Patents by Inventor Margaret Gan Guo

Margaret Gan Guo 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).

  • Systems and methods for predicting adverse events and assessing level of sedation during medical procedures
    Patent number: 11972843
    Abstract: Systems and methods are disclosed herein for quantitatively identifying a patient's sedation level and predicting adverse events, based on one or more capnograms or outputs from a pharmacokinetic, pharmacodynamic, or ventilatory model. A sensor measures a carbon dioxide concentration of air exhaled by a patient into a breath receiver. A processor processes the sensor data to generate a capnogram including one or more respiratory cycles, computes the outputs of pharmacokinetic, pharmacodynamic, or ventilatory models, and extracts one or more of the resulting features from the capnogram and pharmacokinetic, pharmacodynamic, or ventilatory model outputs. A multi-parameter metric is computed based on the one or more extracted features and estimates the current or predicted sedation level of the patient.
    Type: Grant
    Filed: June 26, 2019
    Date of Patent: April 30, 2024
    Assignees: Massachusetts Institute of Technology, Children's Medical Center Corporation
    Inventors: George Cheeran Verghese, Margaret Gan Guo, Rebecca Mieloszyk, Thomas Heldt, Baruch Shlomo Krauss
  • SYSTEMS AND METHODS FOR PREDICTING ADVERSE EVENTS AND ASSESSING LEVEL OF SEDATION DURING MEDICAL PROCEDURES
    Publication number: 20190378595
    Abstract: Systems and methods are disclosed herein for quantitatively identifying a patient's sedation level and predicting adverse events, based on one or more capnograms or outputs from a pharmacokinetic, pharmacodynamic, or ventilatory model. A sensor measures a carbon dioxide concentration of air exhaled by a patient into a breath receiver. A processor processes the sensor data to generate a capnogram including one or more respiratory cycles, computes the outputs of pharmacokinetic, pharmacodynamic, or ventilatory models, and extracts one or more of the resulting features from the capnogram and pharmacokinetic, pharmacodynamic, or ventilatory model outputs. A multi-parameter metric is computed based on the one or more extracted features and estimates the current or predicted sedation level of the patient.
    Type: Application
    Filed: June 26, 2019
    Publication date: December 12, 2019
    Applicants: Massachusetts Institute of Technology, Children's Medical Center Corporation
    Inventors: George Cheeran Verghese, Margaret Gan Guo, Rebecca Mieloszyk, Thomas Heldt, Baruch Shlomo Krauss
  • Systems and methods for predicting adverse events and assessing level of sedation during medical procedures
    Patent number: 10388405
    Abstract: Systems and methods are disclosed herein for quantitatively identifying a patient's sedation level and predicting adverse events, based on one or more capnograms or outputs from a pharmacokinetic, pharmacodynamic, or ventilatory model. A sensor measures a carbon dioxide concentration of air exhaled by a patient into a breath receiver. A processor processes the sensor data to generate a capnogram including one or more respiratory cycles, computes the outputs of pharmacokinetic, pharmacodynamic, or ventilatory models, and extracts one or more of the resulting features from the capnogram and pharmacokinetic, pharmacodynamic, or ventilatory model outputs. A multi-parameter metric is computed based on the one or more extracted features and estimates the current or predicted sedation level of the patient.
    Type: Grant
    Filed: August 12, 2016
    Date of Patent: August 20, 2019
    Assignees: Massachusetts Institute of Technology, Children's Medical Center Corporation
    Inventors: George Cheeran Verghese, Margaret Gan Guo, Rebecca Mieloszyk, Thomas Heldt, Baruch Shlomo Krauss
  • SYSTEMS AND METHODS FOR PREDICTING ADVERSE EVENTS AND ASSESSING LEVEL OF SEDATION DURING MEDICAL PROCEDURES
    Publication number: 20170042475
    Abstract: Systems and methods are disclosed herein for quantitatively identifying a patient's sedation level and predicting adverse events, based on one or more capnograms or outputs from a pharmacokinetic, pharmacodynamic, or ventilatory model. A sensor measures a carbon dioxide concentration of air exhaled by a patient into a breath receiver. A processor processes the sensor data to generate a capnogram including one or more respiratory cycles, computes the outputs of pharmacokinetic, pharmacodynamic, or ventilatory models, and extracts one or more of the resulting features from the capnogram and pharmacokinetic, pharmacodynamic, or ventilatory model outputs. A multi-parameter metric is computed based on the one or more extracted features and estimates the current or predicted sedation level of the patient.
    Type: Application
    Filed: August 12, 2016
    Publication date: February 16, 2017
    Inventors: George Cheeran Verghese, Margaret Gan Guo, Rebecca Mieloszyk, Thomas Heldt, Baruch Shlomo Krauss