Spiral wave control via dynamic learning optimized photon scanning approach

Optogenetics holds immense potential for modulating arrhythmias, yet its application is constrained by the difficulty in localizing the core of spiral waves, with inadequate optical stimulation often inducing wave breakup. The photon-scanning approach eliminates spiral waves by scanning a light stripe, anchoring the spiral wave core, and guiding the core to drift toward the medium boundary. This novel approach eliminates spiral waves without the need for accurate core localization and tissue properties, thereby overcoming the limitations of conventional approaches. This paper proposes an approach using dynamic learning to optimize photon scanning (DLOPS) through integrating photon scanning with the dynamic learning of synchronization techniques. The DLOPS approach eliminates spiral waves in various tissues by adjusting the illuminated area and intensity to reduce the number of activated LEDs. Simulation results indicate that compared to the original photon scanning approach, the DLOPS approach can reduce optical energy consumption by 50% to 85%. Additionally, we propose a “sandwich scanning approach” under challenging periodic boundary conditions, which successfully suppresses wave diffusion and reduces the energy consumption to levels comparable with those under no-flow boundary conditions. Finally, the DLOPS approach exhibits high robustness even in complex heterogeneous tissues. The DLOPS approach proposed in this paper could provide new insights for future research into arrhythmia treatment, thereby offering a novel low-energy and high-efficiency solution.