US-12622613-B2 - Remote monitoring of oxygenation status and blood pulsation within skin tissue

US12622613B2US 12622613 B2US12622613 B2US 12622613B2US-12622613-B2

Abstract

A method of measuring blood oxygenation including acquiring one or more images of a portion of a body with an RGB camera, converting RGB colors in the one or more images into a multispectral data imaging cube, wherein the multispectral date imaging cube comprises a red channel, a blue channel, and a green channel, decoupling an oxygenated blood information and a deoxygenated blood information from the multispectral data imaging cube based on a first reflectance of the green channel and a second reflectance of the red channel, and determining a blood measurement based on the oxygenated blood information and the deoxygenated blood information.

Inventors

Ruikang K. Wang
Qinghau He

Assignees

UNIVERSITY OF WASHINGTON

Dates

Publication Date: 20260512
Application Date: 20220225

Claims (18)

1 . A method of measuring blood oxygenation comprising: acquiring one or more images of a portion of a body with an RGB camera; converting RGB colors in the one or more images into a multispectral data imaging cube, wherein the multispectral data imaging cube comprises a red channel, a blue channel, and a green channel; decoupling an oxygenated blood information and a deoxygenated blood information from the multispectral data imaging cube based on a first reflectance of the green channel and a second reflectance of the red channel, wherein decoupling the oxygenated blood information and the deoxygenated blood information comprises: recording the first reflectance at the green channel and the second reflectance the red channel; calculating a ratio of ratios from the first reflectance of the green channel and the second reflectance of the red channel, wherein the ratio of ratios is determined as: R = ε Hb ( λ 1 ) + [ ε HbO 2 ( λ 1 ) - ε Hb ( λ 1 ) ] ⁢ SO 2 ε Hb ( λ 2 ) + [ ε HbO 2 ( λ 2 ) - ε Hb ( λ 2 ) ] ⁢ SO 2 where ε Hb is an extinction coefficient of the deoxygenated blood, ε HbO 2 , is an extinction coefficient of the oxygenated blood, λ 1 is a first wavelength; λ 2 is a second wavelength, and SO 2 is an oxygen saturation; and measuring an average gray value of the red channel, green channel, and blue channel, wherein the average gray value is the sum of the gray values of all the pixels in the image divided by the number of pixels; and determining a blood measurement based on the oxygenated blood information and the deoxygenated blood information.
2 . The method of claim 1 , wherein the multispectral data imaging cube represents spectral information at wavelengths of 450, 500, 550, 600, 650 and 700 nm.
3 . The method of claim 1 , wherein determining the blood measurement comprises applying a multiple linear regression algorithm to the oxygenated blood information and the deoxygenated blood information based on the calculated ratio of ratios and the averaged gray values of the red channel, green channel, and blue channel.
4 . The method of claim 1 , wherein the blood measurement is a set of blood pulsation amplitudes, a set of blood pulsation phases, or both.
5 . The method of claim 4 , wherein obtaining the set of blood pulsation amplitudes further comprises applying a window-based lock-in amplification to the oxygenated blood information and the deoxygenated blood information.
6 . The method of claim 1 , wherein the RGB camera is on a communication device.
7 . The method of claim 6 , wherein the communication device is a smartphone.
8 . The method of claim 7 , wherein the method further comprises displaying the blood measurement on a second communication device.
9 . The method of claim 1 , wherein the method further includes illuminating the portion of the body with a light source while acquiring the one or more images of the portion of the body.
10 . The method of claim 9 , wherein the light source is on communication device.
11 . The method of claim 1 , wherein the method further comprises calibrating the RGB camera with a Weiner estimation method and a color-checker.
12 . The method of claim 1 , wherein the method further comprises taking the oxygenated blood information and the deoxygenated blood information from a first region of a body and a second region of a body in an image.
13 . The method of claim 1 , wherein the one or more images comprise a video.
14 . A method of measuring blood oxygenation comprising: acquiring one or more images of a portion of a body with an RGB camera; converting RGB colors in the one or more images into a multispectral data imaging cube, wherein the multispectral data imaging cube comprises a red channel, a blue channel, and a green channel; decoupling an oxygenated blood information and a deoxygenated blood information from the multispectral data imaging cube based on a first reflectance of the green channel and a second reflectance of the red channel, and performing bilateral asymmetry analysis on the oxygenated blood information and the deoxygenated blood information of both the first region of the body and the second region of the body, wherein performing bilateral asymmetry analysis comprises: generating a phase map and an amplitude map; and regionally extracting a first pulse signal from the first region of the body, and a second pulse signal from the second region of the body.
15 . The method of claim 14 , wherein generating the phase map and the amplitude map comprises: filtering the first pulse signal and the second pulse signal with one or more heartbeat frequencies to generate a filtered signal; and using the filtered signal as a reference function to extract and amplify the first pulse signal and the second pulse signal with the same frequency as the filtered signal at each voxel of the image.
16 . The method of claim 14 , wherein the first region of the body comprises bilateral carotid regions of a neck and the second region of the body comprises bilateral jugular regions of a neck.
17 . The method of claim 16 , wherein the first pulse signal comprises a carotid pulse, and the second pulse signal comprises a jugular vein pulse.
18 . A computer-implemented method comprising: acquiring one or more images of a portion of a body with an RGB camera; converting RGB colors in the one or more images into a multispectral data imaging cube, wherein the multispectral date imaging cube comprises a red channel, a blue channel, and a green channel; decoupling an oxygenated blood information and a deoxygenated blood information from the multispectral data imaging cube based on a first reflectance of the green channel and a second reflectance of the red channel, wherein decoupling the oxygenated blood information and the deoxygenated blood information comprises: recording the first reflectance at the green channel and the second reflectance the red channel; calculating a ratio of ratios from the first reflectance of the green channel and the second reflectance of the red channel, wherein the ratio of ratios is determined as: R = ε Hb ( λ 1 ) + [ ε HbO 2 ( λ 1 ) - ε Hb ( λ 1 ) ] ⁢ SO 2 ε Hb ( λ 2 ) + [ ε HbO 2 ( λ 2 ) - ε Hb ( λ 2 ) ] ⁢ SO 2 where ε Hb is an extinction coefficient of the deoxygenated blood, ε HbO 2 is an extinction coefficient of the oxygenated blood, λ 1 is a first wavelength; μ 2 is a second wavelength, and SO 2 is an oxygen saturation; and measuring an average gray value of the red channel, green channel, and blue channel, wherein the average gray value is the sum of the gray values of all the pixels in the image divided by the number of pixels; and determining a blood measurement based on the oxygenated blood information and the deoxygenated blood information.

Description

CROSS-REFERENCE(S) TO RELATED APPLICATION This application is a National Stage of International Application No. PCT/US2022/017848 filed Feb. 25, 2022, which claims the benefit of U.S. Provisional Patent Application No. 63/154,100, filed Feb. 26, 2021, the disclosures of each of which are expressly incorporated herein by reference in their entirety. BACKGROUND Oxygen saturation (SO2) is a measure of the relative concentration of oxygenated hemoglobin with respect to the total amount of hemoglobin. The human body tissue demands and auto-regulates a precise and specific balance of oxygen content within blood circulation throughout various organs and tissue types. Oxygen saturation, including peripheral SO2 (SpO2), is one of the key physiological indices commonly used to indicate the physical and medical conditions of a person. For instance, an abnormal level of oxygen saturation is often associated with severe medical conditions, e.g., hypoxia, chronic obstructive pulmonary disease and obstructive sleep apnea. More importantly, in the devastating COVID-19 pandemic, SpO2 is a vital parameter to monitor as its decrease may reflect a compromised oxygen intake through the respiratory system, thus be alarming for a suspected infection of the coronavirus. Therefore, regular measurement and monitoring of SpO2 is of great importance for at-home health monitoring and clinical practices in dealing with various medical conditions and the pandemic of COVID-19. Current clinical gold standard for SpO2 measurement is blood gas analysis with invasive blood sampling. It was not until the early 1980s that SpO2 was continuously measured non-invasively with a contact-mode light-based pulse oximetry, which has revolutionized the way blood oxygen is monitored in clinical practice as well as in-hospital monitoring. The detecting principle of pulse oximetry is based on the distinct absorption difference between oxygenated (HbO2) and deoxygenated hemoglobin (Hb) in the visible and near infrared wavelength range. This fact is being continually utilized in the popular development of remote, non-contact measurements of SpO2 using imaging photoplethysmography (iPPG), by leveraging the advances in area array sensors, for example CCD cameras. The ability to remotely assess SpO2 information could benefit both clinical and research efforts such as in the intensive care unit and sleep studies. In addition to the efforts of developing monochromatic camera-based devices, there are intense research activities over the recent years focusing on developing devices and algorithms for estimating SpO2 from the RBG-channel signals provided by a color CCD camera. The success of almost all the prior studies was essentially based on the observed relationship of the oxygen saturation to the ratio of AC/DC ratios between two wavelengths of interest, which was derived from the Beer-Lambert law. However, when using the Beer-Lambert law, only the absorbances from the chromophores within skin tissue were considered in the derivation, for example skin pigmentation, reduced and oxygenated hemoglobin. Accordingly, methods and systems for measuring SpO2 remotely with a communication device are needed. SUMMARY This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. The effect of the variation caused by light scattering on the measured reflectance images was neglected in the prior art technologies, which may cause considerable errors or misinterpretation of the measured SpO2. According to biomedical optics, the light scattering properties of the heterogeneous skin tissue and the absorption and scattering strength of the effective blood volume would inevitably affect the appearance of reflectance images recorded by the CCD camera. The change in reflectance depends mainly on the effective blood volume, which may be determined by many physiological factors, such as local temperature, cardiac index and peripheral vasoconstriction. Therefore, even under a stable illumination condition, the reflectance variation due to the changes in scattering and absorption can lead to a poor estimation of the relationship of oxygen saturation to the ratio of AC/DC ratios, giving rise to a considerable deviation of measured SpO2 from the true value. While the camera-array sensor approach has been the main stay for the development of remote SpO2 monitoring, there is an increasing interest in the development of smartphone-based approach simply because of its ever-growing accessibility and affordability in the community. In this regard, effort has been paid to develop pulse oximeter in which a contact light sensor is connected to smartphone-based mobile devices. Mobile devices offer many advantages, such as user-friendly custo