An Improved Approach for Atrial Fibrillation Detection in Long-Term ECG Using Decomposition Transforms and Least-Squares Support Vector Machine
Atrial fibrillation is a common heart rhythm disorder that is now becoming a significant healthcare challenge as it affects more and more people in developed countries. This paper proposes a novel approach for detecting this disease. For this purpose, we examined the ECG signal by detecting QRS comp...
Main Author: | Tomasz Pander |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-11-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/22/12187 |
Similar Items
-
Fibrillatory Wave Amplitude Evolution during Persistent Atrial Fibrillation Ablation: Implications for Atrial Substrate and Fibrillation Complexity Assessment
by: Fabien Squara, et al.
Published: (2022-08-01) -
Detection of Ventricular Fibrillation Using Ensemble Empirical Mode Decomposition of ECG Signals
by: Seungrok Oh, et al.
Published: (2024-02-01) -
Machine Learning for Detecting Atrial Fibrillation from ECGs: Systematic Review and Meta-Analysis
by: Chenggong Xie, et al.
Published: (2024-01-01) -
Robust Artificial Intelligence Tool for Atrial Fibrillation Diagnosis: Novel Development Approach Incorporating Both Atrial Electrograms and Surface ECG and Evaluation by Head‐to‐Head Comparison With Hospital‐Based Physician ECG Readers
by: Yuji Zhang, et al.
Published: (2024-02-01) -
Automated Signal Quality Assessment of Single-Lead ECG Recordings for Early Detection of Silent Atrial Fibrillation
by: Markus Lueken, et al.
Published: (2023-06-01)