Patents by Inventor Matthew Howe-Patterson

Matthew Howe-Patterson 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: 10765350
    Abstract: A light-based method and technique for measuring the static and average plasma glucose concentration over a prolonged period of time. More specifically, the disclosure relates to a method that utilizes mathematical analysis of appendage mobile LED flash IR light transmittance, absorption and scattering by using high resolution mobile camera data to estimate the concentration of glucose and glycated hemoglobin (HbA1c) in millimoles per liter (mmol/L).
    Type: Grant
    Filed: March 16, 2017
    Date of Patent: September 8, 2020
    Assignee: ANALYTICS FOR LIFE INC.
    Inventors: Sunny Gupta, Timothy Burton, Matthew Howe-Patterson
  • Publication number: 20200046286
    Abstract: Systems to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another system, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.
    Type: Application
    Filed: October 14, 2019
    Publication date: February 13, 2020
    Inventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta
  • Patent number: 10441216
    Abstract: Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.
    Type: Grant
    Filed: March 20, 2018
    Date of Patent: October 15, 2019
    Assignee: ANALYTICS FOR LIFE INC.
    Inventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta
  • Publication number: 20180206787
    Abstract: Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.
    Type: Application
    Filed: March 20, 2018
    Publication date: July 26, 2018
    Inventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta
  • Patent number: 9968265
    Abstract: Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.
    Type: Grant
    Filed: February 12, 2015
    Date of Patent: May 15, 2018
    Assignee: ANALYTICS FOR LIFE
    Inventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta
  • Publication number: 20170181670
    Abstract: A light-based method and technique for measuring the static and average plasma glucose concentration over a prolonged period of time. More specifically, the disclosure relates to a method that utilizes mathematical analysis of appendage mobile LED flash IR light transmittance, absorption and scattering by using high resolution mobile camera data to estimate the concentration of glucose and glycated hemoglobin (HbA1c) in millimoles per liter (mmol/L).
    Type: Application
    Filed: March 16, 2017
    Publication date: June 29, 2017
    Inventors: Sunny Gupta, Timothy Burton, Matthew Howe-Patterson
  • Publication number: 20170095164
    Abstract: Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.
    Type: Application
    Filed: February 12, 2015
    Publication date: April 6, 2017
    Inventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta
  • Patent number: 9597021
    Abstract: A light based method and technique for measuring the static and average plasma glucose concentration over a prolonged period of time. More specifically, the disclosure relates to a method that utilizes mathematical analysis of appendage mobile LED flash IR light transmittance, absorption and scattering by using high resolution mobile camera data to estimate the concentration of glucose and glycated hemoglobin (HbA1c) in millimoles per liter (mmol/L).
    Type: Grant
    Filed: January 14, 2015
    Date of Patent: March 21, 2017
    Assignee: ANALYTICS FOR LIFE
    Inventors: Sunny Gupta, Timothy Burton, Matthew Howe-Patterson
  • Publication number: 20150216426
    Abstract: Methods to identify and risk stratify disease states, cardiac structural defects, functional cardiac deficiencies induced by teratogens and other toxic agents, pathological substrates, conduction delays and defects, and ejection fraction using single channel biological data obtained from the subject. A modified Matching Pursuit (MP) algorithm may be used to find a noiseless model of the data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to characterize the cardiac system. In another method, space-time domain is divided into a number of regions (which is largely determined by the signal length), the density of the signal is computed in each region and input to a learning algorithm to associate them to the desired cardiac dysfunction indicator target.
    Type: Application
    Filed: February 12, 2015
    Publication date: August 6, 2015
    Inventors: Timothy Burton, Shyamlal Ramchandani, Matthew Howe-Patterson, Mohsen Yazdi, Sunny Gupta