IPC분류정보
국가/구분 |
United States(US) Patent
등록
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국제특허분류(IPC7판) |
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출원번호 |
US-0012902
(2001-10-22)
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발명자
/ 주소 |
- Routt, Wilson
- Rice, Mark J.
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출원인 / 주소 |
|
대리인 / 주소 |
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인용정보 |
피인용 횟수 :
122 인용 특허 :
44 |
초록
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The determination of blood glucose in an individual is carried out by projecting illuminating light into an eye of the individual to illuminate the retina with the light having wavelengths that are absorbed by rhodopsin and with the intensity of the light varying in a prescribed temporal manner. The
The determination of blood glucose in an individual is carried out by projecting illuminating light into an eye of the individual to illuminate the retina with the light having wavelengths that are absorbed by rhodopsin and with the intensity of the light varying in a prescribed temporal manner. The light reflected from the retina is detected to provide a signal corresponding to the intensity of the detected light, and the detected light signal is analyzed to determine the changes in form from that of the illuminating light. For a biased sinusoidal illumination, these changes can be expressed in terms of harmonic content of the detected light. The changes in form of the detected light are related to the ability of rhodopsin to absorb light and regenerate, which in turn is related to the concentration of blood glucose, allowing a determination of the relative concentration of blood glucose. Other photoreactive analytes can similarly be determined by projecting time varying illuminating light into the eye, detecting the light reflected from the retina, and analyzing the detected light signal to determine changes in form of the signal due to changes in absorptivity of a photoreactive analyte.
대표청구항
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The determination of blood glucose in an individual is carried out by projecting illuminating light into an eye of the individual to illuminate the retina with the light having wavelengths that are absorbed by rhodopsin and with the intensity of the light varying in a prescribed temporal manner. The
The determination of blood glucose in an individual is carried out by projecting illuminating light into an eye of the individual to illuminate the retina with the light having wavelengths that are absorbed by rhodopsin and with the intensity of the light varying in a prescribed temporal manner. The light reflected from the retina is detected to provide a signal corresponding to the intensity of the detected light, and the detected light signal is analyzed to determine the changes in form from that of the illuminating light. For a biased sinusoidal illumination, these changes can be expressed in terms of harmonic content of the detected light. The changes in form of the detected light are related to the ability of rhodopsin to absorb light and regenerate, which in turn is related to the concentration of blood glucose, allowing a determination of the relative concentration of blood glucose. Other photoreactive analytes can similarly be determined by projecting time varying illuminating light into the eye, detecting the light reflected from the retina, and analyzing the detected light signal to determine changes in form of the signal due to changes in absorptivity of a photoreactive analyte. rming the motion compensation. 11). Kegelmeyer, Jr., W. P., "Evaluation of Stellate Lesion Detection in a Standard Mammogram Data Set," State of the Art in Digital Mammographic Image Analysis, Boyer, K.W. et al., editors, 1994, (pp. 262-279). Lidbrink, E.K., et al., "The General Mammography Screening Program in Stockholm: Organisation and First-Round Results," Acta Oncologica, vol. 33, No. 4, 1994, (pp. 353-358). Nishikawa, R.M., "Computer-Aided Detection and Diagnosis of Masses and Clustered Microcalcifications from Digital Mammograms," State of the Art in Digital Mammographic Image Analysis, Boyer, K.W., et al., editors, 1994, (pp. 82-102). Petrosian, A., et al., "Computer-Aided Diagnosis in Mammography: Classification of Mass and Normal Tissue by Texture Analysis," Phys. Med. Biol., vol. 39, 1994, (pp. 2273-2288). Shen, L., et al., "Detection and Classification of Mammographic Calcifications," State of the Art in Digital Mammographic Image Analysis, Boyer, K. W., et al., editors, 1994, (pp. 198-212). Wilding, P., et al., "Application of Backpropagation Neural Networks in Diagnosis of Breast and Ovarian Cancer," Cancer Letters, vol. 77, 1994, (pp. 145-153). Woods, K.S., et al., "Comparative Evaluation of Pattern Recognition Techniques for Detection of Microcalcifications in Mammography," S
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