MCU-Hybrid: An Entropy-Based Real-Time Seizure Detection System Derived from the Universal Consciousness Model

This work introduces MCU-Hybrid, an entropy-based real-time seizure detection system derived from the Universal Consciousness Model (MCU).The system computes a multidimensional instability score from EEG signals, using RMS, spectral entropy, dynamic fluctuation B(t), and median coherence across electrodes.When applied to public and simulated EEG data, MCU-Hybrid anticipates epileptic seizures with a lead time of up to 90 seconds, and demonstrates significant performance (AUC = 0.91).This model is not only a technical contribution, but also the first practical application of the MCU framework to neurodiagnostic use, bridging neuroscience and AI-based consciousness modeling.