ArticleFrontiers in human neuroscience2025
Discriminative power of diverse nonlinear EEG dynamics across consciousness states during auditory stimulation in disorders of consciousness.
Article in Frontiers in human neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- XGBoost Classification of Epileptic EEG Using Nonlinear Dynamical Features and SHAP.Entropy (Basel, Switzerland) · 2026Article
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Abstract
Objective: This study addressed the challenge of assessing consciousness in patients with disorders of consciousness (DOC) using nonlinear dynamic parameters applied to electroencephalogram (EEG) characteristics stimulated by music. Method: EEG signals from 57 patients with DOC at the Rehabilitation Medical Center of the Second Hospital of Shandong University were analyzed using the Lyapunov Exponent (LE), Approximate Entropy (ApEn), Lempel-Ziv Complexity (LZC), and Correlation Dimension (D2). These parameters were then correlated with the total CRS-R score to evaluate their effectiveness. The results indicated that preferred music significantly improved cortical excitability in minimally conscious state (MCS) patients, as evidenced by the ApEn, LZC, and D2 algorithms, but had no significant effect on vegetative state (VS)/unresponsive wakefulness syndrome (UWS) patients. Results: LE, however, showed significant responsiveness in the frontal and middle temporal lobes of patients with VS/UWS. Correlation analysis revealed significant associations between changes in ApEn, LZC, and D2 due to musical stimulation and the total CRS-R score, whereas the LE showed no such correlation. Conclusion: ApEn, LZC, and D2 are valuable for assessing and distinguishing conscious states in patients with DOC, with LE providing supplementary information for patients with VS/UWS. Nonlinear EEG parameters offer promising reference values for effective clinical interventions in DOC.
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