Ferree T C, Hwa R C
Department of Radiology and Bioengineering Graduate Group, University of California, San Francisco, CA 94143, USA.
Phys Med Biol. 2005 Sep 7;50(17):3927-39. doi: 10.1088/0031-9155/50/17/001. Epub 2005 Aug 11.
A method of EEG analysis is described which provides new insights into EEG pathology in cerebral ischaemia. The method is based on a variant of detrended fluctuation analysis (DFA), which reduces short (10 s) segments of spontaneous EEG time series to two dimensionless scaling exponents. The spatial variability of each exponent is expressed in terms of its statistical moments across EEG channels. Linear discriminant analysis combines the moments into concise indices, which distinguish normal and stroke groups remarkably well. On average over the scalp, stroke patients have larger fluctuations on the longest time scales. This is consistent with the notion of EEG slowing, but extends that notion to a wider range of time scales. The higher moments show that stroke patients have markedly reduced variability over the scalp. This contradicts the notion of a purely focal EEG scalp topography and argues instead for a highly distributed effect. In these indices, subacute patients appear further from normal than acute patients.