Sleep apnea classification using ECG-signal wavelet-PCA features
Author:
Affiliation:
1. Department of Electronic Engineering, Pukyong National University, Busan 608-737, Korea
Publisher
IOS Press
Subject
Biomedical Engineering,Biomaterials,General Medicine
Cited by 36 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. MFS-DBF: A trustworthy multichannel feature sieve and decision boundary formulation system for Obstructive Sleep Apnea detection;Computers in Biology and Medicine;2024-09
2. Detection of cardiac abnormalities from 12-lead ecg using complex wavelet sub-band features;Biomedical Physics & Engineering Express;2024-04-04
3. Application of LightGBM hybrid model based on TPE algorithm optimization in sleep apnea detection;Frontiers in Neuroscience;2024-02-19
4. Three methods for determining respiratory waves from ECG (Part I);Metrology and Measurement Systems;2023-11-20
5. Assessment of obstructive sleep apnea severity using audio-based snoring features;Biomedical Signal Processing and Control;2023-09
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