System and method for analyzing progress of labor and preterm labor

Patent metadata

Field	Value
Publication number	US-9974474-B2
Application number	US-201213443161-A
Country	US
Kind code	B2
Filing date	Apr 10, 2012
Priority date	Dec 11, 2006
Publication date	May 22, 2018
Grant date	May 22, 2018

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.

First claim

We claim:

1. A uterine monitoring system comprising:
a plurality of surface sensors suitable for attaching to a patient's abdomen and receiving uterine electrical signals;
a user interface, one or more processors, an interface that is connected to the plurality of surface sensors, and a non-transitory computer readable medium with computer software stored thereon that, when executed, causes the one or more processors of the uterine monitoring system to:
receive or determine a location of each of the plurality of surface sensors and recording the location of each of the plurality of surface sensors;
record electrical signals from each of the plurality of surface sensors over time;
convert the electrical signals from each of the plurality of surface sensors into contraction intensity information; and
create a plurality of uterine contractile maps, each for a specific point in time, by spatially correlating the contraction intensity information based on the location of each of the plurality of surface sensors;
classify, based at least in part on the plurality of uterine contractile maps, contraction patterns as LUS-Fundal, LUS-LUS, Fundal-LUS, or Fundal-Fundal, wherein classifying the contraction patterns includes calculating a percentage of time each contraction pattern occurs within a predetermined period of time represented by the plurality of uterine contractile maps, and wherein the classification of the contraction patterns is based at least in part on the percentage of time each contraction pattern occurs within the predetermined period of time;
cause communication, to a clinician, of clinically relevant findings that determine contraction efficiency stemming from the plurality of uterine contractile maps; and
based on the clinically relevant findings stemming from the plurality of uterine contractile maps, either initiate, modify, or discontinue administration of oxytocin to the patient.

2. The system of claim 1 , wherein the computer software, when executed, further causes the one or more processors to sequentially display the plurality of uterine contractile maps on the user interface.

3. The system of claim 1 , wherein the computer software, when executed, further causes the one or more processors to determine a contractile direction, or direction of contractile propagation, by sequentially analyzing the plurality of uterine contractile maps.

4. The system of claim 1 , wherein the computer software, when executed, further causes the one or more processors to determine a contractile origin by sequentially analyzing the plurality of uterine contractile maps.

5. The system of claim 1 , wherein the computer software, when executed, further causes the one or more processors to determine contraction frequency, contraction duration, and changes in contraction intensity over time.

6. The system of claim 1 , wherein the plurality of surface sensors are provided in a mesh, vest, or body wrap, and wherein the plurality of uterine contractile maps is over the abdomen.

7. The system of claim 1 , wherein the computer software, when executed, further causes the one or more processors to determine at least one of (i) a spatial location of a peak of contraction based on at least one of the plurality of uterine contractile maps or (ii) a peak contraction power in time based on the plurality of uterine contractile maps.

8. The system of claim 1 , wherein the computer software, when executed, further causes the one or more processors to determine fundal dominance, fundal origin, propagation time, and regularity.

9. A method for monitoring uterine contractility in a patient comprising:
placing a plurality of surface sensors on a patient's abdomen and receiving uterine electrical signals;
determining a location of each of the plurality of surface sensors and recording the location of each of the plurality of surface sensors;
recording electrical signals from each of the plurality of surface sensors over time;
converting the electrical signals from each of the plurality of surface sensors into contraction intensity information;
creating, by a processor, a plurality of uterine contractile maps, each for a specific point in time, by spatially correlating the contraction intensity information based on the location of each of the plurality of surface sensors;
classifying, by the processor and based at least in part on the plurality of uterine contractile maps, contraction patterns as LUS-Fundal, LUS-LUS, Fundal-LUS, or Fundal-Fundal, wherein classifying the contraction patterns includes calculating, by the processor, a percentage of time each contraction pattern occurs within a predetermined period of time represented by the plurality of uterine contractile maps, and wherein the classification of the contraction patterns is based at least in part on the percentage of time each contraction pattern occurs within the predetermined period of time; and
communicating, to a clinician, clinically relevant findings stemming from the plurality of uterine contractile maps that determine contraction efficiency; and
based on the clinically relevant findings stemming from the plurality of uterine contractile maps, either initiating, modifying, or discontinuing administration of oxytocin to the patient.

10. The method of claim 9 , wherein the method further comprises sequentially analyzing the plurality of uterine contractile maps to determine contractile propagation speed and extent of contractile propagation.

11. The method of claim 9 , wherein the method further comprises determining a contractile direction, or direction of contractile propagation, by sequentially analyzing the plurality of uterine contractile maps.

12. The method of claim 9 , wherein the method further comprises determining a contractile origin by sequentially analyzing the plurality of uterine contractile maps.

13. The method of claim 9 , wherein the method further comprises determining contraction frequency, contraction duration, and changes in contraction intensity over time.

14. The method of claim 9 , wherein the plurality of surface sensors are provided in a mesh, vest, or body wrap.

15. The method of claim 9 , wherein the method further comprises determining at least one of (i) a spatial location of a peak of contraction based on at least one of the plurality of uterine contractile maps or (ii) a peak contraction power in time based on the plurality of uterine contractile maps.

16. The method of claim 9 , wherein the method further comprises determining fundal dominance, fundal origin, propagation time, and regularity.

17. The method of claim 9 , wherein the method further comprises determining whether labor augmentation is needed followed by administration of oxytocin.

18. The method of claim 9 , wherein a percentage of each pattern is calculated over a period of time.

Assignees

• Principe Jose C
• Maroserro Dorothee
• Euliano Tammy Y
• Euliano Ii Neil Russell
• Convergent Eng Inc
• Univ Florida

Inventors

• Principe Jose C
• Maroserro Dorothee
• Euliano Tammy Y
• Euliano Ii Neil Russell

Classifications

• A61B2503/02

  Foetus · CPC title

• A61B5/7264

  Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems · CPC title

• A61B5/4356 Primary

  Assessing uterine contractions (A61B5/033 takes precedence) · CPC title

• A61B5/1107

  Measuring contraction of parts of the body, e.g. organ or muscle · CPC title

• A61B2562/046

  in a matrix array · CPC title