Harmonic Hidden Markov Models for the Study of EEG Signals - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2010

Harmonic Hidden Markov Models for the Study of EEG Signals

Résumé

A new approach for modelling multichannel signals via hidden states models in the time-frequency space is described. Multichannel signals are expanded using a local cosine basis, and the (time-frequency labelled) coefficients are modelled as multivariate random variables, whose distribution is governed by a (hidden) Markov chain. Several models are described, together with maximum likelihood estimation algorithms. The model is applied to electroencephalogram data, and it is shown that variance-covariance matrices labelled by sensor and frequency indices can yield relevant informations on the analyzed signals. This is examplified by a case study on the characterization of alpha waves desynchronization in the context of multiple sclerosis disease.
Fichier principal
Vignette du fichier
1569292597.pdf (317.41 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00492800 , version 1 (17-06-2010)

Identifiants

  • HAL Id : hal-00492800 , version 1

Citer

Bruno Torrésani, Emilie Villaron. Harmonic Hidden Markov Models for the Study of EEG Signals. EUSIPCO 2010, Aug 2010, Aalborg, Denmark. ⟨hal-00492800⟩
166 Consultations
209 Téléchargements

Partager

Gmail Mastodon Facebook X LinkedIn More