IPC분류정보
| 국가/구분 |
United States(US) Patent
등록
|
| 국제특허분류(IPC7판) |
|
| 출원번호 |
US-0828565
(2001-04-06)
|
|
발명자
/ 주소 |
|
| 출원인 / 주소 |
|
| 대리인 / 주소 |
Myers Bigel Sibley & Sajovec PA
|
| 인용정보 |
피인용 횟수 :
4 인용 특허 :
93 |
초록
▼
Methods, systems and computer program products are provided for determining an obscured contact point based on a visible portion of an acoustic sensor of a medical device contacting a patient by acquiring a first image containing an upper surface of the acoustic sensor from a first viewpoint and a s
Methods, systems and computer program products are provided for determining an obscured contact point based on a visible portion of an acoustic sensor of a medical device contacting a patient by acquiring a first image containing an upper surface of the acoustic sensor from a first viewpoint and a second image containing the upper surface of the acoustic sensor from a second viewpoint different from the first viewpoint. The acoustic sensor is located in the first image and the second image and the centroid of the acoustic sensor is determined based on the location of the acoustic sensor in the first image and the corresponding location of the acoustic sensor in the second image. A plane of the visible portion of the acoustic sensor is also determined based on the position of the upper surface of the acoustic sensor in the first image and the corresponding position of the upper surface of the acoustic sensor in the second image. The contact point of the obscured portion of the acoustic sensor may then be determined by projecting a predetermined depth through the centroid of the acoustic sensor in a direction having a predefined relationship with the plane of the visible portion of the acoustic sensor.
대표청구항
▼
Methods, systems and computer program products are provided for determining an obscured contact point based on a visible portion of an acoustic sensor of a medical device contacting a patient by acquiring a first image containing an upper surface of the acoustic sensor from a first viewpoint and a s
Methods, systems and computer program products are provided for determining an obscured contact point based on a visible portion of an acoustic sensor of a medical device contacting a patient by acquiring a first image containing an upper surface of the acoustic sensor from a first viewpoint and a second image containing the upper surface of the acoustic sensor from a second viewpoint different from the first viewpoint. The acoustic sensor is located in the first image and the second image and the centroid of the acoustic sensor is determined based on the location of the acoustic sensor in the first image and the corresponding location of the acoustic sensor in the second image. A plane of the visible portion of the acoustic sensor is also determined based on the position of the upper surface of the acoustic sensor in the first image and the corresponding position of the upper surface of the acoustic sensor in the second image. The contact point of the obscured portion of the acoustic sensor may then be determined by projecting a predetermined depth through the centroid of the acoustic sensor in a direction having a predefined relationship with the plane of the visible portion of the acoustic sensor. Mellitus with Dermal Interstitial Fluid," Copyright .COPYRGT. 1997 by Mosby-Year Book, Inc., 9 pages. Blank, T.B. et al., "Transfer of Near-Infrared Multivariate Calibrations Without Standards," Anal. Chem., vol. 68 (1996) p. 2987. Brasunas John C. et al., "Uniform Time-Sampling Fourier Transform Spectroscopy," Applied Optics, vol. 36, No. 10, Apr. 1, 1997, pp. 2206-2210. Brault, James W., "New Approach to High-Precision Fourier Transform Spectrometer Design," Applied Optics, Vo. 35, No. 16, Jun. 1, 1996, pp. 2891-2896. Cassarly, W.J. et al., "Distributed Lighting Systems: Uniform Light Delivery," Source Unknown, pp. 1698-1702. Chang, Chong-Min et al., "An Uniform Rectangular Illuminating Optical System for Liquid Crystal Light Valve Projectors," Euro Display '96 (1996) pp. 257-260. Coyne, Lawrence J. et al., "Distributive Fiber Optic couplers Using Rectangular Lightguides as Mixing Elements," (Information Gatekeepers, Inc. Brookline, MA, 1979) pp. 160-164. de Noord, Onno E., "Multivariate Calibration Standardization," Chemometrics and Intelligent Laboratory Systems 25, (1994) pp. 85-97. Despain, Alvin M. et al., "A Large-Aperture Field-Widened Interferometer-Spectrometer for Airglow Studies," Aspen International Conference on Fourier Spectroscopy, 1970, pp. 293-300. Faber, Nicolaas, "Multivariate Sensitivity for the Interpretation of the Effect of Spectral Pretreatment Methods on Near-Infrared Calibration Model Predictions," Analytical Chemistry, vol. 71, No. 3, Feb. 1, 1999, pp. 557-565. Geladi, Paul et al., A Multivariate NIR Study of Skin Alterations in Diabetic Patients as Compared to Control Subjects, J. Nera Infrared Spectrosc., vol. 8 (2000) pp. 217-227. Haaland, David M. et al. "Reagentless Near-Infrared Determination of Glucose in Whole Blood Using Multivariate Calibration," Applied Spectroscopy, vol. 46, No. 10 (1992) pp. 1575-1578. Harwit, M. et al., "Chapter 5--Instrumental Considerations" Hadamard Transform Optics, Academic Press (1979) pp. 109-145. Heise H. Michael et al., "Near-Infrared Reflectance Spectroscopy for Noninvasive Monitoring of Metabolites," Clin. Chem. Lab. Med. 2000, 38(2) (2000) pp. 137-145. Heise, H.M. et al., "Near Infrared Spectrometric Investigation of Pulsatile Blood Flow for Non-Invasive Metabolite Monitoring," CP430, Fourier Transform Spectroscopy: 11thInternational Conference, (1998) pp. 282-285. Heise, H.M. et al., "Noninvasive Blood Glucose Sensors Based on Near-Infrared Spectroscopy," Artif Organs, vol. 18, No. 6 (1994) pp. 1-9. Heise, H.M. "Non-Invasive Monitoring of Metabolites Using Near Infrared Spectroscopy: State of the Art," Horm. Metab. Res., vol. 28 (1996) pp. 527-534. Hopkins, George W. et al., "In-vivo NIR Diffuse-reflectance Tissue Spectroscopy of Human Subjects," SPIE, vol. 3597, Jan. 1999, pp. 632-641. Jagemann, Kay-Uwe et al. "Application of Near-Infrared Spectroscopy for Non-Invasive Determination of Blood/Tissue Glucose Using Neural Networks," Zeitschrift for Physikalische Chemie, Bd.191, S. 179-190 (1995). Khalil, Omar S., "Spectroscopic and Clinical Aspects of Noninvasive Glucose Measurements," Clinical Chemistry, 45:2 (1999) pp. 165-177. Kohl, Matthias et al., "The Influence of Glucose Concentration Upon the Transport of Light in Tissue-simulating Phantoms," Phys. Med. Biol., vol. 40 (1995) pp. 1267-1287. Korte, E.H. et al., "Infrared Diffuse Reflectance Accessory for Local Analysis on Bulky Samples," Applied Spectroscopy, vol. 42, No. 1, Jan. 1988, pp. 38-43. Kumar, G. et al., "Optimal Probe Geometry for Near-Infrared Spectroscopy of Biological Tissue," Applied Spectroscopy, vol. 36 (19979) p. 2286. Lorber, Avraham et al., "Local Centering in Multivariate Calibration," Journal of Chemometrics, vol. 10 (1996) pp. 215-220. Lorber, Avraham et al., "Net Analyte Signal Calculation in Multivariate Calibration," Analytical Chemistry, vol. 69, No. 8, Apr. 15, 1997, pp. 1620-1626. Marbach, Ralf, "Measurement Techniques for IR Spectrosco pic Blood Glucose Determination," (1994) pp. 1-158. Marbach, R. et al. "Noninvasive Blood Glucose Assay be Near-Infrared Diffuse Reflectance Spectroscopy of the Human Inner Lip," Applied Spectroscopy, vol. 47, No. 7 (1993) pp. 875-881. Marbach, R. et al., "Optical Diffuse Reflectance Accessory for Measurements of Skin Tissue by Near-Infrared Spectroscopy," Applied Optics, vol. 34, No. 4, Feb. 1, 1995, pp. 610-621. Mardia, K.V. et al., Multivariate Analysis, Academic Press (1979) pp. 300-325. Martens, Harald et al., Updating Multivariate Calibrations of Process NIR Instruments, Adv. Instru Control (1990) pp. 371-381. McIntosh, Bruce C. et al. Quantitative Reflectance Spectroscopy in the Mid-IR, 16thAnnual FACSS Conference, Oct. 1989. Nichols, et al., Design and Testing of a White-Light, Steady-State Diffuse Reflectance Spectrometer for Determination of Optical Properties of Highly Scattering Systems, Applied Optics, Jan. 1, 1997, 36(1), pp. 93-104. Offner, A., "New Concepts in Projection Mask Aligners," Optical Engineering, vol. 14, No. 2, Mar.-Apr. 1975, pp. 130-132. Osborne, B.G. et al., "Optical Matching of Near Infrared Reflectance Monochromator Instruments for the Analysis of Ground and Whole Wheat," J. Near Infrared Spectrosc., vol. 7 (1999) p. 167. Ozdemir, d. et al., "Hybrid Calibration Models: An Alternative to Calibration Transfer," Appl. Spectros., vol. 52, No. 4 (1998) p. 599. Powell, J.R. et al, "An Algorithm for the Reproducible Spectral Subtraction of Water from the FT-IR Spectra of Proteins in Dilute Solutions and Adsorbed Monolayers," Applied Spectroscopy, vol. 40, No. 3 (1986) pp. 339-344. Ripley, B.D. Pattern Recognition and Neural Networks, Cambridge University Press (1996) pp. 91-120. Robinson, M. Ries et al., "Noninvasive Glucose Monitoring in Diabetic Patients: A Preliminary Evaluation," Clinical Chemistry, vol. 38, No. 9 (1992) pp. 1618-1622. Royston, David D. et al., "Optical Propeties of Scattering and Absorbing Materials Used in the Development of Optical Phantoms at 1064 NM," Journal of Biomedical Optics, vol. 1, No. 1, Jan. 1996, pp. 110-116. Rutan, Sarah C. et al., "Correction for Drift in Multivariate Systems Using the Kalman Filter," Chemometrics and Intelligent Laboratory Systems 35, (1996) pp. 199-211. Salit, M.L. et al., "Heuristic and Statistical Algorithms for Automated Emission Spectral Background Intensity Estimation," Applied Spectroscopy, vol. 48, No. 8 (1994) pp. 915-925. Saptari, Vidi Alfandi, "Analysis, Design and Use of a Fourier-Transform Spectrometer for Near Infrared Glucose Absorption Measurement," (Massachusetts Institute of Technology, 1999) pp. 1-76. Schmitt, J.M. et al., "Spectral Distortions in Near-Infrared Spectroscopy of Turbid Materials," Applied Spectroscopy, No. 50 (1996) p. 1066. Service, F. John et al., Dermal Interstitial Glucose as an Indicator of Ambient Glycemia, Diabetes Care, vol. 20, No. 9, Sep. 1997, 9 pages. Shroder, Robert, (Internet Article) MicroPac Forum Presentation, Current performance results, May 11, 2000. Sjoblom, J. et al., "An Evaluation of Orthogonal Signal correction Applied to Calibration Transfer of Near Infrared Spectra," Chemom & Intell Lab. Sys., vol. 44 (1998) p. 229. Steel, W.H., "Interferometers for Fourier Spectroscopy," Aspen International Conference on Fourier Spectroscopy, (1970) pp. 43-53. Sternberg R.S. et al., "A New Type of Michelson Interference Spectrometer," Sci. Instrum., vol. 41 (1964) pp. 225-226. Stork, Chris L. et al., "Weighting Schemes for Updating Regression Models--a Theoretical Approach," Chemometrics and Intelligent Laboratory Systems 48, (1999) pp. 151-166. Sum, Stephen T. et al., "Standardization of Fiber-Optic Probes for Near-Infrared Multivariate Calibrations," Applied Spectroscopy, vol. 52, No. 6 (1998) pp. 869-877. Swierenga, H. et al., "Comparison of Two Different Approaches Toward Model Transferability in NIR Spectroscopy," Applied Spectroscopy, vol. 52, No. 1 (1998) pp. 7 -16. Swierenga, H. et al., "Improvement of PLS Model Transferability by Robust Wavelength Selection," Chemometrics and Intelligent Laboratory Systems, vol. 41 (1998) pp. 237-248. Swierenga, H. et al., "Strategy for Constructing Robust Multivariate Calibration Models," Chemometrics and Intelligent Laboratory Systems, vol. 49, (1999) pp. 1-17. Teijido, J.M. et al., "Design of a Non-conventional Illumination System Using a Scattering Light Pipe," SPIE, Vo. 2774 (1996) pp. 747-756. Teijido, J.M. et al., "Illumination Light Pipe Using Micro-0ptics as Diffuser," SPIE, vol. 2951 (1996) pp. 146-155. Thomas, Edward V. et al., "Development of Robust Multivariate Calibration Models," Technometrics, vol. 42, No. 2, May 2000, pp. 168-177. Tipler, Paul A., Physics, Second Edition, Worth Publishers, Inc., Chapter 34, Section 34-2, Nov. 1983, pp. 901-908. Wang, Y-D. et al., "Calibration Transfer and Measurement Stability of Near-Infrared Spectrometers," Appl. Spectros., vol. 46, No. 5 (1992) pp. 764-771. Wang, Y-D. et al., "Improvement of Multivariate Calibration Through Instrument Standardization," Anal. Chem., vol. 64 (1992) pp. 562-564. Wang, Z., "Additive Background Correction in Multivariate Instrument Standardization," Anal. Chem., vol. 67 (1995) pp. 2379-2385. Ward, Kenneth J. et al., "Post-Prandial Blood Glucose Determination by Quantitative Mid-Infrared Spectroscopy," Applied Spectroscopy, vol. 46, No. 6 (1992) pp. 959-965. Webb, Paul, "Temperatures of Skin, Subcutaneous Tissue, Muscle and Core in Resting Men in Cold, Comfortable and Hot Conditions," European Journal of Applied Physiology, vol. 64 (1992) pp. 471-476. Whitehead, L.A. et al., "High-efficiency Prism Light Guides with Confocal Parabolic Cross Sections," Applied Optics, vol. 37, No. 22 (1998) pp. 5227-5233. of a Clark Error Grid when compared to a reference measurement. 3. The apparatus of claim 1, wherein said calibration maintenance subsystem comprises a reference sample which receives a portion of said infrared light and reflects a portion thereof and produces a spectrum similar to a representative human tissue sample. 4. The apparatus of claim 3, wherein the representative human tissue sample includes multiple samples from multiple subjects. 5. The apparatus of claim 4, wherein the reference sample has a spectral similarity ratio, when compared with the representative human tissue sample spectra, of 30 or less over a spectral range of 4,200 cm-1to 7,200 cm-1. 6. The apparatus of claim 4, wherein the reference sample has a spectral similarity ratio, when compared with the representative human tissue sample spectra, of 30 or less using discrete wavelengths, in wavenumbers (cm-1) selected from the group consisting of: 4196, 4227, 4273, 4281, 4304, 4320, 4335, 4366, 4389, 4436, 4451, 4459, 4497, 4528, 4559, 4613, 4690, 4775, 4829, 4860, 4883, 4922, 5014, 5091, 5176, 5230, 5269, 5299, 5315, 5338, 5369, 5392, 5454, 5469, 5477, 5515, 5585, 5623, 5662, 5701, 5731, 5755, 5785, 5809, 5839, 5893, 5924, 5947, 6001, 6094, 6163, 6187, 6287, 6318, 6349, 6449, 6472, 6557, 6595, 6673, 6696, 6935, 6973, 7004, 7043, 7066, 7205, and combinations thereof. 7. The apparatus of claim 4, wherein the reference sample has a spectral similarity ratio, when compared with the representative human tissue sample spectra, of 30 or less over a spectral range of 4,440 cm-1to 4,800 cm-1and 5,440 cm-1to 6,400 cm-1. 8. The apparatus of claim 4, wherein the reference sample has a regression weighted spectral similarity ratio, when compared to the representative human tissue spectra, of 30 or less over a spectral range of 4,200 cm-1to 7,200 cm-1. 9. The apparatus of claim 4, wherein the reference sample has a regression weighted spectral similarity ratio, when compared to the representative human tissue spectra, of 30 or less using discrete wavelengths, in wavenumbers (cm-1) selected from the group consisting of: 4196, 4227, 4273, 4281, 4304, 4320, 4335, 4366, 4389, 4436, 4451, 4459, 4497, 4528, 4559, 4613, 4690, 4775, 4829, 4860, 4883, 4922, 5014, 5091, 5176, 5230, 5269, 5299, 5315, 5338, 5369, 5392, 5454, 5469, 5477, 5515, 5585, 5623, 5662, 5701, 5731, 5755, 5785, 5809, 5839, 5893, 5924, 5947, 6001, 6094, 6163, 6187, 6287, 6318, 6349, 6449, 6472, 6557, 6595, 6673, 6696, 6935, 6973, 7004, 7043, 7066, 7205, and combinations thereof. 10. The apparatus of claim 4, wherein the reference sample has a regression weighted spectral similarity ratio, when compared to the representative human tissue sample spectra, of 30 or less over a spectral range of 4,440 cm-1to 4,800 cm-1and 5,440 cm-1to 6,400 cm-1. 11. The apparatus of claim 3, wherein the representative human tissue sample is from a single subject. 12. The apparatus of claim 11, wherein the reference sample has a spectral similarity ratio, when compared with the representative human tissue sample spectra, of 1500 or less over a spectral range of 4,200 cm-1to 7,200 cm-1. 13. The apparatus of claim 8, wherein the reference sample has a spectral similarity ratio, when compared with the representative human tissue sample spectra, of 1500 or less using discrete wavelengths, in wavenumbers (cm-1) selected from the group consisting of: 4196, 4227, 4273, 4281, 4304, 4320, 4335, 4366, 4389, 4436, 4451, 4459, 4497, 4528, 4559, 4613, 4690, 4775, 4829, 4860, 4883, 4922, 5014, 5091, 5176, 5230, 5269, 5299, 5315, 5338, 5369, 5392, 5454, 5469, 5477, 5515, 5585, 5623, 5662, 5701, 5731, 5755, 5785, 5809, 5839, 5893, 5924, 5947, 6001, 6094, 6163, 6187, 6287, 6318, 6349, 6449, 6472, 6557, 6595, 6673, 6696, 6935, 6973, 7004, 7043, 7066, 7205, and combi nations thereof. 14. The apparatus of claim 11, wherein the reference sample has a spectral similarity ratio, when compared with the representative human tissue sample spectra, of 7500 or less over a spectral range of 4,440 cm-1to 4,800 cm-1and 5,440 cm-1to 6,400 cm-1. 15. The apparatus of claim 11, wherein the reference sample has a regression weighted spectral similarity ratio, when compared to the representative human tissue sample spectra, of 4500 or less over a spectral range of 4,200 cm-1to 7,200 cm-1. 16. The apparatus of claim 11, wherein the reference sample has a regression weighted spectral similarity ratio, when compared to the representative human tissue sample spectra, of 3000 or less using discrete wavelengths, in wavenumbers (cm-1) selected from the group consisting of: 4196, 4227, 4273, 4281, 4304, 4320, 4335, 4366, 4389, 4436, 4451, 4459, 4497, 4528, 4559, 4613, 4690, 4775, 4829, 4860, 4883, 4922, 5014, 5091, 5176, 5230, 5269, 5299, 5315, 5338, 5369, 5392, 5454, 5469, 5477, 5515, 5585, 5623, 5662, 5701, 5731, 5755, 5785, 5809, 5839, 5893, 5924, 5947, 6001, 6094, 6163, 6187, 6287, 6318, 6349, 6449, 6472, 6557, 6595, 6673, 6696, 6935, 6973, 7004, 7043, 7066, 7205, and combinations thereof. 17. The apparatus of claim 11, wherein the reference sample has a regression weighted spectral similarity ratio, when compared to the representative human tissue sample spectra, of 9000 or less over a spectral range of 4,440 cm-1to 4,800 cm-1and 5,440 cm-1to 6,400 cm-1. 18. The apparatus of claim 3, wherein the reference sample has a spatial similarity, expressed in terms of standard deviation, of 0.079 or less. 19. The apparatus of claim 3, wherein the reference sample has an angular similarity, expressed in terms of standard deviation, of 0.051 or less. 20. An apparatus for non-invasive measurement of glucose in human tissue by quantitative near infrared spectroscopy comprising: an illumination subsystem which generates near infrared light, said illumination subsystem including a light homogenizer positioned to receive at least a portion of said infrared light; a tissue sampling subsystem optically coupled to said illumination subsystem which receives at least a portion of said infrared light exiting said light homogenizer, said tissue sampling subsystem including means for irradiating human tissue with at least a portion of said received infrared light and collecting at least a portion of said light diffusely reflected from human tissue; an FTIR spectrometer subsystem selectively optically coupled to said tissue sampling subsystem to receive at least a portion of said light diffusely reflected from said tissue, said FTIR spectrometer subsystem including a spectrometer that creates an interferogram, said FTIR spectrometer subsystem further including a detector which receives the interferogram and converts said interferogram to an electrical representation; a data acquisition subsystem which receives the electrical representation of the interferogram, said data acquisition subsystem including means for amplifying and filtering said electrical representation and converting a resulting electrical signal to its digital representation; and a computing subsystem for receiving said digital representation and further including means for determining glucose concentration in human tissue from said digital representation, wherein in combination said subsystems provide a clinically relevant level of glucose prediction precision and accuracy. 21. The apparatus of claim 20, wherein said apparatus provides a clinically relevant level of glucose measurement precision and accuracy, including 80% or more predictions on a single subject within a physiological range of glucose falling in the "A" region of a Clark Error Grid when compared to a reference measurement. 22. The apparatus of claim 20, wherein said light h
※ AI-Helper는 부적절한 답변을 할 수 있습니다.