Diffuse reflectance monitoring apparatus

Surgery – Diagnostic testing – Measuring or detecting nonradioactive constituent of body...

Reexamination Certificate

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Reexamination Certificate

active

06230034

ABSTRACT:

TECHNICAL FIELD
The present invention relates generally to diffuse reflectance spectroscopy; and more particularly, to an improved method and apparatus for the spectroscopic measurement or analysis of an analyte concentration in human tissue; and still more particularly, to an improved method and apparatus including a specular reflectance control device for use in such a measurement system.
BACKGROUND OF THE INVENTION
The need and demand for an accurate, non-invasive method for determining analyte concentrations in human tissue is well documented. Barnes et al. (U.S. Pat. No. 5,379,764), for example, disclose the necessity for diabetics to frequently monitor glucose levels in their blood. It is further recognized that the more frequent the analysis and subsequent medication, the less likely there will be large swings in glucose levels. These large swings are associated with symptoms and complications of the disease, whose long term effects can include heart disease, arteriosclerosis, blindness, stroke, hypertension, kidney failure, and premature death. As described below, systems have been proposed for the non-invasive measurement of glucose in blood. However, despite these efforts, a lancet cut into the finger is still necessary for all presently commercially available forms of home glucose monitoring. This is believed so compromising to the diabetic patient that the most effective use of any form of diabetic management is rarely achieved.
The various proposed non-invasive methods for determining blood glucose level, discussed individually below, generally utilize quantitative infrared spectroscopy as a theoretical basis for analysis. Infrared spectroscopy measures the electromagnetic radiation (0.7-25 &mgr;m) a substance absorbs at avarious wavelengths. Atoms do not maintain fixed positions with respect to each other, but vibrate back and forth about an average distance. Absorption of light at the appropriate energy causes the atoms to become excited to a higher vibration level. The excitation of the atoms to an excited state occurs only at certain discrete energy levels, which are characteristic for that particular molecule. The most primary vibrational states occur in the mid-infrared frequency region (i.e., 2.5-25 &mgr;m). However, non-invasive analyte determination in blood in this region is problematic, if not impossible, due to the absorption of the light by water. The problem is overcome through the use of shorter wavelengths of light which are not as attenuated by water. Overtones of the primary vibrational states exist at shorter wavelengths and enable quantitative determinations at these wavelengths.
It is known that glucose absorbs at multiple frequencies in both the mid- and near-infrared range. There are, however, other infrared active analytes in the blood which also absorb at similar frequencies. Due to the overlapping nature of these absorption bands, no single or specific frequency can be used for reliable non-invasive glucose measurement. Analysis of spectral data for glucose measurement thus requires evaluation of many spectral intensities over a wide spectral range to achieve the sensitivity, precision, accuracy, and reliability necessary for quantitative determination. In addition to overlapping absorption bands, measurement of glucose is further complicated by the fact that glucose is a minor component by weight in blood, and that the resulting spectral data may exhibit a non-linear response due to both the properties of the substance being examined and/or inherent non-linearities in optical instrumentation.
Robinson et al. (U.S. Pat. No. 4,975,581) disclose a method and apparatus for measuring a characteristic of unknown value in a biological sample using infrared spectroscopy in conjunction with a multivariate model that is empirically derived from a set of spectra of biological samples of known characteristic values. The above-mentioned characteristic is generally the concentration of an analyte, such as glucose, but also may be any chemical or physical property of the sample.
The method of Robinson et al. involves a two-step process that includes both calibration and prediction steps. In the calibration step, the infrared light is coupled to calibration samples of known characteristic values so that there is differential attenuation of at least several wavelengths of the infrared radiation as a function of the various components and analyte comprising the sample with known characteristic value. The infrared light is coupled to the sample by passing the light through the sample or by reflecting the light from the sample. Absorption of the infrared light by the sample causes intensity variations of the light that are a function of the wavelength of the light. The resulting intensity variations at the at least several wavelengths are measured for the set of calibration samples of known characteristic values. Original or transformed intensity variations are then empirically related to the known characteristic of the calibration samples using a multivariate algorithm to obtain a multivariate calibration model.
In the prediction step, the infrared light is coupled to a sample of unknown characteristic value, and the calibration model is applied to the original or transformed intensity variations of the appropriate wavelengths of light measured from this unknown sample. The result of the prediction step is the estimated value of the characteristic in the unknown sample. The disclosure of Robinson et al. is incorporated herein by reference.
Dähne et al. (U.S. Pat. No. 4,655,225) further disclose a method utilizing near infrared spectroscopy for non-invasively transmitting optical energy in the near infrared spectrum through a finger or earlobe of a subject. Dähne also disclose measuring reflected light energy to determine analyte concentration. The reflected light energy is further stated as comprised of light reflected from the surface of the sample and light reflected from deep within the tissue. It is the near infrared energy diffusely reflected from deep within the tissues that Dähne disclose as containing analyte information, while surface reflected light energy gives no analyte information and interferes with interpreting or measuring light reflected from deep in the tissue. The present invention is directed to an apparatus for improved measurement of diffusely reflected light, while eliminating the effects of surface reflected light and other light not reflected from deep within the tissue.
Reflectance spectroscopy is known in other non-medical applications. In general, such spectroscopy is concerned with identification of the chemical structure of the sample through the use of reflected information. Diffuse reflectance spectroscopy is also generally known, and is widely used in the visible and near-infrared regions of the light spectrum to study materials such as grains and other food products.
In broad terms, diffuse reflectance spectroscopy utilizes the fact that the sample materials will tend to scatter light in a more or less random fashion. A fraction of the light will eventually be scattered back from the sample and collected by a detector to provide a quantitative or qualitative representation of the sample.
In infrared spectroscopy it is often desirable to use the mid-infrared region of the spectrum. The fundamental vibrational absorptions described earlier are strongest here, in the fundamental region. The goal of infrared spectroscopy sampling is often to prepare a sample so that it may be analyzed with this mid-infrared light. Reflectance spectroscopy is one very popular way of making a sample compatible with mid-infrared light. If a sample is too thick to get any light through in transmission, often a result can be obtained by reflectance. Reflectance spectroscopy is complicated however, by the fact that there is more than one optical phenomenon occurring in this mode.
Reflectance of light from a sample can be largely divided into two categories, diffuse reflectance and specular reflectance. The specular reflectance of a sample is the l

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