C3 Cube: A Label-Free Hyper Neural Network for ECG Arrhythmia Detection via Emergent Cortical Resonance

We introduce C3 Cube, a biologically-inspired neural architecture achieving arrhythmia detection with zero training, zero labels, and zero backpropagation. Classification emerges from resonance: pathological ECG morphologies trigger propagating activity cascades across a 3×3×3 lattice of HyperNeurons, while normal rhythms remain below the resonance threshold. On a synthetic ECG dataset (MIT-BIH style, 5 classes, 750 samples), C3 Cube achieves 100% accuracy (150/150), matching a supervised MLP baseline requiring 500 training epochs. Full technical disclosure withheld pending provisional patent filing.