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US 2026/0191480 A1Published application
Micro AI Fitness Monitoring System and Method
AssigneeTodd Martin
InventorsTodd Martin, Ping Zhang
Life of this patent
Estimating the term…
Abstract
A system 300 and method for biologically monitoring the fitness of an athlete, and providing a warning 338 when an overtraining condition is determined in order to reduce injury. Through implementation of an efficient system architecture, micro-artificial intelligence use is practical for mobile situations where internet coverage is deficient or non-existent.
Claims20
A system for monitoring the fitness of a user, comprising:
- a wearable fitness device including:
- a form factor configured to be worn around an area other than a wrist of a user;
- a heart rate sensor including a light emitter configured to detect a pulse of the user;
- a movement sensor;
- a temperature sensor;
- a peer-to-peer communications transceiver;
- a memory configured to retain current data that is updatable as the user is exercising;
- and
- a local artificial intelligence processor and memory configuration including:
- a comprehensive memory including:
- a latent memory configured to retain latent data including non-individual data not specific to the user, said non-individual data including general historical user data, and including personal data particular to the user, said latent memory being periodically updatable defined by when the local artificial intelligence processor and memory configuration has an active internet connection;
- a current memory configured to retain current data from said wearable device that is updatable as the user is exercising, irrespective of any active internet connection;
- and
- a microprocessor including an artificial intelligence classifier, said microprocessor being configured to:
- determine a user’s biological training condition based on an output of the classifier utilizing data only in said comprehensive memory irrespective of any internet connection;
- determine user movement type based on output from said movement sensor;
- calculate a user sleep score based heart rate data from said heart rate sensor;
- and
- provide a negative fitness indication to the user after determining that the negative fitness condition exists according to the output of the artificial intelligence classifier.
16 more elements
A system for monitoring the fitness of a user, comprising:
- a wearable fitness device including:
- a form factor configured to be worn around an area other than a wrist of a user;
- a heart rate sensor including a light emitter configured to detect a pulse of the user;
- a movement sensor;
- a memory configured to retain current data that is updatable as the user is exercising, said wearable fitness device being configured to communicate with another device using only a Bluetooth communications protocol;
- and
- a local artificial intelligence processor and memory configuration including:
- a comprehensive memory including:
- a latent memory configured to retain latent data including non-individual data not specific to the user, said non-individual data including general historical user data, and including personal data particular to the user, said latent memory being periodically updatable defined by when the local artificial intelligence processor and memory configuration has an active internet connection;
- a current memory configured to retain current data from said wearable device that is updatable as the user is exercising, irrespective of any active internet connection;
- and
- a microprocessor including an artificial intelligence classifier, said microprocessor being configured to:
- determine a user’s biological training condition based on an output of the classifier utilizing data only in said comprehensive memory irrespective of any internet connection;
- determine user movement type based on output from said movement sensor;
- calculate a user sleep score based heart rate data from said heart rate sensor;
- and
- provide a negative fitness indication to the user after determining that the negative fitness condition exists according to the output of the artificial intelligence classifier.
14 more elements
Dependencies are inferred from the claim text.