Review of noise removal techniques in ECG signals

S Chatterjee, RS Thakur, RN Yadav… - IET Signal …, 2020‏ - Wiley Online Library
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 …

A survey on ECG analysis

SK Berkaya, AK Uysal, ES Gunal, S Ergin… - … Signal Processing and …, 2018‏ - Elsevier
The electrocardiogram (ECG) signal basically corresponds to the electrical activity of the
heart. In the literature, the ECG signal has been analyzed and utilized for various purposes …

Accurate prediction of water quality in urban drainage network with integrated EMD-LSTM model

Y Zhang, C Li, Y Jiang, L Sun, R Zhao, K Yan… - Journal of Cleaner …, 2022‏ - Elsevier
Quickly and accurately gras** the water quality in the drainage network is essential for the
management and early warning of the urban water environment. Modeling-based detection …

ECG arrhythmia classification using STFT-based spectrogram and convolutional neural network

J Huang, B Chen, B Yao, W He - IEEE access, 2019‏ - ieeexplore.ieee.org
The classification of electrocardiogram (ECG) signals is very important for the automatic
diagnosis of heart disease. Traditionally, it is divided into two steps, including the step of …

A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification

Ö Yildirim - Computers in biology and medicine, 2018‏ - Elsevier
Long-short term memory networks (LSTMs), which have recently emerged in sequential data
analysis, are the most widely used type of recurrent neural networks (RNNs) architecture …

A movable unshielded magnetocardiography system

W **ao, C Sun, L Shen, Y Feng, M Liu, Y Wu, X Liu… - Science …, 2023‏ - science.org
Magnetocardiography (MCG), which uses high-sensitivity magnetometers to record
magnetic field signals generated by electrical activity in the heart, is a noninvasive method …

Noise reduction in ECG signals using fully convolutional denoising autoencoders

HT Chiang, YY Hsieh, SW Fu, KH Hung, Y Tsao… - Ieee …, 2019‏ - ieeexplore.ieee.org
The electrocardiogram (ECG) is an efficient and noninvasive indicator for arrhythmia
detection and prevention. In real-world scenarios, ECG signals are prone to be …

BAED: A secured biometric authentication system using ECG signal based on deep learning techniques

AJ Prakash, KK Patro, M Hammad… - Biocybernetics and …, 2022‏ - Elsevier
Biometric authentication technology has become increasingly common in our daily lives as
information protection and control regulation requirements have grown worldwide. A …

Machine learning approach to detect cardiac arrhythmias in ECG signals: A survey

S Sahoo, M Dash, S Behera, S Sabut - Irbm, 2020‏ - Elsevier
Cardiac arrhythmia is a condition when the heart rate is irregular either the beat is too slow
or too fast. It occurs due to improper electrical impulses that coordinates the heart beats …

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 …