Title :
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
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;
Conference_Titel :
Bioengineering Conference, 1991., Proceedings of the 1991 IEEE Seventeenth Annual Northeast
Conference_Location :
Hartford, CT
Print_ISBN :
0-7803-0030-0
DOI :
10.1109/NEBC.1991.154569
