Accurate wavelet thresholding method for ECG signals
K Yu, L Feng, Y Chen, M Wu, Y Zhang, P Zhu… - Computers in Biology …, 2024 - Elsevier
Current wavelet thresholding methods for cardiogram signals captured by flexible wearable
sensors face a challenge in achieving both accurate thresholding and real-time signal …
sensors face a challenge in achieving both accurate thresholding and real-time signal …
ECG-based heartbeat classification using exponential-political optimizer trained deep learning for arrhythmia detection
An electrocardiogram (ECG) computes the electrical functioning of the heart, which is mostly
employed for finding various heart diseases of its feasibility and simplicity. Moreover, some …
employed for finding various heart diseases of its feasibility and simplicity. Moreover, some …
[HTML][HTML] Preprocessing and Denoising Techniques for Electrocardiography and Magnetocardiography: A Review
Y Jia, H Pei, J Liang, Y Zhou, Y Yang, Y Cui… - …, 2024 - pmc.ncbi.nlm.nih.gov
This review systematically analyzes the latest advancements in preprocessing techniques
for Electrocardiography (ECG) and Magnetocardiography (MCG) signals over the past …
for Electrocardiography (ECG) and Magnetocardiography (MCG) signals over the past …
RL-ECGNet: resource-aware multi-class detection of arrhythmia through reinforcement learning
Arrhythmia is a fatal cardiac clinical condition that risks the lives of millions every year. It has
multiple classes with variable prevalence rates. Some rare arrhythmia classes are equally …
multiple classes with variable prevalence rates. Some rare arrhythmia classes are equally …
[HTML][HTML] RLS adaptive filter co-design for de-noising ECG signal
Doctors diagnose various heart muscle disorders by continuously analyzing
ELECTROCARDIOGRAM (ECG) signals. Obtaining a noise-free ECG recording is difficult …
ELECTROCARDIOGRAM (ECG) signals. Obtaining a noise-free ECG recording is difficult …
A robust wavelet domain multi-scale texture descriptor for image classification
X Wang, L Feng, D Wang, P Niu - Expert Systems with Applications, 2025 - Elsevier
Local binary pattern (LBP) and many variants adopt the difference information to encode all
the neighborhood binarization, demonstrating excellent ability to distinguish images …
the neighborhood binarization, demonstrating excellent ability to distinguish images …
Transformer-based framework for multi-class segmentation of skin cancer from histopathology images
Introduction Non-melanoma skin cancer comprising Basal cell carcinoma (BCC), Squamous
cell carcinoma (SCC), and Intraepidermal carcinoma (IEC) has the highest incidence rate …
cell carcinoma (SCC), and Intraepidermal carcinoma (IEC) has the highest incidence rate …
Automatic detection of electrodermal activity events during sleep
Currently, there is significant interest in develo** algorithms for processing electrodermal
activity (EDA) signals recorded during sleep. The interest is driven by the growing popularity …
activity (EDA) signals recorded during sleep. The interest is driven by the growing popularity …
[PDF][PDF] A novel approach for denoising ECG signals corrupted with white gaussian noise using wavelet packet transform and soft-thresholding
The electrocardiogram (ECG) is a vital tool for detecting heart abnormalities, However, noise
frequently disrupts the signals during recording, reducing diagnostic precision. During …
frequently disrupts the signals during recording, reducing diagnostic precision. During …
Time series classification for portable medical devices
INTRODUCTION: With the continuous progress of the medical Internet of Things, intelligent
medical wearable devices are also gradually mature. Among them, medical wearable …
medical wearable devices are also gradually mature. Among them, medical wearable …