Alessandro Febretti

CAVE2: a hybrid reality environment for immersive simulation and information analysis

Hybrid Reality Environments represent a new kind of visualization spaces that blur the line between virtual environments and high resolution tiled display walls. This paper outlines the design and implementation of the CAVE2TM Hybrid Reality Environment. CAVE2 is the world’s first near-seamless flat-panel-based, surround-screen immersive system. Unique to CAVE2 is that it will enable users to simultaneously view both 2D and 3D information, providing more flexibility for mixed media applications. CAVE2 is a cylindrical system of 24 feet in diameter and 8 feet tall, and consists of 72 near-seamless, off-axisoptimized passive stereo LCD panels, creating an approximately 320 degree panoramic environment for displaying information at 37 Megapixels (in stereoscopic 3D) or 74 Megapixels in 2D and at a horizontal visual acuity of 20/20. Custom LCD panels with shifted polarizers were built so the images in the top and bottom rows of LCDs are optimized for vertical off-center viewing- allowing viewers to come closer to the displays while minimizing ghosting. CAVE2 is designed to support multiple operating modes. In the Fully Immersive mode, the entire room can be dedicated to one virtual simulation. In 2D model, the room can operate like a traditional tiled display wall enabling users to work with large numbers of documents at the same time. In the Hybrid mode, a mixture of both 2D and 3D applications can be simultaneously supported. The ability to treat immersive work spaces in this Hybrid way has never been achieved before, and leverages the special abilities of CAVE2 to enable researchers to seamlessly interact with large collections of 2D and 3D data. To realize this hybrid ability, we merged the Scalable Adaptive Graphics Environment (SAGE) - a system for supporting 2D tiled displays, with Omegalib - a virtual reality middleware supporting OpenGL, OpenSceneGraph and Vtk applications.

Visualizing Large, Heterogeneous Data in Hybrid-Reality Environments

Constructing integrative visualizations that simultaneously cater to a variety of data types is challenging. Hybrid-reality environments blur the line between virtual environments and tiled display walls. They incorporate high-resolution, stereoscopic displays, which can be used to juxtapose large, heterogeneous datasets while providing a range of naturalistic interaction schemes. They thus empower designers to construct integrative visualizations that more effectively mash up 2D, 3D, temporal, and multivariate datasets.

Usability, playability, and long-term engagement in computer games

Does usability affect long term user engagement in computer games, or are other factors more influential? This paper explores this issue, discussing an evaluation study that measured the relevance of usability versus playability factors for long-term user engagement in eight commercial games.

Omegalib: A multi-view application framework for hybrid reality display environments

In the domain of large-scale visualization instruments, hybrid reality environments (HREs) are a recent innovation that combines the best-in-class capabilities of immersive environments, with the best-in-class capabilities of ultra-high-resolution display walls. HREs create a seamless 2D/3D environment that supports both information-rich analysis as well as virtual reality simulation exploration at a resolution matching human visual acuity. Co-located research groups in HREs tend to work on a variety of tasks during a research session (sometimes in parallel), and these tasks require 2D data views, 3D views, linking between them and the ability to bring in (or hide) data quickly as needed. In this paper we present Omegalib, a software framework that facilitates application development on HREs. Omegalib is designed to support dynamic reconfigurability of the display environment, so that areas of the display can be interactively allocated to 2D or 3D workspaces as needed. Compared to existing frameworks and toolkits, Omegalib makes it possible to have multiple immersive applications running on a cluster-controlled display system, have different input sources dynamically routed to applications, and have rendering results optionally redirected to a distributed compositing manager. Omegalib supports pluggable front-ends, to simplify the integration of third-party libraries like OpenGL, OpenSceneGraph, and the Visualization Toolkit (VTK). We present examples of applications developed with Omegalib for the 74-megapixel, 72-tile CAVE2™ system, and show how a Hybrid Reality Environment proved effective in supporting work for a co-located research group in the environmental sciences.

Nurses' Numeracy and Graphical Literacy: Informing Studies of Clinical Decision Support Interfaces.

We present findings of a comparative study of numeracy and graph literacy in a representative group of 60 practicing nurses. This article focuses on a fundamental concern related to the effectiveness of numeric information displayed in various features in the electronic health record during clinical workflow. Our findings suggest the need to consider numeracy and graph literacy when presenting numerical information as well as the potential for tailoring numeric display types to an individuals cognitive strengths.

Use of Simulation to Study Nurses' Acceptance and Nonacceptance of Clinical Decision Support Suggestions.

Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record–based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse’s belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice.

A component-based evaluation protocol for clinical decision support interfaces

In this paper we present our experience in designing and applying an evaluation protocol for assessing usability of a clinical decision support (CDS) system. The protocol is based on component-based usability testing, cognitive interviewing, and a rigorous coding scheme cross-referenced to a component library. We applied this protocol to evaluate alternate designs of a CDS interface for a nursing plan of care tool. The protocol allowed us to aggregate and analyze usability data at various granularity levels, supporting both validation of existing components and providing guidance for targeted redesign.

The OmegaDesk: towards a hybrid 2D and 3D work desk

OmegaDesk is a device that allows for seamless interaction between 2D and 3D content. In order to develop this hybrid device, a new form of Operating System is needed to manage and display heterogeneous content. In this paper we address the hardware and software requirements for such a system, as well as challenges. A set of heterogeneous applications has been successfully developed on OmegaDesk. They allowed us to develop a set of guidelines to drive future investigations into 2D/3D hybridized viewing and interaction.

Toward a More Robust and Efficient Usability Testing Method of Clinical Decision Support for Nurses Derived From Nursing Electronic Health Record Data

PURPOSE To develop methods for rapid and simultaneous design, testing, and management of multiple clinical decision support (CDS) features to aid nurse decision-making. METHODS We used quota sampling, think-aloud and cognitive interviews, and deductive and inductive coding of synchronized audio video data and archival libraries. FINDINGS Our methods and organizational tools allowed us to rapidly improve the usability, understandability, and usefulness of CDS in a generalizable sample of practicing nurses. CONCLUSIONS The method outlined allows the rapid integration of nursing terminology based electronic health record data into routine workflow and holds strong potential for improving patient outcomes. IMPLICATIONS FOR NURSING PRACTICE The methods and organizational tools for development of multiple CDS system features can be used to translate knowledge into practice.

Parallel processing and immersive visualization of sonar point clouds

The investigation of underwater structures and natural features through Autonomous Underwater Vehicles (AUVs) is an expanding field with applications in archaeology, engineering, environmental sciences and astrobiology. Processing and analyzing the raw sonar data generated by automated surveys is challenging due to the presence of complex error sources like water chemistry, zero-depth variations, inertial navigation errors and multipath reflections. Furthermore, the complexity of the collected data makes it difficult to perform effective analysis on a standard display. Point clouds made up of hundreds of millions to billions of points are not uncommon. Highly interactive, immersive visualization is a desirable tool that researchers can use to improve the quality of a final sonar-based data product. In this paper we present a scalable toolkit for the processing and visualization of sonar point clouds on a cluster-based, large scale immersive visualization environment. The cluster is used simultaneously as a parallel processing platform that performs sonar beam-tracing of the source raw data, and as the rendering driver of the immersive display.