Entropy-Based Pattern Learning Based on Singular Spectrum Analysis Components for Assessment of Physiological Signals

<div>Statistical results of the values of (a) ApEn, (b) SampEn, (c) FuzzyEn, and (d) MSEn for the first to twentieth SSA components of EMG signals under the aggressive and normal physical actions, which are given as means ± standard errors. The order of the SSA components from 1st to 20th is corresponding to the descending order of magnitude of the twenty eignvalues according to the results of the SSA of EMG signals.</div>

Complexity

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Figure 3: Entropy-Based Pattern Learning Based on Singular Spectrum Analysis Components for Assessment of Physiological Signals 