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다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
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Kafe 바로가기국가/구분 | United States(US) Patent 등록 |
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국제특허분류(IPC7판) |
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출원번호 | US-0343838 (2008-12-24) |
등록번호 | US-8442608 (2013-05-14) |
발명자 / 주소 |
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출원인 / 주소 |
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인용정보 | 피인용 횟수 : 0 인용 특허 : 748 |
There is disclosed a system and methods to estimate physiological parameters. In accordance with embodiments a method is disclosed which includes generating distribution data for a plurality of signals. The method may also include deconvolving one of the plurality of signals from the other plurality
There is disclosed a system and methods to estimate physiological parameters. In accordance with embodiments a method is disclosed which includes generating distribution data for a plurality of signals. The method may also include deconvolving one of the plurality of signals from the other plurality of signals to produce clean signals. The clean signals may then be used to calculate physiological parameters.
1. A method for non-invasively estimating a physiological parameter comprising: detecting light over a period of time from a plurality of light sources comprising at least three light sources;generating respective distributions for the detected light of each of the plurality of light sources for the
1. A method for non-invasively estimating a physiological parameter comprising: detecting light over a period of time from a plurality of light sources comprising at least three light sources;generating respective distributions for the detected light of each of the plurality of light sources for the period of time;deconvolving the distribution for the detected light of one of the plurality of light sources from each of the other distributions for the detected light from the other plurality of light sources to produce clean distributions for the period of time; andestimating a physiological parameter based at least in part upon the clean distributions;wherein deconvolving the distribution for the detected light of one of the plurality of light sources comprises using a least squares algorithm, wherein the least squares algorithm comprises:formulating a toeplitz matrix A associated with f; andfinding a vector g with nonnegative elements such that (Ag-f)T(Ag-f) is minimized, wherein g and f are bi-infinite sequences. 2. The method of claim 1, wherein the distribution for the detected light of the one of the plurality of light sources is utilized to estimate the distribution of noise artifacts in a detected signal. 3. The method of claim 1, wherein the plurality of light sources comprises a first light source operating in the red region of the electromagnetic spectrum, a second light source operating in the infrared region of the electromagnetic spectrum, and a third light source operating in region of the electromagnetic spectrum that is selected to detect noise. 4. The method of claim 3, wherein the third light source operates in a blue region of the electromagnetic spectrum. 5. The method of claim 3, wherein the third light source operates in a region comprising the wavelengths approximately in the range of 1250 to 1350 nm. 6. The method of claim 1, wherein deconvolving the distribution for the detected light of the one of the plurality of light sources comprises using a least squares algorithm, wherein the least squares algorithm is solved using non-negative matrix factorization relaxation steps. 7. The method of claim 1, wherein the method further comprises calibrating functions representative of the distribution of a noise signal. 8. The method of claim 7, wherein calibrating functions representative of the distribution of the noise signal comprises: collecting a first set of data for each of the plurality light sources;collecting a second set of data for each of the plurality of light sources; andparameterizing the functions representative of the distribution of the noise signal, wherein parameterizing the functions comprises finding a parameter to produce approximately equal distributions of the first and second sets of data. 9. The method of claim 4, wherein computing physiological parameters comprises determining a scaling difference between distributions of detected light for the red and infrared light sources. 10. The method of claim 1, wherein estimating the physiological parameter comprises estimating a blood oxygen saturation. 11. The method of claim 10, further comprising displaying the blood oxygen saturation on the monitor. 12. The method of claim 1, wherein the three light sources operate at different wavelengths from each other. 13. The method of claim 1, further comprising passing light from the three light sources through blood-perfused tissue, prior to detecting the light. 14. A system for estimating a physiological parameter comprising: a sensor comprising: a plurality of light sources; anda detector configured to generate signals based on detected light from the plurality of light sources over a period of time; anda monitor coupled to the sensor configured to: generate distribution data based on the detected light for the period of time for each of the plurality of light sources; anddeconvolve distribution data for the period of time of one of the plurality of light sources from the distribution data of each of the other plurality of light sources for the period of time, to produce clean distributions;wherein deconvolving the distribution data comprises the monitor using a least squares algorithm, wherein the least squares algorithm comprises:formulating a toeplitz matrix A associated with f; andfinding a vector g with nonnegative elements such that (Ag-f)T(Ag-f) is minimized, wherein q and f are bi-infinite sequences. 15. The system of claim 14, wherein the plurality of light sources comprises three light sources operating at different wavelengths. 16. The system of claim 15, wherein the three light sources comprise: a first light source operating in the red region of the electromagnetic spectrum; anda second light source operating in the IR region of the electromagnetic spectrum. 17. The system of claim 14, wherein at least one of the plurality of light sources is used to obtain data related to artifacts. 18. The system of claim 17, wherein the monitor is configured to find functions representative of the artifacts through a calibration process, wherein the calibration process comprises parameterization of the functions. 19. The system of claim 14, wherein the monitor is further configured to estimate a physiological parameter based at least in part on the clean distributions. 20. The system of claim 19, wherein the parameter comprises blood oxygen saturation. 21. A method for non-invasively estimating a physiological parameter comprising: detecting light over a period of time from a plurality of light sources comprising at least three light sources;generating respective distributions for the detected light of each of the plurality of light sources for the period of time;calibrating functions representative of a distribution of a noise signal,wherein calibrating functions representative of the distribution of the noise signal comprises: collecting a first set of data for each of the plurality light sources;collecting a second set of data for each of the plurality of light sources; andparameterizing the functions representative of the distribution of the noise signal, wherein parameterizing the functions comprises finding a parameter to produce approximately equal distributions of the first and second sets of data;deconvolving the distribution for the detected light of one of the plurality of light sources from each of the other distributions for the detected light from the other plurality of light sources to produce clean distributions for the period of time; andestimating a physiological parameter based at least in part upon the clean distributions. 22. A system for estimating a physiological parameter comprising: a sensor comprising: a plurality of light sources; anda detector configured to generate signals based on detected light from the plurality of light sources over a period of time; anda monitor coupled to the sensor configured to: generate distribution data based on the detected light for the period of time for each of the plurality of light sources;calibrate functions representative of a distribution of a noise signal, wherein calibrating functions representative of the distribution of the noise signal comprises: collecting a first set of data for each of the plurality light sources;collecting a second set of data for each of the plurality of light sources; andparameterizing the functions representative of the distribution of the noise signal, wherein parameterizing the functions comprises finding a parameter to produce approximately equal distributions of the first and second sets of data; anddeconvolve distribution data for the period of time of one of the plurality of light sources from the distribution data of each of the other plurality of light sources for the period of time, to produce clean distributions.
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