ArticleFrontiers in neuroscience2021
Markers of Central Neuropathic Pain in Higuchi Fractal Analysis of EEG Signals From People With Spinal Cord Injury.
Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- An Exploratory EEG Analysis on the Effects of Virtual Reality in People with Neuropathic Pain Following Spinal Cord Injury.Sensors (Basel, Switzerland) · 2022Trial
- Efficient Blended Models for Analysis and Detection of Neuropathic Pain from EEG Signals Using Machine Learning.Bioengineering (Basel, Switzerland) · 2026Article
- Normative Modeling of EEG Complexity Reveals Cortical Rigidity Associated with Pain Severity in Chronic Pain.Journal of pain research · 2026Article
- Generalisation of EEG-Based Pain Biomarker Classification for Predicting Central Neuropathic Pain in Subacute Spinal Cord Injury.Biomedicines · 2025Article
- Entropy, complexity, and spectral features of EEG signals in autism and typical development: a quantitative approach.Frontiers in psychiatry · 2025Article
- Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals.Cognitive neurodynamics · 2024Article
- Fractal Similarity of Pain Brain Networks.Advances in neurobiology · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Central neuropathic pain (CNP) negatively impacts the quality of life in a large proportion of people with spinal cord injury (SCI). With no cure at present, it is crucial to improve our understanding of how CNP manifests, to develop diagnostic biomarkers for drug development, and to explore prognostic biomarkers for personalised therapy. Previous work has found early evidence of diagnostic and prognostic markers analysing Electroencephalogram (EEG) oscillatory features. In this paper, we explore whether non-linear non-oscillatory EEG features, specifically Higuchi Fractal Dimension (HFD), can be used as prognostic biomarkers to increase the repertoire of available analyses on the EEG of people with subacute SCI, where having both linear and non-linear features for classifying pain may ultimately lead to higher classification accuracy and an intrinsically transferable classifier. We focus on EEG recorded during imagined movement because of the known relation between the motor cortex over-activity and CNP. Analyses were performed on two existing datasets. The first dataset consists of EEG recordings from able-bodied participants (
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