Verily Life Sciences LLC

Miguel Angelo Drumond

Nikhil Roy

William James Biederman

Aaron Haywood Stoertz

Cara Leggett Silver

A computer-implemented method improves efficacy of diabetes self-management to obtain a measurement message and/or contextual activity information used to determine a suitable insulin dosage to treat a patient. The method includes simulating a health coach in a natural conversation to obtain a measurement of the patient's blood-glucose level, processing the measured blood-glucose level with a personalized insulin titration algorithm to determine an insulin dosage recommendation, and generating an electronic signal configured to cause a corresponding action to be performed by a computing device.

Virtual health coach for facilitating dynamic dosage titration

Virtual health coach based insulin titration platform

The disclosed embodiments include a computer-implemented method for improving efficacy of diabetes self-management with automated personalized computer engagement that reliably obtains a measurement message and/or contextual information used to determine a suitable insulin dosage of an insulin titration process to treat the diabetic patient. The method includes causing display of a messaging interface that couples the user of the computing device to a chat bot simulating a health coach in a natural conversation to obtain a measurement of the diabetic patient's blood-glucose level. The method includes determining an insulin dosage recommendation to treat the diabetic patient by processing the measured blood-glucose level with an insulin titration algorithm that is personalized for the diabetic patient, and generating an electronic signal configured to cause a corresponding action to be performed by a computing device (e.g., display message of recommended insulin dosage).

Introduced here are techniques for developing personalized retroactive insights into how contextual factors can affect glycemic responses. The personalized retroactive insights can be made available to the corresponding individual so that they can examine the impact certain contextual events have had on blood glucose level. A contextual event represents an activity or a circumstance that is related to glycemic response. Rather than state the absolute amount of certain molecules (e.g., carbohydrates, protein, or fat) in a foodstuff, an insight detection platform can instead interpret disparate data types to discover the effect certain contextual events have on blood glucose level.

Glycemic response insight detection

Example disposable biosensor devices having an activity sensor are disclosed. One example device includes a disposable biosensor that has a first electrode having a distal end to be inserted into a subcutaneous layer beneath a person's skin, the first electrode having a reactive material disposed on the distal end, and a second electrode. The disposable biosensor device also includes an activity sensor that can be activated upon an activity by the person, the activity sensor for detecting the activity and providing data about the activity. The disposable biosensor also includes a radio frequency transmitter for transmitting data obtained from the first or second electrode and the activity sensor.

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Oakland, CA, United States of America

Miguel Angelo Drumond