Rubega, M;
Formaggio, E;
Molteni, F;
Guanziroli, E;
Di Marco, R;
Baracchini, C;
Ermani, M;
... Del Felice, A; + view all
(2021)
EEG Fractal Analysis Reflects Brain Impairment after Stroke.
Entropy
, 23
(5)
p. 592.
10.3390/e23050592.
Preview |
Text
Ward_EEG Fractal Analysis Reflects Brain Impairment after Stroke_VoR.pdf - Published Version Download (7MB) | Preview |
Abstract
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 (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.
Type: | Article |
---|---|
Title: | EEG Fractal Analysis Reflects Brain Impairment after Stroke |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.3390/e23050592 |
Publisher version: | https://doi.org/10.3390/e23050592 |
Language: | English |
Additional information: | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | neurophysiology; stroke; EEG; neuroplasticity; fractal analysis |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10128530 |
Archive Staff Only
![]() |
View Item |