Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.