A gaze-contingent framework for perceptually-enabled applications in healthcare

Patient safety and quality of care remain the focus of the smart operating room of the future. Some of the most influential factors with a detrimental effect are related to suboptimal communication among the staff, poor flow of information, staff workload and fatigue, ergonomics and sterility in the operating room. While technological developments constantly transform the operating room layout and the interaction between surgical staff and machinery, a vast array of opportunities arise for the design of systems and approaches, that can enhance patient safety and improve workflow and efficiency. The aim of this research is to develop a real-time gaze-contingent framework towards a "smart" operating suite, that will enhance operator's ergonomics by allowing perceptually-enabled, touchless and natural interaction with the environment. The main feature of the proposed framework is the ability to acquire and utilise the plethora of information provided by the human visual system to allow touchless interaction with medical devices in the operating room. In this thesis, a gaze-guided robotic scrub nurse, a gaze-controlled robotised flexible endoscope and a gaze-guided assistive robotic system are proposed. Firstly, the gaze-guided robotic scrub nurse is presented; surgical teams performed a simulated surgical task with the assistance of a robot scrub nurse, which complements the human scrub nurse in delivery of surgical instruments, following gaze selection by the surgeon. Then, the gaze-controlled robotised flexible endoscope is introduced; experienced endoscopists and novice users performed a simulated examination of the upper gastrointestinal tract using predominately their natural gaze. Finally, a gaze-guided assistive robotic system is presented, which aims to facilitate activities of daily living. The results of this work provide valuable insights into the feasibility of integrating the developed gaze-contingent framework into clinical practice without significant workflow disruptions.Open Acces

Development of An In Vivo Robotic Camera for Dexterous Manipulation and Clear Imaging

Minimally invasive surgeriy (MIS) techniques are becoming more popular as replacements for traditional open surgeries. These methods benefit patients with lowering blood loss and post-operative pain, reducing recovery period and hospital stay time, decreasing surgical area scarring and cosmetic issues, and lessening the treatment costs, hence greater patient satisfaction would be earned. Manipulating surgical instruments from outside of abdomen and performing surgery needs precise hand-eye coordination which is provided by insertable cameras. The traditional MIS insertable cameras suffer from port complexity and reduced manipulation dexterity, which leads to defection in Hand-eye coordination and surgical flow. Fully insertable robotic camera systems emerged as a promising solution in MIS. Implementing robotic camera systems faces multiple challenges in fixation, manipulation, orientation control, tool-tissue interaction, in vivo illumination and clear imaging.In this dissertation a novel actuation and control mechanism is developed and validated for an insertable laparoscopic camera. This design uses permanent magnets and coils as force/torque generators in an external control unit to manipulate an in vivo camera capsule. The motorless design of this capsule reduces the, wight, size and power consumption of the driven unit. In order to guarantee the smooth motion of the camera inside the abdominal cavity, an interaction force control method was proposed and validated.Optimizing the system\u27s design, through minimizing the control unit size and power consumption and extending maneuverability of insertable camera, was achieved by a novel transformable design, which uses a single permanent magnet in the control unit. The camera robot uses a permanent magnet as fixation and translation unit, and two embedded motor for tilt motion actuation, as well as illumination actuation. Transformable design provides superior imaging quality through an optimized illumination unit and a cleaning module. The illumination module uses freeform optical lenses to control light beams from the LEDs to achieve optimized illumination over surgical zone. The cleaning module prevents lens contamination through a pump actuated debris prevention system, while mechanically wipes the lens in case of contamination. The performance of transformable design and its modules have been assessed experimentally

A Framework for Tumor Localization in Robot-Assisted Minimally Invasive Surgery

Manual palpation of tissue is frequently used in open surgery, e.g., for localization of tumors and buried vessels and for tissue characterization. The overall objective of this work is to explore how tissue palpation can be performed in Robot-Assisted Minimally Invasive Surgery (RAMIS) using laparoscopic instruments conventionally used in RAMIS. This thesis presents a framework where a surgical tool is moved teleoperatively in a manner analogous to the repetitive pressing motion of a finger during manual palpation. We interpret the changes in parameters due to this motion such as the applied force and the resulting indentation depth to accurately determine the variation in tissue stiffness. This approach requires the sensorization of the laparoscopic tool for force sensing. In our work, we have used a da Vinci needle driver which has been sensorized in our lab at CSTAR for force sensing using Fiber Bragg Grating (FBG). A computer vision algorithm has been developed for 3D surgical tool-tip tracking using the da Vinci \u27s stereo endoscope. This enables us to measure changes in surface indentation resulting from pressing the needle driver on the tissue. The proposed palpation framework is based on the hypothesis that the indentation depth is inversely proportional to the tissue stiffness when a constant pressing force is applied. This was validated in a telemanipulated setup using the da Vinci surgical system with a phantom in which artificial tumors were embedded to represent areas of different stiffnesses. The region with high stiffness representing tumor and region with low stiffness representing healthy tissue showed an average indentation depth change of 5.19 mm and 10.09 mm respectively while maintaining a maximum force of 8N during robot-assisted palpation. These indentation depth variations were then distinguished using the k-means clustering algorithm to classify groups of low and high stiffnesses. The results were presented in a colour-coded map. The unique feature of this framework is its use of a conventional laparoscopic tool and minimal re-design of the existing da Vinci surgical setup. Additional work includes a vision-based algorithm for tracking the motion of the tissue surface such as that of the lung resulting from respiratory and cardiac motion. The extracted motion information was analyzed to characterize the lung tissue stiffness based on the lateral strain variations as the surface inflates and deflates

Design and Evaluation of a Contact-Free Interface for Minimally Invasive Robotics Assisted Surgery

Robotic-assisted minimally invasive surgery (RAMIS) is becoming increasingly more common for many surgical procedures. These minimally invasive techniques offer the benefit of reduced patient recovery time, mortality and scarring compared to traditional open surgery. Teleoperated procedures have the added advantage of increased visualization, and enhanced accuracy for the surgeon through tremor filtering and scaling down hand motions. There are however still limitations in these techniques preventing the widespread growth of the technology. In RAMIS, the surgeon is limited in their movement by the operating console or master device, and the cost of robotic surgery is often too high to justify for many procedures. Sterility issues arise as well, as the surgeon must be in contact with the master device, preventing a smooth transition between traditional and robotic modes of surgery. This thesis outlines the design and analysis of a novel method of interaction with the da Vinci Surgical Robot. Using the da Vinci Research Kit (DVRK), an open source research platform for the da Vinci robot, an interface was developed for controlling the robotic arms with the Leap Motion Controller. This small device uses infrared LEDs and two cameras to detect the 3D positions of the hand and fingers. This data from the hands is mapped to the da Vinci surgical tools in real time, providing the surgeon with an intuitive method of controlling the instruments. An analysis of the tracking workspace is provided, to give a solution to occlusion issues. Multiple sensors are fused together in order to increase the range of trackable motion over a single sensor. Additional work involves replacing the current viewing screen with a virtual reality (VR) headset (Oculus Rift), to provide the surgeon with a stereoscopic 3D view of the surgical site without the need for a large monitor. The headset also provides the user with a more intuitive and natural method of positioning the camera during surgery, using the natural motions of the head. The large master console of the da Vinci system has been replaced with an inexpensive vision based tracking system, and VR headset, allowing the surgeon to operate the da Vinci Surgical Robot with more natural movements for the user. A preliminary evaluation of the system is provided, with recommendations for future work

Activity profiling for minimally invasive surgery

Imperial Users onl

Human-Robot Control Strategies for the NASA/DARPA Robonaut

The Robotic Systems Technology Branch at the NASA Johnson Space Center (JSC) is currently developing robot systems to reduce the Extra-Vehicular Activity (EVA) and planetary exploration burden on astronauts. One such system, Robonaut, is capable of interfacing with external Space Station systems that currently have only human interfaces. Robonaut is human scale, anthropomorphic, and designed to approach the dexterity of a space-suited astronaut. Robonaut can perform numerous human rated tasks, including actuating tether hooks, manipulating flexible materials, soldering wires, grasping handrails to move along space station mockups, and mating connectors. More recently, developments in autonomous control and perception for Robonaut have enabled dexterous, real-time man-machine interaction. Robonaut is now capable of acting as a practical autonomous assistant to the human, providing and accepting tools by reacting to body language. A versatile, vision-based algorithm for matching range silhouettes is used for monitoring human activity as well as estimating tool pose

SMART IMAGE-GUIDED NEEDLE INSERTION FOR TISSUE BIOPSY

M.S

Workflow-based Context-aware Control of Surgical Robots

Surgical assistance system such as medical robots enhanced the capabilities of medical procedures in the last decades. This work presents a new perspective on the use of workflows with surgical robots in order to improve the technical capabilities and the ease of use of such systems. This is accomplished by a 3D perception system for the supervision of the surgical operating room and a workflow-based controller, that allows to monitor the surgical process using workflow-tracking techniques

Medical SLAM in an autonomous robotic system

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-operative morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilities by observing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted instruments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This thesis addresses the ambitious goal of achieving surgical autonomy, through the study of the anatomical environment by Initially studying the technology present and what is needed to analyze the scene: vision sensors. A novel endoscope for autonomous surgical task execution is presented in the first part of this thesis. Which combines a standard stereo camera with a depth sensor. This solution introduces several key advantages, such as the possibility of reconstructing the 3D at a greater distance than traditional endoscopes. Then the problem of hand-eye calibration is tackled, which unites the vision system and the robot in a single reference system. Increasing the accuracy in the surgical work plan. In the second part of the thesis the problem of the 3D reconstruction and the algorithms currently in use were addressed. In MIS, simultaneous localization and mapping (SLAM) can be used to localize the pose of the endoscopic camera and build ta 3D model of the tissue surface. Another key element for MIS is to have real-time knowledge of the pose of surgical tools with respect to the surgical camera and underlying anatomy. Starting from the ORB-SLAM algorithm we have modified the architecture to make it usable in an anatomical environment by adding the registration of the pre-operative information of the intervention to the map obtained from the SLAM. Once it has been proven that the slam algorithm is usable in an anatomical environment, it has been improved by adding semantic segmentation to be able to distinguish dynamic features from static ones. All the results in this thesis are validated on training setups, which mimics some of the challenges of real surgery and on setups that simulate the human body within Autonomous Robotic Surgery (ARS) and Smart Autonomous Robotic Assistant Surgeon (SARAS) projects