title: Reference estimation in EEG recordings.
abstract: This work aims to analyze the reference (montage) problem in electroencephalographic (EEG) recordings. It is well accepted that EEG signals are a mixture of cerebral and extracerebral sources, and the solution to the reference problem depends on the hypothesized mixing model. We focus here on an acquisition model using a distant reference electrode and propose a method for determining and eliminating the reference signal which develops and improves Hu et al. work from [1]. The obtained solution, based on a constrained blind source separation (BSS) algorithm, outperforms the cited method on simulated noisy EEG signals for all noise levels.
authors.affiliation: Centre de Recherche en Automatique de Nancy (CRAN UMR 7039), Nancy-Université - CNRS 2 avenue de la Forêt de Haye, F-54500 Vandoeuvre-les-Nancy, France. radu.ranta@ensem.inpl-nancy.fr
authors.forename: R
authors.initials: R
authors.lastname: Ranta
authors.forename: R
authors.initials: R
authors.lastname: Salido-Ruiz
authors.forename: V
authors.initials: V
authors.lastname: Louis-Dorr
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004566:Electrodes; D004569:Electroencephalography / Q000379:methods* / Q000592:standards*; D006801:Humans; D012015:Reference Standards