Blood glucose insight generator for driving applications
AssigneeDiabetes Innovation LLC
InventorsViralkumar N. Shah, Hal Joseph, Trevor J. Dobbertin, Emma Eikermann
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Abstract
Systems and methods are described for monitoring blood glucose when driving. The methods may include receiving blood glucose input for a user over a time period, detecting one or more driving events associated with the user over the time period, correlating the blood glucose input with the one or more driving events; determining, based on the correlation, at least one pattern indicating a blood glucose status for the user, generating, based on the blood glucose status and a repository of user data, at least one insight or trend corresponding to the user, and causing presentation of the at least one insight or trend.
Claims26
A computer-implemented method for monitoring blood glucose of a user during operation of a vehicle, the method comprising:
- receiving blood glucose input for a user over a time period;
- detecting one or more driving events associated with the user over the time period;
- correlating the blood glucose input with the one or more driving events;
- determining, based on the correlation, at least one pattern indicating a blood glucose status for the user, wherein the at least one pattern comprises at least one of:
- a temporal pattern, a threshold violation pattern, a rate-of-change pattern, or a driving-correlated pattern;
- generating, based on the blood glucose status and a repository of user data, at least one insight or trend corresponding to the user;
- and
- causing presentation of the at least one insight or trend.
A system for analyzing blood glucose while driving a vehicle, comprising:
- a computing unit comprising:
- one or more sensors;
- a processor;
- and
- memory communicably coupled to the processor, wherein the memory stores processor-executable instructions, which when executed by the processor, cause the processor to:
- receive blood glucose input for a user over a time period;
- detect one or more driving events associated with the user over the time period;
- correlate the blood glucose input with the one or more driving events;
- determine, based on the correlation, at least one pattern indicating a blood glucose status for the user;
- generate, based on the blood glucose status and a repository of user data, at least one insight or trend corresponding to the user;
- and
- cause presentation of the at least one insight or trend.
A non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
- receiving blood glucose input for a user over a time period;
- detecting one or more driving events associated with the user over the time period;
- correlating the blood glucose input with the one or more driving events;
- determining, based on the correlation, at least one pattern indicating a blood glucose status for the user, wherein the at least one pattern comprises at least one of:
- a temporal pattern, a threshold violation pattern, a rate-of-change pattern, or a driving-correlated pattern;
- generating, based on the blood glucose status and a repository of user data, at least one insight or trend corresponding to the user;
- and
- causing presentation of the at least one insight or trend.
A computer-implemented method for providing a multi-tenant blood glucose monitoring service, the method comprising:
- provisioning a tenant account for an organization within a multi-tenant platform;
- receiving, via an organization web application, configuration parameters comprising alert thresholds, user permissions, and reporting preferences for the tenant account;
- enrolling one or more users associated with the organization, wherein each user is associated with a continuous glucose monitoring device;
- receiving blood glucose data from the one or more users via tenant-specific mobile applications;
- storing the blood glucose data in a tenant-isolated database that maintains data separation between organizations;
- correlating the blood glucose data with driving events detected for each user;
- generating organizational reports comprising aggregated glucose metrics, driving safety scores, and compliance indicators;
- and
- presenting the organizational reports via the organization web application.
Dependencies are inferred from the claim text.