Nonlinear Force Feedback Enhancement for Cooperative Robotic Neurosurgery Enforces Virtual Boundaries on Cortex Surface

Abstract

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 non-linear 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 non-linear force modulation functions (power, sigmoidal and arc tangent). The FFE controller with power modulation was experimentally validated with a pool of non-expert 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.

Gesteme-free context-aware adaptation of robot behavior in human–robot cooperation

“…In particular, in order to achieve high targeting accuracy, the damping characteristic of the manipulator can be modulated with respect to the distance from the desired target [38,39]. Considering K P and D P isotropic and diagonal, thus completely defined with one scalar parameter K P and D P , the space variable (SV) damping criterion [14] computes the D P value (K P is nil) as a function of the distance between the current position of the control point and the known position of the surgical target (x T ), i.e.…”

Virtual reality simulation of robotic transsphenoidal brain tumor resection: Evaluating dynamic motion scaling in a master‐slave system

“…Consequently, much work is in progress in developing new robotic manipulators and in incorporating additional features into the control loop. With the final objective of enhancing the surgeon's dexterity while working in operative conditions that have many spatial and visual restrictions, some valuable features can be incorporated into the control loop such as force feedback, tremor filtering, virtual fixtures, dynamic motion scaling (DMS), and collision avoidance …”

“…With the final objective of enhancing the surgeon's dexterity while working in operative conditions that have many spatial and visual restrictions, some valuable features can be incorporated into the control loop such as force feedback, tremor filtering, virtual fixtures, dynamic motion scaling (DMS), and collision avoidance. [7][8][9][10] On the other hand, the use of surgical simulators that traditionally have shown to be useful for training may have the capability to be used during the development of micro-surgical robotic systems.…”

Toward Improving Safety in Neurosurgery with an Active Handheld Instrument

“…Examples of assistive devices developed for forbidden-region robotic control include neuroArm [61,60], a magnetic resonance-compatible robot for image-guided, ambidextrous microneurosurgery. Cooperative control for precision targeting in neurosurgery was explored in [5,6]. In [62,59] and in [22], cooperatively controlled robots were proposed with applications in retinal surgery.…”