Model based optimization of the cardiopulmonary resuscitation (CPR) procedure

Ali Jalali, Robert A. Berg, Vinay Nadkarni, C. Nataraj

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

This paper is concerned with the optimization of the cardiopulmonary resuscitation (CPR) procedure, which plays a critical rule in saving the life of patients suffering from cardiac arrest. In this paper, we define the performance index for optimization using the oxygen delivery. A model developed earlier is used to calculate the oxygen delivery through CPR. The free parameters of this model which depend on the rescuer performance are ventilation time, compression speed, tidal volume, and fraction of oxygen in the inspired air. Two different optimization problems are carried out. First, a global optimization is implemented to discover the best values of the free parameters which maximize the oxygen delivery. In addition to this, a sequential optimization scheme is explored which uses a two step optimization in each CPR sequence to maximize the oxygen delivery. Results show that the sequential optimization procedure will enhance the performance of the CPR significantly.

Original languageEnglish (US)
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages715-718
Number of pages4
DOIs
StatePublished - 2012
Externally publishedYes
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Country/TerritoryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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