ArticleScience China. Technological sciences2023
Puncture site decision method for venipuncture robot based on near-infrared vision and multiobjective optimization.
Article in Science China. Technological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Intelligent blood collection robot: key technologies, clinical applications, and future challenges.Frontiers in bioengineering and biotechnology · 2025Review
- Phase Transition Liquid Metal Enabled Emerging Biomedical Technologies and Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Review of robotic systems for thoracoabdominal puncture interventional surgery.APL bioengineering · 2024Review
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Authors and funding
3 authors.
Funding
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Abstract
Venipuncture robots have superior perception and stability to humans and are expected to replace manual venipuncture. However, their use is greatly restricted because they cannot make decisions regarding the puncture sites. Thus, this study presents a multi-information fusion method for determining puncture sites for venipuncture robots to improve their autonomy in the case of limited resources. Here, numerous images have been gathered and processed to establish an image dataset of human forearms for training the U-Net with the soft attention mechanism (SAU-Net) for vein segmentation. Then, the veins are segmented from the images, feature information is extracted based on near-infrared vision, and a multiobjective optimization model for puncture site decision is provided by considering the depth, diameter, curvature, and length of the vein to determine the optimal puncture site. Experiments demonstrate that the method achieves a segmentation accuracy of 91.2% and a vein extraction rate of 86.7% while achieving the Pareto solution set (average time: 1.458 s) and optimal results for each vessel. Finally, a near-infrared camera is applied to the venipuncture robot to segment veins and determine puncture sites in real time, with the results transmitted back to the robot for an attitude adjustment. Consequently, this method can enhance the autonomy of venipuncture robots if implemented dramatically.
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