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Technological Innovation for the Internet of Things 4th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013, Costa de Caparica, Portugal, April 15-17, 2013. Proceedings |
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Conference papers
ARMA Modelling for Sleep Disorders Diagnose
Abstract : Differences in EEG sleep spindles constitute a promising indicator of sleep disorders. In this paper Sleep Spindles are extracted from real EEG data using a triple (Short Time Fourier Transform-STFT; Wavelet Transform-WT; Wave Morphology for Spindle Detection-WMSD) algorithm. After the detection, an Autoregressive–moving-average (ARMA) model is applied to each Spindle and finally the ARMA’s coefficients’ mean is computed in order to find a model for each patient. Regarding only the position of real poles and zeros, it is possible to distinguish normal from Parasomnia REM subjects.
Cited literature [7 references]
https://hal.archives-ouvertes.fr/hal-01348764
Contributor : Hal Ifip <>
Submitted on : Monday, July 25, 2016 - 4:29:32 PM
Last modification on : Monday, July 25, 2016 - 4:46:20 PM
Contributor : Hal Ifip <>
Submitted on : Monday, July 25, 2016 - 4:29:32 PM
Last modification on : Monday, July 25, 2016 - 4:46:20 PM
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