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Author Xi Long ♦ Foussier, J. ♦ Fonseca, P. ♦ Haakma, R. ♦ Aarts, R.M.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2013
Language English
Subject Domain (in DDC) Technology ♦ Medicine & health ♦ Engineering & allied operations
Subject Keyword Member and Geographic Activities Board committees ♦ Sleep apnea ♦ Feature extraction ♦ Electrocardiography ♦ Heart rate variability ♦ Accuracy
Abstract In previous work, single-night polysomnography recordings (PSG) of respiratory effort and electrocardiogram (ECG) signals combined with actigraphy were used to classify sleep and wake states. In this study, we aim at classifying rapid-eye-movement (REM) and non-REM (NREM) sleep states. Besides the existing features used for sleep and wake classification, we propose a set of new features based on respiration amplitude. This choice is motivated by the observation that the breathing pattern has a more regular amplitude during NREM sleep than during REM sleep. Experiments were conducted with a data set of 14 healthy subjects using a linear discriminant (LD) classifier. Leave-one-subject-out cross-validations show that adding the new features into the existing feature set results in an increase in Cohen's Kappa coefficient to a value of κ = 0.59 (overall accuracy of 87.6%) compared to that obtained without using these features (κ of 0.54 and overall accuracy of 86.4%). In addition, we compared the results to those reported in some other studies with different features and signal modalities.
Description Author affiliation: Dept. of Electr. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands (Xi Long; Fonseca, P.; Aarts, R.M.) || Philips Res., Eindhoven, Netherlands (Haakma, R.) || Med. Inf. Technol., RWTH Aachen Univ., Aachen, Germany (Foussier, J.)
ISBN 9781457702167
ISSN 1557170X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-07-03
Publisher Place Japan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 178.44 kB
Page Count 4
Starting Page 5017
Ending Page 5020


Source: IEEE Xplore Digital Library