title: 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.
authors.affiliation: Department of Systems and Control Engineering, Faculty of Engineering, University of Malta, Msida, Malta. owen.falzon@um.edu.mt
authors.forename: Owen
authors.initials: O
authors.lastname: Falzon
authors.forename: Kenneth P
authors.initials: KP
authors.lastname: Camilleri
authors.forename: Joseph
authors.initials: J
authors.lastname: Muscat
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D006801:Humans; D007092:Imagination / Q000502:physiology*; D009044:Motor Cortex / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013647:Task Performance and Analysis