AIMC Topic: Heart Rate

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A two-step method for paroxysmal atrial fibrillation event detection based on machine learning.

Mathematical biosciences and engineering : MBE
Detection of atrial fibrillation (AF) events is significant for early clinical diagnosis and appropriate intervention. However, in existing detection algorithms for paroxysmal AF (AFp), the location of AF starting and ending points in AFp is not conc...

A U - Net Deep Learning Model for Infant Heart Rate Estimation from Ballistography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Ballistography(BSG) is a non-intrusive and low- cost alternative to electrocardiography (ECG) for heart rate (HR) monitoring in infants. Due to the inter-patient variance and susceptibility to noise, heartbeat detection in the BSG waveform remains a ...

Lightweight neural network based model for real-time precise HR monitoring during high intensity workout using consumer smartwatches.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Mobile and wearable electronics is one of the rapidly developing areas of high technologies, which regularly appear new devices that offer new features for monitoring our health, level of physical exertion and everyday activity. From the point of vie...

Deep learning based non-contact physiological monitoring in Neonatal Intensive Care Unit.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Preterm babies in the Neonatal Intensive Care Unit (NICU) have to undergo continuous monitoring of their cardiac health. Conventional monitoring approaches are contact-based, making the neonates prone to various nosocomial infections. Video-based mon...

Deep-Learning based Sleep Apnea Detection using SpO2 and Pulse Rate.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work presents automated apnea event de-tection using blood oxygen saturation (SpO2) and pulse rate (PR), conveniently recorded with a pulse oximeter. A large, diverse cohort of patients (n=8068, age≄40 years) from the sleep heart health study da...

[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
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...

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
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...

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

JAMA cardiology
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.

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

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
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.

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
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...