Method and apparatus for estimating systolic and mean pulmonary artery pressures of a patient
First Claim
1. Method of estimating systolic and mean pulmonary artery pressures of a patient, comprising the steps of:
- (a) producing an electric signal xs(t) representative of heart sounds of the patient;
(b) extracting second heart sound S2(t) from the signal produced in step (a);
(c) extracting pulmonary and aortic components P2(t) and A2(t) from S2(t);
(d) extracting a signal representative of mean cardiac interval from the signal produced in step (a);
(e) correlating the pulmonary and aortic components P2(t) and A2(t) to obtain a cross correlation function;
(f) measuring a splitting interval as the time of occurrence of the maximal value of the cross correlation function obtained in step (e);
(g) producing a normalized splitting interval by dividing the splitting interval obtained in step (f) by the mean cardiac interval obtained in step (d); and
(h) estimating the systolic and mean pulmonary artery pressures using of predetermined regressive functions, said predetermined regressive functions describing relationships between the normalized splitting interval and the systolic and mean pulmonary artery pressures.
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Abstract
The method of estimating systolic and mean pulmonary artery pressures of a patient, comprising the steps of (a) producing an electric signal xs(t) representative of heart sounds of the patient; (b) extracting second heart sound S2(t) from the signal produced in step (a); (c) extracting pulmonary and aortic components P2(t) and A2(t) from S2(t); (d) extracting a signal representative of mean cardiac interval; (e) correlating the pulmonary and aortic components P2(t) and A2(t) to obtain a cross correlation function; (f) measuring a splitting interval of the cross correlation function obtained in step (e); (g) producing a normalized splitting interval; and (h) estimating the systolic and mean pulmonary artery pressures by means of predetermined regressive functions. The present invention also relates to an apparatus for estimating systolic and mean pulmonary artery pressures of a patient.
984 Citations
9 Claims
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1. Method of estimating systolic and mean pulmonary artery pressures of a patient, comprising the steps of:
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(a) producing an electric signal xs(t) representative of heart sounds of the patient;
(b) extracting second heart sound S2(t) from the signal produced in step (a);
(c) extracting pulmonary and aortic components P2(t) and A2(t) from S2(t);
(d) extracting a signal representative of mean cardiac interval from the signal produced in step (a);
(e) correlating the pulmonary and aortic components P2(t) and A2(t) to obtain a cross correlation function;
(f) measuring a splitting interval as the time of occurrence of the maximal value of the cross correlation function obtained in step (e);
(g) producing a normalized splitting interval by dividing the splitting interval obtained in step (f) by the mean cardiac interval obtained in step (d); and
(h) estimating the systolic and mean pulmonary artery pressures using of predetermined regressive functions, said predetermined regressive functions describing relationships between the normalized splitting interval and the systolic and mean pulmonary artery pressures. - View Dependent Claims (2, 3, 4, 5, 6)
(i) determining a Wigner-Ville distribution Ws(t,f) in view of time t and frequency f of the signal S2(t) produced in step (b) using the following function;
(ii) filtering Ws(t,f) obtained in step (i) by means of the following function to obtain a masked time frequency representation mA(t,f) of the aortic component A2(t);
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3. Method according to claim 2 wherein the low-pass filtering in step (v) (C) has a cut-off frequency selected within the range of 16 to 64 Hz and the low-pass filtering in step (xii) (C) has a cut-off frequency selected within the range of 16 to 64 Hz.
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4. Method according to claim 3 where determining the cut-off frequency of the low-pass filter in step (v) (C) comprises the steps of:
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(1) transforming the S2(t) signal into frequency domain using a Discrete Fourier Transform to obtain a transform;
(2) determining a power spectrum of the transform obtained in step (1);
(3) determining a main-low frequency energy lobe of the power spectrum;
(4) determining the cut-off frequency as a frequency corresponding to 5% of energy of the main-low frequency energy lobe;
(5) determining frequency bins of the S2(t) signal using a Discrete Fourier Transform;
(6) multiplying real and imaginary parts of frequency bins which are below the cut-off frequency by 1.00;
(7) multiplying real and imaginary parts of the of a frequency bin corresponding to the cut-off frequency by 0.70;
(8) multiplying real and imaginary parts of the of a first frequency bin above the cut-off frequency by 0.20;
(9) multiplying real and imaginary parts of the of a second frequency bin above the cut-off frequency by 0.02;
(10) multiplying real and imaginary parts of all other of frequency bins which are above the cut-off frequency of the low pass filter by 0.00; and
(11) applying inverse Discrete Fourier Transform to the results of steps 6, 7, 8, 9 and 10 to obtain representations in the time domain.
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5. Method according to claim 3 where determining the cut-off frequency of the low-pass filter in step (xii) (C) comprises the steps of:
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(1) transforming the difference signal XD(t) into frequency domain using a Discrete Fourier Transform to obtain a transform;
(2) determining a power spectrum of the transform obtained in step (1);
(3) determining a main-low frequency energy lobe of the power spectrum;
(4) determining the cut-off frequency as a frequency corresponding to 5% of energy of the main-low frequency energy lobe;
(5) determining frequency bins of the difference signal XD(t) using a Discrete Fourier Transform;
(6) multiplying real and imaginary parts of frequency bins which are below the cut-off frequency by 1.00;
(7) multiplying real and imaginary parts of a frequency bin corresponding to the cut-off frequency by 0.70;
(8) multiplying real and imaginary parts of the of a first frequency bin above the cut-off frequency by 0.20;
(9) multiplying real and imaginary parts of the of a second frequency bin above the cut-off frequency by 0.02;
(10) multiplying the real and imaginary parts of all other of the frequency bins which are above the cut-off frequency of the low pass filter by 0.00; and
(11) applying inverse Discrete Fourier Transform to the results of steps 6, 7, 8, 9 and 10 to obtain representations in the time domain.
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6. Method according to claim 1 where the predetermined regressive functions have the form:
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7. Apparatus for estimating systolic and mean pulmonary artery pressures of a patient, comprising:
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first producing means for producing an electric signal xS(t) representative of heart sounds of the patient;
first extracting means for extracting second heart sound S2(t) from the signal produced by the first producing means;
second extracting means for extracting pulmonary and aortic components P2(t) and A2(t) from S2(t) extracted by the first extracting means;
third extracting means for extracting a signal representative of mean cardiac interval from the signal produced by the first producing means;
correlating means for correlating the pulmonary and aortic components P2(t) and A2(t) to obtain a cross correlation function;
measuring means for measuring a splitting interval as the time of occurrence of the maximal value of the cross correlation function obtained by the correlating means;
second producing means for producing a normalized splitting interval by dividing the splitting interval obtained from the measuring means by the mean cardiac interval obtained from the third extracting means; and
estimating means for estimating the systolic and mean pulmonary artery pressures by means of predetermined regressive functions said predetermined regressive functions describing relationships between the normalized splitting interval and the systolic and mean pulmonary artery pressures. - View Dependent Claims (8, 9)
first determining means for determining a Wigner-Ville distribution WS(t,f) in view of time t and frequency f of the signal S2(t) extracted by the first extracting means using the following function;
first filtering means for filtering WS(t,f) obtained from the first determining means using the following function to obtain a masked time frequency representation mA(t,f) of the aortic component A2(t);
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9. Apparatus according to claim 8 where the predetermined regressive functions have the form:
Specification