Heart Rate

[Automatic detection model of hypertrophic cardiomyopathy based on deep convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2022

The diagnosis of hypertrophic cardiomyopathy (HCM) is of great significance for the early risk classification of sudden cardiac death and the screening of family genetic diseases. This research proposed a HCM automatic detection method based on convo...

Humans Electrocardiography Heart Rate Cardiomyopathy, Hypertrophic Algorithms Databases, Factual Neural Networks, Computer

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Transfer learning of CNN-based signal quality assessment from clinical to non-clinical PPG signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021

Photoplethysmography (PPG) is a non-invasive and cost-efficient optical technique used to assess blood volume variation inside the micro-circulation. PPG technology is widely used in a variety of clinical and non-clinical devices in order to investig...

Neural Networks, Computer Photoplethysmography Heart Rate Machine Learning Reproducibility of Results

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Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation.

JAMA cardiology Nov 1, 2021

IMPORTANCE: Millions of clinicians rely daily on automated preliminary electrocardiogram (ECG) interpretation. Critical comparisons of machine learning-based automated analysis against clinically accepted standards of care are lacking.

Humans Follow-Up Studies Heart Rate Cross-Sectional Studies Consensus Electrocardiography Male Middle Aged ROC Curve Algorithms Cardiovascular Diseases Retrospective Studies Neural Networks, Computer Female Machine Learning

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[An arrhythmia classification method based on deep learning parallel network model].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University Aug 31, 2021

OBJECTIVE: We propose a parallel neural network classification method to improve the performance of classification of 4 types of arrhythmias: normal beat, supraventricular ectopic beat, ventricular ectopic beat and fused beat.

Heart Rate Ventricular Premature Complexes Deep Learning Electrocardiography Humans Neural Networks, Computer

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Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?

Journal of autism and developmental disorders Jan 1, 2021

Several studies show altered heart rate variability (HRV) in autism spectrum disorder (ASD), but findings are neither universal nor specific to ASD. We apply a set of linear and nonlinear HRV measures-including phase rectified signal averaging-to seg...

Schools Heart Rate Rest Students Child Electrocardiography Female Male Humans Machine Learning Biomarkers Autism Spectrum Disorder Prospective Studies

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Using high-dimensional features for high-accuracy pulse diagnosis.

Mathematical biosciences and engineering : MBE Oct 9, 2020

Accurate pulse diagnosis is often based on extensive clinical experience. Recently, modern computer-aided pulse diagnostic methods have been developed to help doctors to quickly determine patients' physiological conditions. Most pulse diagnostic meth...

Humans Computers Principal Component Analysis Heart Rate Neural Networks, Computer Algorithms

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Automatic sleep staging using heart rate variability, body movements, and recurrent neural networks in a sleep disordered population.

Sleep Sep 14, 2020

STUDY OBJECTIVES: To validate a previously developed sleep staging algorithm using heart rate variability (HRV) and body movements in an independent broad cohort of unselected sleep disordered patients.

Heart Rate Sleep Sleep Stages Polysomnography Humans Neural Networks, Computer Algorithms

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Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening condition, called Sepsis. Currently, therapeutic protocols through timely antibiotic resuscitation strategie...

Intensive Care Units, Pediatric Prognosis Humans Sepsis Heart Rate Early Diagnosis Neural Networks, Computer Child

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Robot Assisted Instantaneous Heart Rate Estimator using Camera based Remote Photoplethysmograpy via Plane-Orthogonal-to-Skin and Finite State Machine.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020

In this paper, we have presented Turtulebot-assisted instantaneous heart rate (HR) estimator using camera based remote photoplethysmography. We used a Turtlebot with a camera to record human face. For the face detection, we used Haar Cascade algorith...

Skin Humans Algorithms Heart Rate Photoplethysmography Robotics

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Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening condition, called Sepsis. Currently, therapeutic protocols through timely antibiotic resuscitation strategie...

Heart Rate Humans Early Diagnosis Sepsis Neural Networks, Computer Child Prognosis Intensive Care Units, Pediatric

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Explore the latest research on artificial intelligence and machine learning in medicine.

[Automatic detection model of hypertrophic cardiomyopathy based on deep convolutional neural network].

Transfer learning of CNN-based signal quality assessment from clinical to non-clinical PPG signals.

Performance of a Convolutional Neural Network and Explainability Technique for 12-Lead Electrocardiogram Interpretation.

[An arrhythmia classification method based on deep learning parallel network model].

Brief Report: Can a Composite Heart Rate Variability Biomarker Shed New Insights About Autism Spectrum Disorder in School-Aged Children?

Using high-dimensional features for high-accuracy pulse diagnosis.

Automatic sleep staging using heart rate variability, body movements, and recurrent neural networks in a sleep disordered population.

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

Robot Assisted Instantaneous Heart Rate Estimator using Camera based Remote Photoplethysmograpy via Plane-Orthogonal-to-Skin and Finite State Machine.

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers.

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