ARX filtering of single-sweep movement-related brain macropotentials in mono- and multi-channel recordings

L. Capitanio, G. C. Filligoi, D. Liberati, S. Cerutti, F. Babiloni, L. Fattorini, A. Urbano

Research output: Contribution to journalArticlepeer-review

Abstract

A technique of stochastic parametric identification and filtering is applied to the analysis of single-sweep event-related potentials. This procedure, called AutoRegressive with n eXogenous inputs (ARXn), models the recorded signal as the sum of n+1 signals: the background EEG activity, modeled as an autoregressive process driven by white noise, and n signals, one of which represents a filtered version of a reference signal carrying the average information contained in each sweep. The other (n-1) signals could represent various sources of noise (i.e., artifacts, EOG, etc.). An evaluation of the effects of both artifact suppression and accurate selection of the average signal on mono- or multi-channel scalp recordings is presented.

Original languageEnglish
Pages (from-to)28-31
Number of pages4
JournalMethods of Information in Medicine
Volume33
Issue number1
Publication statusPublished - 1994

Keywords

  • Event-Related Potentials
  • Movement Related Brain Macropotentials
  • Single-Sweep Analysis

ASJC Scopus subject areas

  • Health Informatics
  • Nursing(all)
  • Health Information Management

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