Toward Assistive Technologies for Focus Adjustment in Teleoperated Robotic Non-Contact Laser Surgery

verfasst von
Dennis Kundrat, Andreas Schoob, Thomas Piskon, René Grässlin, Patrick J. Schuler, Thomas K. Hoffmann, Luder A. Kahrs, Tobias Ortmaier
Abstract

In the last decade, focused laser radiation has become an alternative instrumentation for soft tissue surgery due to precise ablation with simultaneous coagulation. However, adjustment of the focal position with respect to the tissue surface is crucial for optimal energy input and minimised trauma. Advantageous laser delivery without tissue contact poses challenges and demands for assistance. This contribution introduces three novel concepts for user assistance during focal adaptation in noncontact laser surgery with robotic teleoperation. Visual, haptic, and visuo-haptic feedback modalities are designed based on real-time scene reconstruction and laser-to-camera registration. The performance of proposed methods was assessed in a phantom study with positioning tasks under different assistance conditions using a teleoperated extensible continuum robot. Focal position error and task execution time were selected as performance metrics. In total, 15 subjects conducted trials under four different conditions ( N=240 ). A mean error reduction from 1.2 mm for nonassisted to 0.25 mm for visuo-haptic feedback was revealed and error outliers were eliminated efficiently. Mean execution times of below 13 s were achieved for applied conditions. Presented work decreased the error to one-fifth in comparison to absence of assistance in teleoperation. The results strongly motivate prospective integration to surgical devices for noncontact laser delivery.

Organisationseinheit(en)
Institut für Mechatronische Systeme
Institut für Dynamik und Schwingungen
Typ
Artikel
Journal
IEEE Transactions on Medical Robotics and Bionics
Band
1
Seiten
145-157
Anzahl der Seiten
13
ISSN
2576-3202
Publikationsdatum
26.07.2019
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
ASJC Scopus Sachgebiete
Angewandte Informatik, Artificial intelligence, Mensch-Maschine-Interaktion, Steuerung und Optimierung, Biomedizintechnik
Elektronische Version(en)
https://doi.org/10.1109/tmrb.2019.2931438 (Zugang: Geschlossen)