Haptic Modes for Multiparameter Control in Robotic Surgery

Schleer, Philipp; Drobinsky, Sergey; Hmaid, Tahany; Radermacher, Klaus

doi:10.1007/978-3-030-32254-0_20

Cited by 1 publication

(2 citation statements)

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“…The achieved tracing accuracy on the master side is in line with the results of Schleer et al [ 7 ], where mean unsigned path deviations of 0.3 mm with and 0.5 mm without haptic assistance were achieved ( =15 mm/s). This study shows that higher tracing accuracies of up to 0.07 mm on the slave side can be achieved with higher stiffness guidance or motion scaling.…”

Section: Discussionsupporting

confidence: 89%

“…Due to motion scaling, the actual required master-side tracing speed was the product of master-side scale factor and slave-side target feed rate. Haptic assistance and a visual representation of the virtual environment were implemented using Matlab Simulink (2018b, Mathworks, Natick, MA, USA) and the real-time add-on Quarc (2019 SP1, Quanser, Markham, Canada) as described in [ 7 ].…”

Section: Methodsmentioning

confidence: 99%

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Accuracy of on-site teleoperated milling with haptic assistance

et al. 2023

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Purpose In bone surgery specialties, like orthopedics, neurosurgery, and oral and maxillofacial surgery patient safety and treatment success depends on the accurate implementation of computer-based surgical plans. Unintentional plan deviations can result in long-term functional damage to the patient. With on-site teleoperation, the surgeon operates a slave robot with a physically-decoupled master device, while being directly present at the operation site. This allows the surgeon to perform surgical tasks with robotic accuracy, while always remaining in the control loop. Methods In this study the master- and slave-side accuracy of an on-site teleoperated miniature cooperative robot (minaroHD) is evaluated. Master-side accuracy is investigated in a user study regarding scale factor, target feed rate, movement direction and haptic guidance stiffness. Scale factors are chosen to correspond to primarily finger, hand, and arm movements. Slave-side accuracy is investigated in autonomous milling trials regarding stepover, feed rate, movement direction, and material density. Results Master-side user input errors increase with increasing target feed rate and scale factor, and decrease with increasing haptic guidance stiffness. Resulting slave-side errors decrease with increasing scale factor and are < 0.07 mm for optimal guidance parameters. Slave-side robot position errors correlate with the feed rate but show little correlation with stepover distance. For optimal milling parameters, the 95th percentile of tracked slave-side position error is 0.086 mm with a maximal error of 0.16 mm. Conclusion For optimal guidance and milling parameters, the combined error of 0.23 mm is in the range of the dura mater thickness (< 0.27 mm) or mandibular canal wall (~ 0.85 mm). This corresponds to safety margins in high-demand surgical procedures like craniotomies, laminectomies, or decortication of the jaw. However, for further clinical translation, the performance and usability of on-site teleoperated milling must be further evaluated for real-life clinical application examples with consideration of all error sources in a computer-assisted surgery workflow.

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Section: Discussionsupporting

confidence: 89%

Section: Methodsmentioning

confidence: 99%