Complex-valued spatial filters for task discrimination

Abstract

The method of common spatial patterns (CSP)

has been widely adopted for the discrimination of mental

tasks using EEG data. In this paper, some limitations of the

standard CSP implementation when considering data where

phase relationships play a significant role are highlighted.

Furthermore, a variant of the CSP method based on the

analytic representation of signals is proposed to make up

for these drawbacks. The advantages of the proposed method

over the standard CSP implementation are demonstrated using

simulated data and tests with real EEG data. Specifically, it is

shown that the complex-valued spatial filters and the derived

spatial patterns can improve the discrimination process and give

a more adequate representation of the tasks being considered,

respectively.