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公开(公告)号：US20240341645A1
公开(公告)日：2024-10-17
申请号：US18626950
申请日：2024-04-04
Applicant: Dexcom, Inc.
Inventor： Rui Ma , Naresh C. Bhavaraju , Thomas Hamilton , Johathan M. Hughes , Jeff Jackson , David Lee , Peter C. Simpson , Stephen J. Vanslyke
IPC: A61B5/1495 , A61B5/145 , A61B5/1486 , G01N33/66
CPC classification number: A61B5/1495 , A61B5/14532 , G01N33/66 , A61B5/14865
Abstract: Systems and methods are disclosed which provide for a “factory-calibrated” sensor. In doing so, the systems and methods include predictive prospective modeling of sensor behavior, and also include predictive modeling of physiology. With these two correction factors, a consistent determination of sensitivity can be achieved, thus achieving factory calibration.
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公开(公告)号：US12014821B2
公开(公告)日：2024-06-18
申请号：US18163255
申请日：2023-02-01
Applicant: Dexcom, Inc.
Inventor： Naresh C. Bhavaraju , Arturo Garcia , Phil Mayou , Thomas A. Peyser , Apurv Ullas Kamath , Aarthi Mahalingam , Kevin Sayer , Thomas Hall , Michael Robert Mensinger , Hari Hampapuram , David Price , Jorge Valdes , Murrad Kazalbash
IPC: G16H50/30 , A61M5/142 , A61M5/172 , G01N33/49 , G16H15/00 , G16H20/17 , G16H40/63 , G16H40/67 , G16H50/00
CPC classification number: G16H40/67 , A61M5/142 , A61M5/1723 , G01N33/49 , G16H15/00 , G16H20/17 , G16H40/63 , G16H50/00 , G16H50/30
Abstract: Methods and apparatus, including computer program products, are provided for processing analyte data. In some example implementations, a method may include generating glucose sensor data indicative of a host's glucose concentration using a glucose sensor; calculating a glycemic variability index (GVI) value based on the glucose sensor data; and providing output to a user responsive to the calculated glycemic variability index value. The GVI may be a ratio of a length of a line representative of the sensor data and an ideal length of the line. Related systems, methods, and articles of manufacture are also disclosed.
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公开(公告)号：US20240148284A1
公开(公告)日：2024-05-09
申请号：US18521110
申请日：2023-11-28
Applicant: Dexcom, Inc.
Inventor： Derek James Escobar , Naresh C. Bhavaraju , Gary A. Morris , Jorge Valdes
IPC: A61B5/145 , A61B5/00 , A61M5/142 , A61M5/172 , G06N20/00 , G06N20/20 , G16H10/60 , G16H20/17 , G16H40/67 , G16H50/20 , G16H50/30 , H04L9/30 , H04W12/033 , H04W12/037
CPC classification number: A61B5/14532 , A61B5/0004 , A61B5/425 , A61B5/6801 , A61B5/743 , A61B5/7475 , A61M5/14244 , A61M5/1723 , G06N20/00 , G06N20/20 , G16H10/60 , G16H20/17 , G16H40/67 , G16H50/20 , G16H50/30 , H04L9/30 , H04W12/033 , H04W12/037 , A61M2205/18 , A61M2205/3553 , A61M2205/3584 , A61M2205/3592 , A61M2205/502 , A61M2205/52 , A61M2205/581 , A61M2205/582 , A61M2205/583 , A61M2205/8206 , A61M2230/201
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.
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公开(公告)号：US11766194B2
公开(公告)日：2023-09-26
申请号：US16269480
申请日：2019-02-06
Applicant: DexCom, Inc.
Inventor： Alexandra Elena Constantin , Scott M. Belliveau , Naresh C. Bhavaraju , Jennifer Blackwell , Eric Cohen , Basab Dattaray , Anna Leigh Davis , Rian Draeger , Arturo Garcia , John Michael Gray , Hari Hampapuram , Nathaniel David Heintzman , Lauren Hruby Jepson , Matthew Lawrence Johnson , Apurv Ullas Kamath , Katherine Yerre Koehler , Phil Mayou , Patrick Wile McBride , Michael Robert Mensinger , Sumitaka Mikami , Andrew Attila Pal , Nicholas Polytaridis , Philip Thomas Pupa , Eli Reihman , Peter C. Simpson , Tomas C. Walker , Daniel Justin Wiedeback , Subrai Girish Pai , Matthew T. Vogel
IPC: A61B5/145 , G16H70/20 , A61B5/00 , G06N20/00 , G06N5/045 , A61B5/11 , A61B5/01 , A61B5/0205 , G16H50/20 , A61B5/024 , A61B5/08
CPC classification number: A61B5/14532 , A61B5/0022 , A61B5/01 , A61B5/02055 , A61B5/1118 , A61B5/486 , A61B5/4839 , A61B5/4866 , A61B5/7221 , A61B5/7275 , A61B5/7282 , A61B5/746 , A61B5/7475 , G06N5/045 , G06N20/00 , G16H70/20 , A61B5/024 , A61B5/0816 , G16H50/20
Abstract: Systems and methods are provided to provide guidance to a user regarding management of a physiologic condition such as diabetes. The determination may be based upon a patient glucose concentration level. The glucose concentration level may be provided to a stored model to determine a state. The guidance may be determined based at least in part on the determined state.
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公开(公告)号：US11737692B2
公开(公告)日：2023-08-29
申请号：US16882334
申请日：2020-05-22
Applicant: DexCom, Inc.
Inventor： Naresh C. Bhavaraju , Sebastian Bohm , Robert J. Boock , Daiting Rong , Peter C. Simpson
IPC: A61B5/145 , A61B5/1495 , A61B5/1473 , A61B5/1459 , A61B5/00 , A61B5/1486
CPC classification number: A61B5/1495 , A61B5/1459 , A61B5/1473 , A61B5/14532 , A61B5/14865 , A61B5/7221 , A61B5/7246 , A61B5/7278 , A61B2562/04
Abstract: Disclosed herein are devices, systems, and methods for a continuous analyte sensor, such as a continuous glucose sensor. In certain embodiments disclosed herein, various in vivo properties of the sensor's surroundings can be measured. In some embodiments, the measured properties can be used to identify a physiological response or condition in the body. This information can then be used by a patient, doctor, or system to respond appropriately to the identified condition.
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Patent Agency Ranking
公开(公告)号：US11723560B2
公开(公告)日：2023-08-15
申请号：US16269533
申请日：2019-02-06
Applicant: DexCom, Inc.
Inventor： Alexandra Elena Constantin , Scott M. Belliveau , Naresh C. Bhavaraju , Jennifer Blackwell , Eric Cohen , Basab Dattaray , Anna Leigh Davis , Rian Draeger , Arturo Garcia , John Michael Gray , Hari Hampapuram , Nathaniel David Heintzman , Lauren Hruby Jepson , Matthew Lawrence Johnson , Apurv Ullas Kamath , Katherine Yerre Koehler , Phil Mayou , Patrick Wile McBride , Michael Robert Mensinger , Sumitaka Mikami , Andrew Attila Pal , Nicholas Polytaridis , Philip Thomas Pupa , Eli Reihman , Peter C. Simpson , Tomas C. Walker , Daniel Justin Wiedeback
IPC: A61B5/145 , G16H70/20 , A61B5/00 , G06N20/00 , G06N5/045 , A61B5/11 , A61B5/01 , A61B5/0205 , G16H50/20 , A61B5/024 , A61B5/08
CPC classification number: A61B5/14532 , A61B5/0022 , A61B5/01 , A61B5/02055 , A61B5/1118 , A61B5/486 , A61B5/4839 , A61B5/4866 , A61B5/7221 , A61B5/7275 , A61B5/7282 , A61B5/746 , A61B5/7475 , G06N5/045 , G06N20/00 , G16H70/20 , A61B5/024 , A61B5/0816 , G16H50/20
Abstract: Systems and methods are provided to provide guidance to a user regarding management of a physiologic condition such as diabetes. The determination may be based upon a patient glucose concentration data sensed by a glucose concentration sensor. A host state change associated with the host glucose concentration data may be determined. A guidance message based at least in part on the host state change may also be determined. The guidance message may be delivered through a user interface.
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公开(公告)号：US11656195B2
公开(公告)日：2023-05-23
申请号：US16402101
申请日：2019-05-02
Applicant: DexCom, Inc.
Inventor： Naresh C. Bhavaraju , Becky L. Clark , Vincent P. Crabtree , Chris W. Dring , Arturo Garcia , Jason Halac , Jonathan Hughes , Jeff Jackson , Lauren Hruby Jepson , David I-Chun Lee , Ted Tang Lee , Rui Ma , Zebediah L. McDaniel , Jason Mitchell , Andrew Attila Pal , Daiting Rong , Disha B. Sheth , Peter C. Simpson , Stephen J. Vanslyke , Matthew D. Wightlin , Anna Leigh Davis , Hari Hampapuram , Aditya Sagar Mandapaka , Alexander Leroy Teeter , Liang Wang
IPC: G01N27/327 , A61B5/145 , A61B5/1495
CPC classification number: G01N27/3274 , A61B5/1495 , A61B5/14532 , A61B2560/0223
Abstract: Systems and methods are provided that address the need to frequently calibrate analyte sensors, according to implementation. In more detail, systems and methods provide a preconnected analyte sensor system that physically combines an analyte sensor to measurement electronics during the manufacturing phase of the sensor and in some cases in subsequent life phases of the sensor, so as to allow an improved recognition of sensor environment over time to improve subsequent calibration of the sensor.
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公开(公告)号：US11193924B2
公开(公告)日：2021-12-07
申请号：US16698498
申请日：2019-11-27
Applicant: DexCom, Inc.
Inventor： Naresh C. Bhavaraju , Arturo Garcia , Hari Hampapuram , Apurv Ullas Kamath , Aarthi Mahalingam , Dmytro Sokolovskyy , Stephen J. Vanslyke
IPC: G01N33/487 , G16C20/80 , G16C99/00 , A61B5/00 , G01M99/00 , A61B5/145 , A61B5/1495 , G01N33/49 , G01N33/66
Abstract: Systems and methods for processing sensor data and end of life detection are provided. In some embodiments, a method for determining the end of life of a continuous analyte sensor includes evaluating a plurality of risk factors using an end of life function to determine an end of life status of the sensor and providing an output related to the end of life status of the sensor. The plurality of risk factors may be selected from the list including the number of days the sensor has been in use, whether there has been a decrease in signal sensitivity, whether there is a predetermined noise pattern, whether there is a predetermined oxygen concentration pattern, and error between reference BG values and EGV sensor values.
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公开(公告)号：US20210330219A1
公开(公告)日：2021-10-28
申请号：US17368541
申请日：2021-07-06
Applicant: DexCom, Inc.
Inventor： Rui Ma , Naresh C. Bhavaraju , Thomas Stuart Hamilton , Jonathan Hughes , Jeff Jackson , David I-Chun Lee , Peter C. Simpson , Stephen J. Vanslyke
IPC: A61B5/1495 , A61B5/145 , G01N33/66
Abstract: Systems and methods are disclosed which provide for a “factory-calibrated” sensor. In doing so, the systems and methods include predictive prospective modeling of sensor behavior, and also include predictive modeling of physiology. With these two correction factors, a consistent determination of sensitivity can be achieved, thus achieving factory calibration.
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公开(公告)号：US20210260287A1
公开(公告)日：2021-08-26
申请号：US17114142
申请日：2020-12-07
Applicant: DexCom, Inc.
Inventor： 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
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.
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