Avent, Inc.

Shane A Duffy

Kenneth C Hsu

Justin Jeffrey Coker

Michael Rashidi Avendi

Bao-Tram N Pham

Judith Davenport

Ryan Massengale

Hilton M Kaplan

Thomas D Mina

Shirzad Shahriari

Donald J McMichael

Steve Saeed Khalaj

Hasnain Somji

Marc Comtois

Joost L Mulders

Andrew Victor Polijanczuk

Donald J Mcmichael

Tingting Wang

Ambar A Avila

Henry Gomersall

Dominique J Fantasia

Jamie Collin

Hakan J Yazarel

Aimee T Bui

A non-electrically driven enteral feeding pump including an expandable elastomeric bladder is provided. The enteral feeding pump includes a fluid delivery tube. The fluid delivery tube controls flow rate of fluid from the pump. The present invention further describes an enteral feeding pump assembly including the portable enteral feeding pump and a peristaltic pump. The peristaltic pump can be configured to be operatively coupled to the elastomeric bladder of the enteral feeding pump for transferring fluid from a reservoir external to the elastomeric bladder into a chamber of the elastomeric bladder.

Elastomeric enteral feeding pump and filling system

Systems and methods are provided for signaling a condition of an infusion assembly. An example system may comprise an elastomeric pump that includes a chamber for receipt of a volume of fluid, an outer layer configured to expand and contract as the chamber receives and dispenses the fluid, and a passive indicator provided on the outer layer for signaling a change in the volume of the fluid in the chamber. The example system further may comprise an image capture device configured to capture an image of the pump, and a processing system configured to process the image to signal the condition of the infusion assembly to a user of the system. An example method may comprise capturing the image of the pump; processing the image; and displaying information to the user of the pump to communicate a condition of the pump to the user. Various elastomeric pumps for infusion assemblies also are provided.

Flow indicator for an infusion pump

A method for scanning, identifying, and navigating at least one anatomical object of a patient via an imaging system. Such system includes scanning the anatomical object via a probe of the imaging system, identifying the anatomical object via the probe, and navigating the anatomical object via the probe. Further, the method includes collecting data, inputting the collected data into a deep learning network configured to learn the scanning, identifying, and navigating steps. In addition, the method includes generating a probe visualization guide for an operator based on the deep learning network. Thus, the method also includes displaying the probe visualization guide to the operator wherein the probe visualization guide instructs the operator how to maneuver the probe so as to locate the anatomical object. In addition, the method also includes using haptic feedback in the probe to guide the operator to the anatomical object of the patient.

System and method for identifying and navigating anatomical objects using deep learning networks

Systems and methods are provided for signaling a condition of an infusion assembly. A system may comprise an elastomeric pump that includes a chamber for receipt of a volume of fluid, an outer layer configured to expand and contract as the chamber receives and dispenses fluid, and a passive indicator provided on the outer layer for signaling a change in the volume of fluid in the chamber. The system further may comprise an image capture device configured to capture an image of the pump, and a processing system configured to process the image to signal the condition of the infusion assembly to a user of the system. A method may comprise capturing an image of a pump; processing the image; and displaying information to a user of the pump to communicate the condition of the pump to the user. Elastomeric pumps for infusion assemblies also are provided.

A needle assembly for use with an autonomous ultrasound imaging system includes a needle having a proximal end and a distal end adapted to be inserted into a patient. The needle assembly also includes a needle transducer mounted to an exterior surface of the needle and is electrically coupled to a power source. The needle transducer is configured to receive data signals from the autonomous ultrasound imaging system which contain information relating to a plurality of ultrasound waves generated by an ultrasound probe of the autonomous ultrasound imaging system. The needle assembly further includes at least one processor configured to perform one or more operations, including but not limited to, generating a location signal for at least one portion of the needle based on the data signals from the autonomous ultrasound imaging system and modifying at least one characteristic of the location signal so as to improve visibility of the location signal on the display screen, wherein the modified location signal is displayed on a display screen during use of the needle assembly so as to locate the at least one portion of the needle.

Methods for needle identification on an ultrasound display screen by determining a meta-frame rate of the data signals

The present invention is directed to a system and method for automatic detection, localization, and semantic segmentation of at least one anatomical object in a parameter space of an image generated by an imaging system. The method includes generating the image via the imaging system and providing the image of the anatomical object and surrounding tissue to a processor. Further, the method includes developing and training a parameter space deep learning network comprising convolutional neural networks to automatically detect the anatomical object and the surrounding tissue of the parameter space of the image. The method also includes automatically locating and segmenting, via additional convolutional neural networks, the anatomical object and surrounding tissue of the parameter space of the image. Moreover, the method includes automatically labeling the identified anatomical object and surrounding tissue on the image. Thus, the method also includes displaying the labeled image to a user in real time.

System and method for automatic detection, localization, and semantic segmentation of anatomical objects

The present invention is directed to a system and method for providing navigational directions to a user to locate a target anatomical object during a medical procedure via a medical imaging system. The method includes selecting an anatomical region surrounding the object; generating a plurality of real-time two-dimensional images of scenes from the anatomical region and providing the plurality of images to a controller; developing and training a deep learning network to automatically detect and identify the scenes from the anatomical region; automatically mapping each of the plurality of images from the anatomical region based on a relative spatial location and a relative temporal location of each of the identified scenes in the anatomical region via the deep learning network; and providing directions to the user to locate the object during the medical procedure based on the relative spatial and temporal locations of each of the identified scenes.

System and method for navigation to a target anatomical object in medical imaging-based procedures

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Irvine, CA, United States of America

Shane A Duffy