Evaluation of the Sleep Quality based on bed sensor signals: Time-Variant Analysis

Martin O. Mendez, Matteo Migliorini, Juha M. Kortelainen, Domenino Nistico, Edgar Arce-Santana, Sergio Cerutti, Anna M. Bianchi

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    7 Citations (Scopus)

    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 TVAMLD 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.

    Original languageEnglish
    Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages3994-3997
    Number of pages4
    ISBN (Electronic)978-1-4244-4124-2
    ISBN (Print)978-1-4244-4123-5
    DOIs
    Publication statusPublished - 2010
    MoE publication typeA4 Article in a conference publication
    Event32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
    Duration: 31 Aug 20104 Sep 2010

    Conference

    Conference32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
    Abbreviated titleEMBC'10
    Country/TerritoryArgentina
    CityBuenos Aires
    Period31/08/104/09/10

    Keywords

    • feature extraction
    • sleep
    • indexes
    • heart rate variability
    • accuracy
    • monitoring
    • pathology

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