Patents by Inventor George Cheeran Verghese

George Cheeran Verghese 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).

  • 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
  • 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
  • Patent number: 10327709
    Abstract: A method to quantitatively predict a patient's serum lactate level, comprising measuring arterial blood pressure and heart rate from the patient, computing estimates of one or more cardiovascular parameters from the measured arterial blood pressure and heart rate, providing one or more classifiers that have been trained on a training data set including a reference set of arterial blood pressure, heart rate, and serum lactate levels and using the one or more classifiers to estimate the serum lactate level of the patient.
    Type: Grant
    Filed: August 12, 2016
    Date of Patent: June 25, 2019
    Assignees: Massachusetts Institute of Technology, The General Hospital Corporation
    Inventors: Thomas Heldt, Max H. Dunitz, George Cheeran Verghese, Andrew Tomas Reisner, Michael Filbin
  • 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
  • Publication number: 20170042483
    Abstract: A method to quantitatively predict a patient's serum lactate level, comprising measuring arterial blood pressure and heart rate from the patient, computing estimates of one or more cardiovascular parameters from the measured arterial blood pressure and heart rate, providing one or more classifiers that have been trained on a training data set including a reference set of arterial blood pressure, heart rate, and serum lactate levels and using the one or more classifiers to estimate the serum lactate level of the patient.
    Type: Application
    Filed: August 12, 2016
    Publication date: February 16, 2017
    Inventors: Thomas Heldt, Max H. Dunitz, George Cheeran Verghese, Andrew Tomas Reisner, Michael Filbin
  • Publication number: 20140357965
    Abstract: The systems, devices, and methods described herein provide for the estimation and monitoring of cerebrovascular system properties and intracranial pressure (ICP) from one or more measurements or measured signals. These measured signals may include central or peripheral arterial blood pressure (ABP), and cerebral blood flow (CBF) or cerebral blood flow velocity (CBFV). The measured signals may be acquired noninvasively or minimally-invasively. The measured signals may be used to estimate parameters and variables of a computational model that is representative of the physiological relationships among the cerebral flows and pressures. The computational model may include at least one resistive element, at least one compliance element, and a representation of ICP.
    Type: Application
    Filed: August 20, 2014
    Publication date: December 4, 2014
    Inventors: Faisal Mahmood Kashif, Thomas Heldt, George Cheeran Verghese
  • Publication number: 20140288440
    Abstract: Systems and methods are disclosed herein for quantitatively identifying a patient's physiological state based on one or more capnograms. One or more capnograms are acquired, each capnogram being associated with a patient and including one or more respiratory cycles, and one or more features from the one or more respiratory cycles are extracted. One or more classifiers are provided based on the one or more extracted features, and each classifier is used to select a physiological state from one or more candidate physiological states for each of the one or more respiratory cycles. For each of the selected physiological states, a likelihood value is determined, and a physiological state of the patient is determined based on the likelihood values.
    Type: Application
    Filed: March 22, 2013
    Publication date: September 25, 2014
    Applicants: CHILDREN'S MEDICAL CENTER CORPORATION, MASSACHUSETTS INSTITUTE OF TECHNOLOGY
    Inventors: Rebecca J. Asher, Thomas Heldt, Baruch Shlomo Krauss, George Cheeran Verghese
  • Patent number: 8821402
    Abstract: The systems, devices, and methods described herein provide for the estimation and monitoring of cerebrovascular system properties and intracranial pressure (ICP) from one or more measurements or measured signals. These measured signals may include central or peripheral arterial blood pressure (ABP), and cerebral blood flow (CBF) or cerebral blood flow velocity (CBFV). The measured signals may be acquired noninvasively or minimally-invasively. The measured signals may be used to estimate parameters and variables of a computational model that is representative of the physiological relationships among the cerebral flows and pressures. The computational model may include at least one resistive element, at least one compliance element, and a representation of ICP.
    Type: Grant
    Filed: January 25, 2013
    Date of Patent: September 2, 2014
    Assignee: Massachusetts Institute of Technology
    Inventors: Faisal Mahmood Kashif, Thomas Heldt, George Cheeran Verghese
  • Patent number: 8366627
    Abstract: The systems, devices, and methods described herein provide for the estimation and monitoring of cerebrovascular system properties and intracranial pressure (ICP) from one or more measurements or measured signals. These measured signals may include central or peripheral arterial blood pressure (ABP), and cerebral blood flow (CBF) or cerebral blood flow velocity (CBFV). The measured signals may be acquired noninvasively or minimally-invasively. The measured signals may be used to estimate parameters and variables of a computational model that is representative of the physiological relationships among the cerebral flows and pressures. The computational model may include at least one resistive element, at least one compliance element, and a representation of ICP.
    Type: Grant
    Filed: September 8, 2009
    Date of Patent: February 5, 2013
    Assignee: Massachusetts Institute of Technology
    Inventors: Faisal Mahmood Kashif, Thomas Heldt, George Cheeran Verghese
  • Publication number: 20100063405
    Abstract: The systems, devices, and methods described herein provide for the estimation and monitoring of cerebrovascular system properties and intracranial pressure (ICP) from one or more measurements or measured signals. These measured signals may include central or peripheral arterial blood pressure (ABP), and cerebral blood flow (CBF) or cerebral blood flow velocity (CBFV). The measured signals may be acquired noninvasively or minimally-invasively. The measured signals may be used to estimate parameters and variables of a computational model that is representative of the physiological relationships among the cerebral flows and pressures. The computational model may include at least one resistive element, at least one compliance element, and a representation of ICP.
    Type: Application
    Filed: September 8, 2009
    Publication date: March 11, 2010
    Applicant: Massachusetts Institute of Technology
    Inventors: Faisal Mahmood Kashif, Thomas Heldt, George Cheeran Verghese