ArticleEntropy (Basel, Switzerland)2026
FuzzyEn Compared to SampEn for Evaluation of Dynamic Complexity.
Article in Entropy (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Fuzzy entropy (FuzzyEn) theoretically outperforms sample entropy (SampEn) in quantifying dynamic complexity; however, its anti-noise robustness remains insufficiently validated. This study compares SampEn and FuzzyEn using model simulations and real-world depression electroencephalogram (EEG) signals. The two entropy metrics are first compared using chaotic time series generated from the logistic and two-dimensional Henon maps, with additive white Gaussian noise (SNRs ranging from 1 to 10 dB). Surrogate data analysis reveals that SampEn maintains stronger nonlinear detection performance (lower than the 2.5th percentiles of surrogate data) under noisy conditions. EEG data from 46 depressed patients and 75 healthy subjects are employed to evaluate SampEn and FuzzyEn, with statistical differences corrected by the Bonferroni method. Depressed patients showed significantly increased EEG complexity in the occipital lobe (PO7, PO5, PO3 channels) under visual stimulation (
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