COHb Prediction Model for PC Application

Abstract

Exposure to carbon monoxide (CO) is endemic to the armoured vehicle environment owing to the discharge of CO from weapons firing. Given that small doses of CO can potentially impair the soldier's performance and health, it would be prudent to acquire the capability to predict CO uptake and the resultant formation of blood carboxyhemoglobin (COHb) to prevent or lessen the risk of CO toxicity. Also, given that a validated mathematical model of CO uptake already exists, a transfer of the model for PC application is the most efficient means of providing this capability. This technical memorandum briefly describes the risk and prediction of CO uptake, and more completely describes the design philosophy behind the data inputs and presentation of results. Features include the option to input data directly or from default lists, the ability to edit inputs without restarting the program, presentations of %COHb in both tabular and graphical formats with indications of safe, cautious, and dangerous levels, the ability to store and recall exposure histories, and the ability to printout results or export them for spreadsheet application software. The convenience of a PC-formatted prediction model allows for ease of use either in the field as an operational decision aid or at the desk as an analytical tool.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1996
Accession Number
ADA286902

Entities

People

  • Allan A. Keefe
  • Peter Tikuisis

Organizations

  • Defence Research and Development Canada

Tags

Communities of Interest

  • Biomedical
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Application Software
  • Armored Vehicles
  • Barometric Pressure
  • Carbon Monoxide
  • Classification
  • Dielectric Gases
  • Engineering
  • Hard Copy
  • Human Factors Engineering
  • Mathematical Models
  • Models
  • Monoxides
  • National Security
  • Security
  • Spreadsheet Software

Readers

  • Aviation Safety Risk Assessment.
  • Computational Modeling and Simulation
  • Computer Science.