Blood pressure estimation method and biological information measurement system
US-2024423547-A1 · Dec 26, 2024 · US
US2018368705A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2018368705-A1 |
| Application number | US-201815892300-A |
| Country | US |
| Kind code | A1 |
| Filing date | Feb 8, 2018 |
| Priority date | Aug 14, 2013 |
| Publication date | Dec 27, 2018 |
| Grant date | — |
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Disclosed herein are systems and methods for revascularization assessment. The methods can in some cases include one or more of the steps of measuring blood perfusion as a function of time to obtain time series data, mathematically transforming the time series data into a power spectrum, calculating at least one parameter of the power spectrum within a specific frequency range, and using the at least one calculated parameter as a discriminator for the first population and the second population.
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What is claimed is: 1 . A computer-implemented method for discriminating between at least a first population and a second population, the method comprising: measuring blood perfusion as a function of time to obtain time series data; mathematically transforming the time series data into a power spectrum; calculating at least one parameter of the power spectrum within a specific frequency range; and using the at least one calculated parameter as a discriminator for the first population and the second population. 2 . The method of claim 1 , wherein at least the first population and the second population comprise two patient populations. 3 . The method of claim 1 , wherein the first population comprises a healthy control group and the second population comprises an ischemic population. 4 . The method of claim 1 , wherein measuring blood perfusion as a function of time comprises using an optical measurement method. 5 . The method of claim 4 , wherein the optical method is diffuse correlation spectroscopy. 6 . The method of claim 4 , wherein the optical method is diffuse speckle contrast analysis. 7 . The method of claim 4 , wherein the optical method is diffuse optical tomography. 8 . The method of claim 4 , wherein the optical method is near-infrared spectroscopy. 9 . The method of claim 4 , wherein the optical method is laser Doppler flowmetry. 10 . The method of claim 1 , wherein measuring blood perfusion as a function of time comprises using a non-optical measurement method. 11 . The method of claim 10 , wherein the non-optical measurement method is selected from the group consisting of an electrical measurement method and a magnetic measurement method. 12 . The method of claim 1 , wherein measuring blood perfusion as a function of time comprises using an electrical or magnetic measurement method. 13 . The method of claim 1 , wherein mathematically transforming the time series data into a power spectrum comprises using a Fourier transform. 14 . The method of claim 1 , wherein mathematically transforming the time series data into a power spectrum comprises using a fast Fourier Transform. 15 . The method of claim 1 , wherein mathematically transforming the time series data into a power spectrum comprises using a wavelet transform. 16 . The method of claim 1 , wherein the specific frequency range is between about 0.001 Hz and about 1000 Hz. 17 . The method of claim 1 , wherein the specific frequency range is between about 0.001 Hz and about 0.1 Hz. 18 . The method of claim 1 , wherein the specific frequency range is between about 0.045 Hz and about 0.1 Hz. 19 . The method of claim 1 , wherein the frequency range of interest is between 0.001 Hz and 0.045 Hz. 20 . The method of claim 1 , wherein the at least one parameter is the area under the curve of the power spectrum within the specific frequency range.
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