Encoding Polysomnographic Signals into Spike Firing Rate for Sleep Staging

In this work, an encoding of polysomnographic signals into a spike firing rate, based on the BSA algorithm, is used as a discriminant feature for sleep stage classification. This proposal obtains a better sleep staging compared with the mean power signals frequency. Furthermore, a comparison of clas...

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Bibliographic Details
Published inPattern Recognition pp. 282 - 291
Main Authors Valadez, Sergio, Sossa, Humberto, Santiago-Montero, Raúl, Guevara, Elizabeth
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
BSA algorithm
Classification
EEG
EMG
Encoding
EOG
FIR filter
Polysomnogram
Sleep stages
Spike firing rate
Spike train
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Summary:In this work, an encoding of polysomnographic signals into a spike firing rate, based on the BSA algorithm, is used as a discriminant feature for sleep stage classification. This proposal obtains a better sleep staging compared with the mean power signals frequency. Furthermore, a comparison of classification results obtained by different algorithms - such as Support Vector Machines, Multilayer Perceptron, Radial Basis Function Network, Naïve Bayes, K-Nearest Neighbors and the decision tree algorithm C4.5 - is reported, demonstrating that Multilayer Perceptron has the best performance.
ISBN:3319192639
9783319192635
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-19264-2_27