A Knowledge-Based Diagnosis and Treatment Display Unit

Abstract

The objective of this project was to develop a high-performance diagnostic and treatment display unit that is optimized for a user equivalent to a physician's assistant. A key aspect of the system is the decision-making software which monitors the patient's physiological status and anticipates downturns in medical condition. Data from physiological sensors are combined with a knowledge base that includes treatments for penetrating and blunt trauma. The unit is optimized to monitor trauma victims that are not in need of immediate surgery at a Battalion Aid Station. This makes it possible to provide significantly improved medical care to wounded soldiers while reducing the number of attending medical personnel. The primary application in civilian medical care is in intensive care units. Here, patients are often hemodynamically stable but not hemodynamically normal. The diagnosis and treatment display software runs on a laptop computer and is linked to medical sensors via serial and PCMCIA ports. A variety of real-time displays are available during the patient monitoring period. These include displays of patient status, parsed and processed sensor data, and fully analyzed sensor values and trends. Sensor data are automatically checked by the analysis algorithm for validity, and commonly occurring artifacts are identified and eliminated.

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Document Details

Document Type
Technical Report
Publication Date
Aug 19, 2000
Accession Number
ADA385745

Entities

People

  • Frank T. Djuth
  • Jackie A. Hahn
  • John H. Elder
  • Paul P. Woodward
  • Paula M. Johnston

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Arteries
  • Blood
  • Cardiovascular Physiological Phenomena
  • Cardiovascular System
  • Computer Programming
  • Health Services
  • Hemorrhagic Shock
  • Medical Personnel
  • Thoracic Injuries
  • Wounds And Injuries

Fields of Study

  • Medicine

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Oncology and Biomarker-Based Cancer Detection.
  • Sensor Fusion and Tracking Systems.