AIMC Topic: Photoplethysmography

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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...
Algorithms Deep Learning Humans Heart Rate Video Recording Photoplethysmography Skin
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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...
Sleep Stages Deep Learning Photoplethysmography Sleep Heart Rate Accelerometry
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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...
Algorithms Research Design Heart Rate Deep Learning Photoplethysmography
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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.
Blood Pressure Determination Blood Pressure Technology Artificial Intelligence Pulse Wave Analysis Photoplethysmography
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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...
Machine Learning Algorithms Photoplethysmography Support Vector Machine
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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...
Arterial Pressure Prehypertension Photoplethysmography Blood Pressure Determination Blood Pressure Hypotension Deep Learning Hypertension Humans
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A deep learning approach to estimate pulse rate by remote photoplethysmography.

Physiological measurement Jul 25, 2022
This study proposes a U-net shaped Deep Neural Network (DNN) model to extract remote photoplethysmography (rPPG) signals from skin color signals to estimate Pulse Rate (PR).Three input window sizes are used in the DNN: 256 samples (5.12 s), 512 sampl...
Neural Networks, Computer Heart Rate Algorithms Photoplethysmography Deep Learning Signal Processing, Computer-Assisted
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Determination gender-based hybrid artificial intelligence of body muscle percentage by photoplethysmography signal.

Computer methods and programs in biomedicine Jul 8, 2022
BACKGROUND AND OBJECTIVE: Muscle mass is one of the critical components that ensure muscle function. Loss of muscle mass at every stage of life can cause many adverse effects. Sarcopenia, which can occur in different age groups and is characterized b...
Algorithms Humans Photoplethysmography Male Female Artificial Intelligence Muscles Machine Learning Quality of Life
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Photoplethysmogram based vascular aging assessment using the deep convolutional neural network.

Scientific reports Jul 5, 2022
Arterial stiffness due to vascular aging is a major indicator during the assessment of cardiovascular risk. In this study, we propose a method for age estimation by applying deep learning to a photoplethysmogram (PPG) for the non-invasive assessment ...
Heart Rate Artificial Intelligence Photoplethysmography Neural Networks, Computer
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XGBoost Regression of the Most Significant Photoplethysmogram Features for Assessing Vascular Aging.

IEEE journal of biomedical and health informatics Jul 1, 2022
The purpose of this study was to confirm the potential of XGBoost as a vascular aging assessment model based on the photoplethysmogram (PPG) features suggested in previous studies, and to explore the key PPG features for vascular aging assessment thr...
Artificial Intelligence Aging Photoplethysmography Heart Rate Humans
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