AIMC Topic: Photoplethysmography

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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...
Heart Rate Photoplethysmography Signal Processing, Computer-Assisted Neural Networks, Computer Algorithms Deep Learning
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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...
Machine Learning Algorithms Humans Artificial Intelligence Quality of Life Photoplethysmography Female Male Muscles
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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...
Humans Photoplethysmography Heart Rate Artificial Intelligence Aging
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A new deep learning framework based on blood pressure range constraint for continuous cuffless BP estimation.

Neural networks : the official journal of the International Neural Network Society Apr 22, 2022
Blood pressure (BP) is known as an indicator of human health status, and regular measurement is helpful for early detection of cardiovascular diseases. Traditional techniques for measuring BP are either invasive or cuff-based and thus are not suitabl...
Blood Pressure Determination Blood Pressure Humans Algorithms Deep Learning Photoplethysmography
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Deduction learning for precise noninvasive measurements of blood glucose with a dozen rounds of data for model training.

Scientific reports Apr 20, 2022
Personalized modeling has long been anticipated to approach precise noninvasive blood glucose measurements, but challenged by limited data for training personal model and its unavoidable outlier predictions. To overcome these long-standing problems, ...
Algorithms Deep Learning Blood Glucose Photoplethysmography Humans Neural Networks, Computer
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Deep convolutional neural network-based signal quality assessment for photoplethysmogram.

Computers in biology and medicine Mar 22, 2022
Quality assessment of bio-signals is important to prevent clinical misdiagnosis. With the introduction of mobile and wearable health care, it is becoming increasingly important to distinguish available signals from noise. The goal of this study was t...
Neural Networks, Computer Bayes Theorem Heart Rate Big Data Photoplethysmography
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Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement.

Biosensors Feb 28, 2022
Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel ph...
Blood Pressure Determination Artificial Intelligence Humans Pulse Wave Analysis Blood Pressure Electric Impedance Photoplethysmography
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Normalization of photoplethysmography using deep neural networks for individual and group comparison.

Scientific reports Feb 24, 2022
Photoplethysmography (PPG) is easy to measure and provides important parameters related to heart rate and arrhythmia. However, automated PPG methods have not been developed because of their susceptibility to motion artifacts and differences in wavefo...
Heart Rate Female Adult Humans Neural Networks, Computer Male Photoplethysmography Signal Processing, Computer-Assisted Motion
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Application of photoplethysmography signals for healthcare systems: An in-depth review.

Computer methods and programs in biomedicine Feb 1, 2022
BACKGROUND AND OBJECTIVES: Photoplethysmography (PPG) is a device that measures the amount of light absorbed by the blood vessel, blood, and tissues, which can, in turn, translate into various measurements such as the variation in blood flow volume, ...
Blood Pressure Signal Processing, Computer-Assisted Heart Rate Delivery of Health Care Photoplethysmography Machine Learning
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