Vital Signs Evaluator and Blood Type Identification using Deep Learning for Blood Donation

This paper presented an automated system that aid the process of the whole blood donation, specifically from checking the vital signs of a donor such as weight, body temperature, blood pressure, pulse rate and hemoglobin level and to identify the donor’s blood type. The said vital signs were measured by the sensors and other digital measuring devices and the readings were acquired by the system using Arduino microcontroller and MATLAB. The study focuses on identifying eight (8) blood types, specifically Rhesus positive and negative A, B, O and AB. Deep learning model using Python IDE was used. VGG16 was used as the deep learning model to develop the blood type identifier. After training, validation and testing, the system’s overall accuracy is equal to 99.50%.