A Novel Clinical Decision Support System for Analysis of Fetal Heart Rate and Maternal Uterine Pressure Signals Based on Generative Models


Electronic fetal monitoring (EFM) involves simultaneous monitoring of the fetal heart rate (FHR) as well as the maternal uterine pressure (UP) signal. In practice, EFM has been based on visual analysis of FHR patterns and thereby is rather subjective. A reliable computer-based system for accurate and meaningful classification of FHR signals does not exist on the market. The obstetric practice needs a system to fill the void.


Presented is a system for receiving FHR and UP signals and extracting feature values from these signals. The features are used for online classification exploiting the Bayesian machinery. The system provides a real time output summarizing the state of the fetus which can range from fully healthy to abnormal. With the system, an obstetrician has a reliable decision support system that will benefit the fetus, the mother, and the obstetrician.


Sequential real time classification - Assimilation of physician feedback To the system for enhanced learning - data visualization for quantification of classification uncertainty - Encoding of temporal effects - Knowledge Discovery of FHR categories without assistance of gold standard labeling


Classify the fetal data records and assign to the classification a measurement of uncertainty.

Patent Status


Stage Of Development

14/314,918 15/824,215

Licensing Potential

Commercial partner,Licensing,Development partner

Licensing Status

Available for license.

Additional Info


https://stonybrook.technologypublisher.com/files/sites/ug1jml1s8kdcog5lm6gu_pregnancy-maxpixel.png Please note, header image is purely illustrative. Source: Max Pixel, CC0.
Patent Information:
Case ID: R8529
For Information, Contact:
Donna Tumminello
Assistant Director
State University of New York at Stony Brook
Shishir Dash
Gerald Quirk
Petar Djuric