Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study

Abstract Background Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual p...

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Bibliographic Details
Main Authors: Shirin Najdi, Ali Abdollahi Gharbali, José Manuel Fonseca
Format: Article
Language:English
Published: BMC 2017-08-01
Series:BioMedical Engineering OnLine
Subjects:
Sleep stage classification
Feature selection
Rank aggregation
Feature ranking
Polysomnography
Biomedical signal processing
Online Access:http://link.springer.com/article/10.1186/s12938-017-0358-3

Internet

http://link.springer.com/article/10.1186/s12938-017-0358-3

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