A template-based method for the estimation of Event Related Potentials using the Bayesian linear model

Author

Oikonomou, Vangelis P. ; Fotiadis, Dimitrios I.

Author_Institution

Dept. of Comput. Sci., Univ. of Ioannina, Ioannina, Greece

fYear

2009

fDate

5-7 July 2009

Firstpage

1

Lastpage

6

Abstract

In this work a method for the estimation of Event Related Potentials (ERPs) using the linear model is presented. The method consists of two stages. In the first stage, a template is constructed using the averaged ERP. From this template the design matrix of the linear model is extracted. The second stage is related to the estimation of the coefficients of the linear model. In this stage the Bayesian approach is used. However, in our problem the posterior distribution is not easily evaluated and there is need to resort in approximation techniques. One such approach is the Variational Bayesian Methodology. In our study, two prior distributions are used to estimate the ERP. This results in two estimation algorithms having different properties for the coefficients of the linear model. The proposed method is tested in simulated and real ERP data.

Keywords

Bayes methods; bioelectric potentials; matrix algebra; neurophysiology; Bayesian linear model; approximation technique; design matrix; electrophysiological potential; estimation algorithms; event related potentials; nervous system; real ERP data; simulated ERP data; template-based method; variational Bayesian methodology; Bayesian methods; Brain modeling; Computer science; Discrete wavelet transforms; Electroencephalography; Enterprise resource planning; Information systems; Intelligent systems; Noise reduction; Signal to noise ratio; Event Related Potentials; Lineal Model; Variational Bayesian Methodology;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Signal Processing, 2009 16th International Conference on

Conference_Location

Santorini-Hellas

Print_ISBN

978-1-4244-3297-4

Electronic_ISBN

978-1-4244-3298-1

Type

conf

DOI

10.1109/ICDSP.2009.5201150

Filename

5201150