A5064289837- ECG Monitoring and Analysis
- EEG and Brain-Computer Interfaces
- Cardiac electrophysiology and arrhythmias
- Blockchain Technology Applications and Security
- Artificial Intelligence in Healthcare
- IoT and Edge/Fog Computing
- Maritime Transport Emissions and Efficiency
- Hybrid Renewable Energy Systems
- Wind Energy Research and Development
- Advanced Computing and Algorithms
- Internet of Things and AI
- Wastewater Treatment and Nitrogen Removal
- Microbial Fuel Cells and Bioremediation
- Machine Learning in Healthcare
- Brain Tumor Detection and Classification
Minia University
2014
Early diagnosis and classification of arrhythmia from an electrocardiogram (ECG) plays a significant role in smart healthcare systems for the health monitoring individuals with cardiovascular diseases. Unfortunately, nonlinearity low amplitude ECG recordings make process difficult. Thus, performance most traditional machine learning (ML) classifiers is questionable, as interrelationship between parameters not well modeled, especially data features high dimensions. To address limitations ML...
The electrocardiogram (ECG) is a non-invasive tool used to diagnose various heart conditions. Arrhythmia one of the primary causes cardiac arrest. Early ECG beat classification plays significant role in diagnosing life-threatening arrhythmias. However, signal very small, anti-interference potential low, and noise easily influenced. Thus, clinicians face challenges method automatically identify distinguish arrhythmias from invaluable. In this paper, hybrid approach based on marine predators...