公开(公告)号：US20200245910A1

公开(公告)日：2020-08-06

申请号：US16773422

申请日：2020-01-27

Applicant: MEDTRONIC MINIMED, INC

Inventor： Georgios Mallas ,  Andrea Varsavsky ,  Peter Ajemba ,  Jeffrey Nishida ,  Keith Nogueira ,  Elaine Gee ,  Leonardo Nava-Guerra ,  Jing Liu ,  Sadaf S. Seleh ,  Taly G, Engel ,  Benyamin Grosman ,  Steven Lai ,  Luis A. Torres ,  Chi A. Tran ,  David M. Sniecinski

IPC: A61B5/145 ,  A61B5/1468

Abstract: A continuous glucose monitoring system may utilize electrode current (Isig) signals, Electrochemical Impedance Spectroscopy (EIS), and Vcntr values to optimize sensor glucose (SG) calculation in such a way as to enable reduction of the need for blood glucose (BG) calibration requests from users.

公开(公告)号：US12114972B2

公开(公告)日：2024-10-15

申请号：US16773422

申请日：2020-01-27

Applicant: MEDTRONIC MINIMED, INC.

Inventor： Georgios Mallas ,  Andrea Varsavsky ,  Peter Ajemba ,  Jeffrey Nishida ,  Keith Nogueira ,  Elaine Gee ,  Leonardo Nava-Guerra ,  Jing Liu ,  Sadaf S. Seleh ,  Taly G. Engel ,  Benyamin Grosman ,  Steven Lai ,  Luis A. Torres ,  Chi A. Tran ,  David M. Sniecinski

IPC: A61B5/145 ,  A61B5/1468

CPC classification number: A61B5/14532 ,  A61B5/1468 ,  A61B2560/0223 ,  A61B2562/16

Abstract: A continuous glucose monitoring system may utilize electrode current (Isig) signals, Electrochemical Impedance Spectroscopy (EIS), and Vcntr values to optimize sensor glucose (SG) calculation in such a way as to enable reduction of the need for blood glucose (BG) calibration requests from users.

公开(公告)号：US20250134417A1

公开(公告)日：2025-05-01

申请号：US18908980

申请日：2024-10-08

Applicant: Medtronic MiniMed, Inc.

Inventor： Jake G. Basilico ,  Leonardo Nava-Guerra ,  Bahram B. Notghi ,  Molly E. Emig ,  Jing Liu ,  Adam A. Willats ,  Georgios Mallas ,  Yi Zhang

IPC: A61B5/145 ,  A61B5/00

Abstract: A processor-implemented method includes receiving sensor measurement data from a glucose sensor; selecting, based on the sensor measurement data, a first regional sensor glucose (SG) model from a first plurality of regional SG models for respective regions of a first plurality of regions of an input parameter space associated with the sensor measurement data, and a second regional SG model from a second plurality of regional SG models for respective regions of a second plurality of regions of the input parameter space; estimating a first SG value and a second SG value using the first regional SG model and the second regional SG model, respectively; and determining a predicted SG value based on a combination of the first SG value and the second SG value. The input parameter space is partitioned into the first plurality of regions and the second plurality of regions using different partition schemes.