Virtual Patients for Virtual Sick Call Medical Training

Abstract

Training military clinicians and physicians to treat Soldiers directly impacts their mental and physical health and may even affect their sw?vival. Developing skills such as: patient interviewing, interpersonal interaction and diagnosis can be difficult and is severely lacking in hands-on~training due to the cost and availablllty of trained standardized patients. A solution to this problem is in using computer generated virtual patient avatars that exhibit the mental and physiologically accurate symptoms of their particular illness; such physical indicators as sweating blushing and breathing due to discomfort and matching conversational dialog for the disorder. These avatars are highly interactive with speech recognition, natural language understanding, non~ verbal behavior, facial expressions and conversational skills. This paper wi!l discuss the research, technology and the value of developing virtual patients. Previous work will be stated along with issues behind cTeatlng virtual characters and scenarios for the joint forces. It will then focus on subject testing that is being conducted with a Navy scenario at the Navy Independent Duty Corpsman (IDC) Schoo! at the Navy Medical Center in San Diego. 111e protocol involves pre and post tests with a 15 minute interview of the virtual patient. Analysis of the data will yield results in user interactions with the patient and discuss how the system can be used for training for future deployment of these systems for medical professionals. Inc Virtual Sick Call Project under the Joint Medical Simulation Technology Integrated Product Team (JMST IPT) seeks to push the state of the art in developing high fidelity virtual patients that will enable the caregiver to improve interpersonal skills for scenarios that require not only medical experience, but the ability to relate at an interpersonal level, with interviewing and diagnosis skills as patients can be hiding symptoms of post-traumatic stress disorder suicide and domestic

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2010
Accession Number
ADA557318

Entities

People

  • Pat Garrity
  • Patrick G. Kenny
  • Thomas D Parsons

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Anxiety Disorders
  • Artificial Intelligence
  • Automated Speech Recognition
  • Brain Injuries
  • Computer Languages
  • Computers
  • Dialogue Systems
  • Diseases And Disorders
  • Education
  • Health Services
  • Medical Personnel
  • Mental Disorders
  • Natural Language Processing
  • Natural Languages
  • Personality
  • Traumatic Stress Disorder
  • Virtual Reality

Fields of Study

  • Medicine

Readers

  • Military Training and Readiness Simulation
  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.
  • Trauma or Military Medicine

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy