Ontology highlight
ABSTRACT:
SUBMITTER: Malafeev A
PROVIDER: S-EPMC6232272 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
Frontiers in neuroscience 20181106
The classification of sleep stages is the first and an important step in the quantitative analysis of polysomnographic recordings. Sleep stage scoring relies heavily on visual pattern recognition by a human expert and is time consuming and subjective. Thus, there is a need for automatic classification. In this work we developed machine learning algorithms for sleep classification: random forest (RF) classification based on features and artificial neural networks (ANNs) working both with features ...[more]