Real-time 3D cardiac tissue implementation for arrhythmia detection and management

This paper presents a high-performance, real-time hardware implementation of 3D cardiac tissue for the detection and management of complex arrhythmias.

Utilizing the Aliev-Panfilov reaction-diffusion model, we simulate electrical wave propagation in a 200×200×3 lattice comprising 120,000 nodes. To achieve real-time performance on a Xilinx Virtex-7 Field-Programmable Gate Array (FPGA), we developed a massively parallel architecture based on a multi-precision fixed-point arithmetic framework. This approach ensures high physiological fidelity with a Mean Squared Error (MSE) of 10 compared to 64-bit floating-point simulations, while significantly optimizing resource utilization.

Operating at 125 MHz, the proposed processor achieves a full lattice update in 0.96 ms, providing a 56-fold acceleration margin over biological real-time dynamics. Furthermore, the system incorporates a hardware-level supervisory layer that monitors wave-break density and dominant frequency to classify cardiac states into Periodic Spiral (PS), Quasi-Periodic (QS), and Spiral Turbulence (ST).

This "digital twin-inspired framework" framework enables sub-millisecond, closed-loop therapeutic interventions, facilitating the autonomous management of life-threatening arrhythmic conditions with a total power consumption of 5.42 W.