Efficient estimation of a time-varying dimension parameter and its application to EEG analysis

Author

Notley, Scott V. ; Elliott, Stephen J.

Author_Institution

Inst. of Sound & Vibration Res., Univ. of Southampton, Hampshire, UK

Volume

50

Issue

5

fYear

2003

fDate

5/1/2003 12:00:00 AM

Firstpage

594

Lastpage

602

Abstract

Considers the problem of estimating the dimension of nonstationary electroencephalogram (EEG) signals and describes the implementation of an efficient algorithm to calculate a time-varying dimension estimate. The algorithm allows the practical calculation of a dimension estimate and its statistical significance over large data sets with a high temporal resolution. The method is applied to EEG recordings from patients with temporal lobe epilepsy and in one case the results of the analysis are compared with those obtained from an existing method of computing the correlation density.

Keywords

brain models; diseases; electroencephalography; medical signal processing; parameter estimation; signal resolution; time series; time-varying systems; EEG analysis; correlation density; efficient algorithm; epileptic seizures; high temporal resolution; large data sets; nonstationary electroencephalogram signals; statistical significance; temporal lobe epilepsy; time-varying dimension parameter efficient estimation; Brain modeling; Chaos; Electroencephalography; Epilepsy; Performance analysis; Signal analysis; Signal processing; Signal resolution; Stochastic systems; Temporal lobe; Algorithms; Brain Mapping; Computer Simulation; Electroencephalography; Epilepsy, Temporal Lobe; Humans; Models, Neurological; Nonlinear Dynamics; Quality Control; Reproducibility of Results; Sample Size; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Stochastic Processes;

fLanguage

English

Journal_Title

Biomedical Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0018-9294

Type

jour

DOI

10.1109/TBME.2003.810691

Filename

1198249