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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 …
Wearable and Implantable Cortisol‐Sensing Electronics for Stress Monitoring
Cortisol is a steroid hormone that is released from the body in response to stress. Although a
moderate level of cortisol secretion can help the body maintain homeostasis, excessive …
moderate level of cortisol secretion can help the body maintain homeostasis, excessive …
Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network
F Zhu, F Ye, Y Fu, Q Liu, B Shen - Scientific reports, 2019 - nature.com
Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are
used to help diagnose heart disease by recording the heart's activity. However, automated …
used to help diagnose heart disease by recording the heart's activity. However, automated …
An open source benchmarked toolbox for cardiovascular waveform and interval analysis
Objective: This work aims to validate a set of data processing methods for variability metrics,
which hold promise as potential indicators for autonomic function, prediction of adverse …
which hold promise as potential indicators for autonomic function, prediction of adverse …
Deep learning models for electrocardiograms are susceptible to adversarial attack
Electrocardiogram (ECG) acquisition is increasingly widespread in medical and commercial
devices, necessitating the development of automated interpretation strategies. Recently …
devices, necessitating the development of automated interpretation strategies. Recently …
ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization
Objective. Cardiovascular diseases are a major cause of mortality globally, and
electrocardiograms (ECGs) are crucial for diagnosing them. Traditionally, ECGs are stored …
electrocardiograms (ECGs) are crucial for diagnosing them. Traditionally, ECGs are stored …
SLC-GAN: An automated myocardial infarction detection model based on generative adversarial networks and convolutional neural networks with single-lead …
Electrocardiography (ECG) is a sophisticated tool for the diagnosis of myocardial infarction
(MI). Deep learning approaches can support MI diagnosis based on ECG data. However …
(MI). Deep learning approaches can support MI diagnosis based on ECG data. However …
Analysis and applications of respiratory surface EMG: report of a round table meeting
AH Jonkman, RSP Warnaar, W Baccinelli, NM Carbon… - Critical care, 2024 - Springer
Surface electromyography (sEMG) can be used to measure the electrical activity of the
respiratory muscles. The possible applications of sEMG span from patients suffering from …
respiratory muscles. The possible applications of sEMG span from patients suffering from …
ECG pattern analysis for emotion detection
F Agrafioti, D Hatzinakos… - IEEE Transactions on …, 2011 - ieeexplore.ieee.org
Emotion modeling and recognition has drawn extensive attention from disciplines such as
psychology, cognitive science, and, lately, engineering. Although a significant amount of …
psychology, cognitive science, and, lately, engineering. Although a significant amount of …