Dynamic cross-spectral analysis of event-related EEG using ensemble averages

Author

Florian, Gernot ; Pfurtscheller, Gert

Author_Institution

Dept. of Med. Inf., Graz Univ. of Technol., Austria

Volume

2

fYear

1995

fDate

20-23 Sep 1995

Firstpage

883

Abstract

A method of investigating the dynamic cross-spectral properties of event-related EEG is reported. A sequence of multivariate autoregressive models is fitted to segments of the EEG within which the data exhibit local stationarity. For estimation a procedure involving ensemble averages is presented. Time courses of autospectra and coherence are derived from the multivariate models. The method is applied to event-related EEG recorded from primary and supplementary motor areas during externally triggered finger movements

Keywords

autoregressive processes; electroencephalography; medical signal processing; physiological models; spectral analysis; autospectra; dynamic cross-spectral analysis; electrodiagnostics; ensemble averages; event-related EEG; externally triggered finger movements; local stationarity; multivariate models; primary motor area; supplementary motor area; Biomedical engineering; Biomedical informatics; Brain modeling; Covariance matrix; Data analysis; Electroencephalography; Equations; Fingers; Matrices; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference

Conference_Location

Montreal, Que.

Print_ISBN

0-7803-2475-7

Type

conf

DOI

10.1109/IEMBS.1995.579252

Filename

579252