Patents by Inventor Eli Reihman
Eli Reihman 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).
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Patent number: 11399721Abstract: 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: GrantFiled: December 13, 2016Date of Patent: August 2, 2022Assignee: 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
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Patent number: 11382508Abstract: Methods and apparatus, including computer program products, are provided for remote monitoring. In some example implementations, there is provided a method. The method may include receiving, at a remote monitor, a notification message representative of an event detected, by a server, from analyte sensor data obtained from a receiver monitoring an analyte state of a host; presenting, at the remote monitor, the notification message to activate the remote monitor, wherein the remote monitor is configured by the server to receive the notification message to augment the receiver monitoring of the analyte state of the host; accessing, by the remote monitor, the server, in response to the presenting of the notification message; and receiving, in response to the accessing, information including at least the analyte sensor data. Related systems, methods, and articles of manufacture are also disclosed.Type: GrantFiled: August 6, 2021Date of Patent: July 12, 2022Assignee: Dexcom, Inc.Inventors: Michael Robert Mensinger, Eric Cohen, Phil Mayou, Eli Reihman, Katherine Yerre Koehler, Rian Draeger, Angela Marie Traven
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Publication number: 20220192609Abstract: Methods and apparatus, including computer program products, are provided for remote monitoring. In some example implementations, there is provided a method. The method may include receiving, at a remote monitor, a notification message representative of an event detected, by a server, from analyte sensor data obtained from a receiver monitoring an analyte state of a host; presenting, at the remote monitor, the notification message to activate the remote monitor, wherein the remote monitor is configured by the server to receive the notification message to augment the receiver monitoring of the analyte state of the host; accessing, by the remote monitor, the server, in response to the presenting of the notification message; and receiving, in response to the accessing, information including at least the analyte sensor data. Related systems, methods, and articles of manufacture are also disclosed.Type: ApplicationFiled: February 24, 2022Publication date: June 23, 2022Inventors: Eric COHEN, Brian Christopher SMITH, Michael Robert MENSINGER, Rian DRAEGER, Katherine Yerre KOEHLER, Leif N. BOWMAN, David PRICE, Shawn LARVENZ, Eli REIHMAN
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Publication number: 20220160267Abstract: The present embodiments provide systems and methods for, among others, tracking sensor insertion locations in a continuous analyte monitoring system. Data gathered from sensor sessions can be used in different ways, such as providing a user with a suggested rotation of insertion locations, correlating data from a given sensor session with sensor accuracy and/or sensor session length, and providing a user with a suggested next insertion location based upon past sensor accuracy and/or sensor session length at that location.Type: ApplicationFiled: December 13, 2021Publication date: May 26, 2022Inventors: Katherine Yerre KOEHLER, Leif N. BOWMAN, Rian DRAEGER, Laura DUNN, Eli REIHMAN
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Patent number: 11295855Abstract: 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: GrantFiled: November 7, 2017Date of Patent: April 5, 2022Assignee: 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
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Publication number: 20220101995Abstract: This disclosure provides systems, methods and apparatus for processing, transmitting and displaying data received from an analyte sensor, such as a glucose sensor. The system may include a display device with at least one input device. In response to movement of or along the input device, the display device may change a glucose data output parameter and update an output of the display device using the changed output parameter.Type: ApplicationFiled: December 10, 2021Publication date: March 31, 2022Inventors: Eric Johnson, Michael Robert Mensinger, Peter C. Simpson, Thomas Hall, Hari Hampapuram, Kostyantyn Snisarenko, Eli Reihman, Holly Chico, Kassandra Constantine
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Publication number: 20220068452Abstract: 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: ApplicationFiled: November 11, 2021Publication date: March 3, 2022Inventors: 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
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Publication number: 20220000432Abstract: 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: ApplicationFiled: September 21, 2021Publication date: January 6, 2022Inventors: 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
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Patent number: 11213204Abstract: Methods and apparatus, including computer program products, are provided for remote monitoring. In some example implementations, there is provided a method. The method may include receiving, at a remote monitor, a notification message representative of an event detected, by a server, from analyte sensor data obtained from a receiver monitoring an analyte state of a host; presenting, at the remote monitor, the notification message to activate the remote monitor, wherein the remote monitor is configured by the server to receive the notification message to augment the receiver monitoring of the analyte state of the host; accessing, by the remote monitor, the server, in response to the presenting of the notification message; and receiving, in response to the accessing, information including at least the analyte sensor data. Related systems, methods, and articles of manufacture are also disclosed.Type: GrantFiled: June 8, 2017Date of Patent: January 4, 2022Assignee: DexCom, Inc.Inventors: Michael Robert Mensinger, Eric Cohen, Phil Mayou, Eli Reihman, Katherine Yerre Koehler, Rian Draeger, Angela Marie Traven
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Patent number: 11197626Abstract: The present embodiments provide systems and methods for, among others, tracking sensor insertion locations in a continuous analyte monitoring system. Data gathered from sensor sessions can be used in different ways, such as providing a user with a suggested rotation of insertion locations, correlating data from a given sensor session with sensor accuracy and/or sensor session length, and providing a user with a suggested next insertion location based upon past sensor accuracy and/or sensor session length at that location.Type: GrantFiled: June 13, 2019Date of Patent: December 14, 2021Assignee: DexCom, Inc.Inventors: Katherine Yerre Koehler, Leif N. Bowman, Rian Draeger, Laura Dunn, Eli Reihman
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Publication number: 20210361163Abstract: Methods and apparatus, including computer program products, are provided for remote monitoring. In some example implementations, there is provided a method. The method may include receiving, at a remote monitor, a notification message representative of an event detected, by a server, from analyte sensor data obtained from a receiver monitoring an analyte state of a host; presenting, at the remote monitor, the notification message to activate the remote monitor, wherein the remote monitor is configured by the server to receive the notification message to augment the receiver monitoring of the analyte state of the host; accessing, by the remote monitor, the server, in response to the presenting of the notification message; and receiving, in response to the accessing, information including at least the analyte sensor data. Related systems, methods, and articles of manufacture are also disclosed.Type: ApplicationFiled: August 6, 2021Publication date: November 25, 2021Inventors: Michael Robert Mensinger, Eric Cohen, Phil Mayou, Eli Reihman, Katherine Yerre Koehler, Rian Draeger, Angela Marie Traven
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Patent number: 11160452Abstract: Methods and apparatus, including computer program products, are provided for remote monitoring. In some example implementations, there is provided a method. The method may include receiving, at a remote monitor, a notification message representative of an event detected, by a server, from analyte sensor data obtained from a receiver monitoring an analyte state of a host; presenting, at the remote monitor, the notification message to activate the remote monitor, wherein the remote monitor is configured by the server to receive the notification message to augment the receiver monitoring of the analyte state of the host; accessing, by the remote monitor, the server, in response to the presenting of the notification message; and receiving, in response to the accessing, information including at least the analyte sensor data. Related systems, methods, and articles of manufacture are also disclosed.Type: GrantFiled: December 23, 2020Date of Patent: November 2, 2021Assignee: DexCom, Inc.Inventors: Michael Robert Mensinger, Eric Cohen, Phil Mayou, Eli Reihman, Katherine Yerre Koehler, Rian Draeger, Angela Marie Traven
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Patent number: 11154253Abstract: 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: GrantFiled: August 10, 2017Date of Patent: October 26, 2021Assignee: 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
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Patent number: 11141116Abstract: 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: GrantFiled: August 10, 2017Date of Patent: October 12, 2021Assignee: 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
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Patent number: 11109757Abstract: Methods and apparatus, including computer program products, are provided for remote monitoring. In some example implementations, there is provided a method. The method may include receiving, at a remote monitor, a notification message representative of an event detected, by a server, from analyte sensor data obtained from a receiver monitoring an analyte state of a host; presenting, at the remote monitor, the notification message to activate the remote monitor, wherein the remote monitor is configured by the server to receive the notification message to augment the receiver monitoring of the analyte state of the host; accessing, by the remote monitor, the server, in response to the presenting of the notification message; and receiving, in response to the accessing, information including at least the analyte sensor data. Related systems, methods, and articles of manufacture are also disclosed.Type: GrantFiled: December 23, 2020Date of Patent: September 7, 2021Assignee: DexCom, Inc.Inventors: Michael Robert Mensinger, Eric Cohen, Phil Mayou, Eli Reihman, Katherine Yerre Koehler, Rian Draeger, Angela Marie Traven
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Publication number: 20210260289Abstract: 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: ApplicationFiled: December 7, 2020Publication date: August 26, 2021Inventors: 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
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Publication number: 20210260286Abstract: 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: ApplicationFiled: December 7, 2020Publication date: August 26, 2021Inventors: 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
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Publication number: 20210260287Abstract: 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: ApplicationFiled: December 7, 2020Publication date: August 26, 2021Inventors: 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
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Publication number: 20210260288Abstract: 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: ApplicationFiled: December 7, 2020Publication date: August 26, 2021Inventors: 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
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Publication number: 20210259591Abstract: 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: ApplicationFiled: December 7, 2020Publication date: August 26, 2021Inventors: 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