Hierarchical spatial hashing-based collision detection and hybrid collision response in a haptic surgery simulator

Prevalence of haptic feedback in robot-mediated surgery: a systematic review of literature

With the successful uptake and inclusion of robotic systems in minimally invasive surgery and with the increasing application of robotic surgery (RS) in numerous surgical specialities worldwide, there is now a need to develop and enhance the technology further. One such improvement is the implementation and amalgamation of haptic feedback technology into RS which will permit the operating surgeon on the console to receive haptic information on the type of tissue being operated on. The main advantage of using this is to allow the operating surgeon to feel and control the amount of force applied to different tissues during surgery thus minimising the risk of tissue damage due to both the direct and indirect effects of excessive tissue force or tension being applied during RS. We performed a two-rater systematic review to identify the latest developments and potential avenues of improving technology in the application and implementation of haptic feedback technology to the operating surgeon on the console during RS. This review provides a summary of technological enhancements in RS, considering different stages of work, from proof of concept to cadaver tissue testing, surgery in animals, and finally real implementation in surgical practice. We identify that at the time of this review, while there is a unanimous agreement regarding need for haptic and tactile feedback, there are no solutions or products available that address this need. There is a scope and need for new developments in haptic augmentation for robot-mediated surgery with the aim of improving patient care and robotic surgical technology further.

Advances in collision detection and non-linear finite mixed element modelling for improved soft tissue simulation in craniomaxillofacial surgical planning

BACKGROUND

There is a huge demand to develop a method for assisting surgeons in automatically predicting soft tissue deformation in terms of a bone-remodelling plan.

METHODS

This paper introduces several novel elements into a system for the simulation of postoperative facial appearances with respect to prespecified bone-remodelling plans. First, a new algorithm for efficient detection of collisions, using the signed distance field, is described. Next, the penalty method is applied to determine the contact load of bone on facial soft tissue. Finally, a non-linear finite mixed element model is developed to estimate the tissue deformation induced by the prescribed bone remodelling plan.

RESULTS

The performance of the proposed collision detection algorithm has been improved in memory requirements and computational efficiency compared with conventional methods. In addition, the methodology is evaluated over both synthetic and real data, with simulation performance averaging <0.5 mm pointwise error over the facial surface in six mid-face distraction osteotogenesis procedures.

CONCLUSIONS

The experimental results support the novel methodological advancements in collision detection and biomechanical modelling proposed in this work.