Common Spatial Pattern for EEG Signals

1. What are spatial filters in EEG?
2. How common spatial pattern works?
3. Is CSP supervised?

What are spatial filters in EEG?

The spatial filter is applied to the EEG data before the estimation of the power spectrum. As it is referred by McFarland [7], the surface Laplacian is the most appropriate technique to filter the EEG data spatially. It provides an estimate of the local radial (normal) current density through the skull into the scalp.

How common spatial pattern works?

The common spatial patterns (CSP) algorithm is a feature extraction method that uses spatial filters to maximize the discriminability of two classes. CSP algorithm has been widely used for feature extraction in EEG-based BCI systems for motor imagery (MI) [14,15].

Is CSP supervised?

Abstract. Common Spatial Patterns (CSP) is a widely used spatial filtering technique for electroencephalography (EEG)-based brain-computer interface (BCI). It is a two-class supervised technique that needs subject-specific training data.