Low-cost low-power acceleration of a microwave imaging algorithm for brain stroke monitoring

Microwave imaging can effectively image the evolution of a hemorrhagic stroke thanks to the dielectric contrast between the blood and the surrounding brain tissues. To keep low both the form factor and the power consumption in a bedside device, we propose implementing a microwave imaging algorithm for stroke monitoring in a programmable system-on-chip, in which a simple ARM-based CPU offloads to an FPGA the heavy part of the computation. Compared to a full-software implementation in the ARM CPU, we obtain a 5× speed increase with hardware acceleration without loss in accuracy and precision.