Surgical Robotics & Technologies

Capsule Robots are meso-scale devices that leverage extreme miniaturization to access and operate in environments that are out of reach for larger robots. In medicine, capsule robots can enter the human body through natural orifices or small incisions, and perform endoscopy and surgery while minimizing the invasiveness of the procedure. Our research focuses on two main aspects of medical capsule robots.

The first is more fundamental and aims to study novel approaches for magnetic manipulation of capsule robots combined with real-time proprioceptive sensing. Specifically, we are studying remote magnetic manipulation for controlling a capsule deep inside the human body, and local magnetic actuation to transfer controlled mechanical power across the skin. Proprioceptive sensing provides online estimations of the capsule position and orientation, and an indication of the coupling force.

We are also interested in the science of autonomy applied to medical capsule robots. Real-time tissue interaction models and novel methods for interpreting endoscopic images are being used to provide environmental awareness and guarantee safety during surgical operations. Closed-loop control of magnetic manipulation, combined with high-level intelligence, will enable the level of assistance provided by the robotic platform to the clinician to span from transparent teleoperation to autonomous execution of surgical tasks. This will enable intelligent capsule robots to amplify the diagnostic and interventional capabilities of gastroenterologists and surgeons.

As the World Health Organization (WHO) recently highlighted, sustainable development in low resource countries will be hard to achieve unless the international health and development community addresses the enormous global burden of surgical conditions. In low and middle-income countries (LMICs) over 90% of the population do not have access to safe, affordable surgical care. There is an urgent need to scale-up surgical services to prevent them becoming a major barrier to national income growth, economic productivity, and improved human welfare. The goals of our research are to identify the barriers to surgical care, characterise and prioritise the unmet surgical needs, and develop affordable technological solutions that are intelligent enough to lower the barriers for healthcare delivery. Our work is highly multidisciplinary and is the result of a well-established link between the Faculty of Engineering, the Academic Unit of Surgery, the Nuffield Centre for International Health and Development, and a strong network of partners in LMICs, including Sierra Leone, India, Honduras and rural areas of China.

Surgical robotics platforms that are currently available to hospitals straightforwardly compare to standard automobiles, as they transparently execute user’s intent. Similarly to recent advances in the automotive sector, increasing levels of automation will soon enable robots to perform parts of the procedure, thus lowering the burden for the surgical team and improving healthcare outcomes. Furthermore, current robotic platforms still require a relevant number of incisions to access the patient’s body and often rely on rigid or semi-rigid instrumentation.

At the University of Leeds, we are interested in automating specific surgical tasks, in designing flexible and compliant instruments, and in reducing the number of incisions required to perform abdominal surgery. We also collaborate with the Institute of Psychological Sciences to objectively improve human/machine interfaces and to assess surgical training methods. We test part of our research hypotheses on the daVinci Research Kit that was kindly donated us by our industrial partner Intuitive Surgical, Inc.

We conduct research examining how robotic devices can be used to accelerate the learning of surgical skills in order to reduce the magnitude and frequency of operating mistakes. We use a range of surgical technologies from low fidelity surgical box trainers through to high end robot and virtual reality systems so that trainees can practice dental (pictured) and minimally invasive surgery. The strength of our approach lies in our use of rigorous laboratory controlled experiments on human behavior (i.e. psychophysics) derived from cognitive and sensorimotor learning theory to optimise training processes. Example research topics include investigating how haptic forces should be presented to users to improve surgical skill and performance and examining how surgeons might use surgical technologies can be used to “warm-up” for complex cases through patient specific rehearsal.