Visual vein-finding for robotic IV insertion

This paper presents a new algorithm for selecting the optimal needle insertion point in images of hand veins for robotic IV insertion. The 3D coordinates and orientation of the vein that the algorithm detects would eventually be fed to a robot for insertion of the IV needle. The goal of the algorithm is to identify venous bifurcations and determine an insertion point and approach angle for the needle in between their branches. The algorithm uses an annular tracking window that tracks along the veins and searches for bifurcations. We describe methods for centering the initial bifurcation estimates, error-checking, and positioning the needle exactly in between the bifurcation branches. We conclude with an experimental study of 50 subjects that shows a 32.4% success rate at detecting all bifurcations and a 82.6% success rate at finding at least one bifurcation in each image that contains bifurcations.