Work

Factorial Switching Kalman Filters for Condition Monitoring in Neonatal Intensive Care

Year: 2005

Type: article

Abstract: The observed physiological dynamics of an infant receiving intensive care are affected by many possible factors, including interventions to the baby, the operation of the monitoring equipment and the state of health. The Factorial Switching Kalman Filter can be used to infer the presence of such factors from a sequence of observations, and to estimate the true values where these observations have been corrupted. We apply this model to clinical time series data and show it to be effective in identifying a number of artifactual and physiological patterns.

Source: ERA

Authors: Christopher K. I. Williams, John A. Quinn, Neil McIntosh

Institutions: University of Edinburgh, MRC Centre for Reproductive Health

Language: German

Topic: Target Tracking and Data Fusion in Sensor Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W2145504747

FWCI: 3.007

Cites: 10

Cited by: 29

Related to: 10