http://www.cnr.it/ontology/cnr/individuo/prodotto/ID325736
Multidimensional analysis of EEG features using advanced spectral estimates for diagnosis accuracy (Contributo in atti di convegno)
- Type
- Label
- Multidimensional analysis of EEG features using advanced spectral estimates for diagnosis accuracy (Contributo in atti di convegno) (literal)
- Anno
- 2013-01-01T00:00:00+01:00 (literal)
- Alternative label
Lay-Ekuakille A., Vergallo P., Griffo G., Urooj S., Bhateja V., Conversano F., Casciaro S., Trabacca A. (2013)
Multidimensional analysis of EEG features using advanced spectral estimates for diagnosis accuracy
in 8th IEEE International Symposium on Medical Measurements and Applications (MeMeA), Gatineau, CANADA, 4-5 Maggio 2013
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Lay-Ekuakille A., Vergallo P., Griffo G., Urooj S., Bhateja V., Conversano F., Casciaro S., Trabacca A. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- 2013 IEEE INTERNATIONAL SYMPOSIUM ON MEDICAL MEASUREMENTS AND APPLICATIONS PROCEEDINGS (MEMEA) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Department of Innovation Engineering, University of Salento, Lecce, Italy; Dept of Electrical Eng./Dept of Electronics & Comm., Gautam Buddha University/SRM University, Greater-Noida (U.P.)/Lucknow-Deva (U.P.), India; National Council of Research, Institute of Clinical Physiology, Lecce, Italy; IRCCS \"E. Medea\", Scientific Institute for Research Hospitalization and Health Care - Ass. La Nostra Famiglia, Brindisi, Italy (literal)
- Titolo
- Multidimensional analysis of EEG features using advanced spectral estimates for diagnosis accuracy (literal)
- Abstract
- Electroencephalogram (EEG) is a source of
interesting information if one is able to extract them according
to appropriate techniques. The conditions of individual under
EEG test is a key issue. In general, EEG feature extraction can
be associated to other information like Electrocardiogram
(ECG), ergospirometry and electromyogram (EMG). However,
in some cases, a multidimensional representation is used;
bispectrum is an example of such a representation. HOS (high
order statistics), for instance, include the bispectrum and the
trispectrum (third and fourth order statistics, respectively).
Advanced estimate spectral analysis can reveal new
information encompassed in EEG signals. That is the reason
the author propose an algorithm based on DSD (Decimated
Signal Diagonalization) that is able of processing exponentially
dumped signals like those that regard EEG features. The
version proposed here is a multidimensional one. (literal)
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