Peripheral venous access is pivotal to a wide range of clinical interventions and is consequently the leading cause of medical injury in the U.S. Complications associated with the procedure are exacerbated in difficult settings, where the rate of success depends heavily on the patient's physiology and the practitioner's experience. My dissertation thesis pertains to the development of imaging and robotic technologies to improve the accuracy and speed of blood draws and IV's. The core technology is an image-guided robotic device that accurately and autonomously introduces a cannula for venous access. The device operates by mapping in real-time the 3D structure of peripheral veins in order to robotically direct a needle into a selected vein. A working prototype has been developed and validated in several studies, the results of which are described in two journal publications. The device combines a 3D near-infrared vein imager, a robot, and computer vision software;these three components form the basis of the three Specific Aims described in this proposal.
The Aims fit into the overall dissertation by 1) incorporating the current imaging hardware into a standalone, handheld imaging device;2) introducing software for the imaging device that assists in selecting suitable cannulation sites;and 3) integrating the imaging device and software with a miniaturized version of the current robot. The outcome of this work will be a compact and low-cost system that is suited for beta-stage development.
Blood draws and IV therapies are one of the most commonly performed medical routines in hospitals and clinics. Injuries to doctors and patients happen frequently because of how difficult it can be to find veins and accurately insert the needle. We are developing a portable and lightweight medical robot to perform the procedure in situations where the doctor is unable to successfully access the veins. This device may greatly improve the safety and accuracy of venous access, and has wide applications in many clinical areas.
|Balter, M L; Leipheimer, J M; Chen, A I et al. (2018) Automated end-to-end blood testing at the point-of-care: Integration of robotic phlebotomy with downstream sample processing. Technology (Singap World Sci) 6:59-66|
|Balter, Max L; Chen, Alvin I; Maguire, Timothy J et al. (2017) Adaptive Kinematic Control of a Robotic Venipuncture Device Based on Stereo Vision, Ultrasound, and Force Guidance. IEEE Trans Ind Electron 64:1626-1635|
|Fromholtz, Alex; Balter, Max L; Chen, Alvin I et al. (2017) Design and Evaluation of a Robotic Device for Automated Tail Vein Cannulations in Rodent Models. J Med Device 11:0410081-410087|
|Chen, Alvin I; Balter, Max L; Chen, Melanie I et al. (2016) Multilayered tissue mimicking skin and vessel phantoms with tunable mechanical, optical, and acoustic properties. Med Phys 43:3117-3131|
|Chen, Alvin I; Balter, Max L; Maguire, Timothy J et al. (2016) 3D Near Infrared and Ultrasound Imaging of Peripheral Blood Vessels for Real-Time Localization and Needle Guidance. Med Image Comput Comput Assist Interv 9902:388-396|
|Balter, Max L; Chen, Alvin I; Colinco, C Amara et al. (2016) Differential Leukocyte Counting via Fluorescent Detection and Image Processing on a Centrifugal Microfluidic Platform. Anal Methods 8:8272-8279|
|Balter, Max L; Chen, Alvin I; Fromholtz, Alex et al. (2016) System Design and Development of a Robotic Device for Automated Venipuncture and Diagnostic Blood Cell Analysis. Rep U S 2016:514-520|
|Chen, Alvin I; Balter, Max L; Maguire, Timothy J et al. (2015) Real-time Needle Steering in Response to Rolling Vein Deformation by a 9-DOF Image-Guided Autonomous Venipuncture Robot. Rep U S 2015:2633-2638|
|Balter, Max L; Chen, Alvin I; Maguire, Timothy J et al. (2015) The System Design and Evaluation of a 7-DOF Image-Guided Venipuncture Robot. IEEE Trans Robot 31:1044-1053|
|Chen, Alvin; Nikitczuk, Kevin; Nikitczuk, Jason et al. (2013) Portable robot for autonomous venipuncture using 3D near infrared image guidance. Technology (Singap World Sci) 1:72-87|