Browsing by Author "Estrada, Sean"

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    Expert Surgeons Can Smoothly Control Robotic Tools With a Discrete Control Interface
    (IEEE, 2019) O'Malley, Marcia K.; Byrne, Michael D.; Estrada, Sean; Duran, Cassidy; Schulz, Daryl; Bismuth, Jean
    Objective assessment of surgical skill is gaining traction in a number of specialty fields. In robot-assisted surgery in particular, the availability of data from the operating console and patient-side robot offers the potential to derive objective metrics of performance based on tool movement kinematics. While these techniques are becoming established in the laparoscopic domain, current assessment techniques for robotic endovascular surgery are based primarily on observation, checklists, and grading scales. This work presents an objective and quantitative means of measuring technical competence based on analysis of the kinematics of endovascular tool tip motions controlled with a robotic interface. We designed an experiment that recorded catheter tip movement from 21 subjects performing fundamental endovascular robotic navigation tasks on a physical model. Motion-based measures of smoothness (spectral arc length and number of submovements) were computed and tested for correlation with subjective scores from a global rating scale assessment tool that has been validated for use when performing manual catheterization. Results show that the smoothness metrics that produced significant correlations with the global rating scale for manual catheterization show similar correlations for robotic catheterization. This finding is notable, since with the robotic interface, tool tip motion is commanded discretely via a control button interface, while in manual procedures the tools are controlled through continuous movements of the surgeon's hands. Logistic regression analysis using a single motion metric was capable of classifying subjects by expertise with better than 90% accuracy. These objective and quantitative metrics that capture movement quality could be incorporated into future training protocols to provide detailed feedback on trainee performance.
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    On the development of objective metrics for surgical skills evaluation based on tool motion
    (IEEE, 2014) Estrada, Sean; O’Malley, Marcia K.; Duran, Cassidy; Schulz, Daryl; Bismuth, Jean
    A key competency requirement in endovascular surgery is to optimally visualize and utilize pre-shaped catheters to navigate complex vascular anatomy, yet current performance assessment techniques are limited to grading scales based solely on observation. Since most endovascular procedures involve performing fine motor control tasks that require complex, dexterous movements, this paper explores the potential for a standardized, objective, and quantitative means of measuring technical competence based on analysis of the kinematics of endovascular tool tip motions. To accomplish this goal, we recorded catheter tip movement from twenty subjects performing fundamental endovascular tasks in an inanimate model and in a simulation environment with a virtual representation of the same inanimate model. Several motion-based performance measures that have been shown to reliably assess skill in other domains were computed and tested for correlation with data that were obtained from the global rating scale assessment tool. The metrics that quantified movement quality by assessing movement smoothness produced reliable correlations with the observation-based assessment metrics. These objective and quantitative metrics that capture movement quality could be incorporated into future training protocols to provide detailed feedback on trainee performance.