Sharif Razzaque

Effect of latency on presence in stressful virtual environments

Previous research has shown that even low end-to-end latency can have adverse effects on performance in virtual environments (VE). This paper reports on an experiment investigating the effect of latency on other metrics of VE effectiveness: physiological response, simulator sickness, and self-reported sense of presence. The VE used in the study includes two rooms: the first is normal and non-threatening; the second is designed to evoke a fear/stress response. Participants were assigned to either a low latency (/spl sim/50 ms) or high latency (/spl sim/90 ms) group. Participants in the low latency condition had a higher self-reported sense of presence and a statistically higher change in heart rate between the two rooms than did those in the high latency condition. There were no significant relationships between latency and simulator sickness.

Tactile virtual buttons for mobile devices

This paper presents a technique to add the tactile cues of real buttons to virtual buttons displayed on mobile devices with touch screens. When the users finger is on the display, tactile feedback coveys a feeling of button location and activation. We describe two implementations of the technique, using a personal digital assistant (PDA) and a pressure sensitive tablet.

Localizing target structures in ultrasound video – A phantom study

The problem of localizing specific anatomic structures using ultrasound (US) video is considered. This involves automatically determining when an US probe is acquiring images of a previously defined object of interest, during the course of an US examination. Localization using US is motivated by the increased availability of portable, low-cost US probes, which inspire applications where inexperienced personnel and even first-time users acquire US data that is then sent to experts for further assessment. This process is of particular interest for routine examinations in underserved populations as well as for patient triage after natural disasters and large-scale accidents, where experts may be in short supply. The proposed localization approach is motivated by research in the area of dynamic texture analysis and leverages several recent advances in the field of activity recognition. For evaluation, we introduce an annotated and publicly available database of US video, acquired on three phantoms. Several experiments reveal the challenges of applying video analysis approaches to US images and demonstrate that good localization performance is possible with the proposed solution.

MACBETH: The avatar which I see before me and its movement toward my hand

When a virtual environment system prevents a users avatar hand from penetrating virtual objects, the seen and felt positions of the hand separate. We propose a new method for reducing this position discrepancy as quickly as possible without introducing perceptible discrepancy between the seen and felt motion of the users hand. We performed a user study to compare this new method to two previous methods of dealing with position discrepancy. Our method showed statistically significant improvements in user-reported naturalness and user preference and showed no loss in user performance

Physiological reaction and presence in stressful virtual environments

A common metric of VE quality is presence --- the degree to which the user feels like they are in the virtual scene as opposed to the real world. Presence is important for many VE applications [Hodges et al. 1994]. Since presence is a subjective condition, it is most commonly measured by self-reporting, either during the VE experience or immediately afterwards by questionnaires. There is vigorous debate in the literature as to how to best measure presence [Meehan 2001].

Recognition in Ultrasound Videos: Where Am I?

A novel approach to the problem of locating and recognizing anatomical structures of interest in ultrasound (US) video is proposed. While addressing this challenge may be beneficial to US examinations in general, it is particularly useful in situations where portable US probes are used by less experienced personnel. The proposed solution is based on the hypothesis that, rather than their appearance in a single image, anatomical structures are most distinctively characterized by the variation of their appearance as the transducer moves. By drawing on recent advances in the non-linear modeling of video appearance and motion, using an extension of dynamic textures, successful location and recognition is demonstrated on two phantoms. We further analyze computational demands and preliminarily explore insensitivity to anatomic variations.

Variability sensitivity of dynamic texture based recognition in clinical CT data

Dynamic texture recognition using a database of template models has recently shown promising results for the task of localizing anatomical structures in Ultrasound video. In order to understand its clinical value, it is imperative to study the sensitivity with respect to inter-patient variability as well as sensitivity to acquisition parameters such as Ultrasound probe angle. Fully addressing patient and acquisition variability issues, however, would require a large database of clinical Ultrasound from many patients, acquired in a multitude of controlled conditions, e.g., using a tracked transducer. Since such data is not readily attainable, we advocate an alternative evaluation strategy using abdominal CT data as a surrogate. In this paper, we describe how to replicate Ultrasound variabilities by extracting subvolumes from CT and interpreting the image material as an ordered sequence of video frames. Utilizing this technique, and based on a database of abdominal CT from 45 patients, we report recognition results on an organ (kidney) recognition task, where we try to discriminate kidney subvolumes/videos from a collection of randomly sampled negative instances. We demonstrate that (1) dynamic texture recognition is relatively insensitive to inter-patient variation while (2) viewing angle variability needs to be accounted for in the template database. Since naively extending the template database to counteract variability issues can lead to impractical database sizes, we propose an alternative strategy based on automated identification of a small set of representative models.