Variability of tissue mechanical response in Sus Domesticus porcine models from in vivo to ex vivo conditions.

Background: Healthcare simulators have been demonstrated to be a valuable resource for training several technical and nontechnical skills. A gap in the fidelity of tissues has been acknowledged as a barrier to application for current simulators; especially for interventional procedures. Inaccurate or unrealistic mechanical response of a simulated tissue to a given surgical tool motion may result in negative training transfer and/or prevents the "suspension of disbelief" necessary for a trainee to engage in the activity.

Synthetic growth by self-lubricated photopolymerization and extrusion inspired by plants and fungi.

Many natural organisms, such as fungal hyphae and plant roots, grow at their tips, enabling the generation of complex bodies composed of natural materials as well as dexterous movement and exploration. Tip growth presents an exemplary process by which materials synthesis and actuation are coupled, providing a blueprint for how growth could be realized in a synthetic system. Herein, we identify three underlying principles essential to tip-based growth of biological organisms: a fluid pressure driving force, localized polymerization for generating structure, and fluid-mediated transport of constituent materials.

Virtual Reality Warm-up Before Robot-assisted Surgery: A Randomized Controlled Trial.

Trial Design: This was a randomized controlled trial.

Background: Intraoperative errors correlate with surgeon skill and skill declines with intervals of inactivity. The goals of this research were to identify the optimal virtual reality (VR) warm-up curriculum to prime a surgeon's technical skill and validate benefit in the operating room.

Crowd-Sourced Reliability of an Assessment of Lower Facial Aging Using a Validated Visual Scale.

Unlabelled: Reliable and valid assessments of the visual endpoints of aesthetic surgery procedures are needed. Currently, most assessments are based on the opinion of patients and their plastic surgeons. The objective of this research was to analyze the reliability of crowdworkers assessing de-identified photographs using a validated scale that depicts lower facial aging.

Bidirectional long short-term memory for surgical skill classification of temporally segmented tasks.

Purpose: The majority of historical surgical skill research typically analyzes holistic summary task-level metrics to create a skill classification for a performance. Recent advances in machine learning allow time series classification at the sub-task level, allowing predictions on segments of tasks, which could improve task-level technical skill assessment.

Methods: A bidirectional long short-term memory (LSTM) network was used with 8-s windows of multidimensional time-series data from the Basic Laparoscopic Urologic Skills dataset.

Temporal variability of surgical technical skill perception in real robotic surgery.

Purpose: Summary score metrics, either from crowds of non-experts, faculty surgeons or from automated performance metrics, have been trusted as the prevailing method of reporting surgeon technical skill. The aim of this paper is to learn whether there exist significant fluctuations in the technical skill assessments of a surgeon throughout long durations of surgical footage.

Methods: A set of 12 videos of robotic surgery cases from common human patient robotic surgeries were used to evaluate the perceived technical skill at each individual minute of the surgical videos, which were originally 12-15 min in length.

A Vision for Using Simulation & Virtual Coaching to Improve the Community Practice of Orthopedic Trauma Surgery.

Background: Many orthopedic surgeries involve the challenging integration of fluoroscopic image interpretation with skillful tool manipulation to enable procedures to be performed through less invasive approaches. Simulation has proved beneficial for teaching and improving these skills for residents, but similar benefits have not yet been realized for practicing orthopedic surgeons. A vision is presented to elevate community orthopedic practice and improve patient safety by advancing the use of simulators for training and assessing surgical skills.

The effect of video playback speed on surgeon technical skill perception.

Purpose:  Finding effective methods of discriminating surgeon technical skill has proved a complex problem to solve computationally. Previous research has shown that obtaining non-expert crowd evaluations of surgical performances is as accurate as the gold standard, expert surgeon review. The aim of this research is: (1) to learn whether crowdsourced evaluators give higher ratings of technical skill to video of performances with increased playback speed, (2) its effect in discriminating skill levels, and (3) whether this increase is related to the evaluator consciously being aware that the video is manually manipulated.

Conditions for reliable grip force and jaw angle estimation of da Vinci surgical tools.

Purpose: This work presents an estimation technique as well as corresponding conditions which are necessary to produce an accurate estimate of grip force and jaw angle on a da Vinci surgical tool using back-end sensors alone.

Methods: This work utilizes an artificial neural network as the regression estimator on a dataset acquired from custom hardware on the proximal and distal ends. Through a series of experiments, we test the effect of estimation accuracy due to change in operating frequency, using the opposite jaw, and using different tools.

Blended shared control utilizing online identification : Regulating grasping forces of a surrogate surgical grasper.

Purpose: Surgical robots are increasingly common, yet routine tasks such as tissue grasping remain potentially harmful with high occurrences of tissue crush injury due to the lack of force feedback from the grasper. This work aims to investigate whether a blended shared control framework which utilizes real-time identification of the object being grasped as part of the feedback may help address the prevalence of tissue crush injury in robotic surgeries.

Methods: This work tests the proposed shared control framework and tissue identification algorithm on a custom surrogate surgical robotic grasping setup.

Stretchable, Flexible, Scalable Smart Skin Sensors for Robotic Position and Force Estimation.

The design and validation of a continuously stretchable and flexible skin sensor for collaborative robotic applications is outlined. The skin consists of a PDMS skin doped with Carbon Nanotubes and the addition of conductive fabric, connected by only five wires to a simple microcontroller. The accuracy is characterized in position as well as force, and the skin is also tested under uniaxial stretch.

Biomechanics of human parietal pleura in uniaxial extension.

Tension pneumothorax, a major preventable cause of battlefield death, often arises from chest trauma and is treated by needle decompression to release trapped air from the pleural cavity. Surgical simulation mannequins are often employed to train medical personnel to perform this procedure properly. Accurate reproduction of the mechanical behavior of the parietal pleura, especially in response to needle penetration, is essential to maximize the fidelity of these surgical simulators.

The minimally acceptable classification criterion for surgical skill: intent vectors and separability of raw motion data.

Purpose: Minimally invasive surgery requires objective methods for skill evaluation and training. This work presents the minimally acceptable classification (MAC) criterion for computational surgery: Given an obvious novice and an obvious expert, a surgical skill evaluation classifier must yield 100% accuracy. We propose that a rigorous motion analysis algorithm must meet this minimal benchmark in order to justify its cost and use.

Predicting surgical skill from the first N seconds of a task: value over task time using the isogony principle.

Purpose: Most evaluations of surgical workflow or surgeon skill use simple, descriptive statistics (e.g., time) across whole procedures, thereby deemphasizing critical steps and potentially obscuring critical inefficiencies or skill deficiencies.

Crowd-Sourced Assessment of Technical Skills for Validation of Basic Laparoscopic Urologic Skills Tasks.

Purpose: The BLUS (Basic Laparoscopic Urologic Skills) consortium sought to address the construct validity of BLUS tasks and the wider problem of accurate, scalable and affordable skill evaluation by investigating the concordance of 2 novel candidate methods with faculty panel scores, those of automated motion metrics and crowdsourcing.

Materials And Methods: A faculty panel of surgeons (5) and anonymous crowdworkers blindly reviewed a randomized sequence of a representative sample of 24 videos (12 pegboard and 12 suturing) extracted from the BLUS validation study (454) using the GOALS (Global Objective Assessment of Laparoscopic Skills) survey tool with appended pass-fail anchors via the same web based user interface. Pre-recorded motion metrics (tool path length, jerk cost etc) were available for each video.

Validation of the AUA BLUS Tasks.

Purpose: Standardized assessment of laparoscopic skill in urology is lacking. We investigated whether the AUA (American Urological Association) BLUS (Basic Laparoscopic Urologic Skills) skill tasks are valid to address this need.

Materials And Methods: This institutional review board approved study included 27 medical students, 42 urology residents, 18 fellows and 37 faculty urologists across 8 sites.

Crowd-Sourced Assessment of Technical Skill: A Valid Method for Discriminating Basic Robotic Surgery Skills.

Background: A surgeon's skill in the operating room has been shown to correlate with a patient's clinical outcome. The prompt accurate assessment of surgical skill remains a challenge, in part, because expert faculty reviewers are often unavailable. By harnessing the power of large readily available crowds through the Internet, rapid, accurate, and low-cost assessments may be achieved.

Crowd-Sourced Assessment of Technical Skills: Differentiating Animate Surgical Skill Through the Wisdom of Crowds.

Background: Objective quantification of surgical skill is imperative as we enter a healthcare environment of quality improvement and performance-based reimbursement. The gold standard tools are infrequently used due to time-intensiveness, cost inefficiency, and lack of standard practices. We hypothesized that valid performance scores of surgical skill can be obtained through crowdsourcing.

Crowd-sourced assessment of technical skills: an adjunct to urology resident surgical simulation training.

Background: Crowdsourcing is the practice of obtaining services from a large group of people, typically an online community. Validated methods of evaluating surgical video are time-intensive, expensive, and involve participation of multiple expert surgeons. We sought to obtain valid performance scores of urologic trainees and faculty on a dry-laboratory robotic surgery task module by using crowdsourcing through a web-based grading tool called Crowd Sourced Assessment of Technical Skill (CSATS).

Beyond task time: automated measurement augments fundamentals of laparoscopic skills methodology.

Background: Laparoscopic psychomotor skills are challenging to learn and objectively evaluate. The Fundamentals of Laparoscopic Skills (FLS) program provides a popular, inexpensive, widely-studied, and reported method for evaluating basic laparoscopic skills. With an emphasis on training safety before efficiency, we present data that explore the metrics in the FLS curriculum.

Crowd-Sourced Assessment of Technical Skills: a novel method to evaluate surgical performance.

Background: Validated methods of objective assessments of surgical skills are resource intensive. We sought to test a web-based grading tool using crowdsourcing called Crowd-Sourced Assessment of Technical Skill.

Materials And Methods: Institutional Review Board approval was granted to test the accuracy of Amazon.

Virtual reality robotic surgery warm-up improves task performance in a dry laboratory environment: a prospective randomized controlled study.

Background: Preoperative simulation warm-up has been shown to improve performance and reduce errors in novice and experienced surgeons, yet existing studies have only investigated conventional laparoscopy. We hypothesized that a brief virtual reality (VR) robotic warm-up would enhance robotic task performance and reduce errors.

Study Design: In a 2-center randomized trial, 51 residents and experienced minimally invasive surgery faculty in General Surgery, Urology, and Gynecology underwent a validated robotic surgery proficiency curriculum on a VR robotic simulator and on the da Vinci surgical robot (Intuitive Surgical Inc).

Low-cost quantitative tool-tissue applied pressure indication method for surgical training and assessment in reality-based physical models.

We present a method of quantitatively measuring the pressure distribution applied to synthetic tissues by surgical tools via dye-impregnated microcapsules that rupture at specified pressures. A method utilizing pre-made indicator sheets is evaluated by force applications on synthetic bowel, and methods for creating paint-on indicator slurries were explored. A high spatial resolution of pressure intensity is demonstrated (0.

Exploratory visualization of surgical training databases for improving skill acquisition.

A new visualization system analyzes multidimensional surgical performance databases of information collected via emerging surgical robot and simulator technologies. In particular, it has visualized force, position, rotation, and synchronized video data from 300 bimanual laparoscopic surgery tasks performed by more than 50 surgeons. To explore data, the system uses a multiple-coordinated-views framework.