Blood Group Identification using FPGA

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Stella J, et. al.


Detection of Blood Group is the first essential proce- dure for major medical surgery. Traditional ways of laboratory
testing techniques like plate test and tube test are susceptible to human fallibility and, the approach of detecting blood groups
is still prevalent in our modern era of digitization. As it is time-consuming, the results are difficult to reproduce, and there is a
need for a domain expert. Our present times necessitate automation of the evaluation process. This approach would be a
lifesaving method for Blood Group Identification.
The proposed system uses a technique of testing using FPGA. Canny Edge Detection Algorithm developed using MATLAB
Simulink and converted to HDL Code for Hardware Implemen- tation on Arty 7000 Zync FPGA using Xilinx Vivado software
as FPGAs have the advantages of speed and reconfigurability for image processing applications. The Detected edges counted
to classify blood group. The proposed Hardware Model FPGA demonstrates 2.5 V power supply with the power usage of 1.83
W. Its Hardware implementation requires only 10.773ns, while Intel Core i5 processor with 1.60 GHz clock rate and 8 GB
RAM takes 120 s upon software-based MATLAB implementation. An accuracy of 99% achieved when tested with each type
of blood with more than 100 various blood samples produced advantages like portable, affordable, durable, and more limited
power consumption than conventional methods of detecting blood group by the proposed hardware solution.


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How to Cite
et. al., S. J. (2021). Blood Group Identification using FPGA. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(10), 168–176. Retrieved from