There is provided herein a computer implemented method for identifying if a subject is being deceptive, the method comprising: exposing a subject to a stimuli sequence and to a visual task; receiving from one or more sensors temporal data, indicative of the dynamics of at least one eye of a subject, wherein the received data comprises responsive and non-responsive data, the responsive data is responsive to the visual task; synchronizing the stimuli sequence with the received temporal data; analyzing the temporal data, which is indicative of the dynamics of the at least one eye of a subject; determining a probability of the subject being deceptive based on the analysis; and producing an output signal indicative of the probability of the subject being deceptive.

A device and method of observing mental condition of a user by interacting with an improved swatch of chain mail mesh that comprises interconnecting, polygonal plastic links suitably interconnected to define a sheet having each of the interconnecting, polygonal links having at least one degree of freedom of movement in at least one direction with respect to its neighbouring polygonal links wherein each of the interconnecting, polygonal links, interconnected to at least one neighbouring interconnecting polygonal link, combine to form an operative upper surface and an operative lower surface of the sheet, and wherein at least a portion of at least one of the operative upper surface and the operative lower surface of the sheet generally feels generally smooth with gaps, which produce a calming or pleasing effect when contacted with or moved over, or combinedly contacted with and moved over a human's body portion which being apt to sense of touch. The sheet has a predetermined drape coefficient, nonlinear motion, and is capable of providing relief in stress or pleasure when a human employs the same. The device is a fidget toy, and when used during observation a diagnosis and a therapy tool.

Systems and methods for detecting deceptive intent of a subject include observing eye movements of the subject and correlating the observed movements to known baseline neurophysiological indicators of deception. A detection system may record eye movement data from the subject, compare the eye movement data to a data model comprising threshold eye movement data samples, and from the comparison make a determination whether or not the subject is lying. The detection system may create an alert if deception is detected. The eye movements detected include saccadic and intersaccadic parameters such as intersaccadic drift velocity. Measurements may be collected in situ with a field testing device, such as a non-invasive, non-contact device attached to the subject's computing device and configured to non-obtrusively record the eye movement data.

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.

Deception can be evaluated by presenting a set of sentences or words to a testee, including some sentences or words that are expected to evoke significant pupil dilation in a testee who is lying and other sentences or words that are not expected to evoke significant pupil dilation in the testee. Changes in the testee's pupil size are compared to ascertain whether a pupil-dilation response to certain sentences or words is larger than for other sentences or words, and an indication of deceptiveness or non-deceptiveness is output based on the results of the ascertaining.

Deception can be evaluated by presenting a set of sentences or words to a testee, including some sentences or words that are expected to evoke significant pupil dilation in a testee who is lying and other sentences or words that are not expected to evoke significant pupil dilation in the testee. Changes in the testee's pupil size are compared to ascertain whether a pupil-dilation response to certain sentences or words is larger than for other sentences or words, and an indication of deceptiveness or non-deceptiveness is output based on the results of the ascertaining.

Sensor data of a subject is received, wherein the sensor data includes eye tracking data and visible light image data. Using one or more processors, the sensor data is automatically analyzed to determine one or more metrics. Using the one or more metrics, an indicator associated with a likelihood the subject is being deceptive is determined.

A terminal is used to obtain authentication information associated with user input information. The terminal measures a set of values of biometric properties of behavior of a person at the terminal, using one or more biometric behavior sensors of the terminal. An indication of a time interval is provided from which the set of values has to be used for obtaining the authentication information for the user input information. Parameters of a biometric of behavior template are read from a user domain storage device, such as a smartphone, to which access is enabled only under control of the person. The parameters define a predetermined class of sets of values of biometric properties that have been determined to occur for the person when the person is in a predetermined type of mental state, or a computation for computing a score value from the set of values that the set of measured values belongs to said class. The parameters are used in the terminal to determine whether or not the set of values in said time interval are within the predetermined class, and/or to compute a score value that the set of values in the time interval belongs to said class, or the terminal may cause a computing device associated with the user domain storage device to do so.

A health status recording and reporting system includes a digital framework that includes a pattern recognition module configured to record and report a health status of a user. The framework includes a digitally recorded library of self-reported human emotions, unconscious agendas and disease conditions of a control group of users selected from a population of users, a digitally recorded set of rules, and a digitally recorded user profile of the user. The system also includes sensors communicably connected to the framework and to the user during a question-answer session with a therapist. The framework is configured to integrate inputs from the library, the rules, the user profile, and sensors, validate an accuracy of the user's response to the plurality of questions posed by the therapist, map and predict a disease condition, and display and report the predicted disease condition of the user on a visible report or a printable report.

A health status validating system is disclosed. The system includes a digital framework including a pattern recognition module configured to measure and validate a change in a health status of a user. The digital framework includes (1) a first digitally recorded library of (i) human emotions, (ii) unconscious agendas, and (iii) physical and mental disease conditions of a control group of users selected from a population of users, to correlate with the emotions, beliefs systems and reported physical or mental conditions of the user, (2) a question engine configured to (i) interrogate the user using a second digitally recorded library of predetermined questions, and (ii) identify a plurality of underlying unconscious agendas of the user that generate behavior of the user and associated negative emotions of the user.