Alvin I. Chen

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.

Robotic systems have slowly entered the realm of modern medicine; however, outside the operating room, medical robotics has yet to be translated to more routine interventions such as blood sampling or intravenous fluid delivery. In this paper, we present a medical robot that safely and rapidly cannulates peripheral blood vessels-a procedure commonly known as venipuncture. The device uses near-infrared and ultrasound imaging to scan and select suitable injection sites, and a 9-DOF robot to insert the needle into the center of the vessel based on image and force guidance. We first present the system design and visual-servoing scheme of the latest generation robot, and then evaluate the performance of the device through workspace simulations and free-space positioning tests. Finally, we perform a series of motion tracking experiments using stereo vision, ultrasound, and force sensing to guide the position and orientation of the needle tip. Positioning experiments indicate sub-millimeter accuracy and repeatability over the operating workspace of the system, while tracking studies demonstrate real-time needle servoing in response to moving targets. Finally, robotic phantom cannulations demonstrate the use of multiple system states to confirm that the needle has reached the center of the vessel.

Accessing the venous bloodstream to deliver fluids or obtain a blood sample is the most common clinical routine practiced in the U.S. Practitioners continue to rely on manual venipuncture techniques, but success rates are heavily dependent on clinician skill and patient physiology. In the U.S., failure rates can be as high as 50% in difficult patients, making venipuncture the leading cause of medical injury. To improve the rate of first-stick success, we have developed a portable autonomous venipuncture device that robotically servos a needle into a suitable vein under image guidance. The device operates in real time, combining near-infrared and ultrasound imaging, image analysis, and a 7-degree-of-freedom (DOF) robotic system to perform the venipuncture. The robot consists of a 3-DOF gantry to image the patient's peripheral forearm veins and a miniaturized 4-DOF serial arm to guide the cannula into the selected vein under closed-loop control. In this paper, we present the system architecture of the robot and evaluate the accuracy and precision through tracking, free-space positioning, and in vitro phantom cannulation experiments. The results demonstrate submillimeter accuracy throughout the operating workspace of the manipulator and a high rate of success when cannulating phantom veins in a skin-mimicking tissue model.