AIMC Topic: Heart Rate

Clear Filters Showing 501 to 510 of 608 articles

Effects of chronic exposure to biomass pollutants on cardiorespiratory responses and the occurrence of exercise-induced bronchoconstriction in healthy men.

Physiological reports
Exposure to charcoal biomass (CB) pollutants affects the cardiorespiratory system. We assessed cardiopulmonary responses (CPR) to exercise in charcoal producers (CPs) compared to farmers and evaluated the prevalence of exercise-induced bronchoconstri...

External validation of a machine learning-based classification algorithm for ambulatory heart rhythm diagnostics in pericardioversion atrial fibrillation patients using smartphone photoplethysmography: the SMARTBEATS-ALGO study.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
AIMS: The aim of this study was to perform an external validation of an automatic machine learning (ML) algorithm for heart rhythm diagnostics using smartphone photoplethysmography (PPG) recorded by patients with atrial fibrillation (AF) and atrial f...

[A review of deep learning methods for non-contact heart rate measurement based on facial videos].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Heart rate is a crucial indicator of human health with significant physiological importance. Traditional contact methods for measuring heart rate, such as electrocardiograph or wristbands, may not always meet the need for convenient health monitoring...

Tracking vigilance fluctuations in real-time: a sliding-window heart rate variability-based machine-learning approach.

Sleep
STUDY OBJECTIVES: Heart rate variability (HRV)-based machine learning models hold promise for real-world vigilance evaluation, yet their real-time applicability is limited by lengthy feature extraction times and reliance on subjective benchmarks. Thi...

Estimation of Central Aortic Pressure Waveforms by Combination of a Meta-Learning Neural Network and a Physics-Driven Method.

International journal for numerical methods in biomedical engineering
The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved....

3D DenseNet with temporal transition layer for heart rate estimation from real-life RGB videos.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Deep learning has demonstrated superior performance over traditional methods for the estimation of heart rates in controlled contexts. However, in less controlled scenarios this performance seems to vary based on the training dataset and ...

[Detection model of atrial fibrillation based on multi-branch and multi-scale convolutional networks].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Atrial fibrillation (AF) is a life-threatening heart condition, and its early detection and treatment have garnered significant attention from physicians in recent years. Traditional methods of detecting AF heavily rely on doctor's diagnosis based on...

[Early classification and recognition algorithm for sudden cardiac arrest based on limited electrocardiogram data trained with a two-stages convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Sudden cardiac arrest (SCA) is a lethal cardiac arrhythmia that poses a serious threat to human life and health. However, clinical records of sudden cardiac death (SCD) electrocardiogram (ECG) data are extremely limited. This paper proposes an early ...

Refined matrix completion for spectrum estimation of heart rate variability.

Mathematical biosciences and engineering : MBE
Heart rate variability (HRV) is an important metric in cardiovascular health monitoring. Spectral analysis of HRV provides essential insights into the functioning of the cardiac autonomic nervous system. However, data artefacts could degrade signal q...

Enhancing Non-Contact Heart Rate Monitoring: An Intelligent Multi-ROI Approach with Face Masking and CNN-Based Feature Adaptation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Heart rate (HR) estimation from facial video streams has emerged in the recent years as a promising method of unobtrusive vitals monitoring. Conventional non-contact HR monitoring algorithms like POS, CHROM, ICA are often applied to a single region o...