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...
Main Authors: | Shirin Najdi, Ali Abdollahi Gharbali, José Manuel Fonseca |
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Format: | Article |
Language: | English |
Published: |
BMC
2017-08-01
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Series: | BioMedical Engineering OnLine |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12938-017-0358-3 |
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