Optimizing and invigilation of neurological disorder analysis with signal pattern multiscale modeling via fractional operator

Abstract

This study develops a multiscale fractional-order model for Alzheimer's Disease (AD), capturing the interplay between neuroinflammation, amyloid-β dynamics and Blood-Brain Barrier (BBB) dysfunction. Using Caputo fractional derivatives, we model memory effects and anomalous diffusion in AD progression. The model's positivity, boundedness and stability are analytically proven. Optimal control strategies reveal that targeting amyloid-β pathways and BBB integrity significantly mitigates disease progression. Numerical simulations, validated via a predictor-corrector method, demonstrate the efficacy of adaptive therapies. Our findings highlight the potential of fractional-order models in designing targeted AD treatments.