Input stimulus design for model discrimination in human respiratory control

Abstract

The existence of a set of alternative models, all competing to characterise respiratory controller structure, leads naturally to a model discrimination problem. This paper considers the problem of input design for enhancing model discrimination. Both empirical and formal methods are considered. The empirical methods utilise frequency domain model characteristics. The formal methods utilise the time domain model responses. Using a class of models given by linear differential equations with time delays, an input consisting of a sum of sinusoidal components under a power constraint is considered. A procedure for designating the power spectrum of the signal is developed. Furthermore, a procedure for obtaining a binary signal with a similar spectrum is illustrated. These concepts are applied to input design for discrimination among models that characterise respiratory control during exercise.

Ventilatory Control Dynamics During Muscular Exercise in Man

“…It appears, therefore, that sinusoidal forcing of work rate in this frequency range approximates to a continuous forcing of the 02 control mechanism. However, it has been suggested that a fast 01 component did appear to reside in these sinusoidal responses (84), which would have been more readily discerned had a higher range of forcing frequencies been employed. Pseudo-random binary sequences (PRBS) ( Fig.…”