Quantitative fetal heart rate and cardiotocographic monitoring system and related method thereof

• US 7,519,417 B2
• Filed: 02/12/2004
• Issued: 04/14/2009
• Est. Priority Date: 02/12/2003
• Status: Active Grant

• Current Assignee: University of Virginia Patent Foundation (University of Virginia)
• Original Assignee: University of Virginia Patent Foundation (University of Virginia)
• Inventors: Ferguson, James E. II, Moorman, J. Randall, Griffin, M. Pamela
• Primary Examiner(s): Manuel; George
• Application Number:
  US10/545,257
• Publication Number:
  US 20060074329A1
• Time in Patent Office: 1,888 Days
• Field of Search: 600/453, 600/509, 600/511, 600/591
• US Class Current: 600/511
• 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 5/352 Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• 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: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A method, system, and computer program product are provide for, among other things, quantitative analysis of heart rate characteristics from fetal heart rate and cardiotocogram monitors that gives information about the well-being of the fetus and the risk of poor fetal outcome. The method comprises (a) continuously measuring fetal heart rate and cardiotocographic characteristics and (b) identifying at least one characteristic abnormality in the heart rate characteristics that is associated with fetal distress. Benefits are appreciated by the fetus and the mother and during the antepartum and intrapartum periods.

Claims

1. A computer method for evaluating fetal well-being and predicting fetal outcome, said method comprising:

a) obtaining simultaneous recordings of fetal heart rate and maternal uterine pressure;

b) calculating one or more parameters;

i. cross-correlation of the fetal heart rate and the uterine pressure,

ii. Lomb periodogram of the fetal heart rate,

iv. sample entropy of the fetal heart rate,

v. sample asymmetry of the fetal heart rate, and

vi. one or more of;

second, third and fourth higher moments, and

percentiles of interest of the fetal heart rate; and

c) determining heart rate characteristic of fetal distress by comparing one of said parameters to a predetermined threshold or mathematical model.

2. The method of claim 1, wherein the calculating step is carried out using a multivariable statistical analysis.

3. The method of claim 2, wherein said multivariable statistical analysis is selected from at least one of but not limited to regression models, nearest-neighbor models, and neural networks, and any combination thereof.

4. The method of claim 1, wherein the implementation of percentiles of interest include 10th, 50th and/or 90th.

5. The method of claim 1, wherein the cross-correlation analysis comprises amplitude and timing relative to uterine contractions of accelerations and decelerations of the fetal heart rate.

6. The method of claim 1, wherein the cross-correlation analysis comprises:

normalizing uterine contraction data, referenced as TOCO, as mean of 0 and standard deviation of 1 according to the formula;

T=[TOCO−

mean(TOCO)]/std(TOCO),

calculating the cross correlation between T and the raw HR data H according the formula;

$C<br><br>\left(l\right)=\frac{1}{N}<br><br>\underset{n=0}{\overset{N-1}{\sum <br><br>}}<br><br>T<br><br>\left(n\right)<br><br><br><br>H<br><br>\left(n=l\right),l=0,1,2,\mathrm{\dots <br><br>}<br><br><br><br>N-1,$

wherein C(l) is the cross correlation at lag l.

7. The method of claim 6, wherein C(l) will reach a minimum value for the value of l that maximally aligns the two traces;

and

if the contraction and the deceleration occur simultaneously, the minimum value occurs at l=0.

8. The method of claim 1, wherein the Lomb periodogram is the variance of the fetal heart rate that is attributed to very low frequency (VLF), low-frequency (LF), and high-frequency (HF) oscillations.

9. The method of claim 1, wherein the Lomb periodogram of a time series with N points |h_j, t_j:

0=j=N−

1| is calculated according to the formula;

$P_N<br><br>\left(f\right)=\frac{1}{N}<br><br>\left(\frac{{\left[\underset{j}{\sum <br><br>}<br><br>\left(h_j-\stackrel{\_}{h}\right)<br><br><br><br>\cos <br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)\right]}^2}{\underset{j}{\sum <br><br>}<br><br>{\cos }^2<br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)}+\frac{{\left[\underset{j}{\sum <br><br>}<br><br>\left(h_j-\stackrel{\_}{h}\right)<br><br><br><br>\sin <br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)\right]}^2}{\underset{j}{\sum <br><br>}<br><br>{\sin }^2<br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)}\right),$

where τ

satisfies the relation

$\tan <br><br>\left(4<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br><br><br>\mathrm{\tau <br><br>}\right)=\frac{\underset{j}{\sum <br><br>}<br><br>\sin <br><br>\left(4<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>{\mathrm{ft}}_j\right)}{\underset{j}{\sum <br><br>}<br><br>\cos <br><br>\left(4<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>{\mathrm{ft}}_j\right)}.$

10. The method of claim 1, wherein the sample entropy of a time series x₁,x₂, . . . ,x_N, wherein x_m(i) denote the m points x_i,x_i+1, . . . ,x_i+m−

1 which defines a template and can be considered a vector of length m;

wherein when all the components of the vector x_m(j) are within a distance r of x_m(i), there is a template match;

wherein B_i denotes the number of template matches with x_m(i);

wherein A_i denotes the number of template matches with x_m+1(i);

wherein p_i=A_i/B_i is an estimate of the conditional probability that the point x_j+m is within r of x<sub>i+m−

1</sub> given that x_m(j) matches x_m(i); and

wherein sample entropy is defined according to the formula;

$\mathrm{SampEn}<br><br>\left(m,r,N\right)=-\log <br><br>\left(\underset{i=1}{\overset{N-m}{\sum <br><br>}}<br><br>A_i/\underset{i=1}{\overset{N-m}{\sum <br><br>}}<br><br>B_i\right).$

11. The method of claim 1, wherein the sample asymmetry comprises:

quantifying deviations of an inter-beat interval with respect to the median towards an increase referred to as R2 and towards a decrease referred to as R1;

compute r₁(x_i)=r(x_i) if x_i<

m;

0 otherwise, and r₂(x_i)=r(x_i) if x_i>

m;

0 otherwise for each inter-beat reading x_i;

wherein R₁ and R₂ are computed as;

$\begin{array}{ccc}{R}_1=\frac{1}{n}<br><br>\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>{r_1<br><br>\left(x_i\right)}^2& \mathrm{and}& R_2=\frac{1}{n}<br><br>\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>{r_2<br><br>\left(x_i\right)}^2,\end{array}<br><br>\mathrm{and}$

wherein the sample asymmetry is determined by the formula R₂/R₁.

12. The method of claim 1, wherein the second and/or higher moments are calculated with the data set x₁,x₂, . . . ,x_N, according to the formula:

${\mathrm{\mu <br><br>}}_n=\frac{1}{n}<br><br>\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>x_i^r.$

13. The method of claim 1, wherein at least one of the following is provided:

earlier diagnosis of intra-amniotic infection;

categorization of fetus health or fetus risk;

and diagnosis of intra-amniotic, or any combination thereof.

14. The method of claim 1, wherein the method is applied during antepartum period or intrapartum period or both antepartum period and intrapartum period.

15. The apparatus of claim 1, wherein the second and/or higher moments are calculated with the data set x₁,x₂, . . . ,x_N, according to the formula:

${\mathrm{\mu <br><br>}}_n=\frac{1}{n}<br><br><br><br>\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>x_i^r.$

16. An apparatus for evaluating fetal well-being and predicting fetal outcome, said apparatus comprising:

a) a monitoring device, which monitors the fetal heart rate and maternal uterine pressure;

b) a microprocessor, said microprocessor performing the steps of;

calculating one or more parameters;

i. cross-correlation of the fetal heart rate and the uterine pressure,

ii. Lomb periodogram of the fetal heart rate,

iii. sample entropy of the fetal heart rate,

iv. sample asymmetry of the fetal heart rate, and

v. one or more of;

second, third and fourth higher moments, and

percentiles of interest of the fetal heart rate; and

determining heart rate characteristics of fetal distress by comparing one of said parameters to a predetermined threshold or mathematical model.

17. The apparatus of claim 16, wherein the calculating step is carried out using a multivariable statistical analysis.

18. The apparatus of claim 17, wherein said multivariable statistical analysis is selected from at least one of but not limited to regression models, nearest-neighbor models, and neural networks, and any combination thereof.

19. The apparatus of claim 16, wherein the implementation of percentiles of interest include 10th, 50th and/or 90th.

20. The apparatus of claim 16, wherein the cross-correlation analysis comprises amplitude and timing relative to uterine contractions of accelerations and decelerations of the fetal heart rate.

21. The apparatus of claim 16, wherein the cross-correlation analysis comprises:

normalizing uterine contraction data, referenced as TOCO, as mean of 0 and standard deviation of 1 according to the formula;

T=[TOCO−

mean(TOCO)]/std(TOCO),

calculating the cross correlation between T and the raw HR data H according the formula;

$C<br><br>\left(l\right)=\frac{1}{N}<br><br>\underset{n=0}{\overset{N-1}{\sum <br><br>}}<br><br>T<br><br>\left(n\right)<br><br><br><br>H<br><br>\left(n=1\right),1=0,1,2,\mathrm{\dots <br><br>}<br><br><br><br>N-1,$

wherein C(l) is the cross correlation at lag l.

22. The apparatus of claim 21, wherein C(l) will reach a minimum value for the value of l that maximally aligns the two traces;

and

if the contraction and the deceleration occur simultaneously, the minimum value occurs at l=0.

23. The apparatus of claim 16, wherein the Lomb periodogram is the variance of the fetal heart rate that is attributed to very low frequency (VLF), low-frequency (LF), and high-frequency (HF) oscillations.

24. The apparatus of claim 16, wherein the Lomb periodogram of a time series with N points |h_j, t_j:

0=j=N−

1 | is calculated according to the formula;

$P_N<br><br>\left(f\right)=\frac{1}{N}<br><br>\left(\frac{{\left[\underset{j}{\sum <br><br>}<br><br>\left(h_j-\stackrel{\_}{h}\right)<br><br><br><br>\cos <br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)\right]}^2}{\underset{j}{\sum <br><br>}<br><br>{\cos }^2<br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)}+\frac{{\left[\underset{j}{\sum <br><br>}<br><br>\left(h_j-\stackrel{\_}{h}\right)<br><br><br><br>\sin <br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)\right]}^2}{\underset{j}{\sum <br><br>}<br><br>{\sin }^2<br><br>\left(2<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br>\left(t_j-\mathrm{\tau <br><br>}\right)\right)}\right),$

where τ

satisfies the relation

$\tan <br><br>\left(4<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>f<br><br><br><br>\mathrm{\tau <br><br>}\right)=\frac{\underset{j}{\sum <br><br>}<br><br>\sin <br><br>\left(4<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>{\mathrm{ft}}_j\right)}{\underset{j}{\sum <br><br>}<br><br>\cos <br><br>\left(4<br><br><br><br>\mathrm{\pi <br><br>}<br><br><br><br>{\mathrm{ft}}_j\right)}.$

25. The apparatus of claim 16, wherein the sample entropy of a time series x₁,x₂, . . . ,x_N, wherein x_m(i) denote the m points x_i,x_i+1, . . . ,x_i+m−

1 which defines a template and can be considered a vector of length m;

wherein when all the components of the vector x_m(j) are within a distance r of x_m(i), there is a template match;

wherein B_i denotes the number of template matches with x_m(i);

wherein A_i denotes the number of template matches with x_m+1(i);

wherein p_i=A_i/B_i is an estimate of the conditional probability that the point x_j+m is within r of x<sub>i+m−

1</sub> given that x_m(j) matches x_m(i); and

wherein sample entropy is defined according to the formula;

$\mathrm{SampEn}<br><br>\left(m,r,N\right)=-\log <br><br>\left(\underset{i=1}{\overset{N-m}{\sum <br><br>}}<br><br>A_i/\underset{i=1}{\overset{N-m}{\sum <br><br>}}<br><br>B_i\right).$

26. The apparatus of claim 16, wherein the sample asymmetry comprises:

quantifying deviations of an inter-beat interval with respect to the median towards an increase referred to as R2 and towards a decrease referred to as R1;

compute r₁(x_i)=r(x_i) if x_i<

m;

0 otherwise, and r₂(x_i)=r(x_i) if x_i>

m;

0 otherwise for each inter-beat reading x_i;

wherein R₁ and R₂ are computed as;

$\begin{array}{ccc}{R}_1=\frac{1}{n}<br><br>\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>{r_1<br><br>\left(x_i\right)}^2& \mathrm{and}& R_2=\frac{1}{n}<br><br>\underset{i=1}{\overset{n}{\sum <br><br>}}<br><br>{r_2<br><br>\left(x_i\right)}^2,\end{array}<br><br>\mathrm{and}$

wherein the sample asymmetry is determined by the formula R₂/R₁.

27. The apparatus of claim 16, wherein at least one of the following is provided:

earlier diagnosis of intra-amniotic infection;

categorization of fetus health or fetus risk; and

diagnosis of intra-amniotic, or any combination thereof.

28. The apparatus of claim 16, wherein the method is applied during antepartum period or intrapartum period or both antepartum period and intrapartum period.

29. A computer program product comprising computer usable medium having computer logic for enabling at lease one processor in a computer system to evaluate fetal well-being and predicting fetal outcome based on a monitoring device, which monitors the fetal heart rate and maternal uterine pressure, said computer logic comprising:

calculating one or more parameters;

i. cross-correlation of the fetal heart rate and the uterine pressure,

ii. Lomb periodogram of the fetal heart rate,

iii. sample entropy of the fetal heart rate,

iv. sample asymmetry of the fetal heart rate, and

v. one or more of;

second, third and fourth higher moments; and

percentiles of interest of the fetal heart rate; and

determining heart rate characteristic of fetal distress by comparing one of said parameters to a predetermined threshold or mathematical model.