Non-invasive method and system for characterizing cardiovascular systems
First Claim
1. A method for localizing and characterizing both the architectural features and function of cardiovascular tissues, comprising the steps of:
- obtaining data associated with measured cardiovascular physiological signals;
processing the data to display an abnormality associated with the tissues in a 3-D image without use of invasive procedures, wherein the processing comprises;
creating a phase space diagram based on the data;
dividing the phase space diagram into a plurality of regions; and
computing one or more space-time density values of each divided regions, wherein the one or more space-time density values contain specific information about non-linear variability of the physiological signal; and
linking, via learning algorithms, one or more nonlinear nested sinusoidal Gaussian equations to a plurality of locations of the heart based on the one or more space-time density values, each location being associated with an architectural feature or function of the tissues to display the abnormality associated with the tissues in the 3-D image.
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Abstract
The present disclosure uses physiological data, ECG signals as an example, to evaluate cardiac structure and function in mammals. Two approaches are presented, e.g., a model-based analysis and a space-time analysis. The first method uses a modified Matching Pursuit (MMP) algorithm to find a noiseless model of the ECG data that is sparse and does not assume periodicity of the signal. After the model is derived, various metrics and subspaces are extracted to image and characterize cardiovascular tissues using complex-sub-harmonic-frequencies (CSF) quasi-periodic and other mathematical methods. In the second method, space-time domain is divided into a number of regions, the density of the ECG signal is computed in each region and inputted into a learning algorithm to image and characterize the tissues.
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21 Claims
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1. A method for localizing and characterizing both the architectural features and function of cardiovascular tissues, comprising the steps of:
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obtaining data associated with measured cardiovascular physiological signals; processing the data to display an abnormality associated with the tissues in a 3-D image without use of invasive procedures, wherein the processing comprises; creating a phase space diagram based on the data; dividing the phase space diagram into a plurality of regions; and computing one or more space-time density values of each divided regions, wherein the one or more space-time density values contain specific information about non-linear variability of the physiological signal; and linking, via learning algorithms, one or more nonlinear nested sinusoidal Gaussian equations to a plurality of locations of the heart based on the one or more space-time density values, each location being associated with an architectural feature or function of the tissues to display the abnormality associated with the tissues in the 3-D image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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Specification