Joint spatial and spectral filter estimation for single trial detection of event related potentials

Author

Ghaderi, Foad

Author_Institution

Robot. Group, Univ. of Bremen, Bremen, Germany

fYear

2013

fDate

22-25 Sept. 2013

Firstpage

1

Lastpage

6

Abstract

It is usually assumed that the main frequency components of ERPs are in some specific frequency bands. Therefore, predefined cutoff frequencies are used to filter the raw data in different applications. Here, an extension of the periodic spatial filter method is proposed that jointly learns spatial filters and the corresponding FIR filters to be used for single trial ERP detection. Experimental results confirm that the proposed spatio-spectral filtering method outperforms its predecessor spatial filter.

Keywords

FIR filters; bioelectric potentials; electroencephalography; medical signal processing; optical filters; spatial filters; ERP detection; FIR filters; electroencephalogram; event related potentials; frequency bands; frequency components; periodic spatial filter method; predefined cutoff frequencies; raw data filter; single trial detection; spatial filters; spatio-spectral filtering; spectral filter estimation; Covariance matrices; Cutoff frequency; Eigenvalues and eigenfunctions; Electroencephalography; Finite impulse response filters; Noise; Vectors; ERP detection; Electroencephalogram; periodic spatial filter; spatio-spectral filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning for Signal Processing (MLSP), 2013 IEEE International Workshop on

Conference_Location

Southampton

ISSN

1551-2541

Type

conf

DOI

10.1109/MLSP.2013.6661938

Filename

6661938