Detection of veins is a critical aspect of intravenous catheterization, but it is a challenging task prone to errors, which can lead to complications such as discomfort or vessel damage. To address this issue, Vein Viewer, an auxiliary tool that employs an infrared camera, has been used to enhance vein visibility. This device captures a subcutaneous venous map using an infrared camera and then processes the images using a Raspberry Pi to display them in real-time on an LCD. This study aims to improve the use of Vein Viewer by analyzing its performance in relation to cliplimit adjustments and varying distances from the skin surface. Our findings indicate that the clearest images are obtained with cliplimits of 500 at 10 cm, 300 at 20 cm, and 400 at 30 cm. These results provide valuable insights into the optimal use of Vein Viewer and offer a practical approach to improve the accuracy of vein detection and reduce the rate of intravenous catheterization errors, ultimately enhancing patient care.
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