Systems and methods for facilitating customized artificial intelligence output based on user neuroperformance state

A computing system for facilitating customized artificial intelligence (AI) output for a user based on a neurostate associated with the user, the computing system comprising:

• at least one computing processor;
• and
• memory comprising instructions that, when executed by the at least one computing processor, enable the computing system to execute a method comprising:
• obtaining, by a computing device, user-device interaction data associated with interactions between the user and a user device, wherein the user-device interaction data comprises raw signal data collected from the user device;
• generating, by the computing device, a set of user-device interaction metrics from the user-device interaction data;
• generating, by the computing device, a neuroprofile based on the set of user-device interaction metrics, wherein generating the neuroprofile comprises:
• identifying a plurality of features or vectors associated with the user-device interaction metrics;
• applying a machine learning model to the plurality of features or vectors to generate a set of neuroprofile metrics, wherein the machine learning model is trained using a dataset of user-device interaction data and corresponding neuroprofile data;
• determining, based on the set of neuroprofile metrics, at least one of a motor skill metric, a cognitive skill metric, and an emotional and/or behavioral metric;
• and
• storing the neuroprofile in association with a user identifier;
• providing, by the computing device, the neuroprofile to an AI system, wherein the AI system is configured to generate a custom response based on the neuroprofile;
• and
• receiving, by the computing device, the custom response from the AI system, wherein the custom response comprises at least one of a personalized content recommendation, a targeted advertisement, or a customized user interface adaptation.

A non-transitory computer readable medium comprising instructions that when executed by a processor enable the processor to execute a method comprising:

• obtaining, by a computing device, user-device interaction data associated with interactions between the user and a user device, wherein the user-device interaction data comprises raw signal data collected from the user device;
• generating, by the computing device, a set of user-device interaction metrics from the user-device interaction data;
• generating, by the computing device, a neuroprofile based on the set of user-device interaction metrics, wherein generating the neuroprofile comprises:
• identifying a plurality of features or vectors associated with the user-device interaction metrics;
• applying a machine learning model to the plurality of features or vectors to generate a set of neuroprofile metrics, wherein the machine learning model is trained using a dataset of user-device interaction data and corresponding neuroprofile data;
• determining, based on the set of neuroprofile metrics, at least one of a motor skill metric, a cognitive skill metric, and an emotional and/or behavioral metric;
• and
• storing the neuroprofile in association with a user identifier;
• providing, by the computing device, the neuroprofile to an AI system, wherein the AI system is configured to generate a custom response based on the neuroprofile;
• and
• receiving, by the computing device, the custom response from the AI system, wherein the custom response comprises at least one of a personalized content recommendation, a targeted advertisement, or a customized user interface adaptation.