System for generating product recommendations using biometric data

A method for recommending a product to a subject, comprising:

• obtaining biometric data in the form of event-related potential of a subject as electroencephalograph (EEG) signals generated by a plurality of EEG electrodes based on exposure to an olfactory stimulus;
• processing the EEG signals to generate EEG data;
• and
• generating a product recommendation based at least on the EEG data, wherein the product recommendation is generated by a recommendation engine that includes a machine learning model trained on a set of supervised training data comprising images of electroencephalographs or brain activity maps of subjects exposed to known fragrances.

A non-transitory computer-readable medium having stored thereon instructions configured to cause a computer system to perform steps comprising:

• obtaining biometric data in the form of event-related potential of a subject as electroencephalograph (EEG) signals generated by a plurality of EEG electrodes based on exposure to an olfactory stimulus;
• processing the EEG signals to generate EEG data;
• and
• generating a product recommendation based at least on the EEG data, wherein the product recommendation is generated by a recommendation engine that includes a machine learning model trained on a set of supervised training data comprising images of electroencephalographs or brain activity maps of subjects exposed to known fragrances,
• wherein the EEG electrodes are positioned at a front left (F7) lobe and front right (F8) lobe of the subject and are configured to detect brain activity associated with approach and avoidance responsive to the exposure to the olfactory stimulus.