Abstract: A computer-implemented method and system can include obtaining, by at least one processor, at least one visual input comprising a face of at least one person. The at least one processor can input the at least one visual input into at least one psychodiagnostic neural network (PNN) to obtain at least one personality metric of the at least one person. The at least one personality metric of the at least one person can include at least one personality dimension and at least one numerical personality score. The at least one numerical personality score may provide a numerical indication of the strength of a particular personality dimension and display at least one personality report on at least one screen of at least one computing device. The at least one personality report may include the at least one personality metric of the at least one person.

Abstract: Some embodiments of a computer-implemented method and system can entail continuously obtaining a visual input comprising a plurality of representations of at least one eye of at least one user to continuously track the plurality of representations over a predetermined time duration. The at least one processor can continually apply at least one eye-gaze movement tracking (EGMT) algorithm to form a time series of eye-gaze vectors. Continually inputting the time series of eye-gaze vectors into an Activity Tracking Neural Network (ATNN) can determine an attentiveness level of the at least one user over the predetermined time duration. The at least one processor can initiate a first action when the attentiveness level is equal to or above a predetermined threshold attentiveness value throughout the predetermined time duration; and initiate a second action when the attentiveness level is below the predetermined threshold attentiveness value throughout the predetermined time duration.

Abstract: A computer-implemented method and system that entails a continuous tracking of a plurality of representations over a predetermined time duration. The method and system also entails a continuous application of at least one eye-gaze movement tracking (EGMT) algorithm to the visual input to form a time series of eye-gaze vectors and a continuous continuously input of the time series of eye-gaze vectors into an Activity Tracking Neural Network (ATNN). The ATNN classifies at least one activity of the at least one user over the predetermined time duration and outputs a measure of the at least one user's engagement with the classified activity.

Abstract: Some embodiments of a computer-implemented method and system can entail continuously obtaining a visual input comprising a plurality of representations of at least one eye of at least one user to continuously track the plurality of representations over a predetermined time duration. The at least one processor can continually apply at least one eye-gaze movement tracking (EGMT) algorithm to form a time series of eye-gaze vectors. Continually inputting the time series of eye-gaze vectors into an Activity Tracking Neural Network (ATNN) can determine an attentiveness level of the at least one user over the predetermined time duration. The at least one processor can initiate a first action when the attentiveness level is equal to or above a predetermined threshold attentiveness value throughout the predetermined time duration; and initiate a second action when the attentiveness level is below the predetermined threshold attentiveness value throughout the predetermined time duration.