Medtronic Minimed, Inc.

Minimed, Inc.

Other

Eli Lilly and Company

University of California

Futrex, Inc.

John Joseph Mastrototaro

Desmond Barry Keenan

William P Van Antwerp

Benyamin Grosman

Anirban Roy

Neha J Parikh

Richard E Purvis

Nannette M Van Antwerp

Edgardo C Halili

Rajiv Shah

Sheldon B Moberg

Alfred E Mann

Cary D Talbot

Gary Williams

Rebecca K Gottlieb

James Causey

James L Henke

Garry M Steil

John Livingston

Bradley J Enegren

John J Shin

Thomas Arnold Peyser

Joe H Satcher, Jr

Jenn-Hann Larry Wang

Paul S Cheney, Ii

Stephen M Lane

Mark C Estes

Udo Hoss

Michael E Miller

Robert D Rosenthal

Bahar Reghabi

Varaz Shahmirian

Yanan Zhang

James D Causey, Iii

Ning Yang

Himanshu P Patel

John C Mueller, Jr

John C Mueller

Clifford W Hague

Peter Hong

Kevin Branch

Brad T Hite

Eric Johnson

Do Kim

Peter C Lord

Richard S Yoon

H Bud Clark

James D Holker

Mike Charles Vallet Tolle

Nannette M Schnabel

Bihong Wu

K Collin McIvor

James L Cabernoch

Andrew C Hayes

Wayne A Morgan

Guillermo A Calle

Sami S Kanderian, Jr

Lu Wang

Kris R Holtzclaw

Edward Chernoff

Christopher B Darrow

“Mike” Charles Vallet Tolle

Eunjoo Jin

Kent L Clark

Nandita D Dangui

Jennifer Harder

Joseph K Frischmann

Andrea Varsavsky

Gopikrishnan Soundararajan

Katherine T Wolfe

Paul H Kovelman

David J Vachon

Glenn Noronha

Kirk Willis Johnson

Brian T Kannard

Tri T Dang

Kenneth W Cooper

Peter I Hong

Sami Kanderian

Kerstin Rebrin

Edward Stapleford Nielsen

Frank Saidara

Brooks B Cochran

Todd M Gross

Aaron M Heiss

Joseph C Walsh

Christian C Decker

Uzair Siddiqui

Ratnakar Vejella

Reynaldo Quintana

Charles Vallet Tolle

Jeff B Sanders

Paul V Goode, Jr

Raymond D Clark

Richard Lemos

Richard Yoon

"mike" Charles Vallet Tolle

A system includes one or more processors and one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of: associating a medical device with an intermediate device, obtaining, from the medical device via the intermediate device, measurement data correlative to a condition of a user, determining updated control information for the medical device based at least in part on the measurement data, and streaming the updated control information to the medical device via the intermediate device.

Streamed communication of updated control information to a medical device via an intermediate device

The subject matter disclosed herein relates to systems, methods and/or devices for calibrating sensor data to be used in estimating a blood glucose concentration. A relationship between sensor measurements and reference readings may be used to estimate a relationship between sensor measurements and blood glucose concentration. Such sensor measurements may be weighted according to a decreasing function of uncertainty associated with sensor values.

System and/or method for glucose sensor calibration

Infusion systems, infusion devices, and related operating methods are provided. An exemplary method of operating an infusion device capable of delivering fluid to a user involves storing alert configuration information for the user, identifying an alert condition while operating the infusion device to deliver the fluid based at least in part on the alert configuration information for the user, and in response to identifying the alert condition, providing a user notification in accordance with the user's stored alert configuration information.

User-configurable closed-loop notifications and infusion systems incorporating same

Apparatus are provided for medical devices and related operating systems and methods. An exemplary medical device includes a motor, one or more data storage elements to maintain control information, and a control module coupled to the motor and the one or more data storage elements. The control module is configured to obtain updated control information via a peer-to-peer communication session over a network, store the updated control information in the one or more data storage elements, and thereafter operate the motor based at least in part on the updated control information.

Medical devices and related updating methods and systems

Processor-implemented methods of controlling an insulin infusion device for a user are provided here. A first method obtains a current insulin on board (IOB) value that estimates active insulin in the user, and compensates a calculated insulin infusion rate in response to the obtained IOB value. A second method supervises the operation of a glucose sensor by obtaining and processing insulin-delivered data and glucose sensor data for the user. An alert is generated if the second method determines that a current glucose sensor value has deviated from a predicted sensor glucose value by at least a threshold amount.

Safeguarding measures for a closed-loop insulin infusion system

Infusion systems, infusion devices, and related operating methods are provided. An exemplary method of operating an infusion device capable of delivering fluid to a user involves identifying a condition of the user that is likely to influence a response to the fluid in the body of the user and classifying the condition as a first type of a plurality of types of conditions. After classifying the condition as the first type, the method continues by adjusting control information for operating the infusion device based on the first type and operating the infusion device to deliver the fluid to the user in accordance with the adjusted control information.

Automatic closed-loop control adjustments and infusion systems incorporating same

A method of measuring blood glucose of a patient is presented here. In accordance with certain embodiments, the method applies a constant voltage potential to a glucose sensor and obtains a constant potential sensor current from the glucose sensor, wherein the constant potential sensor current is generated in response to applying the constant voltage potential to the glucose sensor. The method continues by performing an electrochemical impedance spectroscopy (EIS) procedure for the glucose sensor to obtain EIS output measurements. The method also performs a nonlinear mapping operation on the constant potential sensor current and the EIS output measurements to generate a blood glucose value.

Nonlinear mapping technique for a physiological characteristic sensor

An electronic controller for an insulin infusion device includes at least one processor device and at least one memory element that cooperate to provide a processor-implemented closed-loop initiation module. The initiation module is operated to obtain a most recent calibration factor for a continuous glucose sensor, the most recent calibration factor representing a first conversion value applicable to convert a first sensor value to a first blood glucose value. The initiation module also obtains a prior calibration factor for the sensor, and calibration timestamp data for the most recent calibration factor and the prior calibration factor. The initiation module regulates entry into a closed-loop operating mode of the insulin infusion device, based on the most recent calibration factor, the prior calibration factor, and the calibration timestamp data.

Regulating entry into a closed-loop operating mode of an insulin infusion system

Systems and methods are provided for updating medical devices. An exemplary system includes a medical device and a remote device. The medical device is operable to regulate a condition of a user. The remote device receives measurement data correlative to the condition of the user, determines control information for the medical device based at least in part on the measurement data, and transmits the control information via a first peer-to-peer communication session. The medical device receives the control information via a second peer-to-peer communication session and thereafter regulates the condition of the user based at least in part on the control information and subsequent measurement data.

Systems and methods for updating medical devices

A controller for an insulin infusion device includes at least one processor device and at least one memory element that cooperate to provide a processor-implemented closed-loop start-up module. The start-up module is operated to initiate a closed-loop mode of the infusion device and to obtain a most recent sensor glucose value for the user. The start-up module also calculates a difference between the most recent sensor glucose value and a target glucose setpoint value. When the difference is less than or equal to a threshold value, the closed-loop insulin infusion rate is adjusted over time, based on a fixed final target glucose value that is derived from the target glucose setpoint value. When the difference is greater than the threshold, the infusion rate is adjusted over time, based on a dynamic final target glucose value that decreases over time toward the target glucose setpoint value.

Generation of target glucose values for a closed-loop operating mode of an insulin infusion system

A controller for an insulin infusion device includes a processor device and a memory element that cooperate to provide a processor-implemented closed-loop insulin limit module. The insulin limit module is operated to obtain: a fasting blood glucose value of a user; a total daily insulin value of the user; and fasting insulin delivery data that is indicative of insulin delivered to the user during a fasting period. The insulin limit module calculates a maximum insulin infusion rate for the user based on the fasting blood glucose value, the total daily insulin value, and the fasting insulin delivery data. The maximum insulin infusion rate is applicable during a period of closed-loop operation of the insulin infusion device.

Generation and application of an insulin limit for a closed-loop operating mode of an insulin infusion system

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Los Angeles, CA, United States of America

John Joseph Mastrototaro