公开(公告)号：US20210174949A1

公开(公告)日：2021-06-10

申请号：US16848687

申请日：2020-04-14

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Elaine Gee ,  Peter Ajemba ,  Bahman Engheta ,  Jeffrey Nishida ,  Andrea Varsavsky ,  Keith Nogueira

IPC: G16H40/40 ,  G16H50/30 ,  G16H50/50 ,  G16H50/20 ,  G16H40/67 ,  G16H20/17 ,  G16H10/60 ,  A61B5/00 ,  A61B5/145

Abstract: Medical devices and related systems and methods are provided. A method of estimating a physiological condition involves determining a translation model based at least in part on relationships between first measurement data corresponding to instances of a first sensing arrangement and second measurement data corresponding to instances of a second sensing arrangement, obtaining third measurement data associated with the second sensing arrangement, determining simulated measurement data for the first sensing arrangement by applying the translation model to the third measurement data, and determining an estimation model for a physiological condition using the simulated measurement data, wherein the estimation model is applied to subsequent measurement output provided by an instance of the first sensing arrangement to obtain an estimated value for the physiological condition.

公开(公告)号：US20200038588A1

公开(公告)日：2020-02-06

申请号：US16596675

申请日：2019-10-08

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Andrea Varsavsky ,  Yunfeng Lu ,  Keith Nogueira ,  Jeffrey Nishida

IPC: A61M5/172 ,  G16H10/60 ,  G16H50/50 ,  G16H40/63 ,  G16H40/40 ,  G16H50/20 ,  A61B5/145 ,  A61B5/00

Abstract: Medical devices and related patient management systems and parameter modeling methods are provided. An exemplary method of operating a sensing device associated with a patient involves obtaining current operational context information associated with the sensing device, obtaining a parameter model associated with the patient, calculating a current parameter value based on the parameter model and the current operational context information, obtaining one or more signals from a sensing element configured to measure a condition in a body of the patient, and providing an output that is influenced by the calculated current parameter value and the one or more signals.

公开(公告)号：US10543314B2

公开(公告)日：2020-01-28

申请号：US15240733

申请日：2016-08-18

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Andrea Varsavsky ,  Yunfeng Lu ,  Keith Nogueira ,  Jeffrey Nishida

IPC: G01N33/48 ,  A61M5/172 ,  G06F19/00 ,  G16H40/63 ,  G16H40/40 ,  G16H50/20 ,  A61B5/145 ,  A61B5/00 ,  G16H15/00 ,  A61B5/024

Abstract: Medical devices and related patient management systems and parameter modeling methods are provided. An exemplary method involves obtaining, by a computing device, historical measurements of a condition in a body of the patient previously provided by a sensing device, obtaining, by the computing device, historical operational context information associated with preceding operation of one or more of an infusion device and the sensing device, obtaining, by the computing device, historical values for a parameter from one or more of the infusion device and the sensing device, determining, by the computing device a patient-specific model of the parameter based on relationships between the historical measurements, the historical operational context information and the historical values, and providing, by the computing device via a network, the patient-specific model to one of the infusion device, the sensing device or a client device.

公开(公告)号：US10327680B2

公开(公告)日：2019-06-25

申请号：US14980205

申请日：2015-12-28

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Keith Nogueira ,  Taly G. Engel ,  Raghavendhar Gautham ,  Xiaolong Li ,  Bradley C. Liang ,  Rajiv Shah ,  Jaeho Kim ,  Mike C. Liu ,  Andy Y. Tsai ,  Jeffrey Nishida

IPC: A61B5/00 ,  A61B5/145 ,  A61B5/1486

Abstract: Electrochemical impedance spectroscopy (EIS) may be used in conjunction with continuous glucose monitoring (CGM) to enable identification of valid and reliable sensor data, as well implementation of Smart Calibration algorithms.

公开(公告)号：US20170185733A1

公开(公告)日：2017-06-29

申请号：US14980293

申请日：2015-12-28

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Keith Nogueira ,  Taly G. Engel ,  Benyamin Grosman ,  Xiaolong Li ,  Bradley C. Liang ,  Rajiv Shah ,  Mike C. Liu ,  Andy Y. Tsai ,  Andrea Varsavsky ,  Jeffrey Nishida

IPC: G06F19/00 ,  G06N3/12 ,  G06N99/00

CPC classification number: G06N20/00 ,  A61B5/14532 ,  A61B5/14735 ,  A61B5/1495 ,  A61B5/6849 ,  G06N3/126 ,  G16H40/40

Abstract: A method for retrospective calibration of a glucose sensor uses stored values of measured working electrode current (Isig) to calculate a final sensor glucose (SG) value retrospectively. The Isig values may be preprocessed, discrete wavelet decomposition applied. At least one machine learning model, such as, e.g., Genetic Programming (GP) and Regression Decision Tree (DT), may be used to calculate SG values based on the Isig values and the discrete wavelet decomposition. Other inputs may include, e.g., counter electrode voltage (Vcntr) and Electrochemical Impedance Spectroscopy (EIS) data. A plurality of machine learning models may be used to generate respective SG values, which are then fused to generate a fused SG. Fused SG values may be filtered to smooth the data, and blanked if necessary.

公开(公告)号：US20240285199A1

公开(公告)日：2024-08-29

申请号：US18643565

申请日：2024-04-23

Applicant: Medtronic MiniMed, Inc.

Inventor： Keith Nogueira ,  Peter Ajemba ,  Michael E. Miller ,  Steven C. Jacks ,  Jeffrey Nishida ,  Andy Y. Tsai ,  Andrea Varsavsky

IPC: A61B5/1495 ,  A61B5/00 ,  A61B5/0205 ,  A61B5/021 ,  A61B5/024 ,  A61B5/11 ,  A61B5/145 ,  A61B5/1455 ,  A61B5/1468 ,  A61B5/1486 ,  G01N27/02 ,  G06N5/022 ,  G16H20/17 ,  G16H40/40 ,  G16H50/30 ,  G16H50/70

CPC classification number: A61B5/1495 ,  A61B5/14532 ,  A61B5/1468 ,  A61B5/14865 ,  A61B5/6849 ,  A61B5/686 ,  G01N27/026 ,  G06N5/022 ,  G16H20/17 ,  G16H40/40 ,  G16H50/30 ,  G16H50/70 ,  A61B5/0075 ,  A61B5/02055 ,  A61B5/021 ,  A61B5/024 ,  A61B5/1118 ,  A61B5/14546 ,  A61B5/1455 ,  A61B5/7203 ,  A61B5/7221 ,  A61B5/7267 ,  A61B5/742 ,  A61B2505/07 ,  A61B2560/0223 ,  A61B2560/0252 ,  A61B2560/0257 ,  A61B2562/028 ,  A61B2562/029 ,  A61B2562/164

Abstract: A continuous glucose monitoring system may utilize externally sourced information regarding the physiological state and ambient environment of its user for externally calibrating sensor glucose measurements. Externally sourced factory calibration information may be utilized, where the information is generated by comparing metrics obtained from the data used to generate the sensor's glucose sensing algorithm to similar data obtained from each batch of sensors to be used with the algorithm in the future. The output sensor glucose value of a glucose sensor may also be estimated by analytically optimizing input sensor signals to accurately correct for changes in sensitivity, run-in time, glucose current dips, and other variable sensor wear effects. Correction actors, fusion algorithms, EIS, and advanced ASICs may be used to implement the foregoing, thereby achieving the goal of improved accuracy and reliability without the need for blood-glucose calibration, and providing a calibration-free, or near calibration-free, sensor.

公开(公告)号：US20230360799A1

公开(公告)日：2023-11-09

申请号：US18324820

申请日：2023-05-26

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Keith Nogueira ,  Taly G. Engel ,  Benyamin Grosman ,  Xiaolong Li ,  Bradley C. Liang ,  Rajiv Shah ,  Mike C. Liu ,  Andy Y. Tsai ,  Andrea Varsavsky ,  Jeffrey Nishida

IPC: A61B5/145 ,  A61B5/1495 ,  G06N3/126 ,  G06N20/00 ,  A61B5/1473 ,  G16H50/20 ,  G16H40/40

CPC classification number: G16H50/20 ,  A61B5/14532 ,  A61B5/14735 ,  A61B5/1495 ,  G06N3/126 ,  G06N20/00 ,  G16H40/40 ,  A61B5/6849

Abstract: A method for retrospective calibration of a glucose sensor uses stored values of measured working electrode current (Isig) to calculate a final sensor glucose (SG) value retrospectively. The Isig values may be preprocessed, discrete wavelet decomposition applied. At least one machine learning model, such as, e.g., Genetic Programing (GP) and Regression Decision Tree (DT), may be used to calculate SG values based on the Isig values and the discrete wavelet decomposition. Other inputs may include, e.g., counter electrode voltage (Vcntr) and Electrochemical Impedance Spectroscopy (EIS) data. A plurality of machine learning models may be used to generate respective SG values, which are then fused to generate a fused SG. Fused SG values may be filtered to smooth the data, and blanked if necessary.

公开(公告)号：US11484651B2

公开(公告)日：2022-11-01

申请号：US16596675

申请日：2019-10-08

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Andrea Varsavsky ,  Yunfeng Lu ,  Keith Nogueira ,  Jeffrey Nishida

IPC: A61M5/172 ,  G16H40/63 ,  G16H40/40 ,  G16H50/20 ,  G16H10/60 ,  G16H50/50 ,  G16H20/17 ,  A61B5/145 ,  A61B5/00 ,  G16H15/00 ,  A61M5/142 ,  A61B5/024

Abstract: Medical devices and related patient management systems and parameter modeling methods are provided. An exemplary method of operating a sensing device associated with a patient involves obtaining current operational context information associated with the sensing device, obtaining a parameter model associated with the patient, calculating a current parameter value based on the parameter model and the current operational context information, obtaining one or more signals from a sensing element configured to measure a condition in a body of the patient, and providing an output that is influenced by the calculated current parameter value and the one or more signals.

公开(公告)号：US11471082B2

公开(公告)日：2022-10-18

申请号：US15840673

申请日：2017-12-13

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Andrea Varsavsky ,  Jeffrey Nishida ,  Taly G. Engel ,  Keith Nogueira ,  Andy Y. Tsai ,  Peter Ajemba

IPC: A61B5/1495 ,  A61B5/1473 ,  A61B5/145 ,  A61B5/00 ,  A61M5/142 ,  A61M5/172 ,  A61B5/1486

Abstract: A continuous glucose monitoring system may employ complex redundancy to take operational advantage of disparate characteristics of two or more dissimilar, or non-identical, sensors, including, e.g., characteristics relating to hydration, stabilization, and durability of such sensors. Fusion algorithms, Electrochemical Impedance Spectroscopy (EIS), and advanced Application Specific Integrated Circuits (ASICs) may be used to implement use of such redundant glucose sensors, devices, and sensor systems in such a way as to bridge the gaps between fast start-up, sensor longevity, and accuracy of calibration-free algorithms. Systems, devices, and algorithms are described for achieving a long-wear and reliable sensor which also minimizes, or eliminates, the need for BG calibration, thereby providing a calibration-free, or near calibration-free, sensor.

公开(公告)号：US11344235B2

公开(公告)日：2022-05-31

申请号：US16117733

申请日：2018-08-30

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Keith Nogueira ,  Peter Ajemba ,  Michael E. Miller ,  Steven C. Jacks ,  Jeffrey Nishida ,  Andy Y. Tsai ,  Andrea Varsavsky

IPC: A61B5/1495 ,  A61B5/145 ,  A61B5/1486 ,  A61B5/00 ,  G06N5/02 ,  G16H50/30 ,  G01N27/02 ,  G16H20/17 ,  G16H50/70 ,  A61B5/1468 ,  G16H40/40 ,  A61B5/1455 ,  A61B5/0205 ,  A61B5/021 ,  A61B5/024 ,  A61B5/11

Abstract: A continuous glucose monitoring system may utilize externally sourced information regarding the physiological state and ambient environment of its user for externally calibrating sensor glucose measurements. Externally sourced factory calibration information may be utilized, where the information is generated by comparing metrics obtained from the data used to generate the sensor's glucose sensing algorithm to similar data obtained from each batch of sensors to be used with the algorithm in the future. The output sensor glucose value of a glucose sensor may also be estimated by analytically optimizing input sensor signals to accurately correct for changes in sensitivity, run-in time, glucose current dips, and other variable sensor wear effects. Correction actors, fusion algorithms, EIS, and advanced ASICs may be used to implement the foregoing, thereby achieving the goal of improved accuracy and reliability without the need for blood-glucose calibration, and providing a calibration-free, or near calibration-free, sensor.