Real-time reconstruction of footprint positions using an "intelligent carpet" imaging sensor

Fast real-time reconstruction of the position of footprints on an "intelligent carpet" sensor is achieved on a Field-Programmable Gate Array (FPGA) by parallel computation based on the previously introduced Parallel Center-of-Mass Algorithm (PCoMA). Its performance with synthetic data (numerical phantoms) as well as with data measured with a Photonic Guided-Path Tomography (PGPT) sensor head shows that position error in the order of 10-2 is achievable at tens of kHz frame rate. Additional data processing is possible on the unused FPGA resources to allow efficient streaming of sensor information. This suggests that low-cost, large area PGPT floor sensors can be installed and used in community environments for unobtrusive long-term monitoring of gait stability and changes with age or due the onset of illness.