System and method to predict performance on structured physical activity using wearable sensors

An analysis system comprising:

• a processor;
• and
• a memory having instructions stored thereon, wherein execution of the instructions by the processor causes the processor to:
• receive, by a processor, signals from a wearable sensor device worn by a user during an activity, wherein the activity is defined by the user moving through a plurality of geographic checkpoints at a first location, including a first checkpoint and a second checkpoint;
• and
• determine, via one or more trained AI models or a model derived therefrom, an estimated TTC determined at a given segment of the activity as the user in moving a distance from a start position to a position in the given segment through the plurality of geographic checkpoints as defined by the segments, wherein each respective trained AI model of the one or more trained AI models was trained on one or more physiological signals for a set of users moving through a set of geographic checkpoints up and including to the segment, wherein the one or more trained ML models are trained on one or more physiological signals for a set of users moving through a set of geographic checkpoints corresponding to the segment,
• wherein the estimated time-to-completion of the activity or an estimated complete time derived therefrom is outputted to be displayed at the wearable sensor device or an external remote device.

A non-transitory computer-readable medium having instructions stored thereon, wherein execution of the instructions by a processor causes the processor to:

• receive, by a processor, signals from a wearable sensor device worn by a user during an activity, wherein the activity is defined by the user moving through a plurality of geographic checkpoints at a first location, including a first checkpoint and a second checkpoint;
• and
• determine, via one or more trained AI models or a model derived therefrom, an estimated TTC determined at a given segment of the activity as the user in moving a distance from a start position to a position in the given segment through the plurality of geographic checkpoints as defined by the segments, wherein each respective trained AI model of the one or more trained ML models was trained on one or more physiological signals for a set of users moving through a set of geographic checkpoints up and including to the segment,
• wherein the estimated time-to-completion of the activity or an estimated complete time derived therefrom is outputted to be displayed at the wearable sensor device or an external remote device.