Patents by Inventor B. Westbrook Bernier

B. Westbrook Bernier 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).

  • Patent number: 10729337
    Abstract: The present application relates to systems and methods for non-invasively determining at least one of left ventricular end diastolic pressure (LVEDP) or pulmonary capillary wedge pressure (PCWP) in a subject's heart, comprising: receiving, by a computer, a plurality of signals from a plurality of non-invasive sensors that measure a plurality of physiological effects that are correlated with functioning of said subject's heart, said plurality of physiological effects including at least one signal correlated with left ventricular blood pressure and at least one signal correlated with timing of heartbeat cycles of said subject's heart; training a machine learning model on said computer using said plurality of signals for periods of time in which said plurality of signals were being generated during a heart failure event of said subject's heart; determining said LVEDP or PCWP using said machine learning model at a time subsequent to said training and subsequent to said heart failure event.
    Type: Grant
    Filed: May 5, 2016
    Date of Patent: August 4, 2020
    Assignees: The Johns Hopkins University, Boston Scientific Scimed Inc.
    Inventors: Qian Liu, Nichaluk Leartprapun, Jackline Wanjala, Soumyadipta Acharya, Andrew Bicek, Viachaslau Barodka, Umang Anand, Majd Alghatrif, David Kass, B. Westbrook Bernier, Chao-Wei Hwang, Peter Johnston, Trent Langston
  • Publication number: 20180160917
    Abstract: The present application relates to systems and methods for non-invasively determining at least one of left ventricular end diastolic pressure (LVEDP) or pulmonary capillary wedge pressure (PCWP) in a subject's heart, comprising: receiving, by a computer, a plurality of signals from a plurality of non-invasive sensors that measure a plurality of physiological effects that are correlated with functioning of said subject's heart, said plurality of physiological effects including at least one signal correlated with left ventricular blood pressure and at least one signal correlated with timing of heartbeat cycles of said subject's heart; training a machine learning model on said computer using said plurality of signals for periods of time in which said plurality of signals were being generated during a heart failure event of said subject's heart; determining said LVEDP or PCWP using said machine learning model at a time subsequent to said training and subsequent to said heart failure event.
    Type: Application
    Filed: May 5, 2016
    Publication date: June 14, 2018
    Applicants: The Johns Hopkins University, Boston Scientific Scimed Inc.
    Inventors: Qian Liu, Nichaluk Leartprapun, Jackline Wanjala, Soumyadipta Acharya, Andrew Bicek, Viachaslau Barodka, Umang Anand, Majd Alghatrif, David Kass, B. Westbrook Bernier, Chao-Wei Hwang, Peter Johnston, Trent Langston