Transparent and Shaped Stiffness Reflection for Telesurgery

status: publishe

In-Human Robot-Assisted Retinal Vein Cannulation, A World First.

Retinal Vein Occlusion (RVO) is a blinding disease caused by one or more occluded retinal veins. Current treatment methods only focus on symptom mitigation rather than targeting a solution for the root cause of the disorder. Retinal vein cannulation is an experimental eye surgical procedure which could potentially cure RVO. Its goal is to dissolve the occlusion by injecting an anticoagulant directly into the blocked vein. Given the scale and the fragility of retinal veins on one end and surgeons' limited positioning precision on the other, performing this procedure manually is considered to be too risky. The authors have been developing robotic devices and instruments to assist surgeons in performing this therapy in a safe and successful manner. This work reports on the clinical translation of the technology, resulting in the world-first in-human robot-assisted retinal vein cannulation. Four RVO patients have been treated with the technology in the context of a phase I clinical trial. The results show that it is technically feasible to safely inject an anticoagulant into a [Formula: see text]-thick retinal vein of an RVO patient for a period of 10 min with the aid of the presented robotic technology and instrumentation.status: publishe

Hysteresis Modeling of Robotic Catheters based on Long Short-Term Memory Network for Improved Environment Reconstruction

Catheters are increasingly being used to tackle problems in the cardiovascular system. However, positioning precision of the catheter tip is negatively affected by hysteresis. To ensure tissue damage due to imprecise positioning is avoided, hysteresis is to be understood and compensated for. This work investigates the feasibility to model hysteresis with a Long Short-Term Memory (LSTM) network. A bench-top setup containing a catheter distal segment was developed for model evaluation.The LSTM was first tested using four groups of test datasets containing diverse patterns. To compare with the LSTM, a Deadband Rate-Dependent Prandtl-Ishlinskii (DRDPI) model and a Support Vector Regression (SVR) model were established. The results demonstrated that the LSTM is capable of predicting the tip bending angle with sub-degree precision. The LSTM outperformed the DRDPI model and the SVR model by 60.1% and 36.0%, respectively, in arbitrarily varying signals. Next, the LSTM was further validated in a 3D reconstruction experiment using Forward-Looking Optical Coherence Tomography (FL-OCT). The results revealed that the LSTM was able to accurately reconstruct the environment with a reconstruction error below 0.25 mm. Overall, the proposed LSTM enabled precise free-space control of a robotic catheter in the presence of severe hysteresis. The LSTM predicted the catheter tip response precisely based on proximal input pressure, minimizing the need to install sensors at the catheter tip for localization.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Medical Instruments & Bio-Inspired Technolog