System and method for determining and providing activity recommendations

A nontransitory computer-readable medium having stored thereon computer-executable instructions which, when executed by a computing processor, perform a process for determining and providing activity recommendations, the process comprising:

• receiving, from at least one glucose collection device associated with an individual, glucose level data representing a plurality of glucose level readings taken from the individual over a plurality of time periods;
• forming, from the glucose level data representing the plurality of glucose level readings, a plurality of subsamples of glucose levels data, each subsample of glucose level data comprising glucose levels data representing individual glucose levels of the plurality of glucose levels taken within a given time period,
• receiving, from an activity data source associated with the individual, activity data representing one or more activities performed by the individual, with at least one activity being received with respect to each of the time periods;
• determining, for each subsample, an average area under the curve associated with the glucose levels of the subsample;
• determining, for each subsample, a standard deviation of the glucose readings of the subsample;
• performing, for each subsample, a biotransform algorithm on each individual glucose reading of the subsample;
• determining, for each subsample, a min-max total associated with the glucose readings of the subsample;
• ranking each subsample against each other subsample, the rankings being at least partly based on the average area under the curve for each subsample, the standard deviation for each subsample, the biotransform for each subsample and the min-max total for each subsample;
• determining a highest ranked time period associated with a highest ranked subsample;
• determining one or more activities of the activity data representing one or more activities performed by the individual that were performed within the determined highest ranked time period;
• and
• recommending that the individual increase a number of instances which the one or more determined activities are performed.

A system for determining and providing activity recommendations, comprising:

• one or more computing processors;
• one or more memories operatively coupled the one or more computing processors, the one or more memories having stored therein computing processor executable instructions which when executed by the one or more computing processors perform a process for determining and providing activity recommendations comprising:
• receiving, from at least one glucose collection device associated with an individual, glucose level data representing a plurality of glucose level readings taken from the individual over a plurality of time periods;
• forming, from the glucose level data representing the plurality of glucose level readings, a plurality of subsamples of glucose levels data, each subsample of glucose level data comprising glucose levels data representing individual glucose levels of the plurality of glucose levels taken within a given time period,
• receiving, from an activity data source associated with the individual, activity data representing one or more activities performed by the individual, with at least one activity being received with respect to each of the time periods;
• determining, for each subsample, an average area under the curve associated with the glucose levels of the subsample;
• determining, for each subsample, a standard deviation of the glucose readings of the subsample;
• performing, for each subsample, a biotransform algorithm on each individual glucose reading of the subsample;
• determining, for each subsample, a min-max total associated with the glucose readings of the subsample;
• ranking each subsample against each other subsample, the rankings being at least partly based on the average area under the curve for each subsample, the standard deviation for each subsample, the biotransform for each subsample and the min-max total for each subsample;
• determining a highest ranked time period associated with a highest ranked subsample;
• determining one or more activities of the activity data representing one or more activities performed by the individual that were performed within the determined highest ranked time period;
• and
• recommending that the individual increase a number of instances which the one or more determined activities are performed.