PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Physiological Data Classification 0500680.4.
Iead Rezek


In this patent we use a model which generalises the autoregressive class of polyspectral models by having a semi-parametric description of the residual probability density. We estimate the model in the Variational Bayesian framework and extract higher order spectral features. Testing their importance for depth of anaesthesia classification is done on three different EEG data sets collected under exposure to different agents. The results show that significant improvements can be made with higher order spectral features.

EPrint Type:Patent
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
ID Code:1123
Deposited By:Iead Rezek
Deposited On:13 October 2005