Patents by Inventor Gary A. Morris

Gary A. Morris 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: 20220263829
    Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In embodiments, a method of using a diabetes management partner interface to configure an analyte sensor system for wireless communication with a plurality of partner devices is provided. The method includes the analyte sensor system receiving authorization to provide one of the partner devices with access to a set of configuration parameters via the diabetes management partner interface. The set of configuration parameters is stored in a memory of the analyte sensor system. The method also includes, responsive to input received from the one partner device via the diabetes management partner interface, the analyte sensor system setting or causing a modification to the set of configuration parameters, according to a system requirement of the one partner device.
    Type: Application
    Filed: May 2, 2022
    Publication date: August 18, 2022
    Inventors: Apurv Ullas KAMATH, Michael Robert MENSINGER, Nicholas POLYTARIDIS, Gary A. MORRIS, Alexandra Elena CONSTANTIN, Douglas William BURNETTE, Mario REMON, Jorge R. BARRERAS, Benjamin Elrod WEST, Christopher Robert HANNEMANN
  • Patent number: 11363025
    Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In embodiments, a method of using a diabetes management partner interface to configure an analyte sensor system for wireless communication with a plurality of partner devices is provided. The method includes the analyte sensor system receiving authorization to provide one of the partner devices with access to a set of configuration parameters via the diabetes management partner interface. The set of configuration parameters is stored in a memory of the analyte sensor system. The method also includes, responsive to input received from the one partner device via the diabetes management partner interface, the analyte sensor system setting or causing a modification to the set of configuration parameters, according to a system requirement of the one partner device.
    Type: Grant
    Filed: October 24, 2018
    Date of Patent: June 14, 2022
    Assignee: Dexcom, Inc.
    Inventors: Apurv Ullas Kamath, Michael Robert Mensinger, Nicholas Polytaridis, Gary A. Morris, Alexandra E. Constantin, Douglas William Burnette, Mario Remon, Jorge R. Barreras, Benjamin Elrod West, Christopher R. Hannemann
  • Patent number: 11222724
    Abstract: Disclosed are systems and methods for secure and seamless set up and modification of bolus calculator parameters for a bolus calculator tool by a health care provider (HCP). In one aspect, a method for enabling HCP set up of a bolus calculator includes providing a server accessible by both an HCP and a patient; upon login by the HCP, displaying, or transmitting for display, a fillable form, the fillable form including one or more fields for entry of one or more bolus calculator parameters; receiving data from the fillable form, the data corresponding to one or more bolus calculator parameters; and upon login by the patient, transmitting data to a device associated with the patient, the transmitted data based on the received data, where the transmitted data corresponds to one or more of the bolus calculator parameters in a format suitable for entry to a bolus calculator.
    Type: Grant
    Filed: September 8, 2017
    Date of Patent: January 11, 2022
    Assignee: DexCom, Inc.
    Inventors: Anna Leigh Davis, Scott M. Belliveau, Esteban Cabrera, Jr., Alexandra Elena Constantin, Rian Draeger, Peter Galuardi, Hari Hampapuram, Matthew Lawrence Johnson, Apurv Ullas Kamath, Katherine Yerre Koehler, Aarthi Mahalingam, Gary A. Morris, Philip Thomas Pupa, Peter C. Simpson, Brian Christopher Smith, Tomas C. Walker
  • Publication number: 20220000432
    Abstract: Disclosed are systems and methods for generating graphical displays of analyte data and/or health information. In some implementations, the graphical displays are generating based on a self-referential dataset that are modifiable based on identified portions of the data. The modified graphical displays can indicate features in the analyte data of a host.
    Type: Application
    Filed: September 21, 2021
    Publication date: January 6, 2022
    Inventors: Esteban Cabrera, JR., Lauren Danielle Armenta, Scott M. Belliveau, Jennifer Blackwell, Leif N. Bowman, Rian Draeger, Arturo Garcia, Timothy Joseph Goldsmith, John Michael Gray, Andrea Jean Jackson, Apurv Ullas Kamath, Katherine Yerre Koehler, Paul Kramer, Aditya Sagar Mandapaka, Michael Robert Mensinger, Sumitaka Mikami, Gary A. Morris, Hemant Mahendra Nirmal, Paul Noble-Campbell, Philip Thomas Pupa, Eli Reihman, Peter C. Simpson, Brian Christopher Smith, Atiim Joseph Wiley
  • Patent number: 11183298
    Abstract: Disclosed are systems and methods for secure and seamless set up and modification of bolus calculator parameters for a bolus calculator tool by a health care provider (HCP). In one aspect, a method for enabling HCP set up of a bolus calculator includes providing a server accessible by both an HCP and a patient; upon login by the HCP, displaying, or transmitting for display, a fillable form, the fillable form including one or more fields for entry of one or more bolus calculator parameters; receiving data from the fillable form, the data corresponding to one or more bolus calculator parameters; and upon login by the patient, transmitting data to a device associated with the patient, the transmitted data based on the received data, where the transmitted data corresponds to one or more of the bolus calculator parameters in a format suitable for entry to a bolus calculator.
    Type: Grant
    Filed: April 17, 2019
    Date of Patent: November 23, 2021
    Assignee: DexCom, Inc.
    Inventors: Anna Leigh Davis, Scott M. Belliveau, Esteban Cabrera, Jr., Alexandra Elena Constantin, Rian Draeger, Peter Galuardi, Hari Hampapuram, Matthew Lawrence Johnson, Apurv Ullas Kamath, Katherine Yerre Koehler, Aarthi Mahalingam, Gary A. Morris, Philip Thomas Pupa, Peter C. Simpson, Brian Christopher Smith, Tomas C. Walker
  • Patent number: 11154253
    Abstract: Disclosed are systems and methods for generating graphical displays of analyte data and/or health information. In some implementations, the graphical displays are generating based on a self-referential dataset that are modifiable based on identified portions of the data. The modified graphical displays can indicate features in the analyte data of a host.
    Type: Grant
    Filed: August 10, 2017
    Date of Patent: October 26, 2021
    Assignee: DexCom, Inc.
    Inventors: Esteban Cabrera, Jr., Lauren Danielle Armenta, Scott M. Belliveau, Jennifer Blackwell, Leif N. Bowman, Rian Draeger, Arturo Garcia, Timothy Joseph Goldsmith, John Michael Gray, Andrea Jean Jackson, Apurv Ullas Kamath, Katherine Yerre Koehler, Paul Kramer, Aditya Sagar Mandapaka, Michael Robert Mensinger, Sumitaka Mikami, Gary A. Morris, Hemant Mahendra Nirmal, Paul Noble-Campbell, Philip Thomas Pupa, Eli Reihman, Peter C. Simpson, Brian Christopher Smith, Atiim Joseph Wiley
  • Patent number: 11150217
    Abstract: A method of directly measuring SO2 and other trace gases by configuring an electrochemical cell (ECC) sonde; and an ECC sonde pump inlet filter to remove ozone and other trace gases. Further, calibration and operation procedures for the SO2 and other trace gas ECC sondes are disclosed.
    Type: Grant
    Filed: March 13, 2018
    Date of Patent: October 19, 2021
    Assignee: UNIVERSITY OF HOUSTON SYSTEM
    Inventors: James Flynn, Gary A. Morris
  • Patent number: 11153317
    Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In embodiments, a method of using a diabetes management partner interface to configure an analyte sensor system for wireless communication with a plurality of partner devices is provided. The method includes the analyte sensor system receiving authorization to provide one of the partner devices with access to a set of configuration parameters via the diabetes management partner interface. The set of configuration parameters is stored in a memory of the analyte sensor system. The method also includes, responsive to input received from the one partner device via the diabetes management partner interface, the analyte sensor system setting or causing a modification to the set of configuration parameters, according to a system requirement of the one partner device.
    Type: Grant
    Filed: October 24, 2018
    Date of Patent: October 19, 2021
    Assignee: DexCom, Inc.
    Inventors: Apurv Ullas Kamath, Michael Robert Mensinger, Nicholas Polytaridis, Gary A. Morris, Alexandra E. Constantin, Douglas William Burnette, Mario Remon, Jorge R. Barreras, Benjamin Elrod West, Christopher R. Hannemann
  • Publication number: 20210316070
    Abstract: Methods, devices and systems are disclosed for inter-app communications between software applications on a mobile communications device. In one aspect, a computer-readable medium on a mobile computing device comprising an inter-application communication data structure to facilitate transitioning and distributing data between software applications in a shared app group for an operating system of the mobile computing device includes a scheme field of the data structure providing a scheme id associated with a target software app to transition to from a source software app, wherein the scheme id is listed on a scheme list stored with the source software app; and a payload field of the data structure providing data and/or an identification where to access data in a shared file system accessible to the software applications in the shared app group, wherein the payload field is encrypted.
    Type: Application
    Filed: March 16, 2021
    Publication date: October 14, 2021
    Inventors: Gary A. Morris, Scott M. Belliveau, Esteban Cabrera, JR., Rian Draeger, Laura J. Dunn, Timothy Joseph Goldsmith, Hari Hampapuram, Christopher Robert Hannemann, Apurv Ullas Kamath, Katherine Yerre Koehler, Patrick Wile McBride, Michael Robert Mensinger, Francis William Pascual, Philip Mansiel Pellouchoud, Nicholas Polytaridis, Philip Thomas Pupa, Anna Leigh Davis, Kevin Shoemaker, Brian Christopher Smith, Benjamin Elrod West, Atiim Joseph Wiley
  • Patent number: 11141116
    Abstract: Disclosed are systems and methods for generating graphical displays of analyte data and/or health information. In some implementations, the graphical displays are generating based on a self-referential dataset that are modifiable based on identified portions of the data. The modified graphical displays can indicate features in the analyte data of a host.
    Type: Grant
    Filed: August 10, 2017
    Date of Patent: October 12, 2021
    Assignee: DexCom, Inc.
    Inventors: Esteban Cabrera, Jr., Lauren Danielle Armenta, Scott M. Belliveau, Jennifer Blackwell, Leif N. Bowman, Rian Draeger, Arturo Garcia, Timothy Joseph Goldsmith, John Michael Gray, Andrea Jean Jackson, Apurv Ullas Kamath, Katherine Yerre Koehler, Paul Kramer, Aditya Sagar Mandapaka, Michael Robert Mensinger, Sumitaka Mikami, Gary A. Morris, Hemant Mahendra Nirmal, Paul Noble-Campbell, Philip Thomas Pupa, Eli Reihman, Peter C. Simpson, Brian Christopher Smith, Atiim Joseph Wiley
  • Publication number: 20210260288
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210260289
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210259591
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210260286
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210260287
    Abstract: Machine learning in an artificial pancreas is described. An artificial pancreas system may include a wearable glucose monitoring device, an insulin delivery system, and a computing device. Broadly speaking, the wearable glucose monitoring device provides glucose measurements of a person continuously. The artificial pancreas algorithm, which may be implemented at the computing device, determines doses of insulin to deliver to the person based on a variety of aspects for the purpose of maintaining the person's glucose within a target range, as indicated by those glucose measurements. The insulin delivery system then delivers those determined doses to the person. As the artificial pancreas algorithm determines insulin doses for the person over time and effectiveness of the insulin doses to maintain the person's glucose level in the target range is observed, an underlying model of the artificial pancreas algorithm may be updated to better determine insulin doses.
    Type: Application
    Filed: December 7, 2020
    Publication date: August 26, 2021
    Inventors: Apurv Ullas Kamath, Derek James Escobar, Sumitaka Mikami, Hari Hampapuram, Benjamin Elrod West, Nathanael Paul, Naresh C. Bhavaraju, Michael Robert Mensinger, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Scott M. Belliveau, Katherine Yerre Koehler, Nicholas Polytaridis, Rian Draeger, Jorge Valdes, David Price, Peter C. Simpson, Edward Sweeney
  • Publication number: 20210251484
    Abstract: The present disclosure relates to systems, devices and methods for receiving biosensor data acquired by a medical device, e.g., relating to glucose concentration values, and controlling the access and distribution of that data. In some embodiments, systems and methods are disclosed for monitoring glucose levels, displaying data relating to glucose values and metabolic health information, and controlling distribution of glucose data between applications executing on a computer, such as a smart phone. In some embodiments, systems and methods are disclosed for controlling access to medical data such as continuously monitored glucose levels, synchronizing health data relating to glucose levels between multiple applications executing on a computer, and/or encrypting data.
    Type: Application
    Filed: March 12, 2021
    Publication date: August 19, 2021
    Inventors: Michael Robert Mensinger, Esteban Cabrera, Jr., Eric Cohen, Nathaniel David Heintzman, Apurv Ullas Kamath, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Jorge Valdes
  • Publication number: 20210171070
    Abstract: The present invention relates broadly to a railway track trolley (10) generally comprising a collapsible chassis (12), two pairs of wheels (14a/b) and (16a/b), and a platform assembly (18). The collapsible chassis (12) includes a pair of opposing beams member (20a) and (20b) interconnected by a pair of adjustable cross-members (22) and (24). The pair of wheels (14a) and (16a) are removably mounted to opposing ends of one of the beam members (20a) whereas the other pair of wheels (14b) and (16b) are removably mounted to opposing ends of the other of the beam members (20b). The railway tracks (26a) and (26b) may be separated at one of a plurality of predetermined track gauges and the collapsible chassis in an expanded condition is designed to match the required lateral separation of the opposing rail members (26a/b).
    Type: Application
    Filed: August 30, 2018
    Publication date: June 10, 2021
    Inventors: Andrew Melvelle, Ben de Rooy, Gary Morris, Jason Casboult
  • Patent number: 10980941
    Abstract: A computer-readable medium on a mobile computing device comprises an inter-application communication data structure to facilitate transitioning and distributing data between software applications in a shared app group for an operating system of the mobile computing device includes a scheme field of the data structure providing a scheme id associated with a target software app to transition to from a source software app, wherein the scheme id is listed on a scheme list stored with the source software app; and a payload field of the data structure providing data and/or an identification where to access data in a shared file system accessible to the software applications in the shared app group, wherein the payload field is encrypted.
    Type: Grant
    Filed: March 30, 2017
    Date of Patent: April 20, 2021
    Assignee: DexCom, Inc.
    Inventors: Gary A. Morris, Scott M. Belliveau, Esteban Cabrera, Jr., Rian Draeger, Laura J. Dunn, Timothy Joseph Goldsmith, Hari Hampapuram, Christopher Robert Hannemann, Apurv Ullas Kamath, Katherine Yerre Koehler, Patrick Wile McBride, Michael Robert Mensinger, Francis William Pascual, Philip Mansiel Pellouchoud, Nicholas Polytaridis, Philip Thomas Pupa, Anna Leigh Davis, Kevin Shoemaker, Brian Christopher Smith, Benjamin Elrod West, Atiim Joseph Wiley
  • Patent number: 10979431
    Abstract: Systems, devices, and methods are disclosed for wireless communication of analyte data. In embodiments, a method of using a diabetes management partner interface to configure an analyte sensor system for wireless communication with a plurality of partner devices is provided. The method includes the analyte sensor system receiving authorization to provide one of the partner devices with access to a set of configuration parameters via the diabetes management partner interface. The set of configuration parameters is stored in a memory of the analyte sensor system. The method also includes, responsive to input received from the one partner device via the diabetes management partner interface, the analyte sensor system setting or causing a modification to the set of configuration parameters, according to a system requirement of the one partner device.
    Type: Grant
    Filed: October 24, 2018
    Date of Patent: April 13, 2021
    Assignee: DexCom, Inc.
    Inventors: Apurv Ullas Kamath, Michael Robert Mensinger, Nicholas Polytaridis, Gary A. Morris, Alexandra Elena Constatin, Douglas William Burnette, Mario Remon, Jorge R. Barreras, Benjamin Elrod West, Christopher Robert Hannemann
  • Patent number: 10945600
    Abstract: The present disclosure relates to systems, devices and methods for receiving biosensor data acquired by a medical device, e.g., relating to glucose concentration values, and controlling the access and distribution of that data. In some embodiments, systems and methods are disclosed for monitoring glucose levels, displaying data relating to glucose values and metabolic health information, and controlling distribution of glucose data between applications executing on a computer, such as a smart phone. In some embodiments, systems and methods are disclosed for controlling access to medical data such as continuously monitored glucose levels, synchronizing health data relating to glucose levels between multiple applications executing on a computer, and/or encrypting data.
    Type: Grant
    Filed: February 9, 2016
    Date of Patent: March 16, 2021
    Assignee: DexCom, Inc.
    Inventors: Michael Robert Mensinger, Esteban Cabrera, Jr., Eric Cohen, Nathaniel David Heintzman, Apurv Ullas Kamath, Gary A. Morris, Andrew Attila Pal, Eli Reihman, Jorge Valdes