Cadence spectra for health and fitness promotion

A method, comprising:

• for each of a plurality of contiguous time intervals spanning a first period of time:
• receiving, via a network, sensor-based real-time user-motion information from a sensor and that corresponds to motion of the user during a time interval within the first period of time;
• determining a time series, wherein the time series is based on the sensor-based real-time user-motion information received during the time interval and based on user-motion information received during previously occurring time intervals within the first period of time;
• determining a level of variability of activity based on the time series;
• specifying a target threshold of activity variability;
• comparing the target threshold to the level of variability of activity for the time interval;
• based on the comparison, determining that the level of variability of activity for the time interval is less than the target threshold;
• responsive to the level of variability of activity for the time interval being less than the target threshold, generating a pseudorandom value;
• and
• based on the generated pseudorandom value, generating an activity reminder associated with the comparison for presentation by way of a user interface on a user device.

A system, comprising:

• one or more motion sensors that measure motion of a user;
• a computing device communicatively coupled through a network to the one or more motion sensors, the computing device comprising one or more processors that execute computer-usable instructions that implement operations comprising:
• receive from the one or more motion sensors, via the network, user-motion information as a measurement of user motion over a time interval for each of a plurality of time intervals spanning a first time period;
• for a first time interval, determine a first time series based on the user-motion information received during the first time interval and user-motion information received during each time interval of a subset of the plurality of time intervals, the subset of the plurality of time intervals occurring within the first time period and before the first time interval;
• determine a first level of variability of activity based on the first time series for the first time interval;
• specify a target threshold of activity variability;
• compare, in a first comparison, the target threshold to the first level of variability;
• based at least on the first level of variability being less than the target threshold, generate a pseudorandom value;
• and
• based on the generated pseudorandom value, generate an activity reminder associated with the first level of variability for presentation by way of a user interface on the computing device.