Extending the GDE paradigm to physiology

Keith L. Downing

doi:10.1117/12.56872

1 March 1992 Extending the GDE paradigm to physiology

Keith L. Downing

Proceedings Volume 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems; (1992) https://doi.org/10.1117/12.56872
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

In 1986, de Kleer and Williams first described the general diagnostic engine (GDE), which combines simulation, truth maintenance, and information theory to perform model-based diagnosis (MBD) of complex physical devices. Currently, a large proportion of research within MBD follows the GDE paradigm. Most of this work applies to digital electronics topologies that lack feedback and are composed of standard component models such as adders and multipliers. We extend the GDE paradigm to physiological domains, where both modeling problems and feedback abound. To deal with the modeling differences between electronics and physiology, we generalize the GDE concept of component to mechanism, since mechanisms based on fundamental laws and feedback loops are the focal modules of many physiological systems. Using steady-state constraints to represent these mechanisms, we employ constraint propagation as a simulation/prediction engine. Although partially describable by steady-state equations, homeostatic systems also exhibit complex dynamic behaviors. In response to initial perturbations/faults, regulators cause physiological systems to evolve through a series of states, each characterized by a unique set of faults. We therefore view the diagnosis of regulated systems as a fourfold tasks: 1) find the fault sets of 'candidate' diagnoses within each state, 2) use static regulatory models to explain as many candidate faults as possible, 3) use dynamic regulatory models to link candidates from temporally adjacent states into global explanation chains, and 4) use these global chains and their estimated likelihoods as the information-theoretic basis for determining which variable to measure next, and when (i.e., in which state). So by focusing on physiological domains, we extend the GDE paradigm to diagnose time-varying systems with dynamic faults (i.e., those that do not necessarily persist throughout diagnosis).

Citation Download Citation

Keith L. Downing "Extending the GDE paradigm to physiology", Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); https://doi.org/10.1117/12.56872

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available