GlucoGlance does not replace your CGM, insulin pump, or diabetes application. It brings information from the diabetes apps you already use into one place and uses that information to provide additional displays, calculations, alerts, and predictive or reactive support.
How Does GlucoGlance Know?
Depending on the source application, GlucoGlance obtains information in one of three ways:
Notification Reader
Some diabetes applications provide glucose, insulin, status, and timing information through Android notifications.
For supported apps, GlucoGlance reads those notifications and extracts the specific data needed for glucose display, insulin calculations, status tracking, and related alerts.
Poller
Some services provide information that GlucoGlance can periodically retrieve.
For example, FreeStyle Libre Phone Owner glucose data can be obtained through LibreLinkUp cloud polling.
GlucoGlance periodically requests the latest available information and updates the app when new data is available.
Receiver
Some Companion applications can broadcast glucose or other diabetes information directly on the phone.
GlucoGlance listens for supported broadcasts and receives that data locally without needing to read a notification or poll a cloud service.
Glucose Is Only Part of the Picture
When insulin information is available, GlucoGlance uses Insulin on Board (IOB) and its timestamp as the foundation for its insulin calculations.
GlucoGlance then combines that information with the Phone Owner’s insulin settings, including settings such as:
- Insulin Action Duration
- Correction Factor
- Carb Ratio
- Target Glucose
- Basal information when available
These settings allow GlucoGlance to interpret the insulin information in the context of the individual user.
Building More From IOB
GlucoGlance can receive Insulin on Board (IOB) from two supported sources: Gluroo and Omnipod 5.
Gluroo can provide glucose, IOB, and COB directly through its notifications.
Omnipod 5 only provides IOB. GlucoGlance uses the IOB value and its timestamp, together with glucose data and the Phone Owner’s insulin settings, to derive additional insulin-related information.
For GlucoGlance to provide meaningful reactive and predictive notifications, the user must enter the same insulin settings used for their diabetes management, including:
- Target Glucose
- Carb Ratio (CR)
- Correction Factor (CF)
- Basal settings
- Insulin decay / action duration
Using the IOB value, timestamp, glucose data, and these user-entered settings, GlucoGlance can estimate or reconstruct information such as:
- Bolus activity
- Last Bolus
- Carbohydrates on Board (COB)
- Insulin trends
- Excess insulin
- Excess carbohydrates
These derived values provide the foundation for GlucoGlance’s reactive and predictive support.
Predictive and Reactive Support
GlucoGlance is designed to do more than display four numbers from another diabetes application.
By combining glucose, insulin, timing, and the user’s individual settings, GlucoGlance can evaluate what has already happened and what may be developing.
Reactive support looks at the current glucose and insulin state and identifies conditions that may need attention.
- Excess Carbs
GlucoGlance determines that available insulin may not be sufficient for the current glucose situation. It can surface that state through notifications and complications, effectively providing a recommended bolus based on the user’s insulin settings and live data. - Excess Insulin
The inverse condition. GlucoGlance determines that there may be more active insulin than needed for the current glucose situation and surfaces that state through the same types of alerts and displays.
Predictive support extends beyond glucose and insulin alone. GlucoGlance’s Predictive Metabolic Variance Modeling combines glucose, IOB, user insulin settings, and wearable sensor data such as heart rate, resting heart rate, HRV, steps, activity, and other physiological signals to help identify non-insulin factors that may be affecting glucose. The goal is to distinguish expected insulin-driven changes from metabolic variance caused by factors such as exercise, stress, or possible infusion-site performance.
For more detail, see Predictive Modeling in GlucoGlance
One App, Multiple Sources
Different diabetes applications expose their information in different ways.
GlucoGlance handles those differences behind the scenes so the user does not need to understand whether their data came from a:
Notification Reader, Poller, or Receiver.
The user selects their diabetes applications, and GlucoGlance determines how to obtain and use the supported information.