FETAL DATA PROCESSING SYSTEM AND METHOD EMPLOYING A TIME-FREQUENCY REPRESENTATION

• US 20010014776A1
• Filed: 06/21/1999
• Published: 08/16/2001
• Est. Priority Date: 09/21/1994
• Status: Abandoned Application

• Current Assignee: Frederick M. Bennett, Nancy E. Oriol
• Original Assignee: Frederick M. Bennett, Nancy E. Oriol
• Inventors: ORIOL, NANCY E., BENNETT, FREDERICK M.
• Application Number:
  US09/337,145
• Publication Number:
  US 20010014776A1
• Time in Patent Office: Days
• US Class Current: 600/511
• CPC Class Codes: A61B 5/02411 of foetuses
• CPC Class Codes: A61B 5/344 Foetal cardiography
• CPC Class Codes: A61B 5/4035 Evaluating the autonomic nervous system
• CPC Class Codes: A61B 5/4362 Assessing foetal parameters
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: Y10S 128/925 Neural network

Abstract

A fetal data processing system and method and a fetal monitor and method for monitoring the condition of a fetus are disclosed. A fetal heart rate time series is received and sampled. A non-linear time-frequency transformation is performed to generate a time-frequency representation of the fetal heart rate time series for heart rate time series data spanning a time period which is preferably less than ten seconds. Analysis of fetal heart rate and fetal heart rate variability and other available data is performed to evaluate fetal well-being. Because of the high time resolution of the transformation, short-term transient variations in heart rate and heart rate variability are considered in the analysis.

Claims

1. A fetal data processing method comprising:

providing a fetal heart rate moniter;

receiving a signal indicative of fetal heart rate time data for the fetus from the monitor, said fetal heart rate time data indicating heart rate of the fetus over time;

performing a non-linear time-frequency transformation on the fetal heart rate time data to generate a frequency domain representation for the fetal heart rate time data; and

analyzing the frequency domain representation to indicate a condition of the fetus related to the fetal heart rate time data.

2. The method of

claim 1

further comprising indicating transient change in fetal heart rate variability.

3. The method of

claim 1

further comprising indicating transient change in fetal heart rate.

4. The method of

claim 1

wherein the fetal heart rate time data is also used to perform the indicating step.

5. The method of

claim 1

wherein a uterine contraction signal is also used to perform the indicating step.

6. The method of

claim 1

wherein a fetal movement signal is also used to perform the indicating step.

7. The method of

claim 1

further comprising predicting outcome for the fetus.

8. The method of

claim 1

wherein the indicating step comprises applying a set of classification rules to fetal data.

9. The method of

claim 1

wherein the indicating step comprises applying a pattern of fetal data to a neural network.

10. The method of

claim 1

wherein the indicating step comprises analyzing the time-frequency representation in plural frequency bands.

11. The method of

claim 1

wherein the time-frequency representation spans a frequency range from 0.02 Hz to 1.1 Hz.

12. The method of

claim 1

wherein the indicating step comprises computing areas under the time-frequency representation.

13. The method of

claim 1

wherein the time-frequency representation is generated for fetal heart rate time data from a time period of less than ten seconds.

14. The method of

claim 1

further comprising sampling the fetal heart rate time data at a frequency greater than 2 Hz.

15. The method of

claim 1

further comprising displaying in real time variables used to indicate the condition of the fetus.

16. The method of

claim 1

further comprising displaying a three-dimensional plot of the time-frequency representation.

17. The method of

claim 16

, wherein the three-dimensional plot of the time-frequency representation is updated with frequency amplitude data at 1.0 second intervals.

18. The method of

claim 16

, wherein the three-dimensional plot of the time-frequency representation is color coded to indicate different conditions.

19. The method of

claim 1

further comprising generating recommendations regarding fetal well-being.

20. The method of

claim 1

wherein the non-linear time-frequency representation is performed for each sampling period over which fetal heart rate time date is collected where the sampling period is not to exceed 10 seconds.

21. The method of

claim 1

wherein the time-frequency representation is generated using a smoothed Wigner distribution.

22. A fetal data processing system comprising:

a fetal heart rate monitor;

an input that receives fetal heart rate time data for a fetus from the monitor, said fetal heart rate time data indicating heart rate of the fetus over time; and

a processing system comprising a processor and a memory, the processor running under control of a program stored in the memory that receives the fetal heart rate time data, and further comprising a subsystem that samples the fetal heart rate time data over a sample time period that does not exceed 10 seconds such that sampled fetal heart time data is generated, the system performing a time-frequency transformation on the sampled fetal heart rate time data, said transformation generating a frequency-domain representation for the fetal heart rate time data.

23. The fetal data processing system of

claim 22

further comprising a classifying subsystem that analyzes the fetal heart rate time data to indicate the condition of the fetus.

24. The fetal data processing system of

claim 23

wherein the classifying subsystem also analyzes a uterine contraction signal to indicate the condition of the fetus.

25. The fetal data processing system of

claim 23

wherein the classifying subsystem also analyzes a fetal movement signal to indicate the condition of the fetus.

26. The fetal data processing system of

claim 23

wherein the classifying subsystem analyzes the time-frequency representation in plural frequency bands.

27. The fetal data processing system of

claim 23

wherein the classifying subsystem applies a set of classifying rules to a pattern of fetal data to classify the fetal data.

28. The fetal data processing system of

claim 23

wherein the classifying subsystem comprises at least one neural network for receiving a pattern of fetal data to classify the fetal data.

29. The fetal data processing system of

claim 23

wherein the classifying subsystem predicts an outcome for the fetus.

30. The fetal data processing system of

claim 22

further comprising a display for displaying in real time variables used to indicate the condition of the fetus.

31. The fetal data processing system of

claim 22

further comprising a display controller for selecting for display in real time variables used to predict outcome for the fetus.

32. The fetal data processing system of

claim 22

wherein the frequency-domain representation is analyzed to indicate, based on the analysis of the frequency-domain representation, a condition of the fetus related to the sampled fetal heart rate time data.