Editorial. Ethical nuances and medicolegal vulnerabilities in robotic neurosurgery

Surgeons can benefit from the cooperation with a robotic assistant during the repetitive execution of precise targeting tasks on soft tissues, such as brain cortex stimulation procedures in open-skull neurosurgery. Position-based force-to-motion control schemes may not be satisfactory solution to provide the manipulator with the high compliance desirable during guidance along wide trajectories. A new torque controller with nonlinear force feedback enhancement (FFE) is presented to provide augmented haptic perception to the operator from instrument-tissue interaction. Simulation tests were performed to evaluate the system stability according to different nonlinear force modulation functions (power, sigmoidal and arc tangent). The FFE controller with power modulation was experimentally validated with a pool of nonexpert users using brain-mimicking gelatin phantoms (8–16% concentration). Besides providing hand tremor rejection for a stable holding of the tool, the FFE controller was proven to allow for a safer tissue contact with respect to both robotic assistance without force feedback and freehand executions (50% and 75% reduction of the indentation depth, respectively). Future work will address the evaluation of the safety features of the FFE controller with expert surgeons on a realistic brain phantom, also accounting for unpredictable tissue motions as during seizures due to cortex stimulation.

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Robotic neurosurgery and post-COVID 19 neurological syndrome: two colossal challenges for low- and middle-income countries

Journal of Neurosurgical Sciences ◽

10.23736/s0390-5616.21.05489-8 ◽

2021 ◽

Author(s):

Michael G. ORTEGA-SIERRA ◽

Osnaider A. CUELLO-TORRES ◽

Alexander JIMÉNEZ-ARTEAGA ◽

Lina M. PÉREZ-BENITEZ ◽

María P. BOLAÑO-ROMERO

Keyword(s):

Middle Income ◽

Neurological Syndrome ◽

Middle Income Countries ◽

Robotic Neurosurgery ◽

Low And Middle Income

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Future Directions in Robotic Neurosurgery

Operative Neurosurgery ◽

10.1093/ons/opab135 ◽

2021 ◽

Author(s):

Christopher R Wagner ◽

Timothy Phillips ◽

Serge Roux ◽

Joseph P Corrigan

Keyword(s):

Machine Learning ◽

Operating Room ◽

Key Factors ◽

Future Directions ◽

Factors Affecting ◽

Implementation Challenges ◽

Image Guided ◽

Robotic Neurosurgery ◽

Specific Technology ◽

Technology Trends

Abstract In this paper, we highlight promising technologies in each phase of a robotic neurosurgery operation, and identify key factors affecting how quickly these technologies will mature into products in the operating room. We focus on specific technology trends in image-guided cranial and spinal procedures, including advances in imaging, machine learning, robotics, and novel interfaces. For each technology, we discuss the required effort to overcome safety or implementation challenges, as well as identifying example regulatory approved products in related fields for comparison. The goal is to provide a roadmap for clinicians as to which robotic and automation technologies are in the developmental pipeline, and which ones are likely to impact their practice sooner, rather than later.

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