ArticleEntropy (Basel, Switzerland)2021
EEG Fractal Analysis Reflects Brain Impairment after Stroke.
Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Spike dynamics in primate lateral prefrontal cortex during working memory and decision-making: A fractal analysis.iScience · 2026Article
- Non-linear and spectral EEG dynamics as stage-specific biomarkers of neuropsychological recovery post-stroke.Frontiers in neuroscience · 2026Article
- Clinical feasibility of motor hotspot localization based on electroencephalography using convolutional neural networks in stroke.Journal of neuroengineering and rehabilitation · 2025Article
- Post-stroke spontaneous motor recovery in mice can be predicted from acute-phase local field potential using machine learning.APL bioengineering · 2025Article
- EEG Microstates as a Signature of Hemispheric Lateralization in Stroke.Brain topography · 2024Article
- Article
- RSBagging: An ensemble classifier detecting the after-effects of ischemic stroke through EEG connectivity and microstates.PloS one · 2024Article
- Experimental protocol to investigate cortical, muscular and body representation alterations in adolescents with idiopathic scoliosis.PloS one · 2023Article
- Frequency-tuned electromagnetic field therapy improves post-stroke motor function: A pilot randomized controlled trial.Frontiers in neurology · 2022Article
- Experimental Protocol to Assess Neuromuscular Plasticity Induced by an Exoskeleton Training Session.Methods and protocols · 2021Article
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
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.
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Registered trials
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