ETD

Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-09192016-170443

Tipo di tesi

Tesi di laurea magistrale

URN

etd-09192016-170443

Titolo

Computational modeling and analysis of ECoG data through Support Vector Machines algorithms.

Dipartimento

INGEGNERIA DELL'INFORMAZIONE

Corso di studi

INGEGNERIA BIOMEDICA

Parole chiave

ECoG
Machine Learning
Multivariate Analysis
SVM

Data inizio appello

07/10/2016

Consultabilità

Non consultabile

Data di rilascio

07/10/2086

Riassunto (Inglese)

Riassunto (Italiano)

In this work some ElectoCorticography data has been taken in account, a multivariate analysis has been proposed considering spatial and time-frequency features. The Dataset has been recorded following the Recalibration and Adaptation paradigm about ambigous and not-ambigous audio-visual stimulation. A classification between these two conditions through a Support Vector Machine algorithm using a RBF kernel has been implemented. An intra- and inter- subject discussion of the results will close the dissertation.

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