BP signal analysis using emerging techniques and its validation using ECG signal

V Gupta, M Mittal, V Mittal, NK Saxena - Sensing and imaging, 2021 - Springer
Monitoring of blood pressure (BP), heart rate (HR), respiratory (RSP),
Photoplethysmography (PPG), and Electrocardiogram (ECG) are generally used for any …

Automatic cardiac arrhythmia classification using combination of deep residual network and bidirectional LSTM

R He, Y Liu, K Wang, N Zhao, Y Yuan, Q Li… - IEEE …, 2019 - ieeexplore.ieee.org
Cardiac arrhythmia is associated with abnormal electrical activities of the heart, which can
be reflected by altered characteristics of electrocardiogram (ECG). Due to the simplicity and …

High-performance personalized heartbeat classification model for long-term ECG signal

P Li, Y Wang, J He, L Wang, Y Tian… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Long-term electrocardiogram (ECG) has become one of the important diagnostic assist
methods in clinical cardiovascular domain. Long-term ECG is primarily used for the …

Perirhinal input to neocortical layer 1 controls learning

G Doron, JN Shin, N Takahashi, M Drüke, C Bocklisch… - Science, 2020 - science.org
INTRODUCTION Arguably one of the biggest mysteries in neuroscience is how the brain
stores long-term memories. Since the 1950s, it has been well established that long-term …

ECG signal enhancement based on improved denoising auto-encoder

P **ong, H Wang, M Liu, S Zhou, Z Hou, X Liu - Engineering Applications of …, 2016 - Elsevier
The electrocardiogram (ECG) is a primary diagnostic tool for examining cardiac tissue and
structures. ECG signals are often contaminated by noise, which can manifest with similar …

Fractional S-transform and its properties: a comprehensive survey

R Ranjan, N **dal, AK Singh - Wireless Personal Communications, 2020 - Springer
In time–frequency analysis, generalization of S-transform (ST) is known as fractional S-
transform. Recently, fractional S-transform (FrST) has played an important role in the area of …

ECG quality assessment based on hand-crafted statistics and deep-learned S-transform spectrogram features

G Liu, X Han, L Tian, W Zhou, H Liu - Computer Methods and Programs in …, 2021 - Elsevier
Abstract Background and Objective Electrocardiogram (ECG) quality assessment is
significant for automatic diagnosis of cardiovascular disease and reducing the massive …

An ECG signal denoising method using conditional generative adversarial net

X Wang, B Chen, M Zeng, Y Wang, H Liu… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
In this paper, a novel denoising method for electrocardiogram (ECG) signal is proposed to
improve performance and availability under multiple noise cases. The method is based on …

ECG beats classification using mixture of features

MK Das, S Ari - International scholarly research notices, 2014 - Wiley Online Library
Classification of electrocardiogram (ECG) signals plays an important role in clinical
diagnosis of heart disease. This paper proposes the design of an efficient system for …

A stacked contractive denoising auto-encoder for ECG signal denoising

P **ong, H Wang, M Liu, F Lin, Z Hou… - Physiological …, 2016 - iopscience.iop.org
As a primary diagnostic tool for cardiac diseases, electrocardiogram (ECG) signals are often
contaminated by various kinds of noise, such as baseline wander, electrode contact noise …