# Enabling Technology for Safe Robot-assisted Surgical Micromanipulation > **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2024 · $417,264 ## Abstract Project Summary / Abstract The goal of this grant is to develop enabling technology to address fundamental limitations in microsurgery with a specific focus on developing coordinated bilateral assistance for the vitreoretinal surgeon. Retinal vein occlusion (RVO) is the second-most-prevalent vision threatening disease of retinal blood vessels, with no consistently successful clinical treatments to directly resolve the occlusion. A strategic approach, that is particularly amenable to robotic assistance, is to cannulate the occluded retinal vein with a micro-cannula and to inject a clot-dissolving agent. Due to human physiological limitations (tremor, tactile perception, visualization, stress, cognitive requirements, incomplete sensory information, etc.), as well as retinal fragility and the inability to regenerate retinal tissue, various robotic systems have been developed that target select aspects of retinal vein cannulation (RVC). However, even with all present and emerging technological advances, a number of imminently solvable challenges remain as barriers to consistently successful treatment. We propose a bilateral robotic system with real-time multisensory feedback that assesses multiple points of instrument contact located both inside and outside of the eye. Our bilateral system will enhance retina and sclera safety, increase the rate of RVC success, diminish forces on the cannula and vein, reduce the human mental and physical requirements, and allow the surgeon enhanced motion precision to enable more advanced surgical procedures benefitted by bilateral manipulation. To prove the hypothesis that bilateral robot-assisted retinal cannulation is possible and safe, we propose the following specific aims: (1) Demonstrate coordinated position/force hybrid control algorithms for enabling real- time sensorimotor capabilities at sclerotomy for safe bilateral robot-assisted vitreoretinal microsurgery: real-time sensorimotor capabilities at the sclerotomy will be uniquely used to control the robots through a machine learning method that adaptively learns a nonlinear mapping from user behavior to sclera-force/position and predicts unsafe motions; (2) Demonstrate position/force-input control algorithms for enabling real-time sensorimotor capabilities at the tool-tip for safe bilateral robot-assisted vein cannulation: real-time tool-tip-to-tissue interaction force sensing and non-linear robot control algorithms based on observing user behavior will be used to control the tool-tip position and force and to prevent entry into subretinal areas during RVC; (3) Demonstrate and evaluate bilateral RVC using SHER in animal model in vivo: real-time, position/force hybrid control algorithms based on dual-point (tool-shaft and tip) information fusion will provide sensorimotor guidance of surgical maneuvers during RVC. Statistically significant results in vivo, in clinically realistic conditions will demonstrate the feasibility of our approach. This highly innov... ## Key facts - **NIH application ID:** 10757451 - **Project number:** 5R01EB023943-06 - **Recipient organization:** JOHNS HOPKINS UNIVERSITY - **Principal Investigator:** PETER LOUIS GEHLBACH - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $417,264 - **Award type:** 5 - **Project period:** 2017-03-15 → 2025-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10757451 ## Citation > US National Institutes of Health, RePORTER application 10757451, Enabling Technology for Safe Robot-assisted Surgical Micromanipulation (5R01EB023943-06). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10757451. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*