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.

First-in-human evaluation of a hand-held automated venipuncture device for rapid venous blood draws.

Obtaining venous access for blood sampling or intravenous (IV) fluid delivery is an essential first step in patient care. However, success rates rely heavily on clinician experience and patient physiology. Difficulties in obtaining venous access result in missed sticks and injury to patients, and typically require alternative access pathways and additional personnel that lengthen procedure times, thereby creating unnecessary costs to healthcare facilities. Here, we present the first-in-human assessment of an automated robotic venipuncture device designed to safely perform blood draws on peripheral forearm veins. The device combines ultrasound imaging and miniaturized robotics to identify suitable vessels for cannulation and robotically guide an attached needle toward the lumen center. The device demonstrated results comparable to or exceeding that of clinical standards, with a success rate of 87% on all participants (n = 31), a 97% success rate on nondifficult venous access participants (n = 25), and an average procedure time of 93 ± 30 s (n = 31). In the future, this device can be extended to other areas of vascular access such as IV catheterization, central venous access, dialysis, and arterial line placement.

Design and Evaluation of a Robotic Device for Automated Tail Vein Cannulations in Rodent Models.

Preclinical testing in rodent models is a ubiquitous part of modern biomedical research and commonly involves accessing the venous bloodstream for blood sampling and drug delivery. Manual tail vein cannulation is a time-consuming process and requires significant skill and training, particularly since improperly inserted needles can affect the experimental results and study outcomes. In this paper, we present a miniaturized, robotic medical device for automated, image-guided tail vein cannulations in rodent models. The device is composed of an actuated three degrees-of-freedom (DOFs) needle manipulator, three-dimensional (3D) near-infrared (NIR) stereo cameras, and an animal holding platform. Evaluating the system through a series of workspace simulations and free-space positioning tests, the device exhibited a sufficient work volume for the needle insertion task and submillimeter accuracy over the calibration targets. The results indicate that the device is capable of cannulating tail veins in rodent models as small as 0.3 mm in diameter, the smallest diameter vein required to target.