Patents by Inventor Benjamin Elrod West

Benjamin Elrod West 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: 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
  • 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: 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: 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: 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: 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: 20210142912
    Abstract: Systems and methods disclosed provide ways for Health Care Professionals (HCPs) to be involved in initial patient system set up so that the data received is truly transformative, such that the patient not just understands what all the various numbers mean but also how the data can be used. For example, in one implementation, a CGM device is configured for use by a HCP, and includes a housing and a circuit configured to receive a signal from a transmitter coupled to an indwelling glucose sensor. A calibration module converts the received signal into clinical units. A user interface is provided that is configured to display a measured glucose concentration in the clinical units. The user interface is further configured to receive input data about a patient level, where the input data about the patient level causes the device to operate in a mode appropriate to the patient level.
    Type: Application
    Filed: January 7, 2021
    Publication date: May 13, 2021
    Inventors: Scott M. Belliveau, Naresh C. Bhavaraju, Darin Edward Chum Dew, Eric Cohen, Anna Leigh Davis, Mark Dervaes, Laura J. Dunn, Minda McDorman Grucela, Hari Hampapuram, Matthew Lawrence Johnson, Apurv Ullas Kamath, Steven David King, Katherine Yerre Koehler, Aditya Sagar Mandapaka, Zebediah L. McDaniel, Sumitaka Mikami, Subrai Girish Pai, Philip Mansiel Pellouchoud, Stephen Alan Reichert, Eli Reihman, Peter C. Simpson, Brian Christopher Smith, Stephen J. Vanslyke, Robert Patrick Van Tassel, Matthew D. Wightlin, Richard C. Yang, James Stephen Amidei, David Derenzy, Benjamin Elrod West, Vincent Crabtree, Michael Levozier Moore, Douglas William Burnette, Alexandra Elena Constantin, Nicholas Polytaridis, Dana Charles Cambra, Abhishek Sharma, Kho Braun, Patrick Wile McBride
  • 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
  • Publication number: 20200375457
    Abstract: Systems, methods, apparatuses, and devices, for the wireless communication of analyte data are provided. In some embodiments, a method and calibration station for calibrating a continuous analyte sensor system is provided. Methods and testing systems for testing a continuous analyte sensor system is provided. Continuous analyte sensor systems, display devices and peripheral devices configured for wireless communication of analyte, connection, alarm and/or alert data and associated methods are provided.
    Type: Application
    Filed: May 22, 2020
    Publication date: December 3, 2020
    Inventors: Robert Patrick Van Tassel, John Francis Loughlin, Sean S. Nihalani, James Stephen Amidei, Stephen Alan Reichert, Sebastian Bohm, Krishna Prashant Daita, Brian Christopher Smith, Michael A. Ploof, Benjamin Elrod West, Mark S. Dervaes, Vincent P. Crabtree, William A. Pender, Douglas William Burnette
  • Publication number: 20200375455
    Abstract: Systems, methods, apparatuses, and devices, for the wireless communication of analyte data are provided. In some embodiments, a method and calibration station for calibrating a continuous analyte sensor system is provided. Methods and testing systems for testing a continuous analyte sensor system is provided. Continuous analyte sensor systems, display devices and peripheral devices configured for wireless communication of analyte, connection, alarm and/or alert data and associated methods are provided.
    Type: Application
    Filed: May 22, 2020
    Publication date: December 3, 2020
    Inventors: Robert Patrick Van Tassel, John Francis Loughlin, Sean S. Nihalani, James Stephen Amidei, Stephen Alan Reichert, Sebastian Bohm, Krishna Prashant Daita, Brian Christopher Smith, Michael A. Ploof, Benjamin Elrod West, Mark S. Dervaes, Vincent P. Crabtree, William A. Pender, Douglas William Burnette
  • Publication number: 20200316296
    Abstract: Systems and methods are disclosed that provide smart alerts to users, e.g., alerts to users about diabetic states that are only provided when it makes sense to do so, e.g., when the system can predict or estimate that the user is not already cognitively aware of their current condition, e.g., particularly where the current condition is a diabetic state warranting attention. In this way, the alert or alarm is personalized and made particularly effective for that user. Such systems and methods still alert the user when action is necessary, e.g., a bolus or temporary basal rate change, or provide a response to a missed bolus or a need for correction, but do not alert when action is unnecessary, e.g., if the user is already estimated or predicted to be cognitively aware of the diabetic state warranting attention, or if corrective action was already taken.
    Type: Application
    Filed: June 17, 2020
    Publication date: October 8, 2020
    Inventors: Anna Leigh Davis, Scott M. Belliveau, Naresh C. Bhavaraju, Leif N. Bowman, Rita M. Castillo, Alexandra Elena Constantin, Rian Draeger, Laura J. Dunn, Gary Brian Gable, Arturo Garcia, Thomas Hall, Hari Hampapuram, Christopher Robert Hannemann, Anna Claire Harley-Trochimczyk, Nathaniel David Heintzman, Andrea Jean Jackson, Lauren Hruby Jepson, Apurv Ullas Kamath, Katherine Yerre Koehler, Aditya Sagar Mandapaka, Samuel Jere Marsh, Gary A. Morris, Subrai Girish Pai, Andrew Attila Pal, Nicholas Polytaridis, Philip Thomas Pupa, Eli Reihman, Ashley Anne Rindfleisch, Sofie Wells Schunk, Peter C. Simpson, Daniel Smith, Stephen J. Vanslyke, Matthew T. Vogel, Tomas C. Walker, Benjamin Elrod West, Atiim Joseph Wiley
  • Patent number: 10737025
    Abstract: Systems and methods are disclosed that provide smart alerts to users, e.g., alerts to users about diabetic states that are only provided when it makes sense to do so, e.g., when the system can predict or estimate that the user is not already cognitively aware of their current condition, e.g., particularly where the current condition is a diabetic state warranting attention. In this way, the alert or alarm is personalized and made particularly effective for that user. Such systems and methods still alert the user when action is necessary, e.g., a bolus or temporary basal rate change, or provide a response to a missed bolus or a need for correction, but do not alert when action is unnecessary, e.g., if the user is already estimated or predicted to be cognitively aware of the diabetic state warranting attention, or if corrective action was already taken.
    Type: Grant
    Filed: August 23, 2017
    Date of Patent: August 11, 2020
    Assignee: DexCom, Inc.
    Inventors: Anna Leigh Davis, Scott M. Belliveau, Naresh C. Bhavaraju, Leif N. Bowman, Rita M. Castillo, Alexandra Elena Constantin, Rian Draeger, Laura J. Dunn, Gary Brian Gable, Arturo Garcia, Thomas Hall, Hari Hampapuram, Christopher Robert Hannemann, Anna Claire Harley-Trochimczyk, Nathaniel David Heintzman, Andrea J. Jackson, Lauren Hruby Jepson, Apurv Ullas Kamath, Katherine Yerre Koehler, Aditya Sagar Mandapaka, Samuel Jere Marsh, Gary A. Morris, Subrai Girish Pai, Andrew Attila Pal, Nicholas Polytaridis, Philip Thomas Pupa, Eli Reihman, Ashley Anne Rindfleisch, Sofie Wells Schunk, Peter C. Simpson, Daniel Smith, Stephen J. Vanslyke, Matthew T. Vogel, Tomas C. Walker, Benjamin Elrod West, Atiim Joseph Wiley
  • Patent number: 10596318
    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: Grant
    Filed: March 30, 2017
    Date of Patent: March 24, 2020
    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: 10406287
    Abstract: Systems and methods are disclosed that provide smart alerts to users, e.g., alerts to users about diabetic states that are only provided when it makes sense to do so, e.g., when the system can predict or estimate that the user is not already cognitively aware of their current condition, e.g., particularly where the current condition is a diabetic state warranting attention. In this way, the alert or alarm is personalized and made particularly effective for that user. Such systems and methods still alert the user when action is necessary, e.g., a bolus or temporary basal rate change, or provide a response to a missed bolus or a need for correction, but do not alert when action is unnecessary, e.g., if the user is already estimated or predicted to be cognitively aware of the diabetic state warranting attention, or if corrective action was already taken.
    Type: Grant
    Filed: July 6, 2018
    Date of Patent: September 10, 2019
    Assignee: DexCom, Inc.
    Inventors: Anna Leigh Davis, Scott M. Belliveau, Naresh C. Bhavaraju, Leif N. Bowman, Rita M. Castillo, Alexandra Elena Constantin, Rian Draeger, Laura J. Dunn, Gary Brian Gable, Arturo Garcia, Thomas Hall, Hari Hampapuram, Christopher Robert Hannemann, Anna Claire Harley-Trochimczyk, Nathaniel David Heintzman, Andrea J. Jackson, Lauren Hruby Jepson, Apurv Ullas Kamath, Katherine Yerre Koehler, Aditya Sagar Mandapaka, Samuel Jere Marsh, Gary A. Morris, Subrai Girish Pai, Andrew Attila Pal, Nicholas Polytaridis, Philip Thomas Pupa, Eli Reihman, Ashley Anne Rindfleisch, Sofie Wells Schunk, Peter C. Simpson, Daniel Smith, Stephen J. Vanslyke, Matthew T. Vogel, Tomas C. Walker, Benjamin Elrod West, Atiim Joseph Wiley
  • Patent number: 10328204
    Abstract: Systems and methods are disclosed that provide smart alerts to users, e.g., alerts to users about diabetic states that are only provided when it makes sense to do so, e.g., when the system can predict or estimate that the user is not already cognitively aware of their current condition, e.g., particularly where the current condition is a diabetic state warranting attention. In this way, the alert or alarm is personalized and made particularly effective for that user. Such systems and methods still alert the user when action is necessary, e.g., a bolus or temporary basal rate change, or provide a response to a missed bolus or a need for correction, but do not alert when action is unnecessary, e.g., if the user is already estimated or predicted to be cognitively aware of the diabetic state warranting attention, or if corrective action was already taken.
    Type: Grant
    Filed: April 28, 2017
    Date of Patent: June 25, 2019
    Assignee: DexCom, Inc.
    Inventors: Anna Leigh Davis, Arturo Garcia, Thomas Hall, Hari Hampapuram, Christopher Robert Hannemann, Anna Claire Harley-Trochimczyk, Nathaniel David Heintzman, Andrea J. Jackson, Lauren Hruby Jepson, Apurv Ullas Kamath, Katherine Yerre Koehler, Scott M. Belliveau, Aditya Sagar Mandapaka, Samuel Jere Marsh, Gary A. Morris, Subrai Girish Pai, Andrew Attila Pal, Nicholas Polytaridis, Philip Thomas Pupa, Eli Reihman, Ashley Anne Rindfleisch, Sofie Wells Schunk, Naresh C. Bhavaraju, Peter C. Simpson, Daniel Smith, Stephen J. Vanslyke, Matthew T. Vogel, Tomas C. Walker, Benjamin Elrod West, Atiim Joseph Wiley, Leif N. Bowman, Rita M. Castillo, Alexandra Elena Constantin, Rian Draeger, Laura J. Dunn, Gary Brian Gable
  • Publication number: 20190173885
    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: October 24, 2018
    Publication date: June 6, 2019
    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: 20190125224
    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: October 24, 2018
    Publication date: May 2, 2019
    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: 20190132801
    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: October 24, 2018
    Publication date: May 2, 2019
    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