Review on Obstructive Sleep Apnea Detection using ECG Signals
Author:
Affiliation:
1. Karunya Institute of Sciences & Technology,Department of Biomedical Engineering,Coimbatore,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9716239/9716227/09716342.pdf?arnumber=9716342
Reference33 articles.
1. Fusion based Feature Extraction Analysis of ECG Signal Interpretation-A Systematic Approach;vijayakumar;Journal of Artificial Intelligence,2021
2. A novel ECG signal classification method using DEA-ELM
3. Literature Review on Sleep APNEA Analysis by Machine Learning Algorithms Using ECG Signals
4. An Experimental Review on Obstructive Sleep Apnea Detection Based on Heart Rate Variability and Machine Learning Techniques
5. PhysioBank, PhysioToolkit, and PhysioNet
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1. Ensemble Classification of Sleep Apnea Using Single-Lead Electrocardiogram Signal;2024 International Conference on Integrated Circuits, Communication, and Computing Systems (ICIC3S);2024-06-08
2. Deep Learning Approach for Sleep Apnea Detection Using Single Lead ECG: Comparative Analysis Between CNN and SNN;2023 26th International Conference on Computer and Information Technology (ICCIT);2023-12-13
3. Time-Frequency Ridge Analysis of Sleep Stage Transitions;2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB);2022-12-03
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