In an illustrative embodiment, systems and methods for automating candidate video assessments include receiving a submission from a candidate for an available position including baseline response video segments and question response video segments. The system can determine, from detected nonverbal features within the baseline response video segments, nonverbal baseline scores. For each of the interview questions, candidate response attributes can be detected including a response direction, a response speed, and nonverbal features. A nonverbal reaction score is calculated from the detected nonverbal features and the baseline scores. A response score can be calculated from the response direction and response speed, and a trustworthiness score is determined based on a correspondence between the response score and the nonverbal reaction score. A next interview question can be determined in real-time from a benchmarked version of the response score. Overall scores reflecting candidate trustworthiness can be presented within a user interface screen.

A method of providing an interactive computer-to-computer link for remote communication between a patient's computer and a therapist's computer, comprising establishing two-way audio/visual communication between said patient's computer and said therapist's computer, and incorporating an emotional recognition algorithm in said patient's computer for recognizing said patient's emotional state.

The present disclosure provides systems and methods for assessing a mental state of a subject in a single session or over multiple different sessions, using for example an automated module to present and/or formulate at least one query based in part on one or more target mental states to be assessed. The query may be configured to elicit at least one response from the subject. The query may be transmitted in an audio, visual, and/or textual format to the subject to elicit the response. Data comprising the response from the subject can be received. The data can be processed using one or more individual, joint, or fused models. One or more assessments of the mental state associated with the subject can be generated for the single session, for each of the multiple different sessions, or upon completion of one or more sessions of the multiple different sessions.

A method of deception detection based upon ocular information of a subject provides a video camera configured to record a close-up view of a subject's eye. A cognitive state model is configured to determine a high to a low cognitive load experienced by the subject. An emotional state model is configured to determine a high to a low state of arousal experienced by the subject. After asking a question, the ocular information is processed to identify changes in ocular signals of the subject. The cognitive state and emotional state models are evaluated based solely on the changes in ocular signals where a probability of the subject being either truthful or deceptive is estimated for a binary output.

A method of assessing operational risk based upon ocular information of a subject includes providing a video camera recording a close-up view of a subject's eye. The ocular information is processed to identify changes in ocular signals of the subject through the use of convolutional neural networks. Changes in ocular signals are evaluated from the convolutional neural networks by a machine learning algorithm. A duty fitness result is determined for the subject where the duty fitness result is either fit for duty, unfit for duty or more information needed. The results can then be displayed to the subject and/or to a supervisor.

A method of discovering relationships between iris physiology and cognitive states and/or emotional states of a subject includes providing a computing device and a video camera to record a close-up view of the subject's eye. A first light is held to the lower eyelid skin and a second light a distance away illuminating the stroma of the eye. The first and second light are electronically synced together and configured to flash alternatively. The user engages in a plurality of tasks while recording ocular information which is processed to identify correlations between the responses in the iris musculature and the distortions in the stroma through the use optimized algorithms. One can then identifying at least one predictive distortion is identified in the stroma capturable solely with a visible-spectrum camera correlating to a predicted responses in the iris musculature.

A method to optimize learning based upon ocular information of a subject includes providing a video camera for recording a close-up view of a subject's eye. A first electronic display shows a plurality of educational subject matter to the subject. A second electronic display shows an output to an instructor. Changes in ocular signals of the subject are processed through the use optimized algorithms. A cognitive state model determines a low to a high cognitive load experienced by the subject. The cognitive state model is evaluated based on the changes in the ocular signals for determining a probability of the low to the high cognitive load experienced by the subject. The probability of the low to the high cognitive load experienced by the subject is displayed to the instructor.

An eye tracking-based concealed information testing, which includes: presenting images of objects at certain coordinates on a computer display; operating a camera to track eye movements of a human subject observing the display; computing one or more gaze parameters for each of the objects, based on the tracked eye movements and the certain coordinates; and determining that a certain one of the objects is familiar to the human subject based on the gaze parameter. The eye tracking-based concealed information testing is optionally integrated with a short-term memory task, to enhance detection of concealed information.

Examples herein include systems for detecting cheating in card games, including bridge. The system can acquire board data for multiple events, the events including bridge games. For each event, determining performance values for a player based on the board data, wherein the performance values may additionally be based in part on timing data. The system can detect a deviation of by comparing the performance values against a threshold, wherein the threshold is based on past performance of known cheating players. Then the system can alert a user when the likelihood of cheating exceeds a threshold.

The present disclosure provides systems and methods for assessing a mental state of a subject in a single session or over multiple different sessions, using for example an automated module to present and/or formulate at least one query based in part on one or more target mental states to be assessed. The query may be configured to elicit at least one response from the subject. The query may be transmitted in an audio, visual, and/or textual format to the subject to elicit the response. Data comprising the response from the subject can be received. The data can be processed using one or more individual, joint, or fused models. One or more assessments of the mental state associated with the subject can be generated for the single session, for each of the multiple different sessions, or upon completion of one or more sessions of the multiple different sessions.