ReviewSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2025
[Thoughts and Prospects on Precision Control and Intelligent Positioning Robotic Systems Applied in Nasojejunal Feeding Tube Placement].
Review in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
10 authors.
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Abstract
Nasojejunal feeding tubes are widely used in surgical, intensive care, and older patients. Manual blind insertion of nasojejunal feeding tubes is technically challenging, associated with a high failure rate, and prone to complications. The primary causes of suboptimal placement outcomes are the uncertainty and weak controllability of the interaction forces during the coordination between manual posterior advancement and the patient's physiological state. While current auxiliary techniques such as X-ray, ultrasound, and endoscopy can improve the success rate of nasojejunal tube placement and reduce complications to some extent, the accuracy and safety of placement remain constrained by challenges in controlling insertion forces and achieving precise positional localization. Robotic technology holds promise for addressing the uncertainties and controllability issues inherent in the placement process. By leveraging precise sensing, real-time navigation, and efficient control, robots can achieve intelligent positioning and precise control over the direction and location of the catheter tip during nasojejunal intubation. However, current research on robotic applications for nasojejunal feeding tube placement is still in an early stage, facing challenges such as high costs, operational complexity, and concerns over safety and reliability. Herein, we analyzed the limitations and causes of failure in existing placement methods and explored the application prospects of robotic technologies for precise control and intelligent positioning in nasojejunal feeding tube placement. The paper provides new insights for developing nursing techniques that enable safer and more effective, comfortable, and rapid intubation. Future efforts should focus on deepening the integration of artificial intelligence and robotics, optimizing drive technologies, and accelerating the translation of these technologies from the laboratory to clinical practice. This will drive the advancement of nasojejunal feeding tube placement techniques towards intelligent, precise, and accessible solutions.
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Registered trials
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