Why and How One Models Exercise on a Computer (A Tutorial)
Abstract
The principal reason for modeling exercise or any physiological phenomenon is simply stated, “because we do not understand all we know.” This is particularly true in the mature parts of science where the principal characteristics of the subject have been described in a corpus of literature encompassing conceptually interlocking experiments and where conflicting or partial theory exists. Theory which is the formulation of a causal myth to explain elements in a catalog of observation serves the function of economizing on memory and increasing human control over processes that the knowledge describes, i.e., technology. Modeling, then, is no more than publication in an idiom which recalls many considerations necessary to any given situation and discovers new or unexpected implications of old systems of ideas. Instead of dialectic, computer simulation with models produces unambiguously the implied consequences of the assumptions which include both the declarative and the procedural forms of knowledge. Modeling is parsimonious. In physiology the variety of laboratory experiments that pertain to a global function like exercise is redundant exposition of a common underlying mechanism.
Keywords
Ventilatory Response Neural Signal Common Underlying Mechanism Relational Data Base Respiratory OscillatorPreview
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References
- 1.B. Benchetrit, P. Baconnier and J. Demongeot, eds., “Concepts and Formalization in the Control of Breathing,” Manchester University Press, (1987).Google Scholar
- 2.B. Whipp and D.M. Wiberg, eds., “Modelling and Control of Breathing,” Elsevier Science Pub., New York (1983).Google Scholar
- 3.W. S. Yamamoto and W. F. Raub, Models of the regulation of external respiration in mammals, Comput. and Biomed. Res. 1: 65–104 (1967).CrossRefGoogle Scholar
- 4.W. S. Yamamoto, Information systems approach to integrated responses in the respiratory control system, Ann. Biomed. Eng. 11: 349–360 (1983).PubMedCrossRefGoogle Scholar
- 5.W. S. Yamamoto and E. S. Walton, On the evolution of the physiological model, Ann. Rev. Biophysics & Bioengin. 4: 81–102 (1975).CrossRefGoogle Scholar
- 6.W. S. Yamamoto, A mathematical simulation of the hyperpneas of metabolic CO 2 production and inhalation, Am. J. Physiol. 235: R265–R278 (1978).PubMedGoogle Scholar
- 7.W. S. Yamamoto, Computer simulation of ventilatory control by both neural and humoral C0 2 signals, Am. J. Physiol. 238: R28–R35 (1980).PubMedGoogle Scholar
- 8.E. A. Phillipson, J. Duffin and J. D. Cooper, Critical dependence of respiratory rhythmicity on metabolic C0 2 load, J. Appl. Physiol. 50: 45–54 (1981).PubMedGoogle Scholar
- 9.W. S. Yamamoto, Model of steady state breathing at rest and responses to low CO 2 levels, Fed. Proc. 38: 3 (1979).Google Scholar
- 10.M. I. Cohen, Neurogenesis of respiratory rhythm in the mammal, Physiol. Rev. 59: 1105–1173 (1979).PubMedGoogle Scholar
- 11.S. A. Ward and B. J. Whipp, Ventilatory control during exercise with increased external dead space, J. Appl. Physiol. 48: 225–231 (1980).Google Scholar
- 12.W. S. Yamamoto and W. D. Kirk, Model analysis of steady—state ventilatory response to C0 2 into component factors, J. Appl. Physiol. 60: 2128–2134 (1986).PubMedGoogle Scholar
- 13.W. S. Yamamoto and P. G. Wolff, On the identification of verbs in computer programs of physiological models, Comput. & Biomed. Res. 17: 175–184 (1984).CrossRefGoogle Scholar
- 14.W. S. Yamamoto, Converting mathematical models of physiological systems to relational data base schemes for analysis and comparison, IEEE Trans, on Biomed. Eng. 32: 273–276 (1988).CrossRefGoogle Scholar
- 15.W. S. Yamamoto, Analogies between models of physiological systems and relational data bases, Proc 6th Annual Symposium on Computer Applications in Medical Care pp. 879–881 (1982).Google Scholar