Robotic-Arm-Based Force Control in Neurosurgical Practice
Ibai Inziarte-Hidalgo,
Irantzu Uriarte,
Unai Fernandez-Gamiz,
Gorka Sorrosal and
Ekaitz Zulueta ()
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Ibai Inziarte-Hidalgo: University of the Basque Country (UPV-EHU), 48940 Leioa, Spain
Irantzu Uriarte: University of the Basque Country (UPV-EHU), 48940 Leioa, Spain
Unai Fernandez-Gamiz: University of the Basque Country (UPV-EHU), 48940 Leioa, Spain
Gorka Sorrosal: Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), 20500 Arrasate-Mondragon, Spain
Ekaitz Zulueta: University of the Basque Country (UPV-EHU), 48940 Leioa, Spain
Mathematics, 2023, vol. 11, issue 4, 1-12
Abstract:
This research proposes an optimal robotic arm speed shape in neurological surgery to minimise a cost functional that uses an adaptive scheme to determine the brain tissue force. Until now, there have been no studies or theories on the shape of the robotic arm speed in such a context. The authors have applied a robotic arm with optimal speed control in neurological surgery. The results of this research are as follows: In this article, the authors propose a control scheme that minimises a cost functional which depends on the position error, trajectory speed and brain tissue force. This work allowed us to achieve an optimal speed shape or trajectory to reduce brain retraction damage during surgery. The authors have reached two main conclusions. The first is that optimal control techniques are very well suited for robotic control of neurological surgery. The second conclusion is that several studies on functional cost parameters are needed to achieve the best trajectory speed of the robotic arm. These studies could attempt to optimise the functional cost parameters and provide a mechanical characterisation of brain tissue based on real data.
Keywords: neurosurgical robotics; optimal control; optimal speed shape (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:4:p:828-:d:1059676
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