SPECTRUM ANALYTICAL METHOD FOR QUANTIFYING HEAT-LUNG INTERACTION
First Claim
1. A spectrum analytical method for quantifying heart-lung interaction, comprising performing spectrum analysis of arterial blood pressure signals within a time domain by the following steps:
- (a) transforming the arterial blood pressure signals to pulse pressure signals;
(b) subjecting the pulse pressure signals to spectrum transform to obtain power spectrum signals;
(c) choosing a frequency band of 0.1˜
1.5 Hz from the power spectrum signals to obtain a power spectral density distribution curve, integrating all energy values of the power spectral densities over the chosen frequency band to obtain an integrated energy value of the power spectral densities, which is used as a predictor of cardiac function.
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Abstract
The present invention is related to a spectrum analytical method for quantifying hear-lung interaction, which can estimate cardiac function by using a heart-associated monitoring signal. According to the method of the present invention, quantification of heart-lung interaction is conducted by choosing spectrum signals within a specified frequency band, such that the interference to the heart-associated monitoring signals by incidental events occurring at a low frequency, can be avoided. Therefore, the method of the present invention can be performed even in the subjects who are not in a state of general anesthesia or sedation, and hence is very useful in estimating the cardiac function of the test subjects.
11 Citations
23 Claims
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1. A spectrum analytical method for quantifying heart-lung interaction, comprising performing spectrum analysis of arterial blood pressure signals within a time domain by the following steps:
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(a) transforming the arterial blood pressure signals to pulse pressure signals; (b) subjecting the pulse pressure signals to spectrum transform to obtain power spectrum signals; (c) choosing a frequency band of 0.1˜
1.5 Hz from the power spectrum signals to obtain a power spectral density distribution curve, integrating all energy values of the power spectral densities over the chosen frequency band to obtain an integrated energy value of the power spectral densities, which is used as a predictor of cardiac function. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A spectrum analytical method for quantifying heart-lung interaction, comprising performing spectrum analysis of stroke volume signals within a time domain by the following steps:
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(a) subjecting the stroke volume signals to spectrum transform to obtain power spectrum signals; (b) choosing a frequency band of 0.1˜
1.5 Hz from the power spectrum signals to obtain a power spectral density distribution curve, integrating all energy values of the power spectral densities over the chosen frequency band to obtain an integrated energy value of the power spectral densities, which is used as a predictor of cardiac function. - View Dependent Claims (8, 9, 10, 11)
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12. A spectrum analytical method for quantifying heart-lung interaction, comprising performing spectrum analysis of a blood flow signals within a time domain by the following steps:
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(a) transforming the blood flow signals to a blood flow difference signals; (b) subjecting the blood flow difference signals to spectrum transform to obtain power spectrum signals; (c) choosing a frequency band of 0.1˜
1.5 Hz from the power spectrum signals to obtain a power spectral density distribution curve over the chosen frequency band, integrating all energy values of the power spectral densities over the chosen frequency band to obtain an integrated energy value of the power spectral densities, which is used as a predictor of cardiac function. - View Dependent Claims (13, 14, 15, 16, 17)
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18. A spectrum analytical method for quantifying heart-lung interaction, comprising performing spectrum analysis of a blood flow velocity signals within a time domain by the following steps:
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(a) transforming the blood flow velocity signals to blood flow velocity difference signals; (b) subjecting the blood flow velocity difference signals to spectrum transform to obtain power spectrum signals; (c) choosing a frequency band of 0.1˜
1.5 Hz from the power spectrum signals to obtain a power spectral density distribution, integrating all energy values of the power spectral densities over the chosen frequency band to obtain an integrated energy value of the power spectral densities, which is used as a predictor of cardiac function. - View Dependent Claims (19, 20, 21, 22, 23)
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Specification