Johns Hopkins University

Dale E Olsen

John C Harris

Ronald Peter Lesser

John A Cristion

W Robert Webber

A computer based training tool and method that emulates human behavior using a computer-simulated person in a realistic scenario. It provides an interactive experience in detecting deception during interviews and acceptance of statements during interpersonal conversations. The simulated person provides verbal responses in combination with an animated video display reflecting the body language of the simulated person in response to questions asked and during and after responses to the questions. The questions and responses are pre-programmed and interrelated groups of questions and responses are maintained in dynamic tables which are constantly adjusted as a function of questions asked and responses generated. The system provides a critique and numerical score for each training session.

Apparatus and method for training using a human interaction simulator

A polygraph automated scoring system in which polygraph signals are input and a probability of deception is output. To begin the process, digitized polygraph signals are transformed into more fundamental signals. These fundamental signals are then subjected to standardization, a critical step. The standardized signals then have certain features extracted at each question. The features for all of the relevant questions are then standardized against the features for all of the control questions. From each of the resulting standardized relevant features, the 80th percentile is taken. Finally, a logistic regression model (logit) converts this set of 80th percentile features into a probability of deception.

Polygraph automated scoring systems

A patient monitoring system and a method of operating same, including automatically detecting a seizure in the patient, by detecting an electrical discharge in the patient's brain; converting the detected electrical discharge into a digital signal; inputting the digital signal into a microprocessor; detecting a seizure by dividing the digital signals into time segments, preprocessing each time segment including standardizing the signal, reducing the signal in each time segment to a feature, the feature providing information about whether a seizure is occurring using the feature from each time segment; and indicating that a seizure is occurring.

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Columbia, MD, United States of America

Dale E Olsen