Modeling and Parameter Estimation in Respiratory Control

  • Michael C. K. Khoo

Table of contents

  1. Front Matter
    Pages i-x
  2. Modeling of Respiratory Control During Exercise

  3. Chemical Control of Ventilation — Empirical Models and Parameter Estimation

  4. Neural Control and Breathing Pattern Analysis

  5. Sleep and Respiratory Control Stability

    1. Front Matter
      Pages N7-N7
    2. Jerome A. Dempsey, James B. Skatrud, Kathe G. Henke
      Pages 153-159
    3. Neil S. Cherniack, Guy Longobardo
      Pages 161-169
    4. David W. Carley
      Pages 171-180
    5. Allan I. Pack, Allan Gottschalk, Michael Cola, Adrian Goldszmidt
      Pages 181-191
  6. Back Matter
    Pages 205-208

About this book


Experimentalists tend to revel in the complexity and multidimensionality of biological processes. Modelers, on the other hand, generally look towards parsimony as a guiding prin­ ciple in their approach to understanding physiological systems. It is therefore not surprising that a substantial degree of miscommunication and misunderstanding still exists between the two groups of truth-seekers. However, there have been numerous instances in physiology where the marriage of mathematical modeling and experimentation has led to powerful in­ sights into the mechanisms being studied. Respiratory control represents one area in which this kind of cross-pollination has proven particularly fruitful. While earlier modeling ef­ forts were directed primarily at the chemical control of ventilation, more recent studies have extended the scope of modeling to include the neural and mechanical aspects pertinent to respiratory control. As well, there has been a greater awareness of the need to incorpo­ rate interactions with other organ systems. Nevertheless, it is necessary from time to time to remind experimentalists of the existence of modelers, and vice versa. The 4th Annual Biomedical Simulations Resource (BMSR) Short Course was held in Marina Del Rey on May 21-22,1989, to acquaint respiratory physiologists and clinical researchers with state-of-the­ art methodologies in mathematical modeling, experiment design and data analysis, as well as to provide an opportunity for experimentalists to challenge modelers with their more recent findings.


biological complexity experiment forebrain gas exchange kinetics mathematical modeling muscle physiology pollination respiration simulation

Editors and affiliations

  • Michael C. K. Khoo
    • 1
  1. 1.School of EngineeringUniversity of Southern CaliforniaLos AngelesUSA

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