Micro models and layered prediction models for estimating sensor glucose values and reducing sensor glucose signal blanking

A system comprising:

• one or more processors;
• and
• one or more processor-readable storage media operatively coupled with the one or more processors, the one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of operations comprising:
• receiving continuous glucose monitoring (CGM) sensor data measured by a sensor device;
• inputting the CGM sensor data into a plurality of machine learning models, wherein each machine learning model of the plurality of machine learning models is trained to predict a sensor glucose value under a respective sensor operating condition;
• determining a sensor operating condition associated with the CGM sensor data;
• determining weights of the plurality of machine learning models based on the sensor operating condition;
• determining an estimated sensor glucose value based on the weights and outputs of the plurality of machine learning models in response to the CGM sensor data;
• and
• causing displaying of the estimated sensor glucose value on a display interface, thereby reducing sensor glucose signal blanking on the display interface.

A glucose monitoring system comprising:

• a continuous glucose monitoring (CGM) sensor;
• a display interface;
• one or more processors;
• and
• one or more processor-readable storage media operatively coupled with the one or more processors, the one or more processor-readable storage media storing instructions which, when executed by the one or more processors, cause performance of operations comprising:
• receiving sensor data measured by the CGM sensor;
• inputting the sensor data into a plurality of machine learning models, wherein each machine learning model of the plurality of machine learning models is trained to predict a sensor glucose value under a different respective sensor operating condition;
• determining an estimated sensor glucose value based on weighting outputs of the plurality of machine learning models in response to the sensor data;
• and
• displaying, via the display interface, the estimated sensor glucose value, thereby reducing sensor glucose signal blanking on the display interface.