Automatic detection of overnight deep sleep based on heart rate variability : a preliminary study

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Samenvatting

This preliminary study investigated the use of cardiac information or more specifically, heart rate variability (HRV), for automatic deep sleep detection throughout the night. The HRV data can be derived from cardiac signals, which were obtained from polysomnography (PSG) recordings. In total 42 features were extracted from the HRV data of 15 single-night PSG recordings (from 15 healthy subjects) for each 30-s epoch, used to perform epoch-by-epoch classification of deep sleep and non-deep sleep (including wake state and all the other sleep stages except deep sleep). To reduce variation of cardiac physiology between subjects, we normalized each feature per subject using a simple Z-score normalization method by subtracting the mean and dividing by the standard deviation of the feature values. A correlation-based feature selection (CFS) method was employed to select informative features as well as removing feature redundancy and a linear discriminant (LD) classifier was applied for deep and non-deep sleep classification. Results show that the use of Z-score normalization can significantly improve the classification performance. A Cohen's Kappa coefficient of 0.42 and an overall accuracy of 81.3% based on a leave-one-subject-out cross-validation were achieved.
Originele taal-2Engels
TitelProceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'14), 26-30 August 2014, Chicago, Illinois
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's50-53
ISBN van geprinte versie978-1-4244-7929-0
DOI's
StatusGepubliceerd - 2014
Evenement36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014) - Chicago, Verenigde Staten van Amerika
Duur: 26 aug 201430 aug 2014
Congresnummer: 36

Congres

Congres36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014)
Verkorte titelEMBC 2014
LandVerenigde Staten van Amerika
StadChicago
Periode26/08/1430/08/14
AnderEMBC 2014, Chicago, USA

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Citeer dit

Long, X., Fonseca, P., Haakma, R., Foussier, J., & Aarts, R. M. (2014). Automatic detection of overnight deep sleep based on heart rate variability : a preliminary study. In Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'14), 26-30 August 2014, Chicago, Illinois (blz. 50-53). Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/EMBC.2014.6943526