EyeDetect uses a statistical method to analyze independent ocular data. The data is gathered and tracked by an infrared camera that observes changes in eye behavior during a question & answer session with an examinee. The test is administered by a computer. Resulting from the analysis of the examinee’s responses and the ocular data, a “binary” outcome is derived called the Converus Credibility Score.
Some of the independent variables used by EyeDetect are pupil dilation, response accuracy, response time, gaze fixation, blink rates, reading behavior and other variables. The object of this logistic regression analysis of various independent variables is to obtain a biologically reasonable answer to describe the binary (two) characteristics in question: credibility or deception.
The score used by EyeDetect intends to “maximize the likelihood” of the categorization of deception or credibility. When a person obtains a Converus Credibility Score between 1 and 49, they are categorized as deceptive. When a person obtains a score between 50 and 99, they are categorized as credible. And because EyeDetect uses a statistical formula, there is a range of credibility scores. The closer the Credibility score is to 1, the likelihood of deception is maximized. Conversely, the closer the score is to 99, the likelihood of credibility is maximized. Thus, if a person obtains a Converus Credibility Score of 51, 52, 53, etc., the probability of credibility is minimal.