System and method for analyzing progress of labor and preterm labor

• US 8,160,692 B2
• Filed: 06/01/2009
• Issued: 04/17/2012
• Est. Priority Date: 12/11/2006
• 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: Principe, Jose C., Maroserro, Dorothee, Euliano, Tammy Y., Euliano, Neil Russell II
• Primary Examiner(s): Hindenburg, Max
• Assistant Examiner(s): DANEGA, RENEE A
• Application Number:
  US12/475,911
• Publication Number:
  US 20090299212A1
• Time in Patent Office: 1,051 Days
• Field of Search: 600/547, 600/558, 600/511
• US Class Current: 600/547
• CPC Class Codes: A61B 2503/02 Foetus
• CPC Class Codes: A61B 2562/046 in a matrix array
• CPC Class Codes: A61B 5/1107 Measuring contraction of parts of the body, e.g. organ, muscle apparatus for measuring work or force in general G01L
• CPC Class Codes: A61B 5/391 of genito-urinary organs
• CPC Class Codes: A61B 5/4356 Assessing uterine contractions A61B5/033 takes precedence
• 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: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Systems and methods for monitoring uterus contraction activity and progress of labor. The system of the subject invention can comprises (1) a plurality 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, progress of labor, prediction and monitoring of preterm labor, and intrauterine pressure prediction. In a preferred embodiment, the 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 as well as delivery strategy.

Claims

1. A uterine contractile monitoring system comprising:

a) a plurality of surface sensors to receive and communicate myometrium signals from a patient'"'"'s abdomen;

b) a data storage device for collecting information communicated by the sensors; and

c) a computing means comprising hardware and software, wherein said software comprises an electrohysterogram (EHG) extraction function to extract multiple channels of EHG signals based on information communicated by the plurality of sensors and a function for utilizing and analyzing the multiple EHG signals;

wherein the function for utilizing and analyzing the multiple EHG signals of the software is adapted to perform at least;

(i) pairwise subtraction of the multiple EHG signals to emphasize local contractility of the patient'"'"'s uterus at the respective surface sensor;

(ii) derivation of data detailing differences in timing and amplitude of the signals following step (i);

(iii) assessment of values for the data of step (ii) and assigning the values to a grid of locations corresponding to the sensors placed on the patient'"'"'s abdomen;

wherein the function for utilizing and analyzing the multiple EHG signals extracts any single one or combination of the following parameters from the grid;

time of contraction, location of contraction, extent of contraction, direction of propagation, speed of propagation over the abdomen, average contraction over time, spatial location of the peak of contraction and its variance, spread of the contraction, abdominal intensity distribution, abdominal frequency distribution, patterns of contraction intensity over time, distance of peak power propagation, power changes over time, and frequency changes over time,

wherein the computing means further comprises a means for utilizing the grid to ascertain any single one or combination of the following data;

uterine tonus, fundal dominance, and spatio-temporal patterns of uterine contractions.

2. The uterine contractile monitoring system of claim 1, wherein the means for utilizing the grid to ascertain data comprises the software.

3. The uterine contractile monitoring system of claim 2, wherein the means for utilizing the grid to ascertain data further comprises at least one intelligence system.

4. The uterine contractile monitoring system of claim 1, wherein the software further comprises a function for evaluating the spatio-temporal patterns of uterine contractions to establish a contractile map of the uterus.

5. The uterine contractile monitoring system of claim 1, wherein the software further comprises a function for evaluating the spatio-temporal patterns of uterine contraction to diagnose normal or abnormal labor.

6. The uterine contractile monitoring system of claim 5 wherein the software function for diagnosing abnormal labor is directed to dystocia.

7. The uterine contractile monitoring system of claim 1, wherein the software further comprises a function for evaluating the spatio-temporal patterns of uterine contraction to predict dilation.

8. The uterine contractile monitoring system of claim 7, wherein the software further comprises a function for utilizing the predicted dilation to ascertain contraction efficiency in oxytocin augmented and non-oxytocin augmented patients.

9. The uterine contractile monitoring system of claim 7, wherein the software further comprises a function for utilizing the predicted dilation to predict labor outcome in oxytocin augmented and non-oxytocin augmented patients.

10. The uterine contractile monitoring system of claim 7, wherein the software further comprises a function for utilizing the predicted dilation to estimate the likelihood of dystocia, vaginal delivery, or preterm delivery.

11. The uterine contractile monitoring system of claim 1, wherein the plurality of surface sensors are provided on a mesh or vest.

12. The system of claim 1, wherein a plurality of grids are derived.

13. The system of claim 1, wherein the data derived from step (ii) comprises a plurality of envelopes of each contraction curve based on each local contractility signal following step (i).

14. A method for monitoring uterine contractions in a patient comprising:

a) placing a plurality of surface sensors connected to a computing means onto the patient'"'"'s abdomen to receive myometrium signals;

b) operating the computing means, wherein the computing means comprises hardware and software, wherein said software comprises an EHG extraction function to extract multiple channels of EHG signals based on information communicated by the plurality of sensors and a function for utilizing and analyzing the multiple EHG signals;

wherein the function for utilizing and analyzing the multiple EHG signals comprises the steps of;

(i) pairwise subtracting the multiple EHG signals to emphasize the local contractility of the patient'"'"'s uterus at the respective surface sensor;

(ii) deriving data detailing differences in timing and amplitude of the signals following step (i); and

(iii) assessing values for the data of step (ii) and assigning the values to a grid of locations corresponding to the sensors placed on the patient'"'"'s abdomen;

wherein the function for utilizing and analyzing the multiple EHG signals extracts any single one or combination of the following parameters;

time of contraction, location of contraction, extent of contraction, direction of propagation, speed of propagation over the abdomen, average contraction over time, spatial location of the peak of contraction and its variance, spread of the contraction, abdominal intensity distribution, abdominal frequency distribution, patterns of contraction intensity over time, distance of peak power propagation, power changes over time, and frequency changes over time,

wherein the software further comprises a function for utilizing the grid to ascertain any single one or combination of the following data;

uterine tonus, fundal dominance, and spatio-temporal patterns of uterine contractions;

c) extracting from the software clinically relevant data with regard to uterine contraction; and

d) communicating the clinically relevant data to a clinician.

15. The method of claim 14, wherein the clinically relevant data comprise(s) normal versus abnormal progress in labor.

16. The method of claim 14, wherein the clinically relevant data comprise(s) data regarding dystocia.

17. The method of claim 14, wherein a plurality of grids are derived.

18. The method of claim 14, wherein the data derived from step (ii) comprises a plurality of envelopes of each contraction curve based on each local contractility signal following step (i).