Patents by Inventor Lynn B. McGrath

Lynn B. McGrath has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • SMARTPHONE-BASED DIGITAL PUPILLOMETER
    Publication number: 20230225612
    Abstract: In some embodiments, techniques for using machine learning to enable visible light pupilometry are provided. In some embodiments, a smartphone may be used to create a visible light video recording of a pupillary light reflex (PLR). A machine learning model may be used to detect a size of a pupil in the video recording over time, and the size over time may be presented to a clinician. In some embodiments, a system that includes a smartphone and a box that holds the smartphone in a predetermined relationship to a subject's face is provided. In some embodiments, a sequential convolutional neural network architecture is used. In some embodiments, a fully convolutional neural network architecture is used.
    Type: Application
    Filed: March 20, 2023
    Publication date: July 20, 2023
    Applicant: University of Washington
    Inventors: Lynn B. McGrath, Anthony Law, Randall Bly, Shwetak N. Patel, Alex T. Mariakakis, Jacob Baudin
  • Smartphone-based digital pupillometer
    Patent number: 11647903
    Abstract: In some embodiments, techniques for using machine learning to enable visible light pupilometry are provided. In some embodiments, a smartphone may be used to create a visible light video recording of a pupillary light reflex (PLR). A machine learning model may be used to detect a size of a pupil in the video recording over time, and the size over time may be presented to a clinician. In some embodiments, a system that includes a smartphone and a box that holds the smartphone in a predetermined relationship to a subject's face is provided. In some embodiments, a sequential convolutional neural network architecture is used. In some embodiments, a fully convolutional neural network architecture is used.
    Type: Grant
    Filed: May 31, 2018
    Date of Patent: May 16, 2023
    Assignee: University of Washington
    Inventors: Lynn B. McGrath, Anthony Law, Randall Bly, Shwetak N. Patel, Alex T. Mariakakis, Jacob Baudin
  • Smartphone-based digital pupillometer
    Patent number: 11627875
    Abstract: In some embodiments, techniques for using machine learning to enable visible light pupilometry are provided. In some embodiments, a smartphone may be used to create a visible light video recording of a pupillary light reflex (PLR). A machine learning model may be used to detect a size of a pupil in the video recording over time, and the size over time may be presented to a clinician. In some embodiments, a system that includes a smartphone and a box that holds the smartphone in a predetermined relationship to a subject's face is provided. In some embodiments, a sequential convolutional neural network architecture is used. In some embodiments, a fully convolutional neural network architecture is used.
    Type: Grant
    Filed: May 31, 2018
    Date of Patent: April 18, 2023
    Assignee: University of Washington
    Inventors: Lynn B. McGrath, Anthony Law, Randall Bly, Shwetak N. Patel, Alex T. Mariakakis, Jacob Baudin
  • SMARTPHONE-BASED DIGITAL PUPILLOMETER
    Publication number: 20200129063
    Abstract: In some embodiments, techniques for using machine learning to enable visible light pupilometry are provided. In some embodiments, a smartphone may be used to create a visible light video recording of a pupillary light reflex (PLR). A machine learning model may be used to detect a size of a pupil in the video recording over time, and the size over time may be presented to a clinician. In some embodiments, a system that includes a smartphone and a box that holds the smartphone in a predetermined relationship to a subject's face is provided. In some embodiments, a sequential convolutional neural network architecture is used. In some embodiments, a fully convolutional neural network architecture is used.
    Type: Application
    Filed: May 31, 2018
    Publication date: April 30, 2020
    Applicant: University of Washington
    Inventors: Lynn B. McGrath, Anthony Law, Randall Bly, Shwetak N. Patel, Alex T. Mariakakis, Jacob Baudin