University of South Florida

Yu Sun

Dmitry B Goldgof

Ghadh A Alzamzmi

Rangachar Kasturi

Terri Ashmeade

Jaime Eduardo Sanchez

Xiaoning Qian

Bingxiong Lin

Md Sirajus Salekin

Yun Lin

Yongqiang Huang

Richard Dennis Gitlin

Peter Randolph Mouton

Alexander S Rosemurgy

Sharona B Ross

Rahul Paul

Adam Anderson

Troi Williams

Adrian S Johnson

Chih-Yun Pai

Sammie Lee Elkins

Thao Ho

Yuongqiang Huang

David Andres Paulius

Michael David Coovert

Maxat Alibayev

Ivan Shindev

A Neonatal CNN (N-CNN) is provided for detecting neonatal pain emotion based upon facial recognition. A cascaded N-CNN is trained using a Neonatal Pain Assessment Database (NPAD) to automatically identify a neonatal patient experience pain in real-time. These results show that the automatic recognition of neonatal pain provided by the embodiments of the present invention is a viable and more efficient alternative to the current standard of pain assessment.

Neonatal pain identification from neonatal facial expressions

A method for motion recognition and embedding is disclosed. The method may include receiving a plurality of frames of an input video for extracting a feature vector of a motion in the plurality of frames, generating a plurality of sets of one or more motion component bits based on the feature vector and a plurality of classifiers, the plurality of sets corresponding to the plurality of classifiers, each set of one or more motion component bits representing a physical or mechanical attribute of the motion; and generating a motion code for a machine to execute the motion by combining the plurality of sets of one or more motion component bits. Other aspects, embodiments, and features are also claimed and described.

Motion taxonomy for manipulation embedding and recognition

A computer-based system and method for generating a current pain assessment of a neonate using facial expressions along with crying sounds, body movement, and vital signs changes and for using the current pain objective assessment to predict future pain objective assessment and assign a future pain probability score by incorporation spatiotemporal data into the multimodal assessment.

System and method for multimodal spatiotemporal pain assessment

System and methods for generating a trajectory of a dynamical system are described herein. An example method includes modelling a policy from demonstration data. The method also includes generating a first set of action particles by sampling from the policy, where each of the action particles in the first set includes a respective system action, predicting a respective outcome of the dynamical system in response to each of the action particles in the first set, and weighting each of the action particles in the first set according to a respective probability of achieving a desired outcome. The method further includes generating a second set of action particles by sampling from the weighted action particles, where each of the action particles in the second set includes a respective system action, and selecting a next system action in the trajectory of the dynamical system from the action particles in the second set.

Systems and methods for learning and generating movement policies for a dynamical system

A system and method of automatically assessing pediatric and neonatal pain using facial expressions along with crying sounds, body movement, and vital signs change to improve the diagnosis and treatment of pain in the pediatric patient population.

Comprehensive and context-sensitive neonatal pain assessment system and methods using multiple modalities

A system and method for measuring an infant's pain intensity is presented. The method for assessing an infant's pain intensity based on facial expressions is comprised of three main stages: detection of an infant's face in video sequence followed by preprocessing operations including face alignment; expression segmentation; and expression recognition or classification. Also presented is a multimodal system for assessing an infant's pain intensity using the following classifiers: facial expression classifier; vital sign classifier; crying recognition classifier; body motion classifier and state of arousal classifier. Each classifier generates an individual score, all of which are normalized and weighed to generate a total pain score that indicates pain intensity.

Machine-based infants pain assessment tool

In some embodiments, a functional object-oriented network (FOON) is provided that includes a plurality of functional units each comprising two or more input object nodes that each identify an object and its state before a manipulation motion is performed, a motion node that identifies a manipulation motion that can be performed using the objects, and one or more output object nodes that each identify an object and its state after the manipulation motion has been performed using the objects. In some embodiment, a robot can used the FOON to determine the discrete actions that are required to perform a given task.

Functional object-oriented networks for manipulation learning

System and methods for generating a trajectory of a dynamical system are described herein. An example method can include generating a desired effect on the dynamical system in response to a plurality of system states and effects, where the desired effect is associated with a confidence value. The method can also include predicting a respective corresponding effect on the dynamical system in response to each of a plurality of possible system actions, where each respective corresponding effect is associated with a confidence value. The method can further include comparing each respective corresponding effect on the dynamical system to the desired effect on the dynamical system, and selecting a next system action in the trajectory of the dynamical system based on the comparison.

A noise and bias can be determined for a sensor. An input vector can be received. A parameter vector can be generated based at least in part on a feed-forward neural network. Components can be determined using the parameter vector based at least in part on a mixture model. A conditional probability density function can be generated based at least in part on the conditional probability density function.

Learning state-dependent sensor measurement models for localization

Aspects of the generation of new robotic motion trajectories are described. In one embodiment, a new robot motion trajectory may be generated by gathering demonstrated motion trajectories, adapting the demonstrated motion trajectories into robot-reachable motion trajectories based on a joint space of a robot model, for example, and generating motion harmonics with reference to the motion trajectories. Further, one or more constraints may be specified for a new goal. The weights of the motion harmonics may then be searched to identify or generate a new motion trajectory for a robot, where the new motion minimizes discrepancy from the demonstrated motion trajectories and error due to the at least one constraint. In the new motion trajectory, the degree to which the constraints are satisfied may be tuned using a weight. According to the embodiments, new motion variants may be generated without the need to learn or review new demonstrated trajectories.

Generating robotic trajectories with motion harmonics

In one embodiment, communicating robot intentions to human beings involves determining movements that a robot will make to complete a task, visually communicating a long-term intention of the robot that provides an indication of the movements the robot will make in completing the task, and visually communicating a short-tem intention of the robot that provides an indication of a movement of the robot will make within the next few seconds in working toward completing the task.

Systems and methods for communicating robot intentions to human beings

In one embodiment, a system and method for planning a robot grasp involve measuring interaction forces imposed on an object by an environment while a task is demonstrated using the object to obtain a disturbance distribution dataset, modeling a task requirement based upon the disturbance distribution dataset, identifying robot grasp types that can be used to satisfy the task requirement, calculating a grasp wrench space for each identified robot grasp, and calculating a grasp quality of each grasp.

Systems and methods for planning a robot grasp that can withstand task disturbances

In one embodiment, a method for providing augmented reality in minimally invasive surgery includes capturing pre-operative image data of internal organs of a patient, capturing intra-operative image data of the internal organs with an endoscope during a surgical procedure, registering the pre-operative image data and the intra-operative data in real time during the surgical procedure, tracking the position and orientation of the endoscope during the surgical procedure, and augmenting the intra-operative image data captured by the endoscope in real time with a rendering of at least a portion of an internal organ of the patient that is in registration with the real time intra-operative image data from the endoscope but outside of the field of view of the endoscope.

Systems and methods for providing augmented reality in minimally invasive surgery

In one embodiment, a method for providing augmented reality in minimally invasive surgery includes capturing pre-operative image data of internal organs of a patient, capturing intra-operative image data of the internal organs with an endoscope during a surgical procedure, registering the pre-operative image data and the intra-operative data in real time during the surgical procedure, tracking the position and orientation of the endoscope during the surgical procedure, and augmenting the intra-operative image data captured by the endoscope in real time with a rendering of an internal organ of the patient.

In one embodiment, a method for projecting images on a subject includes determining a pose and position of the subject, adjusting a three-dimensional model of an anatomical structure of the subject to match the determined pose and position, and projecting an image of the anatomical structure onto the subject in registration with the actual anatomical structure of the subject to illustrate the location of the structure on or within the subject.

Growing community of inventors

Tampa, FL, United States of America

Yu Sun