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Article

Performance and Capability Assessment in Surgical Subtask Automation

by 1,2,3,* and 1,4
1
Antal Bejczy Center for Intelligent Robotics, EKIK, Óbuda University, Bécsi út 96/B, 1034 Budapest, Hungary
2
Doctoral School of Applied Informatics and Applied Mathematics, Óbuda University, Bécsi út 96/B, 1034 Budapest, Hungary
3
Biomatics Institute, John von Neumann Faculty of Informatics, Óbuda University, Bécsi út 96/B, 1034 Budapest, Hungary
4
Austrian Center for Medical Innovation and Technology (ACMIT), Viktor-Kaplan-Straße 2/1, 2700 Wiener Neustadt, Austria
*
Author to whom correspondence should be addressed.
Academic Editor: Iulian I. Iordachita
Sensors 2022, 22(7), 2501; https://doi.org/10.3390/s22072501
Received: 28 January 2022 / Revised: 16 March 2022 / Accepted: 19 March 2022 / Published: 24 March 2022
(This article belongs to the Special Issue Medical Robotics)
Robot-Assisted Minimally Invasive Surgery (RAMIS) has reshaped the standard clinical practice during the past two decades. Many believe that the next big step in the advancement of RAMIS will be partial autonomy, which may reduce the fatigue and the cognitive load on the surgeon by performing the monotonous, time-consuming subtasks of the surgical procedure autonomously. Although serious research efforts are paid to this area worldwide, standard evaluation methods, metrics, or benchmarking techniques are still not formed. This article aims to fill the void in the research domain of surgical subtask automation by proposing standard methodologies for performance evaluation. For that purpose, a novel characterization model is presented for surgical automation. The current metrics for performance evaluation and comparison are overviewed and analyzed, and a workflow model is presented that can help researchers to identify and apply their choice of metrics. Existing systems and setups that serve or could serve as benchmarks are also introduced and the need for standard benchmarks in the field is articulated. Finally, the matter of Human–Machine Interface (HMI) quality, robustness, and the related legal and ethical issues are presented. View Full-Text
Keywords: RAMIS; partial automation; robot surgery validation; robot surgery benchmarking RAMIS; partial automation; robot surgery validation; robot surgery benchmarking
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MDPI and ACS Style

Nagy, T.D.; Haidegger, T. Performance and Capability Assessment in Surgical Subtask Automation. Sensors 2022, 22, 2501. https://doi.org/10.3390/s22072501

AMA Style

Nagy TD, Haidegger T. Performance and Capability Assessment in Surgical Subtask Automation. Sensors. 2022; 22(7):2501. https://doi.org/10.3390/s22072501

Chicago/Turabian Style

Nagy, Tamás D., and Tamás Haidegger. 2022. "Performance and Capability Assessment in Surgical Subtask Automation" Sensors 22, no. 7: 2501. https://doi.org/10.3390/s22072501

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