Statistical method for assessing autonomic balance

• US 7,069,070 B2
• Filed: 05/12/2003
• Issued: 06/27/2006
• Est. Priority Date: 05/12/2003
• Status: Expired due to Fees

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Berger, Ronald D., Carlson, Gerrard M.
• Primary Examiner(s): Schaetzle, Kennedy
• Application Number:
  US10/436,876
• Publication Number:
  US 20040230241A1
• Time in Patent Office: 1,142 Days
• Field of Search: 600/509, 600/481, 600/513, 600/519, 600/521
• US Class Current: 600/519
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/4035 Evaluating the autonomic nervous system
• CPC Class Codes: A61N 1/3622 comprising two or more electrodes co-operating with different heart regions

Abstract

A computationally efficient method for assessing a subject'"'"'s autonomic balance by measurement of heart rate variability is disclosed which is particularly suitable for implementation by an implantable medical device. Statistical surrogates are used to represent frequency components of an RR time series. A ratio of the low frequency component to the high frequency component may then be estimated to assess the subject'"'"'s autonomic balance.

Claims

1. A method for operating an implantable medical device in order to assess a subject'"'"'s autonomic balance, comprising:

sensing electrical activity in a ventricle and generating a ventricular sense signal when the sensed electrical activity exceeds a predetermined threshold;

measuring time intervals between each pair of successive ventricular senses, referred to as RR intervals, over a predetermined long-term period, where N is the total number of RR interval measurements during the predetermined long-term period and the measured RR intervals RR₁ through RR_N are referred to as an RR time series;

computing mean values M_x1 through M_xL of successive x-second segments of the RR time series, where x is a predetermined number and L is the total number of such x-second segments in the RR time series, and computing a variance of the mean values M_x1 through M_xL, referred to as [SD_x]²;

computing mean values M_y1 through M_yK of successive y-second segments of the RR time series, where y is a predetermined number greater than x and K is the total number of such y-second segments in the RR time series, and computing a variance of the mean values M_y1 through M_yK, referred to as [SD_y]²;

computing a mean value of squared successive differences between the RR intervals in the RR time series, referred to as [rMSSD]²; and

,

estimating a ratio of the low frequency content in the RR time series between approximately 1/x Hz and 1/y Hz and higher frequency content in the RR time series, referred to as LF/HF, as;

LF/HF=K([SD_x]²−

[SD_y]²)/[rMSSD]²

wherein K is a defined constant and LF/HF is reflective of the subject'"'"'s autonomic balance.

2. The method of claim 1 further comprising:

defining an integral number T of RR interval bins A₁ through A_T representing RR interval values I₁ through I_T;

assigning each computed mean value M_x1 through M_xL of the successive x-second segments of the RR time series to a corresponding one of the RR interval bins A₁ through A_T;

counting the number of computed mean values assigned to each RR interval bin A₁ through A_T and dividing each such number by L to derive a relative frequency FX_i for each interval value I_i; and

,

computing [SD_x]² as

[SD_x]²=Σ

(I_i)²FX_i−

(Σ

(I_i)FX_i)²

where the summations are carried out from i=1 to T.

3. The method of claim 1 further comprising:

defining an integral number S of RR interval bins B₁ through B_S representing RR interval values I₁ through I_S;

assigning each computed mean value M_y1 through M_yK of the successive y-second segments of the RR time series to a corresponding one of the RR interval bins B₁ through B_S;

counting the number of computed mean values assigned to each RR interval bin B₁ through B_S and dividing each such number by K to derive a relative frequency FY_i for each interval value I_i; and

,

computing [SD_y]² as

[SD_y]²=Σ

(I_i)²FY_i−

(Σ

(I_i)FY_i)²

where the summations are carried out from i=1 to S.

4. The method of claim 1 further comprising:

defining an integral number W of RR interval difference bins C₁ through C_W representing RR interval difference values D₁ through D_W;

computing an interval difference between each pair of RR intervals in the RR time series as (RR₂−

RR₁) through (RR_N−

RR<sub>N−

1</sub>);

assigning each of the computed interval differences between RR intervals in the RR time series to a corresponding one of the RR interval difference bins C₁ through C_W;

counting the number of computed interval differences assigned to each RR interval difference bin C₁ through C_W and dividing each such number by N−

1 to derive a relative frequency FD_i for each interval difference D_i; and

,

computing [rMSSD]² as

[rMSSD]²=Σ

(D_i)²FD_i

where the summation is carried out from i=1 to W.

5. The method of claim 1 further comprising:

cumulatively summing each computed mean value M_xi;

cumulatively summing each computed mean value M_xi squared;

computing [SD_x]² as;

[SD_x]²=(1/L)Σ

(M_xi)²−

((1/L)Σ

M_xi)²

where the summations are carried out from i=1 to L by the cumulative summing operations.

6. The method of claim 1 further comprising:

cumulatively summing each computed mean value M_yi;

cumulatively summing each computed mean value M_yi squared;

computing [SD_y]² as;

[SD_y]²=(1/L)Σ

(M_yi)²−

((1/L)Σ

M_yi)²

where the summations are carried out from i=1 to K by the cumulative summing operations.

7. The method of claim 1 further comprising:

cumulatively summing each computed interval difference value (RR_i+1−

RR_i) squared;

computing [rMSSD]² as;

[rMSSD]²=(1/(N−

1))Σ

(RR_i+1−

RR_i)²

where the summation is carried out from i=1 to N−

1 by the cumulative summing operation.

8. The method of claim 1 wherein the predetermined long-term period is 24 hours.

9. The method of claim 1 wherein the predetermined numbers x and y are 7 and 25, respectively, such that the estimated LF/HF represents a ratio of the low frequency content in the RR time series between approximately 0.04 Hz and 0.15 Hz and the high frequency content in the RR time series between approximately 0.15 Hz and 0.4 Hz.

10. The method of claim 1 further comprising computing a moving average of estimated LF/HF ratios over successive long-term time periods.

11. A cardiac rhythm management device, comprising:

a sensing channel for sensing electrical activity in a ventricle;

a controller interfaced to the sensing channel which detects a ventricular sense when the sensed electrical activity exceeds a predetermined threshold;

wherein the controller is programmed with executable instructions for;

measuring time intervals between each pair of successive ventricular senses, referred to as RR intervals, over a predetermined long-term period, where N is the total number of RR interval measurements during the predetermined long-term period and the measured RR intervals RR₁ through RR_N are referred to as an RR time series;

computing mean values M_x1 through M_xL of successive x-second segments of the RR time series, where x is a predetermined number and L is the total number of such x-second segments in the RR time series, and computing a variance of the mean values M_x1 through M_xL, referred to as [SD_x]²;

computing mean values M_y1 through M_yK of successive y-second segments of the RR time series, where y is a predetermined number greater than x and K is the total number of such y-second segments in the RR time series, and computing a variance of the mean values M_y1 through M_yK, referred to as [SD_y]²;

computing a mean value of squared successive differences between the RR intervals in the RR time series, referred to as [rMSSD]²; and

,

estimating a ratio of the low frequency content in the RR time series between approximately 1/x Hz and 1/y Hz and higher frequency content in the RR time series, referred to as LF/HF, as;

LF/HF=K([SD_x]²−

[SD_y]²)/[rMSSD]²

wherein K is a defined constant and LF/HF is reflective of the subject'"'"'s autonomic balance.

12. The device of claim 11 wherein the controller is further programmed with instructions for:

defining an integral number T of RR interval bins A₁ through A_T representing RR interval values I₁ through I_T;

assigning each computed mean value M_x1 through M_xL of the successive x-second segments of the RR time series to a corresponding one of the RR interval bins A₁ through A_T;

counting the number of computed mean values assigned to each RR interval bin A₁ through A_T and dividing each such number by L to derive a relative frequency FX_i for each interval value I_i; and

,

computing [SD_x]² as

[SD_x]=Σ

(I_i)²FX_i−

Σ

(I_i)FX_i)²

where the summations are carried out from i=1 to T.

13. The device of claim 11 wherein the controller is further programmed with instructions for:

defining an integral number S of RR interval bins B₁ through B_S representing RR interval values I₁ through I_S;

assigning each computed mean value M_y1 through M_yK of the successive y-second segments of the RR time series to a corresponding one of the RR interval bins B₁ through B_S;

counting the number of computed mean values assigned to each RR interval bin B₁ through B_S and dividing each such number by K to derive a relative frequency FY_i for each interval value I_i; and

,

computing [SD_y]² as

[SD_y]²=Σ

(I_i)²FY_i−

(Σ

(I_i)F

where the summations are carried out from i=1 to S.

14. The device of claim 11 wherein the controller is further programmed with instructions for:

defining an integral number W of RR interval difference bins C₁ through C_W representing RR interval difference values D₁ through D_W;

computing an interval difference between each pair of RR intervals in the RR time series as (RR₂−

RR₁) through (RR_N−

RR<sub>N−

1</sub>);

assigning each of the computed interval differences between RR intervals in the RR time series to a corresponding one of the RR interval difference bins C₁ through C_W;

counting the number of computed interval differences assigned to each RR interval difference bin C₁ through C_W and dividing each such number by N−

1 to derive a relative frequency FD_i for each interval difference D_i; and

,

computing [rMSSD]² as

[rMSSD]²=Σ

(D_i)²FD_i

where the summation is carried out from i=1 to W.

15. The device of claim 11 wherein the controller is further programmed with instructions for:

cumulatively summing each computed mean value M_xi;

cumulatively summing each computed mean value M_xi squared;

computing [SD_x]² as;

[SD_x]²=Σ

(1/L)Σ

(M_xi)²−

((1/L)Σ

M_xi)²

where the summations are carried out from i=1 to L by the cumulative summing operations.

16. The device of claim 11 wherein the controller is further programmed with instructions for:

cumulatively summing each computed mean value M_yi;

cumulatively summing each computed mean value M_yi squared;

computing [SD_y]² as;

[SD_y]=(1/L)Σ

(M_yi)²−

((1/L)Σ

M_yi)²

where the summations are carried out from i=1 to K by the cumulative summing operations.

17. The device of claim 11 wherein the controller is further programmed with instructions for:

cumulatively summing each computed interval difference value (RR_i+1−

RR_i) squared;

computing [rMSSD]² as;

[rMSSD]²=(1/(N−

1))Σ

(RR_i+1−

RR_i)²

where the summation is carried out from i=1 to N−

1 by the cumulative summing operation.

18. The device of claim 11 wherein the predetermined long-term period is 24 hours.

19. The device of claim 11 wherein the predetermined numbers x and y are 7 and 25, respectively, such that the estimated LF/HF represents a ratio of the low frequency content in the RR time series between approximately 0.04 Hz and 0.15 Hz and the high frequency content in the RR time series between approximately 0.15 Hz and 0.4 Hz.

20. The device of claim 11 wherein the controller is further programmed with instructions for computing a moving average of estimated LF/HF ratios over successive long-term time periods.