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Heart Rate

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Impact of artificial intelligence arrhythmia mapping on time to first ablation, procedure duration, and fluoroscopy use.

Journal of cardiovascular electrophysiology
INTRODUCTION: Artificial intelligence (AI) ECG arrhythmia mapping provides arrhythmia source localization using 12-lead ECG data; whether this information impacts procedural efficiency is unknown. We performed a retrospective, case-control study to e...

12-Lead ECG Reconstruction Based on Data From the First Limb Lead.

Cardiovascular engineering and technology
PURPOSE: Electrocardiogram (ECG) data obtained from 12 leads are the most common and informative source for analyzing the cardiovascular system's (CVS) condition in medical practice. However, the large number of electrodes, specific placements on the...

Sleep-phasic heart rate variability predicts stress severity: Building a machine learning-based stress prediction model.

Stress and health : journal of the International Society for the Investigation of Stress
We propose a novel approach for predicting stress severity by measuring sleep phasic heart rate variability (HRV) using a smart device. This device can potentially be applied for stress self-screening in large populations. Using a Holter electrocardi...

A Soft Robotic Actuator System for In Vivo Modeling of Normal Pressure Hydrocephalus.

IEEE transactions on bio-medical engineering
OBJECTIVE: The intracranial pressure (ICP) affects the dynamics of cerebrospinal fluid (CSF) and its waveform contains information that is of clinical importance in medical conditions such as hydrocephalus. Active manipulation of the ICP waveform cou...

Predicting Soccer Players' Fitness Status Through a Machine-Learning Approach.

International journal of sports physiology and performance
PURPOSE: The study had 3 purposes: (1) to develop an index using machine-learning techniques to predict the fitness status of soccer players, (2) to explore the index's validity and its relationship with a submaximal run test (SMFT), and (3) to analy...

Person identification with arrhythmic ECG signals using deep convolution neural network.

Scientific reports
Over the past decade, the use of biometrics in security systems and other applications has grown in popularity. ECG signals in particular are attracting increased attention due to their characteristics, which are required for a trustworthy identifica...

Conventional and deep learning methods in heart rate estimation from RGB face videos.

Physiological measurement
Contactless vital signs monitoring is a fast-advancing scientific field that aims to employ monitoring methods that do not necessitate the use of leads or physical attachments to the patient in order to overcome the shortcomings and limits of traditi...

A multi-module algorithm for heartbeat classification based on unsupervised learning and adaptive feature transfer.

Computers in biology and medicine
The scarcity of annotated data is a common issue in the realm of heartbeat classification based on deep learning. Transfer learning (TL) has emerged as an effective strategy for addressing this issue. However, current TL techniques in this realm over...

Time-domain heart rate dynamics in the prognosis of progressive atherosclerosis.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIM: The regular uptake of a high-fat diet (HFD) with changing lifestyle causes atherosclerosis leading to cardiovascular diseases and autonomic dysfunction. Therefore, the current study aimed to investigate the correlation of autonomi...

ECG arrhythmia detection in an inter-patient setting using Fourier decomposition and machine learning.

Medical engineering & physics
ECG beat classification or arrhythmia detection through artificial intelligence (AI) is an active topic of research. It is vital to recognize and detect the type of arrhythmia for monitoring cardiac abnormalities. The AI-based ECG beat classification...