公开(公告)号：US20250134416A1

公开(公告)日：2025-05-01

申请号：US18908892

申请日：2024-10-08

Applicant: Medtronic MiniMed, Inc.

Inventor： Leonardo Nava-Guerra ,  Molly E. Emig ,  Juan E. Arguelles Morales ,  Anup V. Kanale ,  Kelly J. Qiu ,  Mona M. Sharifi Sarabi ,  Chi A. Tran ,  Anthony Haas ,  Francesca Piccinini ,  Bahram Notghi ,  Georgios Mallas ,  Yi Zhang

IPC: A61B5/145

Abstract: Techniques disclosed herein relate to glucose level measurement and/or management. In some embodiments, the techniques involve obtaining in vivo characteristics of a glucose sensor predicted using fabrication process measurement data associated with the glucose sensor, the in vivo characteristics including an in vivo sensitivity, an in vivo intercept, or a combination thereof; receiving sensor measurement data measured by the glucose sensor, the sensor measurement data including sensor current (Isig), counter voltage (Vcntr), electrochemical impedance spectroscopy (EIS) data, an age of the glucose sensor, or a combination thereof; and estimating a sensor glucose (SG) value using an SG model, wherein input parameters of the SG model include the in vivo characteristics of the glucose sensor and the sensor measurement data, and the SG value is an output of the SG model.

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.