Roche Diabetes Care, Inc.

Roche Diagnostics Operations, Inc.

Roche Diagnostics International Ag

University of Bern

Roche Diagnostics Gmbh

F. Hoffmann-la Roche Ag

Alan Greenburg

Paul J Galley

Abhishek S Soni

Stefan Weinert

Steven Bousamra

David L Duke

John F Price

Richard W Wilson

Marshall M Parker

Morris J Young

Christian Ringemann

Karl Werner

Robin S Wagner

Chinmay Uday Manohar

Nader Afshar

Daniel ManHung Wong

Eric R Diebold

Robert E Reinke

Ulrich Porsch

David Bradley Markisohn

Juergen Rasch-Menges

Jason Bush

David A Hasker

Marco De Polo

Maury Zivitz

Schuyler S Buck

P Douglas Walling

Glenn Brassington

Igor Gejdos

Ajay Thukral

Kristin Davenport

Bernhard Teupe

Robert Hellwig

Leon R Organ, Iii

Stavroula Mougiakakou

Gilles Prod'hom

Erica Diebold

Marios Anthimpoulos

Ildiko Amann-Zalan

Brittany A Dressler

Anthony J Butt

Gilles Prodhom

Joachim Dehais

Sergey Shevchick

Erica Rose Diebold

Erica R Diebold

David Hasker

James Long

John Price

Schuyler Buck

Leon R Iii Organ

A method is described herein to detect and treat hypoglycemia. An example of this method involves the detection of hypoglycemia in a patient with a computing device, computation of a recommended carbohydrate amount to ingest by the patient with the computing device in response to said detecting the hypoglycemia, output of the recommended carbohydrate amount with the computing device, and the performance of a hypoglycemia surveillance with the computing device to determine whether the recommended carbohydrate amount remedied the hypoglycemia.

Method for the detection and handling of hypoglycemia

According to some embodiments of the present disclosure, a device and method for determining an allowable amount of blood glucose (bG) of a patient is disclosed. The method further includes receiving a current bG measurement, determining a target bG value, and determining a correction delta bG value based on one or more advice history records. The method includes determining a correction meal rise value and determining a maximum allowed bG value based on the target bG value, the correction delta bG value, and the correction meal rise value. The method includes setting the allowable amount of bG value equal to the maximum allowed bG value when the current bG measurement is greater than the target bG value and determining the allowable amount of bG value using the target bG value and the correction delta bG value when the current bG measurement is less than the target bG value.

Handheld diabetes management device with bolus calculator

Methods and systems are disclosed for treating a person with diabetes by basal rate adjustment of insulin from a therapy delivery device based on risk associated with a glucose state of the person with diabetes. A method may include determining a current risk metric associated with a detected glucose state. The method may include determining a current risk metric associated with the detected glucose state based on a weighted average of cumulative hazard values of return paths generated from a glucose state distribution around a detected glucose state. The method may include calculating an adjustment to a basal rate of a therapy delivery device based on the current risk metric associated with the detected glucose state and a reference risk metric associated with a reference glucose level.

Risk-based control-to-range blood glucose diabetes management device

Embodiments related to a self-administered, behavior modification program facilitated through a structured tailoring method and system thereof which accelerates and enhances the internalization process of the individual, and which provides help when the individual begins to fail in adhering or continuing with the behavior modification are disclosed. Program instructions that when executed by a processor causes a processor to initiate automatically a schedule of events of a structured tailoring procedure upon entry criteria being met at some unknown time, provide intervention according to the intervention preferences when the adherence criteria for one of the events has not been met, and end automatically the structured collection procedure upon exit criteria being met at some unknown time.

Structured tailoring

Embodiments related to a system and method managing the implementation, execution, data collection, data analysis and status reporting of a structured collection procedure running on a portable, hand-held collection device are disclosed. The collection device performing the structured collection procedure has program instructions that when executed by a processor cause the processor to initiate automatically a schedule of events of the structured collection procedure upon one or more entry criteria being met at some unknown time, store in memory patient data collected in accordance to the schedule of events, end automatically the structured collection procedure upon one or more exit criteria being met at some unknown time. Status reporting can be provided throughout the execution of the collection procedure.

Status reporting of a structured collection procedure

Embodiments related to a system and method managing the implementation, execution, data collection, and data analysis of a structured collection procedure running on a portable, hand-held collection device are disclosed. The collection device performing the structured collection procedure has program instructions that when executed by a processor causes the processor to initiate automatically a schedule of events of the structured collection procedure upon one or more entry criterions being met at some unknown time, store in memory patient data collected in accordance to the schedule of events, end automatically the structured collection procedure upon one or more exit criterions being met at some unknown time, and mark/indicate the structured collection procedure as completed if no exception occurred during performance of an event in the schedule of events.

Management method and system implementation, execution, data collection, and data analysis of a structured collection procedure which runs on a collection device

A portable analytical device includes a housing, a measuring facility and a processor in the housing, and an electrical connector having one end electrically connected to the processor and an opposite end operatively connectable to an external electronic device. The measuring facility is configured to analyze a change in a test element resulting from receipt thereon of a liquid sample of a body fluid and to generate measuring values resulting from the analysis. A memory has instructions stored therein executable by the processor to process the measuring values to generate analytical measuring data based thereon and to output the generated analytical measuring data onto the electrical connector. The analytical device does not include an intrinsic user interface for displaying the generated analytical measuring data. Display of the generated analytical measuring data is implemented exclusively by the external electronic device having received the generated analytical measuring data via the electrical connector.

Portable analytical device

Methods and systems are disclosed analyzing a glucose level of a person having diabetes. The method, in at least one example, comprises receiving into a computing device a plurality of measured glucose values from a continuous glucose monitoring system coupled to a person having diabetes, analyzing the plurality of measured glucose values with a probability analysis tool on the computing device to determine a glucose threshold (g), and a boundary glucose value (g) at a probability threshold where the person having diabetes requires at least a predetermined insulin dose, and comparing, with the computing device, the boundary glucose value (g) to the glucose threshold (g), wherein if the boundary glucose value (g) is greater than the glucose threshold (g) then the computing device performs an alert on a user interface.

Methods and systems for analyzing glucose data measured from a person having diabetes

A method and system of determining a basal rate adjustment of insulin in a continuous glucose monitoring system of a person with diabetes is provided. The method includes receiving, by at least one computing device, a signal representative of at least one glucose measurement; detecting, by the at least one computing device, a glucose state of the person based on the signal, the detected glucose state including a glucose level of the person and a rate of change of the glucose level; determining, by the at least one computing device, a current risk metric, the current risk metric indicating a risk of at least one of a hypoglycemic condition and a hyperglycemic condition of the person; and calculating, by the at least one computing device, an adjustment to a basal rate of a therapy delivery device based on the current risk metric and a control-to-range algorithm comprising at least one aggressiveness parameter.

Control-to-range aggressiveness

Methods and systems are disclosed for determining a basal rate adjustment of insulin based on risk associated with a glucose state of a person with diabetes. A method may include detecting a glucose state of the person based on a received glucose measurement signal and determining a current risk metric associated with the detected glucose state. The method may include determining a current risk metric associated with the detected glucose state based on a weighted average of cumulative hazard values of return paths generated from a glucose state distribution around a detected glucose state. The method may include calculating an adjustment to a basal rate of a therapy delivery device based on the current risk metric associated with the detected glucose state and a reference risk metric associated with a reference glucose level.

Risk-based control-to-range

There is disclosed a system for estimating the volume of food on a plate, for example meal, with a mobile device. The system uses a camera and a light pattern projector. Images of the food with and without a projected light pattern on it enable to compute the tridimensional shape and volume, while image segmentation and recognition steps estimate one or more food types in said images. By applying accessible knowledge databases, the carbs content is estimated and the associated insulin bolus doses are provided. Developments comprise coding of the light pattern, different light sources and associated wavelengths, motion compensations, additional optics, estimation of fat content and associated multi-wave boluses. The invention can be implemented in a glucometer or in an insulin pump controller provided with a test strip port or with a mobile phone.

Estimation of food volume and carbs

Growing community of inventors

Indianapolis, IN, United States of America

Alan Greenburg