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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 …
A survey on ECG analysis
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 …
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
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 …
management and early warning of the urban water environment. Modeling-based detection …
ECG arrhythmia classification using STFT-based spectrogram and convolutional neural network
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 …
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
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 …
analysis, are the most widely used type of recurrent neural networks (RNNs) architecture …
A movable unshielded magnetocardiography system
Magnetocardiography (MCG), which uses high-sensitivity magnetometers to record
magnetic field signals generated by electrical activity in the heart, is a noninvasive method …
magnetic field signals generated by electrical activity in the heart, is a noninvasive method …
Noise reduction in ECG signals using fully convolutional denoising autoencoders
The electrocardiogram (ECG) is an efficient and noninvasive indicator for arrhythmia
detection and prevention. In real-world scenarios, ECG signals are prone to be …
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
Biometric authentication technology has become increasingly common in our daily lives as
information protection and control regulation requirements have grown worldwide. A …
information protection and control regulation requirements have grown worldwide. A …
Machine learning approach to detect cardiac arrhythmias in ECG signals: A survey
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 …
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
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 …