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 (STFT, WT and WMSD) algorithm; this algorithm is reported to have sensitivity and a specificity of 94%. After the detection, an 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.
|Title of host publication||IFIP Advances in Information and Communication Technology|
|Publication status||Published - 1 Jan 2013|
|Event||4th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013 - |
Duration: 1 Jan 2013 → …
|Conference||4th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013|
|Period||1/01/13 → …|