A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.

Comparison of the predictability of refractive cylinder correction by laser in situ keratomileusis in eyes with low or high ocular residual astigmatism

Purpose: To compare the manifest refractive cylinder (MRC) predictability of myopic astigmatism laser in situ keratomileusis (LASIK) between eyes with low and high ocular residual astigmatism (ORA). Setting: London Vision Clinic, London, United Kingdom. Design: Retrospective case study. Methods: The ORA was considered the vector difference between the MRC and the corneal astigmatism. The index of success (IoS), difference vector ÷ MRC, was analyzed for different groups as follows: stage 1, low ORA (ORA ÷ MRC <1), high ORA (ORA ÷ MRC ≥1); stage 2, low ORA group reduced to match the high ORA group for MRC; stage 3, grouped by ORA magnitude with low ORA (<0.50 diopters [D]), mid ORA (0.50 to 1.24 D), and high ORA (≥1.25 D); stage 4, high ORA group subdivided into low (<0.75 D) and high (≥0.75 D) corneal astigmatism. Results: For stage 1, the mean preoperative MRC and mean IoS were −1.32 D ± 0.65 (SD) (range −0.55 to −3.77 D) and 0.27, respectively, for low ORA and −0.79 ± 0.20 D (range −0.56 to −2.05 D) and 0.37, respectively, for high ORA. For stage 2, the mean IoS increased to 0.32 for low ORA. For stage 3, the mean IoS was 0.28, 0.29, and 0.31 for low ORA, mid ORA, and high ORA, respectively. For stage 4, the mean IoS was 0.20 for high ORA/low corneal astigmatism and 0.35 for high ORA/high corneal astigmatism. Conclusions: The MRC predictability was slightly worse in eyes with high ORA when grouped by the ORA ÷ MRC. Matching for the MRC and grouping by ORA magnitude resulted in similar predictability; however, eyes with high ORA and high corneal astigmatism were less predictable.