Our purpose is to assess if bone drilling sounds could be used to automatically distinguish between hard- and soft-bone tissues. Such a capability could be of value in a variety of surgical procedures involving drilling through bone. We acquired sound signals from six bovine tibial bones that were being drilled with a surgical drill. We investigated various classifiers including logistic regression, support vector machine (SVM), random forest (RF), and hidden Markov model. We explored different time and frequency features, and considered two training/testing scenarios: leave-one bone-out (LOBO) and bone-specific (BSP). Moreover, we conducted a survey of practicing surgeons to provide a baseline measure for assessing whether our proposed algorithm could improve the ability of surgeons to identify hard- and soft-bone tissues based on drilling sounds. The average accuracies for LOBO and BSP were 79.1% and 84.3%, respectively. In both scenarios, the feature that resulted in the highest accuracy of classification was wavelet packet transform coefficients. Moreover, RF and SVM produced the highest accuracies for LOBO and BSP, respectively. In the survey, the surgeons were unsure on 29.2% of questions, and had an average accuracy of 51.4% on their judged answers. In conclusion, the drilling in hard and soft bones could be automatically identified with good accuracy based on the drilling sounds. Several of the algorithms tested were generalizable across specimens and their accuracy significantly exceeded surgeons' performance. The significance is that these algorithms can potentially be used to reduce challenges associated with bone-drilling procedures.

The objective of this work was to design a compact, accurate, safe, and ease-to-use surgical robot for total knee arthroplasty. The goal of the bone-mounted robot, named Praxiteles, is to precisely position a surgical bone-cutting guide in the appropriate planes surrounding the knee, so that the surgeon can perform the cuts manually using the guide. The robot architecture is comprised of 2 motorized degrees of freedom (DOF) whose axes of rotation are arranged in parallel, and are precisely aligned to the implant cutting planes with a 2 DOF serial adjustment mechanism. An initial prototype was first developed and tested on saw bones and cadavers, and construction of a new, refined version is now well underway. A backdrivable system, with high-stiffness, high-precision static positioning capabilities and safe low-force dynamic movement is achieved using a quick-release, spring-loaded mechanical braking system integrated in a gear transmission unit at the level of the motor outputs. This paper discusses the technical challenges encountered during the development, design, and construction of the system.

This work describes a platform devised to explore the impact on task execution in a virtual environment of the quality, and therefore cost, of the system's haptic hardware. This platform is a complex haptic interface in which hardware quality can be varied in simulation. Software intercepts the position and force signals between the haptic hardware and the virtual environment software, and alters them to supply the effect of increased friction, cogging, backlash, inertia and/or lower force output. All parameters of the introduced effects can be set independently or in combination and on a continuous scale; a primary contribution is the creation of haptically realistic effect models that are stable in combination on complex hardware. This work is part of a larger project in which we test the effect of the simulated degradations on surgeons performance in simulated laparoscopic tasks.

We propose a greatly simplified femoral canal shaping method for robot-assisted total hip replacement surgery that requires neither CT/MRI imaging nor insertion of fiducial markers before surgery. A reamer-shaped registration gauge is inserted into the femoral canal and used to position a base for a robot that is mounted on the top of the femur and used to prepare the femoral canal. In a study using 5 fresh cadavers, the average registration error for selected points near the surface of the femoral cavity was 0.59 mm; this is comparable to the errors reported for the geometry-based registration methods.

Both in designing teleoperators or haptic interfaces and in fundamental biological motor control studies, it is important to characterize the motor commands and mechanical impedance responses of the operator (or subject). Although such a characterization is fundamentally impossible for isolated movements when these two aspects of motor behavior have similar time scales (as is the case with humans), it is nonetheless possible, if we are dealing with repeated movements, to measure a trajectory which is analogous to the current source in Norton-equivalent electrical circuits. We define the attractor trajectory to be this equivalent source and show that it rigorously embodies the notion of the attractor point of a time-evolving system. We demonstrate that most previous attempts to test a controversial motor control hypothesis known as the "equilibrium point" or "virtual trajectory" hypothesis are based on inadequate models of the neuromuscular system, and we propose a model-independent means of testing the hypothesis based on a comparison of measurable attractor trajectories at different levels of the motor system. We present and demonstrate means of making such measurements experimentally and of assigning error bounds to the estimated trajectories.