An end-to-end framework for real-time automatic sleep stage classification-Reference-Cited by-同舟云学术

An end-to-end framework for real-time automatic sleep stage classification

Published:2018-03-26 Issue:5 Volume:41 Page:
ISSN:0161-8105
Container-title:Sleep
language:en
Short-container-title:

Author:

Patanaik Amiya¹^ORCID,Ong Ju Lynn¹,Gooley Joshua J¹,Ancoli-Israel Sonia²,Chee Michael W L¹

Affiliation:

1. Centre for Cognitive Neuroscience, Neuroscience and Behavioral Disorders Program, Duke-NUS Medical School, Singapore

2. University of California, San Diego School of Medicine, San Diego, CA

Funder

National Medical Research Council

Defence Science and Technology Agency - Singapore

The Far East Organization

Publisher

Oxford University Press (OUP)

Subject

Physiology (medical),Neurology (clinical)

Link

http://academic.oup.com/sleep/article-pdf/41/5/zsy041/25092991/zsy041.pdf

Reference40 articles.

1. Interrater reliability for sleep scoring according to the Rechtschaffen & Kales and the new AASM standard;Danker-Hopfe;J Sleep Res,2009

2. An E-health solution for automatic sleep classification according to Rechtschaffen and Kales: validation study of the Somnolyzer 24 x 7 utilizing the Siesta database;Anderer;Neuropsychobiology,2005

3. Automated sleep–wake staging combining robust feature extraction, artificial neural network classification, and flexible decision rules;Chapotot;Int J Adapt Control Signal Process,2010

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