Maternal-fetal monitoring system

• US 7,333,850 B2
• Filed: 05/28/2004
• Issued: 02/19/2008
• Est. Priority Date: 05/28/2004
• Status: Active Grant

• Current Assignee: Convergent Engineering, Inc., University of Florida Research Foundation, Incorporated (State University System of Florida)
• Original Assignee: Convergent Engineering, Inc., University of Florida Research Foundation, Incorporated (State University System of Florida)
• Inventors: Euliano, Neil Russell II, Marossero, Dorothee, Principe, Jose C., Euliano, Tammy Y.
• Primary Examiner(s): Evanisko; George R.
• Assistant Examiner(s): FILOSI, TERRI LYNN
• Application Number:
  US10/857,107
• Publication Number:
  US 20050267376A1
• Time in Patent Office: 1,362 Days
• Field of Search: 600/511, 600/376, 600/304
• US Class Current: 600/511
• CPC Class Codes: A61B 5/0011 Foetal or obstetric data
• CPC Class Codes: A61B 5/02411 of foetuses
• CPC Class Codes: A61B 5/033 Uterine pressure
• CPC Class Codes: A61B 5/344 Foetal cardiography
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/391 of genito-urinary organs
• CPC Class Codes: A61B 5/4362 Assessing foetal parameters
• CPC Class Codes: A61B 5/6805 Vests
• CPC Class Codes: A61B 5/6831 Straps, bands or harnesses
• 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

Abstract

A maternal-fetal monitoring system for use during all stages of pregnancy, including antepartum and intrapartum stages. The maternal-fetal monitoring system of the subject invention comprises (1) a set of sensors; (2) an amplifying/filtering means; (3) a computing means; and (4) a graphical user interface. Accurate clinical data, which can be extracted and provided to the user in real-time using the system of the invention, include without limitation, maternal electrocardiogram (ECG) signals, maternal uterine activity signals (EHG), maternal heart rate, fetal ECG signals, and fetal heart rate. In a preferred embodiment, the maternal-fetal monitoring system of the invention includes an intelligence means, such as a neural network system, to analyze and interpret clinical data for use in clinical diagnosis antepartum, intrapartum and postpartum, as well as delivery strategy.

Claims

1. A maternal-fetal monitoring system comprising:

a) at least two surface sensors to receive a mixture of maternal and fetal vital signals; and

b) a computing means for analyzing the mixture of maternal and fetal vital signals from the sensors, said computing means including hardware and software, wherein said software comprises a separation function to separate maternal from fetal vital signals and a function for assessing the quality of the separated maternal and fetal vital signals by measuring the performance of separating maternal from fetal vital signals.

2. The maternal-fetal monitoring system of claim 1, further comprising a mesh or vest, wherein the sensors are provided on the mesh or vest.

3. The maternal-fetal monitoring system of claim 2, wherein at least two sensors are provided along a midline of the mesh or vest that is adapted to be placed on a maternal abdomen, such that the sensors are vertically aligned along the abdomen.

4. The maternal-fetal monitoring system of claim 1, wherein the software further comprises a means for extracting EHG.

5. The maternal-fetal monitoring system of claim 4, further comprising a mesh or vest adapted to be placed on a maternal abdomen, wherein at least two sensors are provided along a vertical midline of the mesh or vest, wherein the maternal and fetal vital signals from the sensors along the midline are input into the EHG extracting means.

6. The maternal-fetal monitoring system of claim 4, wherein the software further comprises a means for providing an EHG spectrogram, a contraction curve, and an estimation of intra-uterine pressure from the EHG extracting means.

7. The maternal-fetal monitoring system of claim 4, wherein the means for extracting EHG comprises at least one down-sample operator for removing extraneous high-frequency information;

at least one filtering operator to obtain an EHG wave envelope; and

at least one contraction detection operator to detect beginning, end, duration, and amplitude of a uterine muscle contraction.

8. The maternal-fetal monitoring system of claim 4, wherein the means for extracting EHG further comprises at least one intelligence system.

9. The maternal-fetal monitoring system of claim 8, wherein the intelligence system is selected from the group consisting of:

artificial neural networks, fuzzy logic, evolutionary computation, knowledge-based systems, and artificial intelligence.

10. The maternal-fetal monitoring system of claim 1, further comprising an amplifier for amplifying maternal and fetal vital signs extracted by the sensors.

11. The maternal-fetal monitoring system of claim 1, wherein the software further comprises a means for detecting QRS complex peaks in the maternal and fetal vital signals.

12. The maternal-fetal monitoring system of claim 11, wherein the means for detecting QRS complex peaks comprises a band-pass filter;

a differentiation function; and

a moving average function.

13. The maternal-fetal monitoring system of claim 12, wherein the means for detecting QRS complex peaks comprises a butterworth band-pass filter, a differentiation function of 5 point derivatives, and a moving average function of a 20 point window.

14. The maternal-fetal monitoring system of claim 11, wherein the means for detecting QRS complex peaks in maternal and fetal vital signals provides clinical data selected from the group consisting of:

RR intervals, instantaneous heart rate, beat to beat heart rate, average heart rate, heart rate variance, and estimated false positive and false negative QRS complexes.

15. The maternal-fetal monitoring system of claim 1, wherein the software function for separating maternal from fetal vital signals is an independent component analysis.

16. The maternal-fetal monitoring system of claim 15, wherein the independent component analysis means is selected from the group consisting of blind source separation operations;

Infomax ICA operations;

minimum mutual information operations;

maximum entropy and minimum mutual information operations; and

Mermaid ICA operations.

17. The maternal-fetal monitoring system of claim 1, wherein the function for separating the maternal and fetal vital signals comprises at least one input variable, wherein the means for assessing the quality of the separated maternal and fetal vital signals comprises at least one ideal value for clean maternal and fetal vital signals, at least one operation for calculating for each separated maternal and fetal vital signal at least one probability function with at least one input variable when compared to the ideal value for clean maternal and fetal vital signals.

18. The maternal-fetal monitoring system of claim 1, wherein the software further comprises an auto-correlation means for processing the separated maternal and fetal vital signals.

19. The maternal-fetal monitoring system of claim 1, wherein the software further comprises a means for automatically determining the location of fetal vital signals channels and maternal vital signals channels.

20. The maternal-fetal monitoring system of claim 1, wherein the system is portable.

21. The maternal-fetal monitoring system of claim 15, wherein the independent component analysis means analyzes maternal and fetal vital signals to provide clinical data selected from the group consisting of estimated fetal ECG and estimated maternal ECG.

22. The maternal-fetal monitoring system of claim 15, wherein the separation of maternal from fetal vital signals performed by independent component analysis is conducted in real-time.