Dynamic Tactile Synthetic Tissue: from Soft Robotics to Hybrid Surgical Simulators

Author:

Thurner Thomas12ORCID,Maier Julia3,Kaltenbrunner Martin24ORCID,Schrempf Andreas1ORCID

Affiliation:

1. Research Group for Surgical Simulators Linz (ReSSL) Upper Austria University of Applied Sciences Garnisonstr. 21 4020 Linz Austria

2. Division of Soft Matter Physics, Institute for Experimental Physics Johannes Kepler University Altenberger Str. 69 4020 Linz Austria

3. Institute of Polymer Product Engineering Johannes Kepler University Altenberger Str. 66a 4020 Linz Austria

4. Soft Materials Lab, Linz Institute of Technology Johannes Kepler University Altenberger Str. 69 4020 Linz Austria

Abstract

Surgical simulators are valuable educational tools for physicians, enhancing their proficiency and improving patient safety. However, they typically still suffer from a lack of realism as they do not emulate dynamic tissue biomechanics haptically and fail to convincingly mimic real‐time physiological reactions. This study presents a dynamic tactile synthetic tissue, integrating both sensory and actuatory capabilities within a fully soft unit, as a core component for soft robotics and future hybrid surgical simulators utilizing dynamic physical phantoms. The adaptive surface of the tissue replica, actuated via hydraulics, is assessed by an embedded carbon black silicone sensor layer using electrical impedance tomography to determine internally or externally induced deformations. The integrated fluid chambers enable pressure and force measurements. The combination of these principles enables real‐time tissue feedback as well as closed loop operation, allowing optimal interaction with the environment. Based on the concepts of soft robotics, such artificial tissues find broad applicability, demonstrated via a soft gripper and surgical simulation applications including a dynamic, artificial brain phantom as well as a synthetic, beating heart. These advancements pave the way toward enhanced realism in surgical simulators including reliable performance evaluation and bear the potential to transform the future of surgical training methodologies.

Funder

H2020 European Research Council

Publisher

Wiley

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