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You searched for +publisher:"Rutgers University" +contributor:("Maguire, Timothy J"). Showing records 1 – 2 of 2 total matches.

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Rutgers University

1. Balter, Max Loeb, 1989-. Robotic devices for automated venipuncture and diagnostic blood analysis.

Degree: PhD, Biomedical Engineering, 2017, Rutgers University

Diagnostic blood testing is the most ubiquitous clinical procedure in the world, and influences 80% of medical decisions made in hospital, ambulatory, and primary care settings. However, manual blood draw success rates depend heavily on clinician skill and patient physiology, and results are generated almost exclusively in centralized labs from large-volume samples using labor-intensive analytical techniques. This dissertation describes the development of a medical device that enables complete end-to-end blood testing by performing blood draws and providing diagnostic results in fully automated fashion. The device couples an image-guided venipuncture robot, to address the challenges of routine venous access, with a centrifuge-based blood analyzer to obtain quantitative measurements of hematology within minutes of the sample collection. The system uses 3D near-infrared and ultrasound imaging to guide the robotic needle insertion, a sample handling module to deliver the sample to the processing unit, and an analyzer capable of performing multi-analyte detection. In a series of engineering tests, phantom studies, and motion tracking experiments, the venipuncture robot demonstrated sub-millimeter accuracy, real-time needle servoing in response to moving targets, and improved cannulation success rates compared to manual techniques. Multi-analyte detection was then demonstrated on the blood analyzer through white blood cell counting using a bulk-cell analysis approach, and an absorption-based hemoglobin assay. Once translated, this technology has the potential to impact a number of clinical environments, including laboratory testing facilities, pediatric hospitals, oncology care centers, and emergency settings. The underlying technological advancements cover a spectrum of research disciplines, including hematology and diagnostic medicine, optics and microfluidics, as well as robotics and medical device development.

Advisors/Committee Members: Yarmush, Martin l (chair), Maguire, Timothy J (internal member), Pierce, Mark (internal member), Nikitczuk, Kevin (outside member).

Subjects/Keywords: Robotics in medicine; Veins – Puncture

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Balter, Max Loeb, 1. (2017). Robotic devices for automated venipuncture and diagnostic blood analysis. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/53084/

Chicago Manual of Style (16th Edition):

Balter, Max Loeb, 1989-. “Robotic devices for automated venipuncture and diagnostic blood analysis.” 2017. Doctoral Dissertation, Rutgers University. Accessed July 11, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/53084/.

MLA Handbook (7th Edition):

Balter, Max Loeb, 1989-. “Robotic devices for automated venipuncture and diagnostic blood analysis.” 2017. Web. 11 Jul 2020.

Vancouver:

Balter, Max Loeb 1. Robotic devices for automated venipuncture and diagnostic blood analysis. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2020 Jul 11]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53084/.

Council of Science Editors:

Balter, Max Loeb 1. Robotic devices for automated venipuncture and diagnostic blood analysis. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53084/


Rutgers University

2. Chen, Alvin I., 1988-. Image-guided robotics for autonomous venipuncture.

Degree: PhD, Biomedical Engineering, 2016, Rutgers University

Performed over 1.5 billion times each year, venipuncture is the most ubiquitous clinical intervention and leading cause of medical injury in the United States. This dissertation describes the development of a medical device aimed at minimizing venipuncture-related adverse events by drawing blood and placing peripheral vascular catheters in an automated manner. The device may be particularly suited to challenging populations, including pediatric, geriatric, chronically-ill, and obese patients, for whom the rates of success depend heavily on practitioner skill. The device combines 3D near-infrared and ultrasound imaging, computer vision software, and a miniaturized dexterous robot that inserts the needle based on real-time image guidance. Methods to robustly segment, localize, and track the pose of the vessels are presented, and robotic prototypes capable of autonomously aligning and servoing the needle under real-time image guidance are introduced. In imaging studies on human volunteers spanning a broad range of demographic characteristics, the device was able to detect a majority of forearm veins that remained invisible to clinical visual assessment. In cannulation studies on in vitro and in vivo models, the device demonstrated significant improvements in first-stick accuracy and completion time compared to unassisted and image-guided manual venipuncture techniques. The results of these studies may be used to inform future clinical trials evaluating device feasibility in normal and difficult patient groups. Once translated, the device may be targeted to high-volume laboratory testing facilities and hospitals, and the underlying technologies may be extended to other diagnostic and interventional procedures, including automated point-of-care blood analysis, in-clinic and at-home hemodialysis venipuncture, peripherally-inserted central catheter placement, and emergency or military use.

Advisors/Committee Members: Yarmush, Martin l (chair), Maguire, Timothy J (internal member), Pierce, Mark C (internal member), Pantin, Enrique J (outside member), Alam, Kaisar S (outside member).

Subjects/Keywords: Robotics in medicine; Veins – Puncture

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chen, Alvin I., 1. (2016). Image-guided robotics for autonomous venipuncture. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51243/

Chicago Manual of Style (16th Edition):

Chen, Alvin I., 1988-. “Image-guided robotics for autonomous venipuncture.” 2016. Doctoral Dissertation, Rutgers University. Accessed July 11, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/51243/.

MLA Handbook (7th Edition):

Chen, Alvin I., 1988-. “Image-guided robotics for autonomous venipuncture.” 2016. Web. 11 Jul 2020.

Vancouver:

Chen, Alvin I. 1. Image-guided robotics for autonomous venipuncture. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2020 Jul 11]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51243/.

Council of Science Editors:

Chen, Alvin I. 1. Image-guided robotics for autonomous venipuncture. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51243/

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