GRN-Transformer: Enhancing Motion Artifact Detection in PICU Photoplethysmogram Signals
TD Le - arXiv preprint arXiv:2308.03722, 2023 - arxiv.org
This study investigates artifact detection in clinical photoplethysmogram signals using
Transformer-based models. Recent findings have shown that in detecting artifacts from the …
Transformer-based models. Recent findings have shown that in detecting artifacts from the …
Transformer Meets Gated Residual Networks To Enhance Photoplethysmogram Artifact Detection Informed by Mutual Information Neural Estimation
TD Le - arXiv preprint arXiv:2405.16177, 2024 - arxiv.org
This study delves into the effectiveness of various learning methods in improving
Transformer models, focusing particularly on the Gated Residual Network Transformer (GRN …
Transformer models, focusing particularly on the Gated Residual Network Transformer (GRN …
[HTML][HTML] Tiny-PPG: A lightweight deep neural network for real-time detection of motion artifacts in photoplethysmogram signals on edge devices
Y Zheng, C Wu, P Cai, Z Zhong, H Huang, Y Jiang - Internet of Things, 2024 - Elsevier
Photoplethysmogram (PPG) signals are easily contaminated by motion artifacts in real-world
settings, despite their widespread use in Internet-of-Things (IoT) based wearable and smart …
settings, despite their widespread use in Internet-of-Things (IoT) based wearable and smart …
Photoplethysmogram signal quality evaluation by unsupervised learning approach
Photoplethysmography (PPG) is gradually becoming popular tool for cardiovascular and
respiratory function monitoring under ambulatory condition. However, these measurements …
respiratory function monitoring under ambulatory condition. However, these measurements …
Robust PPG motion artifact detection using a 1-D convolution neural network
Background and objectives Continuous monitoring of physiological parameters such as
photoplethysmography (PPG) has attracted increased interest due to advances in wearable …
photoplethysmography (PPG) has attracted increased interest due to advances in wearable …
Label Propagation Techniques for Artifact Detection in Imbalanced Classes using Photoplethysmogram Signals
C Macabiau, TD Le, K Albert, M Shahriari… - IEEE …, 2024 - ieeexplore.ieee.org
This study aimed to investigate the application of label propagation techniques to propagate
labels among photoplethysmogram (PPG) signals, particularly in imbalanced class …
labels among photoplethysmogram (PPG) signals, particularly in imbalanced class …
Motion Artifact Reduction In Photoplethysmography For Reliable Signal Selection
R Mao, M Tweardy, SW Wegerich… - 2021 43rd Annual …, 2021 - ieeexplore.ieee.org
Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital
signs of the human body. Although it has been widely used in consumer and research grade …
signs of the human body. Although it has been widely used in consumer and research grade …
PPGMotion: Model-based detection of motion artifacts in photoplethysmography signals
Photoplethysmography (PPG) is used widely in health wearables to monitor biomarkers like
heart rate. However, motion activities degrade the quality of the measured PPG signal …
heart rate. However, motion activities degrade the quality of the measured PPG signal …
PPG-GAN: An Adversarial Network to De-noise PPG Signals during Physical Activity
Quality photoplethysmographic (PPG) signals are essential for accurate physiological
assessment. However, the PPG acquisition process is often accompanied by spurious …
assessment. However, the PPG acquisition process is often accompanied by spurious …
Deep learning approaches for plethysmography signal quality assessment in the presence of atrial fibrillation
Objective: Photoplethysmography (PPG) monitoring has been implemented in many
portable and wearable devices we use daily for health and fitness tracking. Its simplicity and …
portable and wearable devices we use daily for health and fitness tracking. Its simplicity and …