A deep learning approach for atrial fibrillation classification using multi-feature time series data from ecg and ppg
Atrial fibrillation is a prevalent cardiac arrhythmia that poses significant health risks to
patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and …
patients. The use of non-invasive methods for AF detection, such as Electrocardiogram and …
Artificial intelligence for atrial fibrillation detection, prediction, and treatment: A systematic review of the last decade (2013–2023)
Atrial fibrillation (AF) affects more than 30 million individuals worldwide, making it the most
prevalent cardiac arrhythmia on a global scale. This systematic review summarizes recent …
prevalent cardiac arrhythmia on a global scale. This systematic review summarizes recent …
A Review of Deep Learning Methods for Photoplethysmography Data
Photoplethysmography (PPG) is a highly promising device due to its advantages in
portability, user-friendly operation, and non-invasive capabilities to measure a wide range of …
portability, user-friendly operation, and non-invasive capabilities to measure a wide range of …
Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering
DG Lapitan, DA Rogatkin, EA Molchanova… - Scientific Reports, 2024 - nature.com
Pre-processing of the photoplethysmography (PPG) signal plays an important role in the
analysis of the pulse wave signal. The task of pre-processing is to remove noise from the …
analysis of the pulse wave signal. The task of pre-processing is to remove noise from the …
Introduction to cardiovascular signals and automated systems
Cardiovascular signals such as the electrocardiogram (ECG), phonocardiogram (PCG), and
photoplethysmograph (PPG) provide valuable information for the automated and early …
photoplethysmograph (PPG) provide valuable information for the automated and early …
Effective IoT Based Analysis of Photoplethysmography Waveforms for Investigating Arterial Stiffness and Pulse Rate Variability
In order to detect variations in blood volume in the peripheral arterial pulse,
photoplethysmography (PPG) can be used as an electro-optical method. Recognized as a …
photoplethysmography (PPG) can be used as an electro-optical method. Recognized as a …
A CNN and Transformer Hybrid Network for Multi-Class Arrhythmia Detection from Photoplethysmography
ZD Liu, B Zhou, JK Liu, H Zhao, Y Li… - 2024 46th Annual …, 2024 - ieeexplore.ieee.org
Photoplethysmography (PPG)-based arrhythmia detection methods have gained attention
with wearable technology, enabling early detection of undiagnosed arrhythmias. Existing …
with wearable technology, enabling early detection of undiagnosed arrhythmias. Existing …
[書籍][B] Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing
RK Tripathy, RB Pachori - 2024 - books.google.com
Signal Processing Driven Machine Learning Techniques for Cardiovascular Data
Processing features recent advances in machine learning coupled with new signal …
Processing features recent advances in machine learning coupled with new signal …
[PDF][PDF] PPG signal processing & arrhythmia detection
DBB Piñeiro - epub.fh-joanneum.at
Photoplethysmography (PPG) is a non-invasive optical technique widely used in healthcare
and research to monitor blood volume changes and extract valuable physiological …
and research to monitor blood volume changes and extract valuable physiological …