AIMC Topic: Photoplethysmography
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Deep-learning-based blood pressure estimation using multi channel photoplethysmogram and finger pressure with attention mechanism.
Scientific reports
Jun 8, 2023
Recently, several studies have proposed methods for measuring cuffless blood pressure (BP) using finger photoplethysmogram (PPG) signals. This study presents a new BP estimation system that measures PPG signals under progressive finger pressure, maki...
A deep learning method for continuous noninvasive blood pressure monitoring using photoplethysmography.
Physiological measurement
May 22, 2023
. The aim of this study is to investigate continuous blood pressure waveform estimation from a plethysmography (PPG) signal, thus providing more human cardiovascular status information than traditional cuff-based methods.. The proposed method utilize...
Mental Stress Detection Using a Wearable In-Ear Plethysmography.
Biosensors
Mar 17, 2023
This study presents an ear-mounted photoplethysmography (PPG) system that is designed to detect mental stress. Mental stress is a prevalent condition that can negatively impact an individual's health and well-being. Early detection and treatment of m...
SleepPPG-Net: A Deep Learning Algorithm for Robust Sleep Staging From Continuous Photoplethysmography.
IEEE journal of biomedical and health informatics
Feb 3, 2023
Sleep staging is an essential component in the diagnosis of sleep disorders and management of sleep health. Sleep is traditionally measured in a clinical setting and requires a labor-intensive labeling process. We hypothesize that it is possible to p...
X-iPPGNet: A novel one stage deep learning architecture based on depthwise separable convolutions for video-based pulse rate estimation.
Computers in biology and medicine
Jan 24, 2023
Pulse rate (PR) is one of the most important markers for assessing a person's health. With the increasing demand for long-term health monitoring, much attention is being paid to contactless PR estimation using imaging photoplethysmography (iPPG). Thi...
A Flexible Deep Learning Architecture for Temporal Sleep Stage Classification Using Accelerometry and Photoplethysmography.
IEEE transactions on bio-medical engineering
Dec 26, 2022
Wrist-worn consumer sleep technologies (CST) that contain accelerometers (ACC) and photoplethysmography (PPG) are increasingly common and hold great potential to function as out-of-clinic (OOC) sleep monitoring systems. However, very few validation s...
Deep learning-based remote-photoplethysmography measurement from short-time facial video.
Physiological measurement
Nov 3, 2022
. Efficient non-contact heart rate (HR) measurement from facial video has received much attention in health monitoring. Past methods relied on prior knowledge and an unproven hypothesis to extract remote photoplethysmography (rPPG) signals, e.g. manu...
Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals.
BioMed research international
Oct 1, 2022
OBJECTIVE: To review the progress of research on photoplethysmography- (PPG-) based cuffless continuous blood pressure monitoring technologies and prospect the challenges that need to be addressed in the future.
Impact of Label Noise on the Learning Based Models for a Binary Classification of Physiological Signal.
Sensors (Basel, Switzerland)
Sep 21, 2022
Label noise is omnipresent in the annotations process and has an impact on supervised learning algorithms. This work focuses on the impact of label noise on the performance of learning models by examining the effect of random and class-dependent labe...
DeepCNAP: A Deep Learning Approach for Continuous Noninvasive Arterial Blood Pressure Monitoring Using Photoplethysmography.
IEEE journal of biomedical and health informatics
Aug 11, 2022
Arterial blood pressure (ABP) monitoring may permit the early diagnosis and management of cardiovascular disease (CVD); however, existing methods for measuring ABP outside the clinic use inconvenient cuff sphygmomanometry, or do not estimate continuo...
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