Reducing Workload During Brain Surgery with Robot-Assisted Autonomous Exoscope
Elisa Iovene, Alessandro Casella, Junling Fu, Federico Pessina, Marco Riva, Giancarlo Ferrigno, Elena De Momi
Abstract
In this paper, a position-based visual-servoing control approach is introduced for a robotic camera holder to improve ergonomics and reduce mental stress during brain surgery. The visual tracking system controls and moves the robotic camera holder by following a selected surgical instrument without the need for artificial markers. The system was validated using a 7 Degree-of-Freedoms (DoFs) redundant robotic manipulator with an eye-in-hand stereo camera configuration and compared with conventional control methods using NASA TLX survey and four objective metrics, including execution time, time out of field of view (FoV), target score, and path length. Experimental results demonstrate that the proposed system can reduce the surgeon's workload during brain surgery-related task execution, improve ergonomics and achieve higher performance than traditional control methods.
BibTeX
@inproceedings{iros2023_reducingworkload,
title = {Reducing Workload During Brain Surgery with Robot-Assisted Autonomous Exoscope},
author = {Elisa Iovene and Alessandro Casella and Junling Fu and Federico Pessina and Marco Riva and Giancarlo Ferrigno and Elena De Momi},
booktitle = {IROS 2023},
year = {2023}
}