AI Medical Compendium Topic

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

Heart Rate

Showing 171 to 180 of 543 articles

Clear Filters

Classification and regression of stenosis using an in-vitro pulse wave data set: Dependence on heart rate, waveform and location.

Computers in biology and medicine
BACKGROUND: Data-based approaches promise to use the information in cardiovascular signals to diagnose cardiovascular diseases. Considerable effort has been undertaken in the field of pulse-wave analysis to harness this information. However, the inve...

Deep Learning-Based Energy Expenditure Estimation in Assisted and Non-Assisted Gait Using Inertial, EMG, and Heart Rate Wearable Sensors.

Sensors (Basel, Switzerland)
Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based rehabilitation through human-in-the-loop control to tailor robot assistance towards reducing patients’ energy effort. However, it is usually assessed by i...

DDCNN: A Deep Learning Model for AF Detection From a Single-Lead Short ECG Signal.

IEEE journal of biomedical and health informatics
With the popularity of the wireless body sensor network, real-time and continuous collection of single-lead electrocardiogram (ECG) data becomes possible in a convenient way. Data mining from the collected single-lead ECG waves has therefore aroused ...

Toward Mental Effort Measurement Using Electrodermal Activity Features.

Sensors (Basel, Switzerland)
The ability to monitor mental effort during a task using a wearable sensor may improve productivity for both work and study. The use of the electrodermal activity (EDA) signal for tracking mental effort is an emerging area of research. Through analys...

Machine Learning Methods in Predicting Patients with Suspected Myocardial Infarction Based on Short-Time HRV Data.

Sensors (Basel, Switzerland)
Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of death for 32% of the world's population. Particularly relevant are automated diagnostics using machine learning methods in the digitalization of healthcare and ...

Pulse Signal Analysis Based on Deep Learning Network.

BioMed research international
Pulse signal is one of the most important physiological features of human body, which is caused by the cyclical contraction and diastole. It has great research value and broad application prospect in the detection of physiological parameters, the dev...

Arrhythmia classification of 12-lead and reduced-lead electrocardiograms via recurrent networks, scattering, and phase harmonic correlation.

Physiological measurement
We describe an automatic classifier of arrhythmias based on 12-lead and reduced-lead electrocardiograms. Our classifier comprises four modules: scattering transform (ST), phase harmonic correlation (PHC), depthwise separable convolutions (DSC), and a...

A Deep Neural Network Ensemble Classifier with Focal Loss for Automatic Arrhythmia Classification.

Journal of healthcare engineering
Automated electrocardiogram classification techniques play an important role in assisting physicians in diagnosing arrhythmia. Among these, the automatic classification of single-lead heartbeats has received wider attention due to the urgent need for...

Multi-Level Classification of Driver Drowsiness by Simultaneous Analysis of ECG and Respiration Signals Using Deep Neural Networks.

International journal of environmental research and public health
The high number of fatal crashes caused by driver drowsiness highlights the need for developing reliable drowsiness detection methods. An ideal driver drowsiness detection system should estimate multiple levels of drowsiness accurately without interv...

Analysis of Therapeutic Effect of Elderly Patients with Severe Heart Failure Based on LSTM Neural Model.

Computational intelligence and neuroscience
In recent years, cardiovascular-related diseases have become the "number one killer" threatening human life and health and have received much attention. The timely and accurate detection and diagnosis of arrhythmias and heart failure are relatively c...