Augmented dexterity: How robots can enhance human surgical skills.

Advances in AI and robotics have the potential to enhance the dexterity of human surgeons.

What we look for at .

Science Robotics welcomes papers demonstrating technical and scientific advances, with potential for influence beyond robotics.

Comparison of novel shielded nasopharynx applicator designs for intracavitary brachytherapy.

Purpose: Nasopharyngeal brachytherapy is limited in part by the radiotolerance of nearby organs like the soft palate. This study explores several novel shielding designs for an intracavitary applicator to significantly reduce soft palate dose while adhering to the constraints of standard treatment procedure.

Methods: The Monte Carlo code TOPAS is used to characterize each prototype under typical high-dose-rate treatment conditions.

Five years of .

Looking back at the last 5 years of and looking forward to the next 5.

Getting a grip on reality.

The ability to reliably grasp and manipulate novel objects is a grand challenge for robotics.

Deep learning can accelerate grasp-optimized motion planning.

Robots for picking in e-commerce warehouses require rapid computing of efficient and smooth robot arm motions between varying configurations. Recent results integrate grasp analysis with arm motion planning to compute optimal smooth arm motions; however, computation times on the order of tens of seconds dominate motion times. Recent advances in deep learning allow neural networks to quickly compute these motions; however, they lack the precision required to produce kinematically and dynamically feasible motions.

Combating COVID-19-The role of robotics in managing public health and infectious diseases.

COVID-19 may drive sustained research in robotics to address risks of infectious diseases.

Applying machine learning to predict future adherence to physical activity programs.

Background: Identifying individuals who are unlikely to adhere to a physical exercise regime has potential to improve physical activity interventions. The aim of this paper is to develop and test adherence prediction models using objectively measured physical activity data in the Mobile Phone-Based Physical Activity Education program (mPED) trial. To the best of our knowledge, this is the first to apply Machine Learning methods to predict exercise relapse using accelerometer-recorded physical activity data.

Learning ambidextrous robot grasping policies.

Universal picking (UP), or reliable robot grasping of a diverse range of novel objects from heaps, is a grand challenge for e-commerce order fulfillment, manufacturing, inspection, and home service robots. Optimizing the rate, reliability, and range of UP is difficult due to inherent uncertainty in sensing, control, and contact physics. This paper explores "ambidextrous" robot grasping, where two or more heterogeneous grippers are used.

Personalizing Mobile Fitness Apps using Reinforcement Learning.

Despite the vast number of mobile fitness applications (apps) and their potential advantages in promoting physical activity, many existing apps lack behavior-change features and are not able to maintain behavior change motivation. This paper describes a novel fitness app called CalFit, which implements important behavior-change features like dynamic goal setting and self-monitoring. CalFit uses a reinforcement learning algorithm to generate personalized daily step goals that are challenging but attainable.

Objectively Measured Baseline Physical Activity Patterns in Women in the mPED Trial: Cluster Analysis.

Background: Determining patterns of physical activity throughout the day could assist in developing more personalized interventions or physical activity guidelines in general and, in particular, for women who are less likely to be physically active than men.

Objective: The aims of this report are to identify clusters of women based on accelerometer-measured baseline raw metabolic equivalent of task (MET) values and a normalized version of the METs ≥3 data, and to compare sociodemographic and cardiometabolic risks among these identified clusters.

Methods: A total of 215 women who were enrolled in the Mobile Phone Based Physical Activity Education (mPED) trial and wore an accelerometer for at least 8 hours per day for the 7 days prior to the randomization visit were analyzed.

Evaluating Machine Learning-Based Automated Personalized Daily Step Goals Delivered Through a Mobile Phone App: Randomized Controlled Trial.

Background: Growing evidence shows that fixed, nonpersonalized daily step goals can discourage individuals, resulting in unchanged or even reduced physical activity.

Objective: The aim of this randomized controlled trial (RCT) was to evaluate the efficacy of an automated mobile phone-based personalized and adaptive goal-setting intervention using machine learning as compared with an active control with steady daily step goals of 10,000.

Methods: In this 10-week RCT, 64 participants were recruited via email announcements and were required to attend an initial in-person session.

Evaluation of PC-ISO for customized, 3D Printed, gynecologic 192-Ir HDR brachytherapy applicators.

The purpose of this study was to evaluate the radiation attenuation properties of PC-ISO, a commercially available, biocompatible, sterilizable 3D printing material, and its suitability for customized, single-use gynecologic (GYN) brachytherapy applicators that have the potential for accurate guiding of seeds through linear and curved internal channels. A custom radiochromic film dosimetry apparatus was 3D-printed in PC-ISO with a single catheter channel and a slit to hold a film segment. The apparatus was designed specifically to test geometry pertinent for use of this material in a clinical setting.

Risk factors for osteonecrosis of the jaws: a case-control study from the CONDOR Dental PBRN.

Case reports and cohort studies have linked bisphosphonate therapy and osteonecrosis of the jaws (ONJ), but neither causality nor specific risks for lesion development have been clearly established. We conducted a 1:3 case-control study with 3 dental practice-based research networks, using dentist questionnaires and patient interviews for collection of data on bisphosphonate therapy, demographics, co-morbidities, and dental and medical treatments. Multivariable logistic regression analyses tested associations between bisphosphonate use and other risk factors with ONJ.

Robot-Assisted Needle Steering.

Needle insertion is a critical aspect of many medical treatments, diagnostic methods, and scientific studies, and is considered to be one of the simplest and most minimally invasive medical procedures. Robot-assisted needle steering has the potential to improve the effectiveness of existing medical procedures and enable new ones by allowing increased accuracy through more dexterous control of the needle tip path and acquisition of targets not accessible by straight-line trajectories. In this article, we describe a robot-assisted needle steering system that uses three integrated controllers: a motion planner concerned with guiding the needle around obstacles to a target in a desired plane, a planar controller that maintains the needle in the desired plane, and a torsion compensator that controls the needle tip orientation about the axis of the needle shaft.

NPIP: A skew line needle configuration optimization system for HDR brachytherapy.

Purpose: In this study, the authors introduce skew line needle configurations for high dose rate (HDR) brachytherapy and needle planning by integer program (NPIP), a computational method for generating these configurations. NPIP generates needle configurations that are specific to the anatomy of the patient, avoid critical structures near the penile bulb and other healthy structures, and avoid needle collisions inside the body.

Methods: NPIP consisted of three major components: a method for generating a set of candidate needles, a needle selection component that chose a candidate needle subset to be inserted, and a dose planner for verifying that the final needle configuration could meet dose objectives.

IPIP: A new approach to inverse planning for HDR brachytherapy by directly optimizing dosimetric indices.

Purpose: Many planning methods for high dose rate (HDR) brachytherapy require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose plan is computed using these parameters, and if any dosimetric criteria are not met, the process is iterated until a suitable dose plan is found.

Risk factors for osteonecrosis of the jaws: a case-control study from the CONDOR dental PBRN.

Case reports and cohort studies have linked bisphosphonate therapy and osteonecrosis of the jaws (ONJ), but neither causality nor specific risks for lesion development have been clearly established. We conducted a 1:3 case-control study with three dental Practice-based Research Networks, using dentist questionnaires and patient interviews for collection of data on bisphosphonate therapy, demographics, co-morbidities, and dental and medical treatments. Multivariable logistic regression analyses tested associations between bisphosphonate use and other risk factors with ONJ.

Surgical Retraction of Non-Uniform Deformable Layers of Tissue: 2D Robot Grasping and Path Planning.

Robotic surgical assistants (RSAs) have the potential to facilitate surgeries and reduce human fatigue. In this paper we focus on , the common surgical primitive of grasping and lifting a thin layer of tissue to expose an underlying area. Given a 2D cross-sectional model of heterogeneous tissue with embedded structures (such as veins) and a desired underlying exposure region, we present an algorithm that computes a set of stable and secure grasp-and-retract trajectories, and runs a 3D finite element (FEM) simulation to certify the quality of each trajectory.

Feedback Control for Steering Needles Through 3D Deformable Tissue Using Helical Paths.

Bevel-tip steerable needles are a promising new technology for improving accuracy and accessibility in minimally invasive medical procedures. As yet, 3D needle steering has not been demonstrated in the presence of tissue deformation and uncertainty, despite the application of progressively more sophisticated planning algorithms. This paper presents a feedback controller that steers a needle along 3D helical paths, and varies the helix radius to correct for perturbations.

Planning Fireworks Trajectories for Steerable Medical Needles to Reduce Patient Trauma.

Accurate insertion of needles to targets in 3D anatomy is required for numerous medical procedures. To reduce patient trauma, a "fireworks" needle insertion approach can be used in which multiple needles are inserted from a single small region on the patient's skin to multiple targets in the tissue. In this paper, we explore motion planning for "fireworks" needle insertion in 3D environments by developing an algorithm based on Rapidly-exploring Random Trees (RRTs).

3D Motion Planning Algorithms for Steerable Needles Using Inverse Kinematics.

Steerable needles can be used in medical applications to reach targets behind sensitive or impenetrable areas. The kinematics of a steerable needle are nonholonomic and, in 2D, equivalent to a Dubins car with constant radius of curvature. In 3D, the needle can be interpreted as an airplane with constant speed and pitch rate, zero yaw, and controllable roll angle.