Bigfoot Biomedical, Inc.

A system for displaying blood glucose information includes a blood glucose monitoring device configured to monitor blood glucose levels of a user, and a display. The system may also include one or more processors, and a non-transitory computer-readable medium containing instructions that, when executed by the one or more processors, cause the system to perform operations. The operations may include obtaining the blood glucose levels from the blood glucose monitoring device, where the blood glucose levels include at least a current blood glucose level and a historic blood glucose level. The operations may also include presenting the current blood glucose level at a first location on the display based on a first scale, and presenting the historic blood glucose level at a second location on the display based on a second scale different from the first scale.

The present disclosure is directed to risk management systems, devices, and methods for analyzing and identifying operational deviations of client devices, medical devices, and applications thereon. The systems and methods may receive operational data of a medical device or an application of a client device. The systems and methods may analyze the operational data to identify one or more deviations from an intended operation of the medical device or the application. The systems and methods may generate a notification indicating the one or more deviations, responsive to identifying the one or more deviations. The systems and methods may also provide the notification to one or more of the medical devices or the client device.

A variety of location-based and/or proximity-based features related to diabetes management systems can be used to improve maintenance compliance and/or to provide important information to PWD designated assistance entities (e.g., family, friends, givers, HCPs, emergency medicine providers) under certain conditions. In some cases, a user's location can be tracked or determined to trigger and/or time alerts about upcoming maintenance tasks in a way that will increase the likelihood that the PWD will immediately perform the designated maintenance task. In some cases, methods, devices, and systems provided herein can use proximity to non-paired mobile computing devices to deliver data to PWD designated assistance entities.

A variety of location-based and/or proximity-based features related to diabetes management systems can be used to improve maintenance compliance and/or to provide important information to PWD designated assistance entities (e.g., family, friends, givers, HCPs, emergency medicine providers) under certain conditions. In some cases, a user's location can be tracked or determined to trigger and/or time alerts about upcoming maintenance tasks in a way that will increase the likelihood that the PWD will immediately perform the designated maintenance task. In some cases, methods, devices, and systems provided herein can use proximity to non-paired mobile computing devices to deliver data to PWD designated assistance entities.

A variety of location-based and/or proximity-based features related to diabetes management systems can be used to improve maintenance compliance and/or to provide important information to PWD designated assistance entities (e.g., family, friends, givers, HCPs, emergency medicine providers) under certain conditions. In some cases, a user's location can be tracked or determined to trigger and/or time alerts about upcoming maintenance tasks in a way that will increase the likelihood that the PWD will immediately perform the designated maintenance task. In some cases, methods, devices, and systems provided herein can use proximity to non-paired mobile computing devices to deliver data to PWD designated assistance entities.

A personal diabetes equipment management system can include at least one diabetes treatment device adapted for use with one or more disposable diabetes devices; a remote server system including an inventory database identifying operational diabetes treatment devices and operational disposable diabetes devices in the possession of a user; and a controller in communication with (i) the at least one diabetes treatment device over a first network connection and (ii) the remote server system over a second network connection, the controller adapted to automatically detect use of the at least one diabetes treatment device and determine an operational condition for the diabetes treatment device or the one or more disposable diabetes treatment devices based on information received from the at least one diabetes treatment device over the first network connection, the controller transmitting update information to the remote server system over the second network connection to update the inventory database.

Methods of insulin delivery may include obtaining one or more blood glucose readings from a flash glucose monitor, where the blood glucose readings may be obtained in response to a user invocation of the flash glucose monitor. The method may also include generating multiple insulin delivery profiles of insulin delivery actions over multiple diurnal time segments based on the one or more blood glucose readings. The method may additionally include selecting one of the delivery profiles that is projected to approximate a target blood glucose level, and delivering insulin according to the selected delivery profile. Systems may provide such insulin delivery.

An insulin delivery and data collection system includes at least one insulin delivery device, a holding station, and control system. The holding station includes a body defining at least one cavity extending into the body from an upper surface of the body, the at least one cavity configured to receive the at least one insulin delivery device and at least one load cell disposed at a bottom of the at least one cavity. The control system includes at least one processor and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the control system to receive weight data from the at least one load cell related to the at least one insulin delivery device.

Disclosed embodiments relate, generally, to retrospective missed-bolus detection. Some embodiments relate to systems, methods, and devices for performing retrospective missed-bolus detection by processing insulin therapy data. Some embodiments relate, generally, to systems, methods and devices for training missed-bolus classifiers using machine learning techniques to perform retrospective missed-bolus detection. Some embodiments relate, generally, to systems, methods, and devices for obtaining training data and test data that may be used to train missed-bolus classifiers to perform retrospective missed-bolus detection.

A method of displaying blood glucose information may include monitoring blood glucose levels of a user, where the blood glucose levels include at least a current blood glucose level and a historic blood glucose level. The method may also include presenting the current blood glucose level using a point indicator along an approximately horizontally centered axis based on a non-linear scale, and presenting the historic blood glucose level and a predicted future blood glucose level on the display as a single smoothed curve passing the point indicator.