Patents by Inventor Andrew Attila Pal

Andrew Attila Pal 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: 11399721
    Abstract: Systems and methods for remote and host monitoring communication are disclosed. In some implementations, monitoring systems can comprise a host monitoring device associated with a Host communicatively coupled to one or more remote monitoring devices associated with Remote Monitors. The host monitoring device can send communications based at least in part on analyte measurements of a Host sensor and/or other contextual data giving such measurements context. Different remote monitoring devices can receive different communications based at least in part on the role of the respective Remote Monitors relative to the Host. These roles can be reflected in classifications of Remote Monitors.
    Type: Grant
    Filed: December 13, 2016
    Date of Patent: August 2, 2022
    Assignee: Dexcom, Inc.
    Inventors: Aarthi Mahalingam, Esteban Cabrera, Jr., Basab Dattaray, Rian Draeger, Laura J. Dunn, Derek James Escobar, Thomas Hall, Hari Hampapuram, Apurv Ullas Kamath, Katherine Yerre Koehler, Phil Mayou, Michael Robert Mensinger, Michael Levozier Moore, Andrew Attila Pal, Nicholas Polytaridis, Eli Reihman, Brian Christopher Smith
  • Publication number: 20220104773
    Abstract: Adhesive pad systems that provide longer lasting adherence of the mounting unit to the host's skin are provided. Some systems include a reinforcing overlay that at least partially covers the adhesive pad. The reinforcing overlay may be removable without disturbing the sensor so that the overlay may be replaceable.
    Type: Application
    Filed: December 7, 2021
    Publication date: April 7, 2022
    Inventors: James Jinwoo Lee, Leif N. Bowman, Tim Ray Gackstetter, Jonathan Hughes, Jeff Jackson, Ted Tang Lee, Phong Lieu, Andrew Attila Pal, James R. Petisce, Jack Pryor, Roger Schneider, Peter C. Simpson, George Vigil, Matthew D. Wightlin
  • Patent number: 11295855
    Abstract: Disclosed are systems and methods for providing automated or semi-automated technical support for patients using medical devices, such as continuous glucose monitoring systems. Disclosed embodiments of automated tech support system include collection and storage of copies of streams of medical device data on multiple servers, analysis and comparison of data streams, remote tech support initiation and usage of the automated tech support system for providing improved products and services by storing and analyzing historical tech support data.
    Type: Grant
    Filed: November 7, 2017
    Date of Patent: April 5, 2022
    Assignee: Dexcom, Inc.
    Inventors: Andrew Attila Pal, Leif N. Bowman, Eric Cohen, Basab Dattaray, Edward Day, Apurv Ullas Kamath, Aarthi Mahalingam, Dana Minor, Scott A. Moss, Neil Puri, Eli Reihman, Conrad Woods, Laurie L. Berg, Jorge Valdes
  • Publication number: 20220065795
    Abstract: A method for performing a lateral flow assay is provided. The method includes inserting a sample cartridge (201) in a dark chamber (220) and activating a light emitter (251) in the dark chamber (220). The method includes focusing an optical coupling mechanism (115a, 115b) in an image-capturing device (100a, 100b) to optimize an image of a sensitive area (202) in the sample cartridge (201) and capturing, with an image capturing device (100a, 100b), an image of a sensitive area (202) in the sample cartridge (201) after a selected period of time. The method also includes providing the image of the sensitive area (202) to a processor, wherein the processor comprises an image-capturing application (122). A system and a computer-implemented method to perform at least partially the above method are also provided.
    Type: Application
    Filed: January 15, 2019
    Publication date: March 3, 2022
    Inventors: Andrew Attila PAL, Werner KROLL, Adonis STASSINOPOULOS
  • Publication number: 20220068452
    Abstract: Provided are systems and methods using which users may learn and become familiar with the effects of various aspects of their lifestyle on their health, e.g., users may learn about how food and/or exercise affects their glucose level and other physiological parameters, as well as overall health. In some cases the user selects a program to try; in other cases, a computing environment embodying the system suggests programs to try, including on the basis of pattern recognition, i.e., by the computing environment determining how a user could improve a detected pattern in some way. In this way, users such as type II diabetics or even users who are only prediabetic or non-diabetic may learn healthy habits to benefit their health.
    Type: Application
    Filed: November 11, 2021
    Publication date: March 3, 2022
    Inventors: Peter C. Simpson, Robert J. Boock, David DeRenzy, Laura J. Dunn, Matthew Lawrence Johnson, Katherine Yerre Koehler, Apurv Ullas Kamath, Andrew Attila Pal, David Price, Eli Reihman, Mark Wu
  • Patent number: 11219413
    Abstract: Adhesive pad systems that provide longer lasting adherence of the mounting unit to the host's skin are provided. Some systems include a reinforcing overlay that at least partially covers the adhesive pad. The reinforcing overlay may be removable without disturbing the sensor so that the overlay may be replaceable.
    Type: Grant
    Filed: August 25, 2015
    Date of Patent: January 11, 2022
    Assignee: DexCom, Inc.
    Inventors: James Jinwoo Lee, Leif N. Bowman, Tim Ray Gackstetter, Jonathan Hughes, Jeff Jackson, Ted Tang Lee, Phong Lieu, Andrew Attila Pal, James R. Petisce, Jack Pryor, Roger Schneider, Peter C. Simpson, George Vigil, Matthew D. Wightlin
  • Publication number: 20210294723
    Abstract: Disclosed are systems, methods, and articles for determining compatibility of a mobile application and operating system on a mobile device. In some aspects, a method includes receiving one or more data values from a mobile device having a mobile medical software application installed thereon, the data value(s) characterizing a version of the software application, a version of an operating system installed on the mobile device, and one or more attributes of the mobile device; determining whether the mobile medical software application is compatible with the operating system by at least comparing the received data value(s) to one or more test values in a configuration file; and sending a message to the mobile device based on the determining, the message causing the software application to operate in one or more of a normal mode, a safe mode, and a non-operational mode.
    Type: Application
    Filed: June 3, 2021
    Publication date: September 23, 2021
    Inventors: Issa Sami Salameh, Douglas William Burnette, Tifo Vu Hoang, Steven David King, Stephen M. Madigan, Michael Robert Mensinger, Andrew Attila Pal, Michael Ranen Tyler
  • 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: 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: 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: 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: 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
  • Patent number: 11055198
    Abstract: Disclosed are systems, methods, and articles for determining compatibility of a mobile application and operating system on a mobile device. In some aspects, a method includes receiving one or more data values from a mobile device having a mobile medical software application installed thereon, the data value(s) characterizing a version of the software application, a version of an operating system installed on the mobile device, and one or more attributes of the mobile device; determining whether the mobile medical software application is compatible with the operating system by at least comparing the received data value(s) to one or more test values in a configuration file; and sending a message to the mobile device based on the determining, the message causing the software application to operate in one or more of a normal mode, a safe mode, and a non-operational mode.
    Type: Grant
    Filed: December 27, 2019
    Date of Patent: July 6, 2021
    Assignee: DexCom, Inc.
    Inventors: Issa Sami Salameh, Douglas William Burnette, Tifo Vu Hoang, Steven David King, Stephen M. Madigan, Michael Robert Mensinger, Andrew Attila Pal, Michael Ranen Tyler
  • 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
  • Patent number: 10932672
    Abstract: Systems and methods for remote and host monitoring communication are disclosed. In some implementations, monitoring systems can comprise a host monitoring device associated with a Host communicatively coupled to one or more remote monitoring devices associated with Remote Monitors. The host monitoring device can send communications based at least in part on analyte measurements of a Host sensor and/or other contextual data giving such measurements context. Different remote monitoring devices can receive different communications based at least in part on the role of the respective Remote Monitors relative to the Host. These roles can be reflected in classifications of Remote Monitors.
    Type: Grant
    Filed: December 13, 2016
    Date of Patent: March 2, 2021
    Assignee: DexCom, Inc.
    Inventors: Aarthi Mahalingam, Esteban Cabrera, Jr., Basab Dattaray, Rian Draeger, Laura J. Dunn, Derek James Escobar, Thomas Hall, Hari Hampapuram, Apurv Ullas Kamath, Katherine Yerre Koehler, Phil Mayou, Michael Robert Mensinger, Michael Levozier Moore, Andrew Attila Pal, Nicholas Polytaridis, Eli Reihman, Brian Christopher Smith
  • 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: 10691574
    Abstract: Disclosed are systems, methods, and articles for determining compatibility of a mobile application and operating system on a mobile device. In some aspects, a method includes receiving one or more data values from a mobile device having a mobile medical software application installed thereon, the data value(s) characterizing a version of the software application, a version of an operating system installed on the mobile device, and one or more attributes of the mobile device; determining whether the mobile medical software application is compatible with the operating system by at least comparing the received data value(s) to one or more test values in a configuration file; and sending a message to the mobile device based on the determining, the message causing the software application to operate in one or more of a normal mode, a safe mode, and a non-operational mode.
    Type: Grant
    Filed: October 25, 2016
    Date of Patent: June 23, 2020
    Assignee: DexCom, Inc.
    Inventors: Issa Sami Salameh, Douglas William Burnette, Tifo Vu Hoang, Steven David King, Stephen M. Madigan, Michael Robert Mensinger, Andrew Attila Pal, Michael Ranen Tyler
  • Publication number: 20200142804
    Abstract: Disclosed are systems, methods, and articles for determining compatibility of a mobile application and operating system on a mobile device. In some aspects, a method includes receiving one or more data values from a mobile device having a mobile medical software application installed thereon, the data value(s) characterizing a version of the software application, a version of an operating system installed on the mobile device, and one or more attributes of the mobile device; determining whether the mobile medical software application is compatible with the operating system by at least comparing the received data value(s) to one or more test values in a configuration file; and sending a message to the mobile device based on the determining, the message causing the software application to operate in one or more of a normal mode, a safe mode, and a non-operational mode.
    Type: Application
    Filed: December 27, 2019
    Publication date: May 7, 2020
    Inventors: Issa Sami Salameh, Douglas William Burnette, Tifo Vu Hoang, Steven David King, Stephen M. Madigan, Michael Robert Mensinger, Andrew Attila Pal, Michael Ranen Tyler