Evaluation of the responsiveness pattern to caffeine through a smart data-driven ECG non-linear multi-band analysis
R Domingues, P Batista, M Pintado, P Oliveira-Silva… - Heliyon, 2024 - cell.com
This study aimed to explore more efficient ways of administering caffeine to the body by
investigating the impact of caffeine on the modulation of the nervous system's activity …
investigating the impact of caffeine on the modulation of the nervous system's activity …
ECG arrhythmia detection in an inter-patient setting using Fourier decomposition and machine learning
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 …
topic of research. It is vital to recognize and detect the type of arrhythmia for monitoring …
Classification of ECG signals based on local fractal feature
W Jiang, J Wang - Multimedia Tools and Applications, 2024 - Springer
Accurate and automatic analysis of electrocardiogram (ECG) signals plays a key role in the
diagnosis of cardiovascular disease. This paper aims to investigate the performance of the …
diagnosis of cardiovascular disease. This paper aims to investigate the performance of the …
Automatic diagnosis of 12-lead ECG using DINOv2
The electrocardiogram (ECG), though a cheap, reliable, and fast diagnostic test for detecting
several heart anomalies, needs accurate interpretation by a skilled professional. The …
several heart anomalies, needs accurate interpretation by a skilled professional. The …
ECG-based Cardiovascular Disease Diagnosis: An Ensemble Learning Approach
A Gupta, B Sharadat, T Huddle - 2024 - researchsquare.com
The classification and identification of arrhythmias using ECG signals are of substantial
practical importance in the early prevention and detection of cardiac and cardiovascular …
practical importance in the early prevention and detection of cardiac and cardiovascular …