Shape-sensing by self-sensing of shape memory alloy instruments for minimal invasive surgery

Fischer N, Knapp J, Mathis-Ullrich F (2023)

Publication Type: Journal article

Publication year: 2023

Journal

At-Automatisierungstechnik Oldenbourg Verlag

Book Volume: 71

Pages Range: 554-561

Journal Issue: 7

DOI: 10.1515/auto-2023-0058

Abstract

Shape memory alloy-based flexible instruments have potential for enhancing the safety in minimally invasive surgery compared to passive rigid devices. We developed a data-driven polynomial model to estimate deflection of a 2D bending actuator using electrical resistance. The model accurately predicts deflections (mean error <3.6 mm), but force sensing augmentation is required for unknown load cases. The model is specific to the tested actuator geometry, and future research should investigate multiple actuators and explore nonlinear modeling approaches.

Authors with CRIS profile

Franziska Mathis-Ullrich Professur für Robotische Planung und Kognition in der Chirurgie

Involved external institutions

Karlsruhe Institute of Technology (KIT) DE Germany (DE)

How to cite

APA:

Fischer, N., Knapp, J., & Mathis-Ullrich, F. (2023). Shape-sensing by self-sensing of shape memory alloy instruments for minimal invasive surgery. At-Automatisierungstechnik, 71(7), 554-561. https://doi.org/10.1515/auto-2023-0058

MLA:

Fischer, Nikola, Johannes Knapp, and Franziska Mathis-Ullrich. "Shape-sensing by self-sensing of shape memory alloy instruments for minimal invasive surgery." At-Automatisierungstechnik 71.7 (2023): 554-561.

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