EEG Fractal Analysis Reflects Brain Impairment after Stroke
- Rubega, M
- Formaggio, E
- Molteni, F
- Guanziroli, E
- Di Marco, R
- Baracchini, C
- Ermani, M
- Ward, NS
- Masiero, S
- Del Felice, A
DOIAbstract
Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (similar to 1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after similar to 2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, T...
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