Respiration amplitude analysis for REM and NREM sleep classification

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Samenvatting

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 kappa = 0.59 (overall accuracy of 87.6%) compared to that obtained without using these features (kappa 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.
Originele taal-2Engels
TitelProceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'13), 2-7 September, Osaka, Japan
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's5017-5020
ISBN van geprinte versie978-1-4577-0216-7
DOI's
StatusGepubliceerd - 2013
Evenement35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013) - Osaka, Japan
Duur: 3 jul 20137 jul 2013
Congresnummer: 35

Congres

Congres35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013)
Verkorte titelEMBC 2013
LandJapan
StadOsaka
Periode3/07/137/07/13
AnderThe 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Citeer dit

Long, X., Foussier, J., Fonseca, P., Haakma, R., & Aarts, R. M. (2013). Respiration amplitude analysis for REM and NREM sleep classification. In Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'13), 2-7 September, Osaka, Japan (blz. 5017-5020). Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2013.6610675