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Cricothyrotomy is a life-saving emergency intervention that secures an alternate airway route after a neck injury or obstruction. The procedure starts with identifying the correct location (the cricothyroid membrane) for creating an incision to insert an endotracheal tube. This location is determined using a combination of visual and palpation cues. Enabling robot-assisted remote cricothyrotomy may extend this life-saving procedure to injured soldiers or patients who may not be readily accessible for on-site intervention during search-and-rescue scenarios. As a first step towards achieving this goal, this paper explores the feasibility of palpation-assisted landmark identification for cricothyrotomy. Using a cricothyrotomy training simulator, we explore several alternatives for in-situ remote localization of the cricothyroid membrane. These alternatives include a) unaided telemanipulation, b) telemanipulation with direct force feedback, c) telemanipulation with superimposed motion excitation for online stiffness estimation and display, and d) fully autonomous palpation scan initialized based on the user's understanding of key anatomical landmarks. Using the manually digitized cricothyroid membrane location as ground truth, we compare these four methods for accuracy and repeatability of identifying the landmark for cricothyrotomy, time of completion, and ease of use. These preliminary results suggest that the accuracy of remote cricothyrotomy landmark identification is improved when the user is aided with visual and force cues. They also show that, with proper user initialization, landmark identification using remote palpation is feasible - therefore satisfying a key pre-requisite for future robotic solutions for remote cricothyrotomy., Comment: Accepted for publication in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'2021)

Emerging paradigms furthering the reach of medical technology deeper into human anatomy present unique modeling, control and sensing problems. This paper discusses a brief history of medical robotics leading to the current trend of minimally invasive intervention and diagnostics in confined spaces. Robotics for natural orifice and single port access surgery, capsule and magnetically actuated robotics and microrobotics are discussed with the aim of elucidating the state of the art. Works on modeling, sensing and control of mechanical architectures of robots for natural orifice and single port access surgery are discussed, followed by a presentation of works on magnetic actuation, sensing and localization for capsule robotics and microrobotics. Finally challenges and open problems in each one of these areas are presented.

This thesis explores the design and characterization of a hydrostatic actuator for use in magnetic imaging resonance (MRI) environments. Using a simple fluid flow architecture, the thesis proves the feasibility of using hydrostatic actuators for MRI actuation and lays the theoretical groundwork for further development of hydrostatic actuation for use in creating more complicated hydrostatic systems.

This thesis explores the design and characterization of a hydrostatic actuator for use in magnetic imaging resonance (MRI) environments. Using a simple fluid flow architecture, the thesis proves the feasibility of using hydrostatic actuators for MRI actuation and lays the theoretical groundwork for further development of hydrostatic actuation for use in creating more complicated hydrostatic systems.

In this work, we develop an approach for guiding robots to automatically localize and find the shapes of tumors and other stiff inclusions present in the anatomy. Our approach uses Gaussian processes to model the stiffness distribution and active learning to direct the palpation path of the robot. The palpation paths are chosen such that they maximize an acquisition function provided by an active learning algorithm. Our approach provides the flexibility to avoid obstacles in the robot's path, incorporate uncertainties in robot position and sensor measurements, include prior information about location of stiff inclusions while respecting the robot-kinematics. To the best of our knowledge this is the first work in literature that considers all the above conditions while localizing tumors. The proposed framework is evaluated via simulation and experimentation on three different robot platforms: 6-DoF industrial arm, da Vinci Research Kit (dVRK), and the Insertable Robotic Effector Platform (IREP). Results show that our approach can accurately estimate the locations and boundaries of the stiff inclusions while reducing exploration time., Comment: 8 pages, ICRA 2018