A Novel Approach for Sleep Arousal Disorder Detection Based on the Interaction of Physiological Signals and Metaheuristic Learning

<div>Based on AD, Jaccard, and AD-Jaccard calculations for ECG and EEG signals, the effect of characteristics in crucial stages of the sleep transition (from class 1 to class 4, respectively) was evaluated.</div>

Computational Intelligence and Neuroscience

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Figure 10

Figure 10: A Novel Approach for Sleep Arousal Disorder Detection Based on the Interaction of Physiological Signals and Metaheuristic Learning 