I'm a doctor, not a mathematician! Homeostasis as a proportional-integral control system

TL;DR

This paper proposes modeling glucose homeostasis as a proportional-integral control system, using continuous data from glucose monitors to better understand health status and improve diagnosis.

Contribution

It introduces a universal control model for homeostasis, applying engineering control theory to physiological data for the first time.

Findings

Most subjects' data cluster around the control model

Outliers show less efficient homeostasis

Potential for improved health diagnostics

Abstract

The distinction between "healthy" and "unhealthy" patients is commonly based on single, discrete values taken at an isolated point in time (e.g., blood pressure or core temperature). Perhaps a more robust and insightful diagnosis can be obtained by studying the functional interdependence of such indicators and the homeostasis that controls them. This requires quasi-continuous measurements and a procedure to map the data onto a parsimonious control model with a degree of universality. The current research illustrates this approach using glucose homeostasis as a target. Data were obtained from 41 healthy subjects wearing over-the-counter glucose monitors, and projected onto a simple proportional-integral (PI) controller, widely used in engineering applications. The indicators quantifying the control function are clustered for the great majority of subjects, while a few outliers exhibit less efficient homeostasis. Practical implications for healthcare and education are further discussed.