Non linear force feedback enhancement for cooperative robotic neurosurgery enforces virtual boundaries on cortex surface

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's motions as during seizures due to cortex stimulation

Hand-Tool-Tissue Interaction Forces in Neurosurgery for Haptic Rendering

Haptics provides sensory stimuli that represent the interaction with a virtual or telemanipulated object, and it is considered a valuable navigation and manipulation tool during tele-operated surgical procedures. Haptic feedback can be provided to the user via cutaneous information and kinesthetic feedback. Sensory subtraction removes the kinesthetic component of the haptic feedback, having only the cutaneous component provided to the user. Such a technique guarantees a stable haptic feedback loop, while it keeps the transparency of the tele-operation system high, which means that the system faithfully replicates and render back the user's directives. This work focuses on checking whether the interaction forces during a bench model neurosurgery operation can lie in the solely cutaneous perception of the human finger pads. If this assumption is found true, it would be possible to exploit sensory subtraction techniques for providing surgeons with feedback from neurosurgery. We measured the forces exerted to surgical tools by three neurosurgeons performing typical actions on a brain phantom, using contact force sensors, whilst the forces exerted by the tools to the phantom tissue were recorded using a load cell placed under the brain phantom box. The measured surgeon-tool contact forces were 0.01 - 3.49 N for the thumb and 0.01 - 6.6 N for index and middle finger, whereas the measured tool- tissue interaction forces were from six to eleven times smaller than the contact forces, i.e., 0.01 - 0.59 N. The measurements for the contact forces fit the range of the cutaneous sensitivity for the human finger pad, thus, we can say that, in a tele-operated robotic neurosurgery scenario, it would possible to render forces at the fingertip level by conveying haptic cues solely through the cutaneous channel of the surgeon's finger pads. This approach would allow high transparenc

Intraoperative forces and moments analysis on patient head clamp during awake brain surgery

In brain surgery procedures, such as deep brain stimulation, drug-resistant epilepsy and tumour surgery, the patient is intentionally awakened to map functional neural bases via electrophysiological assessment. This assessment can involve patient's body movements; thus, increasing the mechanical load on the head-restraint systems used for keeping the skull still during the surgery. The loads exchanged between the head and the restraining device can potentially result into skin and bone damage. The aim of this work is to assess such loads for laying down the requirements of a surgical robotics system for dynamic head movements compensation by fast moving arms and by an active restraint able to damp such actions. A Mayfield(A (R)) head clamp was tracked and instrumented with strain gages (SGs). SG locations were chosen according to finite element analyses. During an actual brain surgery, displacements and strains were measured and clustered according to events that generated them. Loads were inferred from strain data. The greatest force components were exerted vertically (median 5.5 N, maximum 151.87 N) with frequencies up to 1.5 Hz. Maximum measured displacement and velocity were 9 mm and 60 mm/s, with frequencies up to 2.8 Hz. The analysis of loads and displacements allowed to identify the surgery steps causing maximal loads on the head-restraint device