y Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram

Erdenebayar Urtnasan; Kim Yoon Ji; Park Jong-Uk; Joo Eun Yeon; Lee Kyoung-Joung

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y Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram

机译：y深度学习方法，用于自动检测心电图睡眠呼吸暂停事件的方法

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Background and Objective: This study demonstrates deep learning approaches with an aim to find the optimal method to automatically detect sleep apnea (SA) events from an electrocardiogram (ECG) signal.

机译：背景和目的：本研究表明了深度学习方法，目的是找到从心电图（ECG）信号自动检测睡眠呼吸暂停（SA）事件的最佳方法。

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来源
《Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice》 |2019年第2019期|共9页
作者
Erdenebayar Urtnasan; Kim Yoon Ji; Park Jong-Uk; Joo Eun Yeon; Lee Kyoung-Joung;
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作者单位

Yonsei Univ Coll Hlth Sci Dept Biomed Engn Wonju 26493 South Korea;

Yonsei Univ Coll Hlth Sci Dept Biomed Engn Wonju 26493 South Korea;

Yonsei Univ Coll Hlth Sci Dept Biomed Engn Wonju 26493 South Korea;

Sungkyunkwan Univ Sch Med Samsung Med Ctr Dept Neurol Seoul South Korea;

Yonsei Univ Coll Hlth Sci Dept Biomed Engn Wonju 26493 South Korea;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
Sleep apnea; Deep learning; Convolutional neural network; Recurrent neural network; Long short-term memory; Gated-recurrent unit;

机译：睡眠呼吸暂停;深入学习;卷积神经网络;经常性神经网络;长短期记忆;门控复发单位;

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1. y Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram [J] . Erdenebayar Urtnasan, Kim Yoon Ji, Park Jong-Uk, Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice . 2019,第期

机译：y深度学习方法，用于自动检测心电图睡眠呼吸暂停事件的方法
2. Automatic Detection of Obstructive Sleep Apnea Events Using a Deep CNN-LSTM Model [J] . Junming Zhang, Zhen Tang, Jinfeng Gao, Computational intelligence and neuroscience . 2021,第a期

机译：使用深层CNN-LSTM模型自动检测阻塞性睡眠呼吸暂停事件
3. Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network [J] . Urtnasan Erdenebayar, Park Jong-Uk, Joo Eun-Yeon, Journal of medical systems . 2018,第6期

机译：使用卷积神经网络自动检测来自单引灯心电图的阻塞性睡眠呼吸暂停事件
4. Detection of sleep apnea events via tracking nonlinear dynamic cardio-respiratory coupling from electrocardiogram signals [C] . Karandikar Kunal, Le Trung Q., Sa-ngasoongsong Akkarapol, Annual Conference of Japanese Society for Medical and Biological Engineering;Annual International Conference of the IEEE Engineering in Medicine and Biology Society . 2013

机译：通过跟踪心电图信号中的非线性动态心肺耦合来检测睡眠呼吸暂停事件
5. Real-time automatic assessment of obstructive sleep apnea and sleep quality: Using the electrocardiogram and support vector machines. [D] . Bsoul, Majdi. 2010

机译：实时自动评估阻塞性睡眠呼吸暂停和睡眠质量：使用心电图和支持向量机。
6. Automatic Detection of Obstructive Sleep Apnea Events Using a Deep CNN-LSTM Model [O] . Junming Zhang, Zhen Tang, Jinfeng Gao, 2021

机译：使用深层CNN-LSTM模型自动检测阻塞性睡眠呼吸暂停事件
7. Deep-ACTINet: End-to-End Deep Learning Architecture for Automatic Sleep-Wake Detection Using Wrist Actigraphy [O] . Taeheum Cho, Unang Sunarya, Minsoo Yeo, 2019

机译：深散式型：使用手腕采集自动睡眠唤醒检测的端到端深度学习架构

y Deep learning approaches for automatic detection of sleep apnea events from an electrocardiogram

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