AIMC Topic: Blood Pressure

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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
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...

AI-Enabled Advanced Development for Assessing Low Circulating Blood Volume for Emergency Medical Care: Comparison of Compensatory Reserve Machine-Learning Algorithms.

Sensors (Basel, Switzerland)
The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to com...

Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement.

Biosensors
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...

End-to-End Automatic Morphological Classification of Intracranial Pressure Pulse Waveforms Using Deep Learning.

IEEE journal of biomedical and health informatics
OBJECTIVE: Mean intracranial pressure (ICP) is commonly used in the management of patients with intracranial pathologies. However, the shape of the ICP signal over a single cardiac cycle, called ICP pulse waveform, also contains information on the st...

Application of photoplethysmography signals for healthcare systems: An in-depth review.

Computer methods and programs in biomedicine
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, ...

Development, validation, and application of a machine learning model to estimate salt consumption in 54 countries.

eLife
Global targets to reduce salt intake have been proposed, but their monitoring is challenged by the lack of population-based data on salt consumption. We developed a machine learning (ML) model to predict salt consumption at the population level based...

Artificial Intelligence Based Blood Pressure Estimation From Auscultatory and Oscillometric Waveforms: A Methodological Review.

IEEE reviews in biomedical engineering
Cardiovascular disease is known as the number one cause of death globally, with elevated blood pressure (BP) being the single largest risk factor. Hence, BP is an important physiological parameter used as an indicator of cardiovascular health. The us...

Blood Pressure Model Based on Hybrid Feature Convolution Neural Network in Promoting Rehabilitation of Patients with Hypertensive Intracerebral Hemorrhage.

Computational and mathematical methods in medicine
OBJECTIVE: Accurate prediction of the rise of blood pressure is essential for the hypertensive intracerebral hemorrhage. This study uses the hybrid feature convolution neural network to establish the blood pressure model instead of the traditional me...

Analyses of child cardiometabolic phenotype following assisted reproductive technologies using a pragmatic trial emulation approach.

Nature communications
Assisted reproductive technologies (ART) are increasingly used, however little is known about the long-term health of ART-conceived offspring. Weak selection of comparison groups and poorly characterized mechanisms impede current understanding. In a ...