INSTINCT - INtuitive Soft, stiffness-controllable hapTic INterfaCe for soft Tissue palpation during robot-assisted minimally invasive surgery

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In open surgery, surgeons are able to directly access soft tissue/organs and perform manual palpation to understand the texture, size, consistency and location of soft tissue areas. Stiffer areas than the surrounding tissue might suggest the presence of tumours. Through vision and, most importantly, tactile sensation of the surgeons' fingertips, surgeons are able to accurately localise unhealthy tissue areas by distinguishing cancerous soft tissue from healthy tissue, and remove tumours. Open surgery has been increasingly replaced by Minimally Invasive Surgery from the mid-1980s and by Robot-assisted Minimally Invasive Surgery (RMIS) from 2000. Surgical instruments are introduced through small incisions ranging from 3-12 mm into the human body to perform surgery. Though RMIS has many advantages over open surgery, including improved therapeutic outcome, shortened postoperative recovery, less immunological stress response of the tissue, reduced tissue trauma, lower postoperative pain, and less scarring, current robotic systems do not provide any type of sensation (haptic feedback) to the operating surgeon. The lack of direct palpation can lead to insufficient tumour excising resulting in an increased rate of biochemical relapse and influence decisions about future treatments such as additional surgery and radiation.Just as the definition of 'instinct' , the vision of this project is to intuitively provide surgeons with soft tissue stiffness information when performing soft tissue palpation during RMIS. Based on previous research creating soft, stiffness-controllable robotic structures and haptic feedback interfaces, the aim of this project is to design, model, fabricate and validate a soft, stiffness-controllable haptic feedback actuator which will be integrated into the da Vinci Research Kit. Of key importance for the success of this work is close collaboration with experienced clinical and industrial experts. Prof. Shervanthi Homer-Vanniasinkam (Professor of Surgery (Founding)), University of Warwick Medical School, Prof. Prokar Dasgupta (Professor of Robotic Surgery and Urological Innovation), King's College London, and Prof. Alberto Arezzo (Associate Professor of Surgery), University of Turin, Dr Alastair Barrow (MD), Generic Robotics, Dr Jerome Perret (CEO), Haption GmbH, and Dr Chris Wagner (Senior Consultant), Cambridge Consultants will consult over the duration of the project on clinical and translational aspects. These Project Partners will form the Expert Working Group meeting at least two times a year, providing feedback and critical appraisal of the experimental design, implementation and outcomes from the research project.The key objectives through which this ambition will be realised are:1) Creating pneumatically actuated, soft, stiffness-controllable fingertip interfaces made of silicone with integrated fabric meshes.2) Integration of stiffness sensor and actuators with the da Vinci Research Kit. 3) Benchmarking tests of different haptic actuator designs distinguishing between healthy and tumorous tissue.POTENTIAL APPLICATIONS AND BENEFITS:To maximise economic and clinical impact, INSTINCT project partners Generic Robotics, Haption GmbH, and Cambridge Consultants will advise on the design process, exploitation opportunities and certification procedure. These internationally operating companies aim at revolutionising therapy through ground-breaking surgical devices and simulators drawing on deep experience in simulation, haptics, engineering, electronics, control systems, Virtual Reality, medical device regulations, and commercialisation. The expertise of the industrial partner and guidance of clinical partners are of paramount importance to translate the results of the INSTINCT projects into a medical device/training simulator. Beyond the healthcare sector, possible application areas include wearable haptic devices for Virtual Reality environments and E-Learning technologies.