - Elsevier
Electrocardiogram (ECG) recordings are indicative for the state of the human heart.
Automatic analysis of these recordings can be performed using various computational …
Automatic analysis of these recordings can be performed using various computational …
Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction
V Sundararaj - International Journal of Biomedical …, 2019 - inderscienceonline.com
Electrocardiogram (ECG) signal is significant to diagnose cardiac arrhythmia among various
biological signals. The accurate analysis of noisy electrocardiographic (ECG) signal is a …
biological signals. The accurate analysis of noisy electrocardiographic (ECG) signal is a …
[HTML][HTML] ECG-based heartbeat classification for arrhythmia detection: A survey
An electrocardiogram (ECG) measures the electric activity of the heart and has been widely
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …
Electrocardiogram soft computing using hybrid deep learning CNN-ELM
S Zhou, B Tan - Applied Soft Computing, 2020 - Elsevier
Electrocardiogram (ECG) can reflect the state of human heart and is widely used in clinical
cardiac examination. However, the electrocardiogram signal is very weak, the anti …
cardiac examination. However, the electrocardiogram signal is very weak, the anti …
[PDF][PDF] An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm
V Sundararaj - Int J Intell Eng Syst, 2016 - inass.org
Electrocardiographic (ECG) signal is significant to diagnose cardiac arrhythmia among
various biological signals. The accurate analysis of noisy Electrocardiographic (ECG) signal …
various biological signals. The accurate analysis of noisy Electrocardiographic (ECG) signal …
A comprehensive survey on ECG signals as new biometric modality for human authentication: Recent advances and future challenges
AN Uwaechia, DA Ramli - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) has extremely discriminative characteristics in the biometric field
and has recently received significant interest as a promising biometric trait. However, ECG …
and has recently received significant interest as a promising biometric trait. However, ECG …
Deep learning approach to cardiovascular disease classification employing modified ECG signal from empirical mode decomposition
NI Hasan, A Bhattacharjee - Biomedical signal processing and control, 2019 - Elsevier
Multiple cardiovascular disease classification from Electrocardiogram (ECG) signal is
necessary for efficient and fast remedial treatment of the patient. This paper presents a …
necessary for efficient and fast remedial treatment of the patient. This paper presents a …
An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks
S Poungponsri, XH Yu - Neurocomputing, 2013 - Elsevier
Electrocardiogram (ECG) signals have been widely used in clinical studies to detect heart
diseases. However, ECG signals are often contaminated with noise such as baseline drift …
diseases. However, ECG signals are often contaminated with noise such as baseline drift …
Inter-patient ECG classification with symbolic representations and multi-perspective convolutional neural networks
This paper presents a novel deep learning framework for the inter-patient electrocardiogram
(ECG) heartbeat classification. A symbolization approach especially designed for ECG is …
(ECG) heartbeat classification. A symbolization approach especially designed for ECG is …