Healing Health Care Disparities: Development and Pilot Testing of a Virtual Reality Implicit Bias Training Module for Physicians in the Context of Black Maternal Health.

Grounded in communication models of cultural competence, this study reports on the development and testing of the first module in a larger virtual reality (VR) implicit bias training for physicians to help them better: (a) recognize implicit bias and its effects on communication, patients, and patient care; (b) identify their own implicit biases and exercise strategies for managing them; and (c) learn and practice communicating with BIPOC patients in a culture-centered manner that demonstrates respect and builds trust. Led by communication faculty, a large, interdisciplinary team of researchers, clinicians, and engineers developed the first module tested herein focused on training goal (a). Within the module, participants observe five scenes between patient Marilyn Hayes (a Black woman) and Dr.

Reliability in performance assessment creates a potential application of artificial intelligence in veterinary education: evaluation of suturing skills at a single institution.

Objectives: To evaluate suturing skills of veterinary students using 3 common performance assessments (PAs) and to compare findings to data obtained by an electromyographic armband.

Sample: 16 second-year veterinary students.

Procedures: Students performed 4 suturing tasks on synthetic tissue models 1, 3, and 5 weeks after a surgical skills course.

Low-Cost UVBot Using SLAM to Mitigate the Spread of Noroviruses in Occupational Spaces.

Noroviruses (NoVs) cause over 90% of non-bacterial gastroenteritis outbreaks in adults and children in developed countries. Therefore, there is a need for approaches to mitigate the transmission of noroviruses in workplaces to reduce their substantial health burden. We developed and validated a low-cost, autonomous robot called the UVBot to disinfect occupational spaces using ultraviolet (UV) lamps.

Classification of Activities of Daily Living Based on Grasp Dynamics Obtained from a Leap Motion Controller.

Stroke is one of the leading causes of mortality and disability worldwide. Several evaluation methods have been used to assess the effects of stroke on the performance of activities of daily living (ADL). However, these methods are qualitative.

Upper Limb Home-Based Robotic Rehabilitation During COVID-19 Outbreak.

The coronavirus disease (COVID-19) outbreak requires rapid reshaping of rehabilitation services to include patients recovering from severe COVID-19 with post-intensive care syndromes, which results in physical deconditioning and cognitive impairments, patients with comorbid conditions, and other patients requiring physical therapy during the outbreak with no or limited access to hospital and rehabilitation centers. Considering the access barriers to quality rehabilitation settings and services imposed by social distancing and stay-at-home orders, these patients can be benefited from providing access to affordable and good quality care through home-based rehabilitation. The success of such treatment will depend highly on the intensity of the therapy and effort invested by the patient.

Convolutional Correlation Analysis for Enhancing the Performance of SSVEP-Based Brain-Computer Interface.

Currently, most of the high-performance models for frequency recognition of steady-state visual evoked potentials (SSVEPs) are linear. However, SSVEPs collected from different channels can have non-linear relationship among each other. Linearly combining electroencephalogram (EEG) from multiple channels is not the most accurate solution in SSVEPs classification.

Hand gesture recognition using surface electromyography.

Surface electromyography has become one of the popular methods for recognizing hand gestures. In this paper, the performance of four classification methods on sEMG signals have been investigated. These methods are developed by combinations of two feature extraction methods, including Mean Absolute Value and Short-Time Fourier Transform, and two classifiers, including Support Vector Machine and Convolutional Neural Network.

Force calibration for an endovascular robotic system with proximal force measurement.

Surgeons, while performing manual endovascular procedures with conventional surgical tools (catheters and guidewires), experience forces on the tool outside the patient's body that are proximal to the point of actuation. Currently, most of the robotic systems for endovascular procedures use active catheters to navigate vasculature and to measure the contact forces at the distal end (tool tip). These tools are more expensive than the conventional surgical tools used in endovascular procedures.

A new implementation for online calculation of manipulator Jacobian.

This paper describes a new implementation for calculating Jacobian and its time derivative for robot manipulators in real-time. The estimation of Jacobian is the key in the real-time implementation of kinematics and dynamics of complex planar or spatial robots with fixed as well as floating axes in which the Jacobian form changes with the structure. The proposed method is suitable for such implementations.

Surgical Robot with Environment Reconstruction and Force Feedback.

We present a new surgical robot hardware-in-the-loop simulator, with 3D surgical field reconstruction in RGB-D sensor range, which allows tool-tissue interactions to be presented as haptic feedback and thus provides the situation awareness of unwanted collision. First, the point cloud of the complete surgical environment is constructed from multiple frames of sensor data to avoid the occlusion issue. Then the user selects a region of interest where the robot's tool must avoid (also called forbidden region).

3D printing for preoperative planning and surgical training: a review.

Surgeons typically rely on their past training and experiences as well as visual aids from medical imaging techniques such as magnetic resonance imaging (MRI) or computed tomography (CT) for the planning of surgical processes. Often, due to the anatomical complexity of the surgery site, two dimensional or virtual images are not sufficient to successfully convey the structural details. For such scenarios, a 3D printed model of the patient's anatomy enables personalized preoperative planning.

Design and Development of Surgeon Augmented Endovascular Robotic System.

Objective: Inadequate visual and force feedback while navigating surgical tools elevate the risk of endovascular procedures. It also poses occupational hazard due to repeated exposure to X-rays. A teleoperated robotic system that augments surgeon's actions is a solution.

Surgeon Training in Telerobotic Surgery via a Hardware-in-the-Loop Simulator.

This work presents a software and hardware framework for a telerobotic surgery safety and motor skill training simulator. The aims are at providing trainees a comprehensive simulator for acquiring essential skills to perform telerobotic surgery. Existing commercial robotic surgery simulators lack features for safety training and optimal motion planning, which are critical factors in ensuring patient safety and efficiency in operation.

Construct validation of the key components of Fundamental Skills of Robotic Surgery (FSRS) curriculum--a multi-institution prospective study.

Background: Recent incorporation of simulation in surgical training necessitates developing validated platforms for training and assessment. A tool should fulfill the fundamental criteria of validation.

Objective: To report the ability of a simulation-based robotic training curriculum-Fundamental Skills of Robotic Surgery (FSRS)-to assess and distinguish between different performance levels of operator experience (construct validity).

Augmented-reality-based skills training for robot-assisted urethrovesical anastomosis: a multi-institutional randomised controlled trial.

Objective: To validate robot-assisted surgery skills acquisition using an augmented reality (AR)-based module for urethrovesical anastomosis (UVA).

Methods: Participants at three institutions were randomised to a Hands-on Surgical Training (HoST) technology group or a control group. The HoST group was given procedure-based training for UVA within the haptic-enabled AR-based HoST environment.

Simulation-based robot-assisted surgical training: a health economic evaluation.

Objective: To determine the overall cost effectiveness of surgical skills training on Robotic Surgical Simulator (RoSS).

Methods: This study evaluates the cost analysis of utilizing RoSS for robot-assisted surgical training, at Roswell Park Center for Robotic Surgery. Trainees were queried for time spent on the RoSS console over a period of 1 year, starting from June 2010 to June 2011.

Development and validation of a composite scoring system for robot-assisted surgical training--the Robotic Skills Assessment Score.

Background: A standardized scoring system does not exist in virtual reality-based assessment metrics to describe safe and crucial surgical skills in robot-assisted surgery. This study aims to develop an assessment score along with its construct validation.

Materials And Methods: All subjects performed key tasks on previously validated Fundamental Skills of Robotic Surgery curriculum, which were recorded, and metrics were stored.

Fundamental skills of robotic surgery: a multi-institutional randomized controlled trial for validation of a simulation-based curriculum.

Objective: To develop and establish effectiveness of simulation-based robotic curriculum--fundamental skills of robotic surgery (FSRS).

Methods: FSRS curriculum was developed and incorporated into a virtual reality simulator, Robotic Surgical Simulator (RoSS). Fifty-three participants were randomized into an experimental group (EG) or control group (CG).

Validation of Robotic Surgery Simulator (RoSS).

Recent growth of daVinci Robotic Surgical System as a minimally invasive surgery tool has led to a call for better training of future surgeons. In this paper, a new virtual reality simulator, called RoSS is presented. Initial results from two studies - face and content validity, are very encouraging.

Content validation of a novel robotic surgical simulator.

Objective: • To assess the content validity of an early prototype robotic simulator. Minimally invasive surgery poses challenges for training future surgeons. The Robotic Surgical Simulator (RoSS) is a novel virtual reality simulator for the da Vinci Surgical System.

Face validation of a novel robotic surgical simulator.

Objectives: To assess the face validity of Robotic Surgery Simulator (RoSS), a novel virtual reality training platform for the da Vinci Surgical System (DVSS).

Methods: Urologic surgeons, fellows, and residents attending the 2009 American Urologic Association Annual Meeting in April 2009 were invited to an orientation session with RoSS. Participants completed a questionnaire after orientation and two modules.

Can image-based virtual reality help teach anatomy?

Objective: To assess the utilization of a novel virtual reality robotic surgical simulator (RoSS) in surgical anatomy training and pattern recognition.

Study Design: Ten surgical trainees (medical students and residents) were recruited to participate in a study that evaluated the efficacy of a robotic simulator in anatomy training. The subjects were divided into two groups of five individuals each.

Design and fabrication of a robotic mechanism for remote steering and positioning of interventional devices.

Background: Recently, robotic systems have been introduced as a method for assisting endovascular interventional procedures. A few commercial and research solutions are available. In a survey it was found that none of the current systems satisfied all basic design requirements set forth for a good robot-assisted therapy platform.

Low cost augmented reality for training of MRI-guided needle biopsy of the spine.

In needle biopsy of the spine, an Augmented Reality (AR) image guidance system can be very effective in ensuring that while targeting the lesion with the biopsy needle, vital organs near the spine are not damaged and that the approach path is accurate. This procedure requires skill that is hard to master on patients. In this paper, we present a low cost AR based training set-up which consists of a software that uses one static single-camera tracking mechanism to locate the biopsy needle in the patient and which then augments the camera feed of the patient with virtual data providing real-time guidance to the surgeon for insertion of the biopsy needle.