Device and system for remote for in-clinic trans-abdominal/vaginal/cervical acquisition, and detection, analysis, and communication of maternal uterine and maternal and fetal cardiac and fetal brain activity from electrical signals

• US 20020193670A1
• Filed: 05/28/2002
• Published: 12/19/2002
• Est. Priority Date: 05/29/2001
• Status: Active Grant

• Current Assignee: Reproductive Health Technologies, Inc.
• Original Assignee: Reproductive Health Technologies, Inc.
• Inventors: Maner, William L., Garfield, Robert E.
• Granted Patent: US 6,816,744 B2
• Time in Patent Office: Days
• US Class Current: 600/304
• CPC Class Codes: A61B 5/0011 Foetal or obstetric data
• CPC Class Codes: A61B 5/282 Holders for multiple electrodes for introduction into the body A61B5/287
• CPC Class Codes: A61B 5/344 Foetal cardiography
• CPC Class Codes: A61B 5/391 of genito-urinary organs
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: A61B 5/4362 Assessing foetal parameters
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7225 Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation A61B5/30, A61B5/316 take precedence; transformers for specific applications H01F38/00; amplifiers H03F
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/726 using Wavelet transforms

Abstract

The present invention presents a method and apparatus for recording and analyzing uterine electrical activity, or electromyography (EMG), from the surface of the abdomen, vagina, or cervix of a patient for the purpose of diagnosing contractile patterns of the uterus in pregnant and non-pregnant women, as well as for monitoring maternal and fetal ECG and fetal brain activity. The method and apparatus described include methods for the systematic detection, analysis, characterization and communication of information about electrical signals recorded from the abdominal/vaginal/cervical surface. The present invention provides data analysis techniques for analyzing the electrical data measured from the surface of a patient to characterize their uterine, abdominal, and cardiac muscle activity, as well as cardiac and brain activity of the fetus simultaneously or separately. These techniques and apparatus are appropriate for use in a clinic or through landline or wireless communication for use as a remote or home uterine/fetal monitoring system.

Claims

1. A method for characterizing uterine electrical activity, comprising:

a. applying an action potential measuring multi-polar arrangement of electrodes to an abdominal, vaginal or cervical surface of a patient;

b. isolating a system from the patient for analog filtering and amplifying an electrical signal as appropriate to isolate desired frequency components of said signal from background noise in said signal;

c. acquiring analog electrical uterine, maternal or fetal cardiac signals, fetal brain signals, or a combination thereof transmitted through said electrodes at a sampling frequency between about 0.5 and 1 kHz for a duration of time sufficient to record at least 3 bursts of action electrical potentials from said signals;

d. removing unwanted signal components through a multi-channel noise elimination scheme;

e. storing said acquired signals;

f. using detection algorithms to detect one or more attributes of said uterine, maternal or fetal cardiac activity, fetal brain activity, or combination thereof that are present in said acquired signals;

g. analyzing at least a portion of said activity, indicating parameters from at least one burst of the action potentials within the stored signals;

h. characterizing said activity from said patient based on said parameter analysis;

i. determining electrically when contractions occur and plotting the contractions;

j. simulating data output of a tocodynamometer or an intra-uterine pressure catheter; and

k. predicting when a patient will go into labor or delivery, or a combination thereof.

2. The method of claim 1, wherein simulating data output comprises simulating when contractions occur, plotting the contractions, displaying the strength of the contractions, or combinations thereof.

3. The method of claim 1, wherein isolating the system comprises isolating electrically or optically.

4. The method of claim 1, wherein removing unwanted signal components comprises using cross-correlation, auto-correlation, adaptive filtering, matched filtering, singular value decomposition, or combinations thereof.

5. The method of claim 1, wherein removing unwanted signal components further comprises determining phase relationships and modifying or maintaining said phase relationships between various channel combinations of the multi-polar arrangement of electrodes.

6. The method of claim 1, further comprising determining at least one of the following:

frequency, duration, amplitude, power density spectrum, wavelet transforms, Fourier transforms, rate of rise and fall of signals, spectral-temporal mapping, complexity, chaos, fractals, zero-crossings, randomness, non-linearity, likelihood ratios, statistical evaluations, Wigner-Ville or Heisenberg-Gabor analysis, or other joint time-frequency analysis of said uterine, maternal or fetal cardiac or fetal brain signal traces, bursts, or groups or series of action potentials, or combinations thereof.

7. The method of claim 1, further comprising determining at least one of the following:

frequency, duration, amplitude, power density spectrum, wavelet transforms, Fourier transforms, spectral-temporal mapping, complexity, chaos, fractals, zero-crossings, randomness, non-linearity, likelihood ratios, and statistical evaluations, Wigner-Ville or Heisenberg-Gabor analysis, or other joint time-frequency analysis of one or more individual action potentials in at least one of said uterine, maternal or fetal cardiac or fetal brain signal traces, bursts, or groups or series of action potentials, or combinations thereof.

8. The method of claim 1, further comprising using “

Fourier”

analysis techniques to determine at least one attribute of the electrical signals, comprising at least one of the following;

a. determining the mean frequency of a plurality of action potentials in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

b. determining the starting frequency of action potentials in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain electrical signals;

c. determining the ending frequency of action potentials in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

d. determining the mean frequency at which peaks occur in the power density spectrum of action potentials in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

e. determining the sum of the power across various frequencies in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

f. determining the power magnitude of various peaks in the power density spectrum of at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

g. determining the spectral-temporal map of one or more frequencies of at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

h. determining the energy of at least a portion of said acquired uterine, maternal, or fetal cardiac or fetal brain electrical signals or combinations thereof in a given range of frequencies by calculating the power of the portion of the signals corresponding to the range of frequencies desired and multiplying by the duration of that portion of the signal.

9. The method of claim 1, further comprising:

a. determining the rate of rise of amplitude in at least one action potential in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals; and

b. determining the rate of fall of amplitude in at least one action potential in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

10. The method of claim 1, further comprising using “

wavelet”

analysis techniques to determine one or more attributes of the electrical signals, comprising at least one of the following;

a. determining wavelet coefficients in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

b. determining spline functions in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

c. determining scales in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals; and

d. determining percent-energy distribution across wavelet scales in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

11. The method of claim 1, further comprising using “

complexity”

or “

randomness”

analysis techniques to determine one or more attributes of the electrical signals, comprising at least one of the following;

a. determining eigenvalues and eigenfunctions in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

b. determining primitive and exhaustive histories in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals; and

c. determining Limpel-Ziv (LZ) complexity measures in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

12. The method of claim 1, further comprising using “

zero-crossing”

analysis techniques to determine at least one attribute of the electrical signals, comprising at least one of the following;

a. determining zeroth-order, first-order, or higher-order crossing counts in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

13. The method of claim 1, further comprising using “

fractal”

analysis techniques to determine at least one attribute of the electrical signals, comprising at least one of the following;

a. determining the Hurst exponent for range/standard deviation (“

R/S”

), power spectrum, roughness-lengths, variograms, or wavelets methods, or combinations thereof, in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

b. determining the fractal dimension for R/S, power spectrum, roughness-lengths, variograms, or wavelets methods, or combinations thereof, in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

c. determining beta values for R/S, power spectrum, roughness-lengths, variograms, or wavelets methods, or combinations thereof, in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

14. The method of claim 1, further comprising using “

nonlinearity” and

“

chaos”

analysis techniques to determine one or more attributes of the electrical signals, comprising at least one of the following;

a. determining the entropy and approximate entropy in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals;

b. determining Kolmogorov-Smirnov statistics in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals; and

c. determining the chaoticity in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

15. The method of claim 1, further comprising using “

likelihood ratios”

analysis techniques to determine at least one attribute of the electrical signals, comprising;

a. determining the likelihood ratios and local generalized likelihood ratios using adaptive cumulative sums and dynamic cumulative sums in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

16. The method of claim 1, further comprising using statistical analysis techniques to determine one or more attributes of the electrical signals, comprising:

a. determining the means, standard deviations, variances, expected values, discreet or continuous random variables or ratios or functions of at least one of said statistical techniques in at least one of said uterine electrical bursts or maternal and fetal cardiac and fetal brain signals.

17. The method of claim 1, further comprising examining one or more trends in uterine activity indicating parameters over time.

18. The method of claim 17, further comprising displaying one or more trends in uterine activity indicating parameters over time.

19. The method of claim 17, further comprising predicting future uterine activity based upon one or more identified trends of examined uterine activity indicating parameters.

20. The method of claim 19, wherein said predicting future uterine activity comprises identifying situations in which treatment for pharmacologically inducing or inhibiting labor in said patient may be indicated.

21. The method of claim 19, wherein said predicting future uterine activity comprises:

a. comparing identified trends of a patient'"'"'s examined uterine activity with trend data collected from other patients in order to identify matching trends; and

b. predicting future uterine activity for a patient under examination based upon the trend behavior shown in the matching trends.

22. The method of claim 21, wherein said predicting is performed with the use of an expert system.

23. The method of claim 1, wherein said detection further comprises detecting the contraction of abdominal muscles in the patient.

24. The method of claim 1, further comprising determining joint time-frequency characteristics of said frequency components of bursts of uterine action potentials and maternal and fetal cardiac and fetal brain electrical signals.

25. The method of claim 1, further comprising monitoring a patient trans-abdominally, trans-vaginally, trans-cervically, or a combination thereof.

26. The method of claim 25, further comprising:

a. evaluating uterine activity;

b. simultaneously determining maternal and fetal heart activity;

c. simultaneously monitoring said fetal brain activity.

27. The method of claim 26, wherein monitoring said fetal brain activity comprises monitoring alpha, beta, theta, delta brain waves, or combinations thereof, and further comprising determining the frequency, amplitude and morphology of such brain waves.

28. The method of claim 26, wherein maternal and fetal heart activity comprises QRST complexes, heart rate, or a combination thereof.

29. The method of claim 1, further comprising:

a. stimulating a vagina of said patient while said uterine, maternal and fetal cardiac, and fetal brain signals are being stored; and

b. diagnosing labor as a function of said analysis of uterine activity.

30. The method of claim 29, further comprising plotting contractions, plotting contraction strength, assessing maternal and fetal heart activity, and fetal brain activity, and accurately predicting labor and delivery, without the need for using a tocodynamometer or an intra-uterine pressure catheter.

31. The method of claim 1, further comprising generating three dimensional mesh plots of said power density spectral characteristics, said mesh plots displaying energy levels versus frequency versus time of pregnancy.

32. A system for recording and analyzing uterine electrical activity for the abdominal, cervical or vaginal surface, comprising:

a. an arrangement of at least three electrodes forming a multi-polar arrangement adapted to measure electrical signals due to action potentials emitted from an abdominal, vaginal, or cervical surface of a patient under analysis to establish uterine, maternal and fetal cardiac, and fetal brain signals and each electrode further adapted to conduct an analog signal indicative of said action potentials, each electrode-pair being identified with one channel of data;

b. at least one analog filter adapted to remove unwanted signal components from the uterine, maternal and fetal cardiac, and fetal brain signals;

c. at least one differential, isolated, analog amplifier electrically coupled to said electrodes to receive and amplify signals indicative of said action potentials measured by said electrodes;

d. at least one analog to digital converter adapted to generate digital signals from the analog signals produced by the amplifiers;

e. at least one memory comprising sufficient storage capacity to store data resulting from a sampling of electrical signals at a sampling frequency of at least 100 Hz from a single patient for at least 1 hour, said memory adapted to receive a digital input from said analog to digital converter;

f. a computer programmed to import electrical signal data from multiple channels, or multiple differential signals from multiple electrode-pairs, formed from an array of said multi-polar arrangement of electrodes, and to perform mathematical functions on at least two of the potentials measured to generate multiple channels of data which are the result of at least one mathematical combination of said potentials from said mathematical functions;

g. said computer programmed to perform multi-channel filtering on at least one of the channels of data to remove unwanted noise components common to one or more channels;

h. said computer programmed to analyze frequency, duration, amplitude, power density spectrum, wavelet transforms, Fourier transforms, rate of rise and fall of signals, spectral-temporal mapping, complexity, chaos, fractals, zero-crossings, randomness, non-linearity, likelihood ratios, statistical evaluations, Wigner-Ville or Heisenberg-Gabor analysis, or other joint time-frequency analysis on the uterine, cardiac, and brain signals acquired, said computer further being adapted to characterize uterine, maternal and fetal cardiac, and fetal brain activity based upon said analysis.

33. The system of claim 32, wherein said system is adapted to plot contractions, plot contraction strength, assess maternal and fetal heart activity, and fetal brain activity, and accurately predict labor and delivery, without the need for using a tocodynamometer or an intra-uterine pressure catheter.

34. The system of claim 32, wherein said multi-channel filtering comprises matched filtering, adaptive filtering, auto-correlation, cross-correlation filtering, singular value decomposition techniques, or combinations thereof.

35. The system of claim 32, wherein said computer is adapted to determine and modify or maintain phase relationships between multiple channel combinations to remove said unwanted noise components.

36. The system of claim 32, wherein said mathematical functions are optionally chosen by an operator operating said computer.

37. The system of claim 32, wherein said mathematical functions are programmed into said computer for automatic execution thereof.

38. The system of claim 32, wherein said computer is adapted to identify abdominal muscle contractions.

39. The system of claim 32, wherein said memory is adapted to store said electrical signals in discrete, predetermined frequency ranges.

40. The system of claim 32, wherein said computer is further adapted to determine a mean frequency, starting frequency, and ending frequency of a plurality of action potentials.

41. The system of claim 32, wherein said electrical signal measuring electrodes comprise needle electrodes, surface electrodes, vaginally-placed, or cervically-located electrodes, or a combination thereof.

42. The system of claim 32, further comprising a monitor coupled to said computer, said monitor adapted to display at least a portion of said electrical signals.

43. A remote uterine monitoring system for remotely characterizing uterine activity, comprising:

a. at least three electrodes forming a multi-polar arrangement adapted to measure electrical signals of action potentials emitted from an abdominal, vaginal, or cervical surface of a patient under analysis and further adapted to emit an analog signal indicative of action potentials measured by said electrodes;

b. an isolation system comprising analog filters adapted to remove unwanted signal components from the uterine, maternal and fetal cardiac, and fetal brain signals;

c. at least one analog differential amplifier coupled to said electrodes, isolated from the patient optically, electrically, or by other standard means, and adapted to receive and amplify signals indicative of action potentials measured by said electrodes;

d. at least one analog to digital converter adapted to produce digital signals from the analog signals produced by the amplifiers;

e. a computer programmed to import electrical signal data from multiple channels, or multiple differential signals from multiple electrode-pairs, formed from an array of said multi-polar arrangement of electrodes, and to perform mathematical functions on two or more of the channels to generate channels of data, which are the result of such mathematical combination of said potentials;

f. said computer adapted to perform multi-channel filtering on said channels of data to remove unwanted noise components common to one or more channels;

g. said computer programmed to analyze the frequency, duration, amplitude, power density spectrum, wavelet transforms, Fourier transforms, rate of rise and fall of signals, spectral-temporal mapping, complexity, chaos, fractals, zero-crossings, randomness, non-linearity, likelihood ratios, statistical evaluations, Wigner-Ville or Heisenberg-Gabor analysis, or other joint time-frequency analysis on the uterine, cardiac, and brain signals acquired, said expert system further being adapted to characterize maternal uterine, maternal and fetal cardiac, and fetal brain activity based upon said analysis;

h. at least one data transmission system, coupled to said computer, adapted to transmit uterine, maternal and fetal cardiac, and fetal brain signals, processed or unprocessed, to a remote location from said computer via a telecommunications link;

i. at least one remote analog to digital converter coupled to said data transmission system to receive an analog input from said amplifier indicative of action potentials measured by said electrodes;

j. at least one memory comprising sufficient storage capacity to store data resulting from a sampling of trans-abdominal, trans-vaginal, trans-cervical electrical signals, or a combination thereof, at a sampling frequency of at least 100 Hz from a single patient for at least 1 hour, said memory adapted to receive a digital input from said analog to digital converter indicative of action potential signals received by said converter;

k. at least one receiver adapted to collect the uterine, cardiac, or brain data, processed or unprocessed, which is transmitted from said computer at the site of the patient; and

l. at least one remote computer located remote from the patient and coupled to said receiver to import received data from the site of the patient and programmed to analyze the frequency, duration, amplitude, power density spectrum, wavelet transforms, Fourier transforms, rate of rise and fall of signals, spectral-temporal mapping, complexity, chaos, fractals, zero-crossings, randomness, non-linearity, likelihood ratios, statistical evaluations, Wigner-Ville or Heisenberg-Gabor analysis, or other joint time-frequency analysis on the uterine, cardiac, and brain signals acquired, said remote computer further being capable of characterizing maternal uterine, maternal and fetal cardiac, and fetal brain activity based upon said analysis.

44. The system of claim 43, wherein said system is adapted to plot contractions, plot contraction strength, assess maternal and fetal heart activity, and fetal brain activity, and accurately predict labor and delivery, without the need for using a tocodynamometer or an intra-uterine pressure catheter.

45. The system of claim 43, wherein said filtering comprises matched filtering, adaptive filtering, auto-correlation and/or cross-correlation, or singular value decomposition filtering techniques, or combinations thereof

46. The system of claim 43, wherein at least one of said computers is adapted to determine and modify or maintain phase relationships between various channel combinations to reduce said unwanted noise components.

47. The system of claim 43, wherein said telecommunications link comprises a wireless communication link.