Fetal outcome predictor and monitoring system

• US 6,254,537 B1
• Filed: 09/17/1999
• Issued: 07/03/2001
• Est. Priority Date: 09/17/1999
• Status: Expired due to Fees

• Current Assignee: Rose Biomedical Development Corporation
• Original Assignee: Rose Biomedical Development Corporation
• Inventors: Nguyen, Duong
• Primary Examiner(s): Nasser, Robert L.
• Assistant Examiner(s): ASTORINO, MICHAEL C
• Application Number:
  US09/398,178
• Time in Patent Office: 655 Days
• Field of Search: 600/300-304, 600/481-486, 600/500-511, 600/529-538, 600/586-588, 128/900, 128/920-925, 705/2-4
• US Class Current: 600/300
• CPC Class Codes: A61B 5/02411 of foetuses
• CPC Class Codes: A61B 5/4356 Assessing uterine contractions A61B5/033 takes precedence
• 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 128/92 Computer assisted medical diagnostics

Abstract

A fetal health assessor and outcome predictor and monitoring system includes a system for automatically assessing fetal health and predicting fetal outcomes based on fetal and maternal data. The system includes a case-based reasoning processor for categorizing the fetus into one of a plurality of cases based on biographical data about the fetus and mother. The system also includes a transducer for converting physical conditions of the fetus and mother (e.g. characteristics based on heart rates and uterine contractions) to signals representative of the conditions. A computer processor converts the signals to a set of signal features. An assessor and predictor receives the processed signal features and assesses fetal health and predicts fetal outcome based on identified fuzzy relationships between fetal and maternal data and fetal outcomes.

Claims

1. A method of automatically providing an output representative of the health of a fetus carried by a mother, based on fetal and maternal data, with a computer-based predictor, the method comprising:

receiving biographical data about the fetus and the mother;

categorizing the fetal and maternal data combination as one of a plurality of types of cases based on the biographical data;

receiving physical data about the current condition of the fetus and the mother;

processing the physical data to extract characteristic features;

selecting a subset of the characteristic features based on the type of case that the fetal and maternal data combination has been categorized as; and

providing an output representative of the health of the fetus from the subset of characteristic features based on previously-developed fuzzy relationships between fetal and maternal data and fetal health.

2. A method as defined in claim 1, further including communicating the output to a user.

3. A method as defined in claim 1, wherein the provided output is representative of the current status of the fetus.

4. A method as defined in claim 1, wherein the provided output is representative of the health of the fetus at a predetermined time in the future.

5. A method as defined in claim 4, wherein the predetermined time is approximately twenty minutes after the output is reported.

6. A method as defined in claim 1, further including developing fuzzy relationships between fetal and maternal data and fetal health based on data and known fetal health from past pregnancies and births.

7. A method as defined in claim 1, further including using the reported fetal health to adjust and optimize the selecting operation.

8. A method as defined in claim 1, further including using the reported fetal health to adjust and optimize the providing operation.

9. A method as defined in claim 1, wherein the received physical data includes fetal heart rate and uterine contraction data.

10. A method as defined in claim 1, wherein the received biographical data includes fetal gender, gestational age, and medication data.

11. A method as defined in claim 1, wherein the categorizing operation includes case-based reasoning.

12. A method as defined in claim 1, wherein the extracted characteristic features in the processing operation include features relating to the variability in the heart rate of the fetus.

13. A method as defined in claim 1, wherein the extracted characteristic features in the processing operation include features relating to the accelerations in the heart rate of the fetus.

14. A method as defined in claim 1, wherein the extracted characteristic features in the processing operation include features relating to the decelerations in the heart rate of the fetus.

15. A method as defined in claim 1, wherein the extracted characteristic features in the processing operation include features relating to the uterine contractions by the mother in a predetermined period of time.

19. A system as defined in claim 11, wherein the processor converts the signal to an optimal set of signal features, the optimal set of features being selected based on a learning process that allows the assessor to categorize the fetal and maternal data as belonging to one of a plurality of types of cases and to select the optimal set of features from a larger set of features based on the case type.

16. A method of automatically reporting fetal health for a fetus carried by a mother, based on fetal and maternal data, with a computer-based assessor, the method comprising:

receiving fetal and maternal data;

processing the fetal and maternal data to generate and select an optimal set of fetal and maternal features; and

applying the optimal selected set of fetal and maternal features to the assessor to assess and predict fetal health based on identified fuzzy relationships between fetal and maternal data and fetal health;

further including a case-based reasoning processor that receives biographical data about the fetus and the mother and, using case-based reasoning, determines the optimal set of data features to be applied to the assessor.

17. A system for automatically assessing fetal health and predicting fetal outcomes based on fetal and maternal data, comprising:

a transducer for converting a physical condition of a fetus or mother to a signal representative thereof;

a processor for converting the signal to a set of signal features, the set of features being based in part on fetal and maternal biographical data; and

an assessor receptive of the processed signal features for assessing fetal health and predicting fetal outcome based on identified fuzzy relationships between fetal and maternal data and fetal outcomes;

further including a case-based reasoning processor that receives biographical data about the fetus and the mother and, using case-based reasoning, determines the optimal set of data features to be applied to the assessor.

18. A method as defined in claim 17, wherein the optimal set of features is selected based on a learning process that allows the assessor to categorize the fetal and maternal data as belonging to one of a plurality of types of cases and to select the optimal set of features from a larger set of features based on the case type.

20. A method for automatically predicting the future health of a particular person based on present data about the person, the method comprising:

automatically developing inference rules based on known data about persons and known data about the future health of those same persons;

receiving physical data about the present status of a particular person;

automatically processing the received data to generate a set of characteristic features; and

applying the inference rules to the derived characteristic features to predict the future health of the particular person.

21. A system for automatically providing an output representative of the health of a fetus carried by a mother, based on fetal and maternal data, with a computer-based predictor, comprising:

means for receiving biographical data about the fetus and the mother;

means for categorizing the fetal and maternal data combination as one of a plurality of types of cases based on the biographical data;

means for receiving physical data about the current condition of the fetus and the mother;

means for processing the physical data to extract characteristic features;

means for selecting a subset of the characteristic features based on the type of case that the fetal and maternal data combination has been categorized as; and

means for providing an output representative of the health of the fetus from the subset of characteristic features based on previously-developed fuzzy relationships between fetal and maternal data and fetal health.

22. A system as defined in claim 21, further including means for communicating the output to a user.

23. A system as defined in claim 21, wherein the provided output is representative of the current status of the fetus.

24. A system as defined in claim 21, wherein the provided output is representative of the health of the fetus at a predetermined time in the future.

25. A system as defined in claim 21, wherein the predetermined time is approximately twenty minutes after the output is reported.

26. A system as defined in claim 21, further including means for developing fuzzy relationships between fetal and maternal data and fetal health based on data and known fetal health from past pregnancies and births.

27. A system as defined in claim 21, further including means for using the reported fetal health to adjust and optimize the selecting operation.

28. A system as defined in claim 21, further including means for using the reported fetal health to adjust and optimize the providing operation.

29. A system as defined in claim 21, wherein the received physical data includes fetal heart rate and uterine contraction data.

30. A system as defined in claim 21, wherein the received biographical data includes fetal gender, gestational age, and medication data.

31. A system as defined in claim 21, wherein the means for categorizing utilizes case-based reasoning.

32. A system as defined in claim 21, wherein the extracted characteristic features include features relating to the variability in the heart rate of the fetus.

33. A system as defined in claim 21, wherein the extracted characteristic features include features relating to the accelerations in the heart rate of the fetus.

34. A system as defined in claim 21, wherein the extracted characteristic features include features relating to the decelerations in the heart rate of the fetus.

35. A system as defined in claim 21, wherein the extracted characteristic features include features relating to the uterine contractions by the mother in a predetermined period of time.

36. A system for automatically reporting fetal health for a fetus caried by a mother, based on fetal and maternal data, with a computer-based assessor, comprising

means for receiving fetal and maternal data;

means for processing the fetal and maternal data to generate and select an optimal set of fetal and maternal features; and

means for applying the optimal selected set of fetal and maternal features to the assessor to assess and predict fetal health based on identified fuzzy relationships between fetal and maternal data and fetal health;

further including a case-based reasoning processor that receives biograhical data about the fetus and the mother and, using case-based reasoning, determines the optimal set of data features to be applied to the assessor.

37. A method as defined in claim 36, wherein the optimal set of features is selected based on a learning process that allows the assessor to categorize the fetal and maternal data as belonging to one of a plurality of types of cases and to select the optimal set of features from a larger set of features based on the case type.