Improved sparse low-rank model via periodic overlapping group shrinkage and truncated nuclear norm for rolling bearing fault diagnosis

Q Zhang, X Li, H Mao, Z Huang, Y Xiao… - Measurement …, 2023 - iopscience.iop.org
The early faults of rolling bearings are the common causes of rotating machinery failures.
Rolling bearings with local faults usually generate periodic shocks during operation, but the …

Machine learning based electrocardiogram peaks analyzer for Wolff-Parkinson-White syndrome

MA Merbouti, D Cherifi - Biomedical Signal Processing and Control, 2023 - Elsevier
The slurred upstroke named Delta in an Electrocardiogram (ECG) signal is known as the
main indicator of the existence of the Wolff-Parkinson-White (WPW) pattern. Previous studies …

Elicitation of fetal ECG from abdominal recordings using Blind Source Separation techniques and Robust Set Membership Affine Projection algorithm for signal quality …

S Diwan, M Sahu, V Bhateja - Computers in Biology and Medicine, 2024 - Elsevier
Background: The utilization of non-invasive techniques for fetal cardiac health surveillance
is pivotal in evaluating fetal well-being throughout the gestational period. This process …

Aircraft engine remaining useful life prediction: A comparison study of Kernel Adaptive Filtering architectures

GD Karatzinis, YS Boutalis… - Mechanical Systems and …, 2024 - Elsevier
Abstract Predicting the Remaining Useful Life (RUL) of mechanical systems poses
significant challenges in Prognostics and Health Management (PHM), impacting safety and …

Identification and classification of epileptic EEG signals using invertible constant-Q transform-based deep convolutional neural network

AS Eltrass, MB Tayel, AF El-Qady - Journal of Neural Engineering, 2022 - iopscience.iop.org
Context. Epilepsy is the most widespread disorder of the nervous system, affecting humans
of all ages and races. The most common diagnostic test in epilepsy is the …

A robust ECG signal enhancement technique through optimally designed adaptive filters

MR Alla, C Nayak - Biomedical Signal Processing and Control, 2024 - Elsevier
Electrocardiogram (ECG) signals are widely used in medical diagnostics to analyze the
electrical activity of the heart. However, in clinical practice, these signals are often …

Cardiac arrhythmias detection framework based on higher-order spectral distribution with deep learning

S Karthikeyani, S Sasipriya, M Ramkumar - Biomedical Signal Processing …, 2024 - Elsevier
In this article, a new framework for arrhythmia identification using higher-order spectral
distributions and deep learning approaches has been proposed. The input signal is first pre …

Discriminative Subspace Learning With Adaptive Graph Regularization

Z Huang, S Zhao, Z Liang, J Wu - The Computer Journal, 2024 - academic.oup.com
Many subspace learning methods based on low-rank representation employ the nearest
neighborhood graph to preserve the local structure. However, in these methods, the nearest …

基于改进ICEEMDAN 的肌电干扰去除算法.

李国权, 朱双青, 黄正文, 庞宇 - Journal of Chongqing …, 2023 - search.ebscohost.com
肌电干扰使心电信号产生细小波纹ꎬ 频率分布范围宽广ꎬ 严重影响心电图的准确性ꎬ
不利于病情诊断ꎮ 针对心电信号中肌电干扰去除效果不好的问题ꎬ 提出基于改进的自适应噪声 …

Two Stage Step-Size Adaptive Filter Design for ECG Denoising

S Sasikala, P Sivaranjani, T Meeradevi… - 2024 15th …, 2024 - ieeexplore.ieee.org
An adaptive filter is a system that includes a linear filter with a converter controlled by input
variables and the ability to change those parameters using an optimization technique. In the …