@inproceedings{f9889efa91ad4bc08d46a528a13df5db,
title = "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{\textquoteright}s coefficients{\textquoteright} 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.",
keywords = "ARMA, EEG, Parasomnia REM, Sleep Spindles",
author = "Costa, {Jo{\~a}o Caldas Da} and Ortigueira, {Manuel Duarte} and Arnaldo Batista and Teresa Paiva",
year = "2013",
doi = "10.1007/978-3-642-37291-9_29",
language = "English",
isbn = "978-3-642-37290-2",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer",
pages = "271--278",
editor = "Camarinha-Matos, {L. M.} and S. Tomic and P. Gra{\c c}a",
booktitle = "Technological Innovation for the Internet of Things. DoCEIS 2013",
address = "Netherlands",
note = "4th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013 ; Conference date: 15-04-2013 Through 17-04-2013",
}