Detection of EEG transients by changes in dimensional complexity

Author

Simon, Richard H. ; Arle, Jeffrey E.

Author_Institution

Div. of Neurosurg., Connecticut Univ. Health Center, Farmington, CT, USA

fYear

1991

fDate

4-5 Apr 1991

Firstpage

37

Abstract

Summary form only given. A simple box accounting algorithm is applied to measure the fractal dimension of electroencephalography (EEG). Artificial transients of varying EEG characteristics are embedded. The change is noted in the fractal dimension within a window that is passed along the entire time series. Three embedded evoked potential spikes 100 ms apart buried anywhere in the time series are detected. Their presence is reflected in a significant change of a fractal dimension from 1.70 to 1.76. Both the power spectra and the autocorrelation functions of the same recordings were studied and no difference between the intervals that contain the transient and those which do not was observed

Keywords

electroencephalography; fractals; waveform analysis; 100 ms; autocorrelation functions; dimensional complexity; electroencephalography; embedded evoked potential spikes; fractal dimension; power spectra; simple box accounting algorithm; Autocorrelation; Change detection algorithms; Chaos; Electroencephalography; Filtering; Fractals; Neurosurgery; Pattern recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 1991., Proceedings of the 1991 IEEE Seventeenth Annual Northeast

Conference_Location

Hartford, CT

Print_ISBN

0-7803-0030-0

Type

conf

DOI

10.1109/NEBC.1991.154569

Filename

154569