Ryan A. Beasley

Medical Robots: Current Systems and Research Directions

First used medically in 1985, robots now make an impact in laparoscopy, neurosurgery, orthopedic surgery, emergency response, and various other medical disciplines. This paper provides a review of medical robot history and surveys the capabilities of current medical robot systems, primarily focusing on commercially available systems while covering a few prominent research projects. By examining robotic systems across time and disciplines, trends are discernible that imply future capabilities of medical robots, for example, increased usage of intraoperative images, improved robot arm design, and haptic feedback to guide the surgeon.

Tactile tracking of arteries in robotic surgery

Locating arteries hidden beneath superficial tissue can be a difficult task in minimally invasive surgery. This paper reports the development of a system that finds the paths of arteries using tactile sensing. The surgeon begins by using the surgical robot to place the tactile sensor instrument on a known artery location. Signal processing algorithms locate the artery from its pulsatile pressure variation. An adaptive extrapolation algorithm then generates predicted locations for the artery based on previous measurements. After moving to the predicted location, if the artery is not located then a backtracking mechanism moves the sensor towards previously detected locations. Tests with model arteries show good tracking ability for circular arcs with curvatures as small as 80 mm, although problems with compliance in the system result in occasional loss of the artery path. Preliminary tests demonstrate the ability to transcutaneously track the radial artery in the human wrist.

Increasing Accuracy in Image-Guided Robotic Surgery Through Tip Tracking and Model-Based Flexion Correction

Robot assistance can enhance minimally invasive image-guided surgery, but flexion of the thin surgical instrument shaft impairs accurate control by creating errors in the kinematic model. Two controller enhancements that can mitigate these errors are improved kinematic models that account for flexing and direct measurement of the instrument tips position. This paper presents an experiment quantifying the benefits of these enhancements in an effort to inform development of an image-guided robot control system accurate in the presence of quasi-static instrument flexion. The study measured a controllers ability to guide a flexing instrument along user-commanded motions while preventing incursions into a forbidden region virtual fixture. Compared with the controller using neither enhancement, improved kinematics and reduced maximum incursion depth into the forbidden region by 28%, tip tracking by 67%, and both enhancements together by 83%.

Model-Based Error Correction for Flexible Robotic Surgical Instruments

Robots promise to enhance minimally-invasive surgery, but flexion of the thin instrument shaft introduces error into models of the robot kinematics. Visual or electromagnetic tracking of the instrument tip provides correct forward kinematics, but uncertainty in shaft bending and port location leaves residual errors in inverse kinematics. These errors can cause incorrect motions that preclude the use of image-guidance tools. This paper proposes a model-based controller to correct the commanded motions. Comparison with a controller assuming a straight instrument shaft quantifies motion errors resulting from the use of a straight shaft controller. Analysis of the flexed shaft controller shows sensitivity to shaft length, shaft stiffness, tip force, and sensor noise.

Kinematic error correction for minimally invasive surgical robots

Robots are useful tools in minimally invasive surgery, providing benefits such as reduction in hand tremor, navigation, and workspace scaling. Unfortunately, minimally invasive configurations result in two likely sources of kinematic error: port displacement and instrument shaft flexion. For a quasistatic system, a measure is presented that relates the errors in the robot Jacobian to the angular difference between desired motions and actual motions. Simulations and experimental data demonstrate this measure for a laboratory system. One potential use for the presented measure is, for bounded errors, determining whether the system monotonically converges for all initial and desired positions in the workspace. In addition, the measure is useful for path planning, determining less error-prone paths.

Technical Aspects of Correspondence Studies

This chapter discusses technical concerns and choices that arise when crafting a correspondence or audit study using external validity as a motivating framework. The chapter discusses resume creation, including power analysis , choice of inputs, pros and cons of matching pairs, solutions to the limited template problem, and ensuring that instruments indicate what the experimenters want them to indicate. Further topics about implementation include when and for how long to field a study, deciding on a participant pool, and whether or not to use replacement from the participant pool . More technical topics include matching outcomes to inputs, data storage, and analysis issues such as when to use clustering, when not to use fixed effects, and how to measure heterogeneous and interactive effects. The chapter ends with a technical checklist that experimenters can utilize prior to fielding a correspondence study.

7 Specific Orthopaedic Imaging Analysis Software: Clinical Benefit for TKR Revision Surgeon

Current 3D imaging modalities generate a wealth of diagnostic information, yet this information is underused in orthopaedics because of the lack of orthopaedic-specific imaging software. In this chapter, we detail how orthopaedic-specific imaging software can improve the diagnostic and planning capabilities of 3D imaging. Specifically, we describe the importance of biomechanical reference frames, as well as how to establish these reference frames using anatomical landmarks. Once these reference frames are established, this provides a basis for surgeon-specific views (i.e. views that the surgeon can directly compare to the operating room) as well as precise joint replacement component measurements.

Intuition in Medical Image Segmentation: Visualizing Graph Edge Weights

Weighting functions for graph-based medical image segmentation algorithms (e.g., Graph cut) have a significant effect on the segmentation, but to our knowledge no tool provides the user with intuition towards their proper selection. The large variety, their complexity, and the limited feedback hinders comparison of choices. This paper describes a package developed to visualize the effects of various edge weighting functions and parameters, in which the image of interest is overlaid with colors depicting the relative distances from the nearest seed to each voxel. By seeing the colors vary while changing parameters, the user gains intuition into the various options for the edge weighting function. A user study demonstrating the benefits of the package is presented. It is our hope that the intuition provided by the software will result in less time required to segment medical images in the clinical work-flow.