In many professions where individuals must work in a team in a high stress environment to accomplish a time-critical task, individual and team performance can benefit from joint twining using distributed virtual envir...
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ISBN:
(纸本)0819425001
In many professions where individuals must work in a team in a high stress environment to accomplish a time-critical task, individual and team performance can benefit from joint twining using distributed virtual environments (DVEs). One professional Geld that lacks but needs a high-fidelity team training environment is the field of Emergency Medicine. Currently, Emergency Department (ED) medical. personnel train by using words to create a mental picture of a situation for the physician and staff, who then cooperate to solve the problems portrayed by the word picture. The need in Emergency Medicine for realistic virtual team training is critical because ED staff typically encounter rarely occurring but life threatening situations only once in their careers and because ED teams currently have no realistic environment in which to practice their team skills. The resulting lack of experience and teamwork makes diagnosis and treatment more difficult. virtual environment based training has the potential to redress these shortfalls. The objective of our research is to develop a state-of-the-art virtual environment for emergency medicine team training. The virtual Emergency Room (VER) allows ED physicians and medical staff to realistically prepare for emergency medical situations by performing triage, diagnosis, and treatment on virtual patients within an environment that provides them with the tools they require and the team environment they need to realistically perform these three tasks. There are several issues that must be addressed before this vision is realized. The key issues deal with distribution of computations;the doctor and staff interface to the virtual patient and ED equipment;the accurate simulation of individual patient organs' response to injury, medication, and treatment;and an accurate modeling of the symptoms and appearance of the patient while maintaining a real-time interaction capability. Our ongoing work addresses all of these issues. In this paper w
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