An end-to-end framework for real-time automatic sleep stage classification.
An end-to-end framework for real-time automatic sleep stage classification.
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DOI：
10.1093/sleep/zsy041
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发表时间：
2018-05-01
期刊：
影响因子：
5.6
通讯作者：
Chee MWL
中科院分区：
文献类型：
--
作者：
Patanaik A;Ong JL;Gooley JJ;Ancoli-Israel S;Chee MWL
在任何睡眠实验室中，睡眠分期都是一个基本但耗时的过程。为了在不影响准确性的情况下大大加快睡眠分期，我们开发了一种用于执行实时自动睡眠阶段分类的新框架。这里采用的客户端-服务器架构提供了一种端到端的解决方案，用于匿名化和有效地将多导睡眠图数据从客户端传输到服务器，并以可互操作的方式接收睡眠阶段。该框架智能地在客户端和服务器之间划分睡眠阶段任务，使多个低端客户端可以与一台服务器一起工作，并且可以在本地和云端部署。该框架进行了测试，包括1700多导睡眠图记录（12000小时的记录）从青少年，年轻人和老年人，涉及健康的人以及那些与医疗条件的四个数据集。我们使用了两个独立的验证数据集：一个包括来自睡眠障碍诊所的患者，另一个包括帕金森病患者。使用该系统，整晚的睡眠被分阶段进行，其准确性与专家人类评分员相当，但要快得多（与30-60分钟相比，5秒）。为了说明这种实时睡眠分期的实用性，我们使用它来促进在慢睡眠振荡的目标相位处自动递送声学刺激以增强慢波睡眠。
Sleep staging is a fundamental but time consuming process in any sleep laboratory. To greatly speed up sleep staging without compromising accuracy, we developed a novel framework for performing real-time automatic sleep stage classification. The client–server architecture adopted here provides an end-to-end solution for anonymizing and efficiently transporting polysomnography data from the client to the server and for receiving sleep stages in an interoperable fashion. The framework intelligently partitions the sleep staging task between the client and server in a way that multiple low-end clients can work with one server, and can be deployed both locally as well as over the cloud. The framework was tested on four datasets comprising 1700 polysomnography records (12000 hr of recordings) collected from adolescents, young, and old adults, involving healthy persons as well as those with medical conditions. We used two independent validation datasets: one comprising patients from a sleep disorders clinic and the other incorporating patients with Parkinson’s disease. Using this system, an entire night’s sleep was staged with an accuracy on par with expert human scorers but much faster (5 s compared with 30–60 min). To illustrate the utility of such real-time sleep staging, we used it to facilitate the automatic delivery of acoustic stimuli at targeted phase of slow-sleep oscillations to enhance slow-wave sleep.
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DOI：
10.1006/cbmr.2000.1549
发表时间：
2000-10-01
期刊：
COMPUTERS AND BIOMEDICAL RESEARCH
影响因子：
--
作者：
Park, HJ;Oh, JS;Park, KS
通讯作者：
Park, KS
影响因子：
5.6
作者：
Malhotra, Atul;Younes, Magdy;Pien, Grace W.
通讯作者：
Pien, Grace W.
影响因子：
16.2
作者：
Ngo, Hong-Viet V.;Martinetz, Thomas;Moelle, Matthias
通讯作者：
Moelle, Matthias
影响因子：
5.6
作者：
Ohayon, MM;Carskadon, MA;Vitiello, MV
通讯作者：
Vitiello, MV
影响因子：
3.2
作者：
Anderer, P;Gruber, G;Dorffner, G
通讯作者：
Dorffner, G