NDLI: Evaluation of the sleep quality based on bed sensor signals: Time-variant analysis

Content Provider	IEEE Xplore Digital Library
Author	Mendez, M.O. Migliorini, M. Kortelainen, J.M. Nistico, D. Arce-Santana, E. Cerutti, S. Bianchi, A.M.
Copyright Year	2010
Description	Author affiliation: Dept. of Biomedical Engineering, Politecnico di Milano, Piazza. Leonardo da Vinci 32, Italy (Migliorini, M.; Nistico, D.; Cerutti, S.; Bianchi, A.M.) \|\| Machine Vision, VTT Technical Research Center of Finland, Tampere, Finland (Kortelainen, J.M.) \|\| Facultad de Ciencias, Diagonal Sur S/N, Zona Universitaria, San Luis Potosi, Mexico (Mendez, M.O.; Arce-Santana, E.)
Abstract	Automatic detection of the sleep macrostructure (Wake, NREM -non Rapid Eye Movement- and REM -Rapid Eye Movement-) based on bed sensor signals is presented. This study assesses the feasibility of different methodologies to evaluate the sleep quality out of sleep centers. The study compares a) the features extracted from time-variant autoregressive modeling (TVAM) and Wavelet Decomposition (WD) and b) the performance of K-Nearest Neighbor (KNN) and Feed Forward Neural Networks (FFNN) classifiers. In the current analysis, 17 full polysomnography recordings from healthy subjects were used. The best agreement for Wake-NREM-REM with respect to the gold standard was 71.95 ± 7.47% of accuracy and 0.42 ± 0.10 of kappa index for TVAM-LD while WD-FFNN shows 67.17 ± 11.88% of accuracy and 0.39 ± 0.13 of kappa index. The results suggest that the sleep quality assessment out of sleep centers could be possible and as consequence more people could be beneficiated.
Starting Page	3994
Ending Page	3997
File Size	581193
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5628005
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Sleep Indexes Heart rate variability Accuracy Monitoring Pathology
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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