Robot Autonomy for Surgery

Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots

Robots and tools for remodeling bone

The field of robotic surgery has progressed from small teams of researchers repurposing industrial robots, to a competitive and highly innovative subsection of the medical device industry. Surgical robots allow surgeons to perform tasks with greater ease, accuracy, or safety, and fall under one of four levels of autonomy; active, semi-active, passive, and remote manipulator. The increased accuracy afforded by surgical robots has allowed for cementless hip arthroplasty, improved postoperative alignment following knee arthroplasty, and reduced duration of intraoperative fluoroscopy among other benefits. Cutting of bone has historically used tools such as hand saws and drills, with other elaborate cutting tools now used routinely to remodel bone. Improvements in cutting accuracy and additional options for safety and monitoring during surgery give robotic surgeries some advantages over conventional techniques. This article aims to provide an overview of current robots and tools with a common target tissue of bone, proposes a new process for defining the level of autonomy for a surgical robot, and examines future directions in robotic surgery

Robotic-assisted internal fixation of femoral fractures

Closed surgical techniques for the internal fixation of femoral fractures require orthopaedic surgeons to work in close proximity to X-rays. In addition to the occupational health risk this imposes, inexperienced surgeons often encounter great difficulty in achieving optimal positioning of fracture repair fixtures. A vision-guided robotic system has been proposed as a possible solution to these problems and an initial investigation involving two exemplar orthopaedic procedures has been undertaken. Robotic surgery assistance imposes rigorous safety-related design constraints, since the orthopaedic robot must operate in close proximity to the patient and operating staff. The design and implementation of a purpose-built robotic system for orthopaedic surgery assistance is described in this paper

Characterization of a Contact-Stylus Surface Digitization Method Using Collaborative Robots: Accuracy Evaluation in the Context of Shoulder Replacement or Resurfacing

Total shoulder arthroplasty (TSA) is the third most common joint replacement. While robot-assisted hip and knee replacement technologies have enjoyed extensive development, this has been limited in the upper limb. This work focused on quantifying the localization accuracy of a robotic system, and evaluating its efficacy in the context of TSA. A collaborative robot was fitted with a stylus tip to perform manual surface digitizations using the robot’s encoder output. In the first experiment, two precision-machined master cubes, representing the working volume around a glenoid structure, were used for system validation. Next, cadaveric glenoids were digitized and compared to a ‘gold standard’ laser scanner. Digitization errors were 0.37±0.27 mm, showing that collaborative robotics can be used for osseous anatomy digitization. This thesis presents two novel concepts: 1) use of collaborative robotics for manually operated surface digitizing, and 2) optical fiducial technique, allowing registration between a laser scanner and stylus digitizer

From Concept to Market: Surgical Robot Development

Surgical robotics and supporting technologies have really become a prime example of modern applied information technology infiltrating our everyday lives. The development of these systems spans across four decades, and only the last few years brought the market value and saw the rising customer base imagined already by the early developers. This chapter guides through the historical development of the most important systems, and provide references and lessons learnt for current engineers facing similar challenges. A special emphasis is put on system validation, assessment and clearance, as the most commonly cited barrier hindering the wider deployment of a system

Computer assisted orthopaedic surgery : past, present and future

Computer technology is ubiquitous and relied upon in virtually all professional activities including neurosurgery, which is why it is surprising that it is not the case for orthopaedic surgery with fewer than 5% of surgeons using available computer technology in their procedures. In this review, we explore the evolution and background of Computer Assisted Orthopaedic Surgery (CAOS), delving into the basic principles behind the technology and the changes in the discussion on the subject throughout the years and the impact these discussions had on the field. We found evidence that industry had an important role in driving the discussion at least in knee arthroplasty-a leading field of CAOS-with the ratio between patents and publications increased from approximately 1:10 in 2004 to almost 1:3 in 2014. The adoption of CAOS is largely restrained by economics and ergonomics with sceptics challenging the accuracy and precision of navigation during the early years of CAOS moving to patient functional improvements and long term survivorship. Nevertheless, the future of CAOS remains positive with the prospect of new technologies such as improvements in image-guided surgery, enhanced navigation systems, robotics and artificial intelligence

Hand eye coordination in surgery

The coordination of the hand in response to visual target selection has always been regarded as an essential quality in a range of professional activities. This quality has thus far been elusive to objective scientific measurements, and is usually engulfed in the overall performance of the individuals. Parallels can be drawn to surgery, especially Minimally Invasive Surgery (MIS), where the physical constraints imposed by the arrangements of the instruments and visualisation methods require certain coordination skills that are unprecedented. With the current paradigm shift towards early specialisation in surgical training and shortened focused training time, selection process should identify trainees with the highest potentials in certain specific skills. Although significant effort has been made in objective assessment of surgical skills, it is only currently possible to measure surgeons’ abilities at the time of assessment. It has been particularly difficult to quantify specific details of hand-eye coordination and assess innate ability of future skills development. The purpose of this thesis is to examine hand-eye coordination in laboratory-based simulations, with a particular emphasis on details that are important to MIS. In order to understand the challenges of visuomotor coordination, movement trajectory errors have been used to provide an insight into the innate coordinate mapping of the brain. In MIS, novel spatial transformations, due to a combination of distorted endoscopic image projections and the “fulcrum” effect of the instruments, accentuate movement generation errors. Obvious differences in the quality of movement trajectories have been observed between novices and experts in MIS, however, this is difficult to measure quantitatively. A Hidden Markov Model (HMM) is used in this thesis to reveal the underlying characteristic movement details of a particular MIS manoeuvre and how such features are exaggerated by the introduction of rotation in the endoscopic camera. The proposed method has demonstrated the feasibility of measuring movement trajectory quality by machine learning techniques without prior arbitrary classification of expertise. Experimental results have highlighted these changes in novice laparoscopic surgeons, even after a short period of training. The intricate relationship between the hands and the eyes changes when learning a skilled visuomotor task has been previously studied. Reactive eye movement, when visual input is used primarily as a feedback mechanism for error correction, implies difficulties in hand-eye coordination. As the brain learns to adapt to this new coordinate map, eye movements then become predictive of the action generated. The concept of measuring this spatiotemporal relationship is introduced as a measure of hand-eye coordination in MIS, by comparing the Target Distance Function (TDF) between the eye fixation and the instrument tip position on the laparoscopic screen. Further validation of this concept using high fidelity experimental tasks is presented, where higher cognitive influence and multiple target selection increase the complexity of the data analysis. To this end, Granger-causality is presented as a measure of the predictability of the instrument movement with the eye fixation pattern. Partial Directed Coherence (PDC), a frequency-domain variation of Granger-causality, is used for the first time to measure hand-eye coordination. Experimental results are used to establish the strengths and potential pitfalls of the technique. To further enhance the accuracy of this measurement, a modified Jensen-Shannon Divergence (JSD) measure has been developed for enhancing the signal matching algorithm and trajectory segmentations. The proposed framework incorporates high frequency noise filtering, which represents non-purposeful hand and eye movements. The accuracy of the technique has been demonstrated by quantitative measurement of multiple laparoscopic tasks by expert and novice surgeons. Experimental results supporting visual search behavioural theory are presented, as this underpins the target selection process immediately prior to visual motor action generation. The effects of specialisation and experience on visual search patterns are also examined. Finally, pilot results from functional brain imaging are presented, where the Posterior Parietal Cortical (PPC) activation is measured using optical spectroscopy techniques. PPC has been demonstrated to involve in the calculation of the coordinate transformations between the visual and motor systems, which establishes the possibilities of exciting future studies in hand-eye coordination