Perspective of Creating Low-Cost Medical Assistant Robot Based on Waffle PI4 Platform with Palm Vein Pattern Scanner
DOI:
https://doi.org/10.20535/RADAP.2024.98.46-54Keywords:
robot, TurtleBot, Raspberry Pi, biometrical scanner, image skeletonization, convolutional neural networkAbstract
The purpose of this study is to develop a set of modifications for the TurtleBot 3 Waffle Pi robotic platform. One of the key achievements of this work is the creation of a biometric identification system based on the venous pattern of the palm. The principle of operation of the identification system is based on the use of infrared radiation absorbed by hemoglobin in the venous system of the palm. The absorbed radiation creates a clear pattern that can be captured using a camera without an infrared filter. The resulting image is pre-processed to reduce noise and unify with other images for further use in training a convolutional neural network used for patient identification. This identification method allows for high-speed and accurate patient identification, even with dirt or scratches on the palm. The described modifications are aimed at expanding the capabilities of the platform for military medical applications. By integrating these modifications into the TurtleBot 3 Waffle Pi robotic platform, military and civilian hospitals can improve their ability to provide timely and accurate medical care to those in need.
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Copyright (c) 2024 Валентин Ануфрієв, Ольга Кравчук, Євгеній Левченко, Олег Глухов, Олена Лінник, Олександр Галат
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