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Heart Rate

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Heart rate complexity helps mortality prediction in the intensive care unit: A pilot study using artificial intelligence.

Computers in biology and medicine
BACKGROUND: In intensive care units (ICUs), accurate mortality prediction is crucial for effective patient management and resource allocation. The Simplified Acute Physiology Score II (SAPS-2), though commonly used, relies heavily on comprehensive cl...

Relationship between external and internal load indicators and injury using machine learning in professional soccer: a systematic review and meta-analysis.

Research in sports medicine (Print)
This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning (ML) approaches. Studies were included if: (1) participants were male professiona...

A Systematic Approach Focused on Machine Learning Models for Exploring the Landscape of Physiological Measurement and Estimation Using Photoplethysmography (PPG).

Journal of cardiovascular translational research
A non-invasive optical technique known as photoplethysmography (PPG) can be used to provide various physiological measurements and estimations. PPG can be used to assess cardiovascular disease (CVD). Hypertension is a primary risk factor for CVD and ...

A systematic review of the development and application of home cage monitoring in laboratory mice and rats.

BMC biology
BACKGROUND: Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside of their home cages at selected time points. However, the outcome of such tests can be influenced by various factors an...

A deep learning-based approach for distinguishing different stress levels of human brain using EEG and pulse rate.

Computer methods in biomechanics and biomedical engineering
In today's world, people suffer from many fatal maladies, and stress is one of them. Excessive stress can have deleterious effects on the health, brain, mind, and nervous system of humans. The goal of this paper is to design a deep learningbased huma...

Analysis of intracranial pressure pulse waveform in studies on cerebrospinal compliance: a narrative review.

Physiological measurement
Continuous monitoring of mean intracranial pressure (ICP) has been an essential part of neurocritical care for more than half a century. Cerebrospinal pressure-volume compensation, i.e. the ability of the cerebrospinal system to buffer changes in vol...

Dimensional emotion recognition from camera-based PRV features.

Methods (San Diego, Calif.)
Heart rate variability (HRV) is an important indicator of autonomic nervous system activity and can be used for the identification of affective states. The development of remote Photoplethysmography (rPPG) technology has made it possible to measure p...

Deep learning-based lung image registration: A review.

Computers in biology and medicine
Lung image registration can effectively describe the relative motion of lung tissues, thereby helping to solve series problems in clinical applications. Since the lungs are soft and fairly passive organs, they are influenced by respiration and heartb...

Monitoring blood pressure and cardiac function without positioning via a deep learning-assisted strain sensor array.

Science advances
Continuous and reliable monitoring of blood pressure and cardiac function is of great importance for diagnosing and preventing cardiovascular diseases. However, existing cardiovascular monitoring approaches are bulky and costly, limiting their wide a...

KPCA-WRF-prediction of heart rate using deep feature fusion and machine learning classification with tuned weighted hyper-parameter.

Network (Bristol, England)
The rapid advancement of technology such as stream processing technologies, deep-learning approaches, and artificial intelligence plays a prominent and vital role, to detect heart rate using a prediction model. However, the existing methods could not...