Josh Leipheimer, Max Balter, Alvin Chen, Martin Yarmush
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Design and Evaluation of a Handheld Robotic Device for Peripheral Catheterization.
Medical robots provide enhanced dexterity, vision, and safety for a broad range of procedures. In this article, we present a handheld, robotic device capable of performing peripheral catheter insertions with high accuracy and repeatability. The device utilizes a combination of ultrasound imaging, miniaturized robotics, and machine learning to safely and efficiently introduce a catheter sheath into a peripheral blood vessel. Here, we present the mechanical design and experimental validation of the device, known as VeniBot. Additionally, we present results on our ultrasound deep learning algorithm for vessel segmentation, and performance on tissue-mimicking phantom models that simulate difficult peripheral catheter placement. Overall, the device achieved first-attempt success rates of 97 ± 4% for vessel punctures and 89 ± 7% for sheath cannulations on the tissue mimicking models (n = 240). The results from these studies demonstrate the viability of a handheld device for performing semi-automated peripheral catheterization. In the future, the use of this device has the potential to improve clinical workflow and reduce patient discomfort by assuring a safe and efficient procedure.
期刊介绍:
The Journal of Medical Devices presents papers on medical devices that improve diagnostic, interventional and therapeutic treatments focusing on applied research and the development of new medical devices or instrumentation. It provides special coverage of novel devices that allow new surgical strategies, new methods of drug delivery, or possible reductions in the complexity, cost, or adverse results of health care. The Design Innovation category features papers focusing on novel devices, including papers with limited clinical or engineering results. The Medical Device News section provides coverage of advances, trends, and events.