Latest Publications
Rizzo A, Newman B, Parsons T, Reger G, Difede J, Rothbaum B.O, Mclay R.N, Holloway K, Graap K, Newman B, Spitalnick J, Bordnick P, Johnston S, & Gahm G.
IEEE Explore: Virtual Rehabilitation 2009
(Haifa, Israel, 06/29/2009)
Read Abstract »
Post Traumatic Stress Disorder (PTSD) is reported to be caused by exposure to an extreme traumatic stressor involving direct personal experience of (or witnessing/learning about) an event that involves actual or threatened death or serious injury, or other threat to one’s physical integrity including (but not limited to) military combat, violent personal assault, being kidnapped or taken hostage and terrorist attacks. Such incidents would be distressing to almost anyone, and are usually experienced with intense fear, horror, and helplessness. Initial data suggests that at least 1 out of 5 Iraq War veterans are exhibiting symptoms of depression, anxiety and PTSD. Virtual Reality (VR) delivered exposure therapy for PTSD has been previously used with reports of positive outcomes. The current paper will present the rationale and description of a VR PTSD therapy application (Virtual Iraq/Afghanistan) and present initial findings from a number of early studies of its use with active duty service members. Virtual Iraq/Afghanistan consists of a series of customizable virtual scenarios designed to represent relevant Middle Eastern VR contexts for exposure therapy, including a city and desert road convoy environment. User-centered design feedback needed to iteratively evolve the system was gathered from returning Iraq War veterans in the USA and from a system deployed in Iraq and tested by an Army Combat Stress Control Team. Results from an open clinical trial using Virtual Iraq with 20 treatment completers indicated that 16 no longer met PTSD diagnostic criteria at post-treatment, with only one not maintaining treatment gains at 3 month follow-up.
Morency L-P.
26th Army Science Conference
(Orlando, FL, 12/4/2008)
Read Abstract »
Accurately estimating the person’s head position and orientation is an important task for a wide range of applications such as driver awareness and human-robot interaction. Over the past two decades, many approaches have been suggested to solve this problem, each with its own advantages and disadvantages. In this paper, we present a probabilistic framework called Monocular Adaptive View-based Appearance Model (MAVAM) which integrates the advantages from two of these approaches: (1) the relative precision and user-independence of differential registration, and (2) the robustness and bounded drift of keyframe tracking. In our experiments, we show how the MAVAM model can be used to estimate head position and orientation in real-time using a simple monocular camera. Our experiments on two previously published datasets show that the MAVAM framework can accurately track for a long period of time (>2 minutes) with an average accuracy of 3.9 degrees and 1.2in with an inertial sensor and a 3D magnetic sensor.
von der Pütten A, Gratch J, Kang S-H, and Krämer N.
Proceedings of the 6th Conference of the Media Psychology Division of the German Psychological Society
(University Duisburg-Essen, Germany, 9/5/2009)
Read Abstract »
According to the Threshold Model of Social Influence (Blascovich et al., 2002) the social influence of real persons will always be high, whereas the influence of an artificial entity depends on the realism of its behavior. Contrariwise, the Ethopeia concept (Nass & Moon, 2000) predicts that automatic social reactions are triggered by situations as soon as they include social cues. The presented study evaluates whether the participants’ belief in interacting with either an avatar (a virtual representation of a human) or an agent (autonomous virtual person) lead to different social effects.
