SleepZzNet: Sleep Stage Classification Using Single-Channel EEG Based on CNN and Transformer | |
Chen HY(陈惠宇)1,2; Yin ZG(尹志刚)1; Zhang P(张鹏)1,2; Liu PF(刘盼飞)1,2 | |
发表期刊 | International Journal of Psychophysiology |
ISSN | 0167-8760 |
2021 | |
卷号 | Volume 168, Supplement页码:Page S168 |
产权排序 | 1 |
摘要 | Sleep stage classification is one of the most important methods to diagnose narcolepsy and sleep disorders. By analyzing the polysomnogram, which includes bioelectrical signals such as EEG and ECG, the whole night’s sleep is divided into 30-second epochs, each belonging to five sleep stages: Wake, N1, N2, N3, and REM stages, according to the AASM guidelines. As deep learning has made breakthroughs in various fields in recent years, automatic sleep stages classification tasks are also undergoing a revolution from traditional methods to deep learning methods. Models combining convolutional neural networks and recurrent neural networks (e.g., LSTM) achieve state-of-the-art performance on many benchmark datasets. |
收录类别 | SCI |
语种 | 英语 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/45036 |
专题 | 国家专用集成电路设计工程技术研究中心_前瞻芯片研制与测试 |
通讯作者 | Chen HY(陈惠宇) |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Chen HY,Yin ZG,Zhang P,et al. SleepZzNet: Sleep Stage Classification Using Single-Channel EEG Based on CNN and Transformer[J]. International Journal of Psychophysiology,2021,Volume 168, Supplement:Page S168. |
APA | Chen HY,Yin ZG,Zhang P,&Liu PF.(2021).SleepZzNet: Sleep Stage Classification Using Single-Channel EEG Based on CNN and Transformer.International Journal of Psychophysiology,Volume 168, Supplement,Page S168. |
MLA | Chen HY,et al."SleepZzNet: Sleep Stage Classification Using Single-Channel EEG Based on CNN and Transformer".International Journal of Psychophysiology Volume 168, Supplement(2021):Page S168. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
SleepZzNet.pdf(49KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论