Devices and methods for estimating the concentration of an analyte, and calibration methods

Abstract

Devices, methods, and calibration methods for estimating the concentration of an analyte are provided. The device for estimating the concentration of an analyte includes: an optical sensor configured to emit light toward an object and receive light reflected from the object; and a processor configured to: obtain a ratio of an absorption coefficient to a scattering coefficient based on the received light, obtain a first absorption spectrum of the object based on the obtained ratio, obtain a second absorption spectrum by eliminating a scattering correction spectrum from the first absorption spectrum, the scattering correction spectrum corresponding to a non-linear change of the scattering coefficient according to the wavelength of the emitted light, and estimate the concentration of the analyte based on the second absorption spectrum.

Description

[0001] This application claims priority to Korean Patent Application No. 10-2019-0135616, filed with the Korean Intellectual Property Office on October 29, 2019, the entire disclosure of which is incorporated herein by reference for all purposes. Technical Field

[0002] Example embodiments consistent with the disclosure relate to an apparatus and method for estimating the concentration of an analyte in a body. Background Art

[0003] Diabetes is a chronic disease that can cause various complications and may be difficult to cure. Therefore, it is recommended that diabetic patients regularly check their blood glucose to prevent complications. Specifically, when insulin is administered to control blood glucose levels, blood glucose levels should be closely monitored to avoid hypoglycemia and control insulin dosage. An invasive method of pricking a finger is commonly used to measure blood glucose levels. However, although this invasive method can provide high reliability of measurement, due to the injection for blood collection, this invasive method may cause pain and inconvenience and increase the risk of infection. Recently, research has been conducted on methods for non-invasively measuring blood glucose levels by using a spectrometer without blood sampling.

[0004] However, in the case of a turbid medium such as skin, due to the change in the length of the optical path (or optical path length) caused by the change in the scattering coefficient, it is difficult to accurately estimate the analyte concentration. Therefore, a technique that can accurately estimate the analyte concentration even in a turbid medium is needed. Summary of the Invention

[0005] One or more example embodiments disclosed provide an apparatus and method for estimating the concentration of an analyte in a body with improved accuracy and a calibration method thereof.

[0006] According to an aspect of an example embodiment, there is provided an apparatus for estimating the concentration of an analyte, the apparatus including: an optical sensor configured to emit light toward an object and receive light reflected from the object; and a processor configured to: obtain a ratio of an absorption coefficient to a scattering coefficient based on the received light, obtain a first absorption spectrum of the object based on the obtained ratio, obtain a second absorption spectrum by eliminating a scattering correction spectrum from the first absorption spectrum, the scattering correction spectrum corresponding to a non-linear change in the scattering coefficient according to the wavelength of the emitted light, and estimate the concentration of the analyte based on the second absorption spectrum.

[0007] The processor may also be configured to: obtain a reflectance of the object based on the received light, obtain an albedo of the object based on the obtained reflectance, and obtain a ratio of the absorption coefficient to the scattering coefficient based on the obtained albedo.

[0008] The processor may also be configured to obtain a first absorption spectrum based on a function of the ratio of the absorption coefficient to the scattering coefficient.

[0009] The scatter correction spectrum may be expressed as a function representing the change in the length of the optical path according to the wavelength of the emitted light; and the processor may also be configured to obtain a second absorption spectrum by using a scatter correction model based on the function.

[0010] The processor may also be configured to generate a plurality of candidate scatter correction models by changing the coefficients of the function, obtain a plurality of second absorption spectra by using the first absorption spectrum and the plurality of candidate scatter correction models; estimate the concentration of the analyte for each of the plurality of second absorption spectra, and select, as the scatter correction model, the candidate scatter correction model having the smallest difference between the estimated concentration and the actual concentration of the analyte among the plurality of candidate scatter correction models.

[0011] The processor may also be configured to estimate the concentration of the analyte by using the second absorption spectrum and the pure component spectrum of the analyte.

[0012] The pure component spectrum of the analyte may be set to a default value, or may be obtained and set in a calibration mode.

[0013] In the calibration mode, the processor may also be configured to obtain the pure component spectrum based on the difference between the second absorption spectrum obtained when the concentration of the analyte in the object is the first concentration and the second absorption spectrum obtained when the concentration of the analyte in the object is the second concentration.

[0014] The processor may also be configured to obtain a second absorption spectrum by eliminating the scatter correction spectrum from the first absorption spectrum by using one of principal component analysis (PCA), independent component analysis (ICA), non - negative matrix factorization (NMF), and singular value decomposition (SVD).

[0015] The analyte may include at least one of glucose, triglyceride, urea, uric acid, lactic acid, protein, cholesterol, antioxidant, and ethanol.

[0016] According to an aspect of an exemplary embodiment, a method for estimating the concentration of an analyte is provided. The method includes: emitting light toward an object and receiving the light reflected from the object; obtaining a ratio of an absorption coefficient to a scattering coefficient based on the received light; obtaining a first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient; obtaining a second absorption spectrum by eliminating a scatter correction spectrum from the first absorption spectrum, the scatter correction spectrum corresponding to a non - linear change in the scattering coefficient according to the wavelength of the emitted light; and estimating the concentration of the analyte based on the second absorption spectrum.

[0017] The steps of obtaining the ratio may include: obtaining the reflectivity of an object based on the received light; obtaining the albedo of the object based on the obtained reflectivity; and obtaining the ratio of the absorption coefficient to the scattering coefficient based on the obtained albedo.

[0018] The steps of obtaining the first absorption spectrum may include: obtaining the first absorption spectrum based on a function of the ratio of the absorption coefficient to the scattering coefficient.

[0019] The scattering correction spectrum may be expressed as a function representing the change in the length of the optical path according to the wavelength of the emitted light; and the steps of obtaining the second absorption spectrum may include: obtaining the second absorption spectrum by using a scattering correction model based on the function.

[0020] The step of estimating may include: estimating the concentration of an analyte by using the second absorption spectrum and the pure component spectrum of the analyte.

[0021] The pure component spectrum of the analyte may be set as a default value, or may be obtained and set in a calibration mode.

[0022] The steps of obtaining the second absorption spectrum may include: obtaining the second absorption spectrum by eliminating the scattering correction spectrum from the first absorption spectrum by using one of principal component analysis (PCA), independent component analysis (ICA), non - negative matrix factorization (NMF), and singular value decomposition (SVD).

[0023] The analyte may include at least one of glucose, triglyceride, urea, uric acid, lactic acid, protein, cholesterol, antioxidant, and ethanol.

[0024] According to an aspect of an exemplary embodiment, a method of calibrating a device for estimating the concentration of an analyte is provided. The calibration method includes: emitting light towards an object and receiving the light reflected from the object; obtaining the ratio of the absorption coefficient to the scattering coefficient based on the received light; obtaining the first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient; generating a plurality of candidate scattering correction models by changing coefficients of a function representing the change in the length of the optical path according to the wavelength of the emitted light; obtaining a plurality of second absorption spectra by using the first absorption spectrum and the plurality of candidate scattering correction models; estimating the concentration of the analyte for each of the plurality of second absorption spectra; and selecting, from the plurality of candidate scattering correction models, a candidate scattering correction model for which the difference between the estimated concentration and the actual concentration of the analyte is minimized.

[0025] The steps of obtaining the ratio may include: obtaining the reflectivity of an object based on the received light; obtaining the albedo of the object based on the obtained reflectivity; and obtaining the ratio of the absorption coefficient to the scattering coefficient based on the obtained albedo.

[0026] The step of obtaining the first absorption spectrum may include: obtaining the first absorption spectrum based on a function of the ratio of the absorption coefficient to the scattering coefficient.

[0027] The step of estimating may include: estimating the concentration of the analyte for each of the plurality of second absorption spectra by using each second absorption spectrum of the plurality of second absorption spectra and the pure component spectrum of the analyte.

[0028] The step of obtaining the plurality of second absorption spectra may include: obtaining the plurality of second absorption spectra by using one of principal component analysis (PCA), independent component analysis (ICA), non - negative matrix factorization (NMF), and singular value decomposition (SVD).

[0029] The analyte may include at least one of glucose, triglyceride, urea, uric acid, lactic acid, protein, cholesterol, antioxidant, and ethanol.

[0030] According to an aspect of an example embodiment, there is provided a method of calibrating a device for estimating the concentration of an analyte, the method including: emitting a first light toward an object and receiving a second light reflected from the object, the concentration of the analyte in the object being a first concentration; obtaining a first ratio of an absorption coefficient to a scattering coefficient based on the received second light; obtaining a first absorption spectrum of the object from the obtained first ratio; obtaining a second absorption spectrum by eliminating a first scattering correction spectrum from the first absorption spectrum, the scattering correction spectrum corresponding to a non - linear change of the scattering coefficient according to the wavelength of the emitted first light; emitting a third light toward the object and receiving a fourth light reflected from the object, the concentration of the analyte in the object being a second concentration; obtaining a second ratio of the absorption coefficient to the scattering coefficient based on the received fourth light; obtaining a third absorption spectrum of the object from the obtained second ratio; obtaining a fourth absorption spectrum of the analyte by eliminating a second scattering correction spectrum from the third absorption spectrum, the second scattering correction spectrum corresponding to a non - linear change of the scattering coefficient according to the wavelength of the emitted third light; and obtaining a pure component spectrum of the analyte based on the obtained second absorption spectrum and the obtained fourth absorption spectrum.

[0031] The step of obtaining the pure component spectrum may include: obtaining the pure component spectrum by using the difference between the fourth absorption spectrum and the second absorption spectrum and the difference between the second concentration and the first concentration.

[0032] The method may further include: generating a concentration estimation model by using the obtained pure component spectrum. Brief Description of the Drawings

[0033] The above and / or other aspects and features of specific example embodiments will become more apparent from the following description taken in conjunction with the drawings, in which:

[0034] Figure 1is a block diagram showing an apparatus for estimating the concentration of an analyte according to an exemplary embodiment;

[0035] Figure 2 is a diagram illustrating a method for correcting the influence of the non - linear change of the scattering coefficient with wavelength according to an exemplary embodiment;

[0036] Figure 3 is a diagram illustrating the difference in the second absorption spectra at each concentration according to an exemplary embodiment;

[0037] Figure 4 is a diagram showing obtaining a pure component spectrum of an analyte according to an exemplary embodiment;

[0038] Figure 5 is a diagram illustrating the result of estimating the concentration of an analyte according to an exemplary embodiment;

[0039] Figure 6 is a block diagram showing an apparatus for estimating the concentration of an analyte according to an exemplary embodiment;

[0040] Figure 7 is a flowchart showing a method for generating a scattering correction model according to an exemplary embodiment;

[0041] Figure 8 is a flowchart showing a method for generating a concentration estimation model according to an exemplary embodiment;

[0042] Figure 9 is a flowchart showing a method for estimating the concentration of an analyte according to an exemplary embodiment; and

[0043] Figure 10 is a diagram showing a wrist - worn wearable device according to an exemplary embodiment. Detailed Description of the Embodiment

[0044] Hereinafter, the disclosed exemplary embodiments will be described in detail with reference to the accompanying drawings. It should be noted that even in different drawings, the same reference numerals denote the same components as much as possible. In the following description, when the detailed description of known functions and configurations included herein may obscure the disclosed subject matter, the detailed description thereof will be omitted.

[0045] Throughout the drawings and the detailed description, unless otherwise described, the same reference numerals will be understood to represent the same elements, features, and structures. For clarity, illustration, and convenience, the relative sizes and depictions of these elements may be exaggerated.

[0046] Unless a specified order is explicitly indicated as necessary in the context of disclosure, the processing steps described herein can be performed in a different order than the specified order. That is, each step can be performed in the specified order, substantially simultaneously, or in the reverse order, or in any order different from the specified order.

[0047] In addition, the terms used throughout this specification are defined in consideration of the functions according to the exemplary embodiments and can vary according to the purposes or precedents of users or administrators, etc. Therefore, the definitions of the terms should be based on the entire context.

[0048] It will be understood that although terms such as first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. Unless otherwise explicitly stated, any reference to the singular may also include the plural. In this specification, it should be understood that terms such as "comprising" or "having" are intended to indicate the presence of features, quantities, steps, actions, components, parts, or combinations thereof disclosed in the specification, and are not intended to exclude the possibility of the existence or addition of one or more other features, quantities, steps, actions, components, parts, or combinations thereof.

[0049] As used herein, when an expression such as "at least one of..." follows a list of elements, it modifies the entire list of elements, rather than modifying a single element in the list. For example, the expression "at least one of a, b, and c" should be understood to include only a, only b, only c, both a and b, both a and c, both b and c, or all of a, b, and c.

[0050] In addition, the components described in the specification will be distinguished only based on the functions mainly performed by the components. That is, two or more components to be described later can be integrated into a single component. In addition, a single component can be divided into two or more components. In addition, each component to be described can additionally perform some or all of the functions performed by another component in addition to its main function. Some or all of the main functions of each component can be performed by another component. Each component can be implemented as hardware, software, or a combination thereof.

[0051] Figure 1 is a block diagram showing a device for estimating the concentration of an analyte according to an exemplary embodiment.

[0052] Figure 1The device 100 for estimating analyte concentration can measure the concentration of an analyte in vivo by analyzing the absorption spectrum of an object, and can be included in an electronic device or encapsulated in a housing to be provided as a separate device. Examples of electronic devices can include: cellular phones, smartphones, tablet personal computers (PCs), laptop computers, personal digital assistants (PDAs), portable multimedia players (PMPs), navigation devices, MP3 players, digital cameras, wearable devices, etc.; examples of wearable devices can include: watch-type wearable devices, wristband-type wearable devices, ring-type wearable devices, belt-type wearable devices, necklace-type wearable devices, ankle-band-type wearable devices, thigh-band-type wearable devices, forearm-band-type wearable devices, etc. However, the electronic devices are not limited to the above examples, and the wearable devices are also not limited to the above examples.

[0053] Here, the analyte can include glucose, triglycerides, urea, uric acid, lactic acid, proteins, cholesterol, antioxidants (e.g., vitamins, carotenoids, flavonoids, ascorbic acid, tocopherols, etc.), ethanol, etc., but is not limited thereto. In the case where the analyte in vivo is glucose, the analyte concentration can indicate the blood glucose level.

[0054] Referring Figure 1 , the device 100 for estimating analyte concentration can include an optical sensor 110 and a processor 120.

[0055] The optical sensor 110 can emit light towards an object and can receive the light reflected from the object. The optical sensor 110 includes a light source 111 and a photodetector 112.

[0056] The light source 111 can emit light towards an object. For example, the light source 111 can emit light of a predetermined wavelength (e.g., visible light or infrared light) towards an object. However, the wavelength of the light emitted by the light source 111 can vary according to the measurement purpose or the type of concentration. In addition, the light source 111 can be not a single light source and can include an array of multiple light sources. In the case where the light source 111 includes multiple light sources, the multiple light sources can emit light of the same wavelength or different wavelengths. In addition, the multiple light sources can be classified into multiple groups, and each group of light sources can emit light of different wavelengths.

[0057] In one exemplary embodiment, the light source 111 can be formed as a light-emitting diode (LED), a laser diode, a phosphor, etc.

[0058] In addition, the light source 111 can also include optical elements (e.g., filters, mirrors, etc.) for selecting light of a desired wavelength or guiding the light emitted by the light source 111 to a desired position.

[0059] The photodetector 112 may receive light reflected from an object. The photodetector 112 may not be a single device and may include an array of multiple devices.

[0060] In one exemplary embodiment, the photodetector 112 may include a photodiode, a phototransistor, an image sensor (e.g., a charge-coupled device (CCD), a complementary metal oxide semiconductor (CMOS), etc.), etc., but is not limited thereto.

[0061] In addition, the photodetector 112 may further include optical elements (e.g., filters, mirrors, etc.) for selecting light of a desired wavelength or directing the light reflected from the object to the photodetector 112.

[0062] The processor 120 may process various signals and operations related to generating a scattering correction model, obtaining pure component spectra, obtaining and correcting absorption spectra, generating a concentration estimation model, estimating a concentration, etc. The processor 120 may include a microprocessor or a central processing unit (CPU).

[0063] The processor 120 may operate in a calibration mode or a concentration estimation mode. Here, the calibration mode may be a mode for establishing a model for estimating a concentration, and the concentration estimation mode may be a mode for estimating a concentration by using the model established in the calibration mode.

[0064] Hereinafter, the calibration mode and the concentration estimation mode will be described.

[0065] <Calibration Mode>

[0066] In the calibration mode according to the exemplary embodiment, the processor 120 may generate a scattering correction model for eliminating the influence of the non-linear change of the scattering coefficient from the absorption spectrum, and generate a concentration estimation model for estimating the concentration of the analyte.

[0067] (1) Generating a Scattering Correction Model

[0068] The processor 120 may control the optical sensor 110 to emit light towards the object and receive the light reflected from the object.

[0069] The processor 120 may obtain the ratio of the absorption coefficient to the scattering coefficient based on the received light. For example, the processor 120 may obtain the reflectance of the object by using the amount of the received light, and may obtain the albedo of the object by using Equation 1 below. In addition, the processor 120 may obtain the ratio of the absorption coefficient to the scattering coefficient by using Equation 2 below.

[0070] [Equation 1]

[0071]

[0072]

[0073] r d = -1.440n rel -2 +0.710n rel -1 +0.668 + 0.0636n rel

[0074] Here, R represents the reflectance, a′ represents the albedo, and n rel represents the ratio of the refractive index of the medium to the refractive index of air (n rel = n medium / n air where n air = 1). k and r d represent coefficients.

[0075] [Equation 2]

[0076]

[0077] Here, μ a represents the absorption coefficient, and μ′ s represents the scattering coefficient.

[0078] After obtaining the ratio of the absorption coefficient to the scattering coefficient, the processor 120 can obtain the first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient.

[0079] The absorbance of the object can be represented by Equation 3 below, and the optical path length can be represented by Equation 4 below.

[0080] [Equation 3]

[0081] Absorbance = μ α × l

[0082] [Equation 4]

[0083]

[0084] Here, l represents the optical path length.

[0085] By substituting the expression for the optical path length in Equation 4 into Equation 3, the absorbance of the object can be expressed as a function of the ratio of the absorption coefficient to the scattering coefficient as represented by Equation 5 below.

[0086] [Equation 5]

[0087]

[0088] In an example embodiment, the processor 120 may calculate the absorbance of an object by using Equation 5 and may obtain a first absorption spectrum based on the calculated absorbance. As discussed above, the absorbance of an object may be expressed as a function of the ratio of the absorption coefficient to the scattering coefficient as represented by Equation 5.

[0089] The scattering coefficient may have a monotonic characteristic in which the scattering coefficient decreases as the wavelength increases. Therefore, this monotonic characteristic of the scattering coefficient may be expressed as a monotonic function by the following Equation 6.

[0090] [Equation 6]

[0091] μ′ s (λ)=Aλ -B

[0092] Here, λ represents the wavelength; μ′ s (λ) represents the scattering coefficient at wavelength λ; A and B respectively represent coefficients related to the scattering density and the size of Mie scatter.

[0093] By substituting the expression of the scattering coefficient in Equation 6 into Equation 4 for approximation, the optical path length may be approximated by the following Equation 7.

[0094] [Equation 7]

[0095]

[0096] As shown by Equation 7, the optical path length may be expressed as a non-linear function of the wavelength of light. C and D are coefficients that appear during the formula transformation.

[0097] The change in the scattering coefficient causes a change in the optical path length, such that by correcting the influence of the non-linear change of the optical path length according to the wavelength, the influence of the non-linear change of the scattering coefficient according to the wavelength may be corrected.

[0098] That is, by using Equation 7 that represents the non-linear change of the optical path length according to the wavelength, the processor 120 may generate a scattering correction model as represented by the following Equation 8.

[0099] [Equation 8]

[0100] S raw =k×(E + Fλ m ) + S corr

[0101] Here, S raw represents the first absorption spectrum, S corr represents the second absorption spectrum obtained by correction, (E + Fλ mrepresents a scattering correction spectrum, which indicates the influence of the non-linear change of the scattering coefficient according to the wavelength or the influence of the non-linear change of the optical path length according to the wavelength. k represents the contribution of the scattering correction spectrum, and E, F, and m represent coefficients.

[0102] Here, k and the second absorption spectrum can be obtained in the process of obtaining the second absorption spectrum by eliminating the influence of the scattering correction spectrum from the first absorption spectrum using various dimensionality reduction algorithms (such as principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NMF), singular value decomposition (SVD), etc.).

[0103] In addition, E, F, and m can be determined by the following method.

[0104] The processor 120 can generate multiple candidate scattering correction models by changing the coefficients E, F, and m. In addition, by using the generated multiple candidate scattering correction models, the processor 120 can obtain multiple second absorption spectra. By using the default concentration estimation model represented by Equation 9 below, the processor 120 can estimate the analyte concentration for each second absorption spectrum.

[0105] [Equation 9]

[0106] S corr = ε g C g + ε1C1 + ε2C2 + …

[0107] Here, ε g represents the pure component spectrum of the analyte set to the default value, C g represents the concentration of the analyte, and ε1 and ε2 respectively represent the pure component spectra of substances other than the analyte set to the default value, and C1 and C2 respectively represent the concentrations of substances other than the analyte.

[0108] In addition, the processor 120 can determine E, F, and m by selecting a candidate scattering correction model for obtaining such a second absorption spectrum from among the multiple candidate scattering correction models, where the difference between the estimated concentration and the actual concentration is minimized for the second absorption spectrum.

[0109] (2) Generate a concentration estimation model

[0110] When the concentration of the analyte in the object is the first concentration, the processor 120 can control the optical sensor 110 to emit light towards the object and receive the light reflected from the object.

[0111] The processor 120 can obtain the ratio of the absorption coefficient to the scattering coefficient based on the received light. For example, the processor 120 can obtain the reflectivity of the object by using the amount of the received light, and can obtain the albedo of the object based on the obtained reflectivity by using Equation 1. In addition, the processor 120 can obtain the ratio of the absorption coefficient to the scattering coefficient based on the obtained albedo by using Equation 2.

[0112] After obtaining the ratio of the absorption coefficient to the scattering coefficient, the processor 120 can obtain the first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient.

[0113] By using the scattering correction model represented by Equation 8 to eliminate the scattering correction spectrum indicating the influence of the non-linear change of the scattering coefficient according to the wavelength from the first absorption spectrum, the processor 120 can obtain the second absorption spectrum when the concentration of the analyte is the first concentration.

[0114] By using the above method, the processor 120 can obtain the second absorption spectrum when the concentration of the analyte is the second concentration. In this case, the second concentration can be a value different from the first concentration.

[0115] The processor 120 can obtain the pure component spectrum of the analyte based on the second absorption spectrum when the concentration of the analyte is the first concentration and the second absorption spectrum when the concentration of the analyte is the second concentration. For example, the processor 120 can obtain the pure component spectrum of the analyte by using Equation 10 below.

[0116] [Equation 10]

[0117]

[0118] Here, ε′ g represents the pure component spectrum of the analyte, C g1 and C g2 represent the first concentration and the second concentration respectively, S corr1 and S corr2 represent the second absorption spectrum obtained at the first concentration and the second absorption spectrum obtained at the second concentration respectively.

[0119] After obtaining the pure component spectrum of the analyte, the processor 120 can generate a concentration estimation model represented by Equation 11 below.

[0120] [Equation 11]

[0121] S corr =ε′ g C g +ε1C1+ε2C2+…

[0122] <Concentration Estimation Model>

[0123] In the concentration estimation mode according to an exemplary embodiment, the processor 120 may control the optical sensor 110 to emit light toward an object and receive the light reflected from the object.

[0124] The processor 120 may obtain the ratio of the absorption coefficient to the scattering coefficient based on the received light. For example, the processor 120 may obtain the reflectance of the object by using the amount of the received light, and may obtain the albedo of the object based on the obtained reflectance by using Equation 1. In addition, the processor 120 may obtain the ratio of the absorption coefficient to the scattering coefficient based on the obtained albedo by using Equation 2.

[0125] After obtaining the ratio of the absorption coefficient to the scattering coefficient, the processor 120 may obtain the first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient.

[0126] By using the scattering correction model represented by Equation 8, the processor 120 may obtain the second absorption spectrum by eliminating the scattering correction spectrum indicating the influence of the non-linear change of the scattering coefficient according to the wavelength from the first absorption spectrum.

[0127] After obtaining the second absorption spectrum, the processor 120 may estimate the analyte concentration by using the concentration estimation model of Equation 9 or Equation 11. In this case, the processor 120 may estimate the analyte concentration by using various dimensionality reduction algorithms (such as principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NMF), singular value decomposition (SVD), etc.).

[0128] Figure 2 is a diagram illustrating a method of correcting the influence of the non-linear change of the scattering coefficient according to the wavelength according to an exemplary embodiment.

[0129] Refer to Figure 1 and Figure 2 and, by controlling the optical sensor 110 to receive light, the processor 120 may obtain the reflectance of the object by using the amount of the received light, and may obtain the ratio of the absorption coefficient to the scattering coefficient based on the obtained reflectance by using Equation 1 and Equation 2.

[0130] After obtaining the ratio of the absorption coefficient to the scattering coefficient, the processor 120 may obtain the first absorption spectrum 210 of the object from the obtained ratio of the absorption coefficient to the scattering coefficient by using Equation 5.

[0131] The processor may generate the second absorption spectrum 230 by eliminating the scattering correction spectrum 220 from the first absorption spectrum 210 by using the scattering correction model of Equation 8 generated in the calibration mode, and the scattering correction spectrum 220 indicates the influence of the non-linear change of the scattering coefficient according to the wavelength or the influence of the non-linear change of the optical path length according to the wavelength.

[0132] Figure 3 This is a diagram illustrating the differences in the second absorption spectra at each concentration according to an exemplary embodiment.

[0133] In Figure 3 the example of 4 mg / dl, reference numeral 310 represents the first absorption spectrum at an analyte concentration of 10 3 mg / dl, and reference numeral 320 represents the first absorption spectrum at an analyte concentration of 10

[0134] In the first absorption spectrum 310 when the analyte concentration is 10 4 mg / dl, the second absorption spectrum 330 can be obtained by correcting the influence of the non-linear change of the scattering coefficient according to the wavelength. In addition, in the first absorption spectrum 320 when the analyte concentration is 10 3 mg / dl, the second absorption spectrum 340 can be obtained by correcting the influence of the non-linear change of the scattering coefficient according to the wavelength.

[0135] As Figure 3 shown, before correction, the reduced scattering coefficient caused by the analyte causes a change in the optical path length, resulting in an offset between the absorption spectra at each concentration of the analyte. In contrast, after correction, the offset between the absorption spectra at each concentration of the analyte is reduced.

[0136] Figure 4 This is a diagram showing the acquisition of the pure component spectrum of an analyte according to an exemplary embodiment.

[0137] Referring to Figure 1 、 Figure 3 and Figure 4 , the processor 120 can obtain the pure component spectrum of the analyte by using Equation 10. For example, based on the second absorption spectrum 330 at an analyte concentration of 10 4 mg / dl and the second absorption spectrum 340 at an analyte concentration of 10 3 mg / dl, the processor 120 can obtain the pure component spectrum 410 of the analyte by using Equation 10.

[0138] Figure 5 This is a diagram illustrating the results of estimating the analyte concentration according to an exemplary embodiment.

[0139] Figure 5 The graph 510 in shows the results of estimating the analyte concentration by the method according to an exemplary embodiment (e.g., obtaining the first absorption spectrum by using an absorbance calculation equation (e.g., Equation 5) represented as a function of the ratio of the absorption coefficient to the scattering coefficient, and obtaining the second absorption spectrum by eliminating the influence of the non-linear change of the scattering coefficient from the first absorption spectrum).Figure 5 The graph 520 in

[0140] shows the result of estimating the analyte concentration by a basic comparison method (e.g., obtaining a first absorption spectrum by using an absorbance calculation equation (absorbance = log(1 / R)) of a function represented as the reciprocal of reflectance, and obtaining a second absorption spectrum by using multiplicative scatter correction (MSC) to correct the influence of the linear change of the scattering coefficient). Figure 5 As shown in

[0141] Figure 6 is a block diagram showing a device for estimating the concentration of an analyte according to an exemplary embodiment.

[0142] Figure 6 The device 600 for estimating the analyte concentration can measure the concentration of the analyte in vivo by analyzing the absorption spectrum of the object, and can be included in an electronic device or can be encapsulated in a housing to be provided as a separate device. Examples of the electronic device may include: cellular phone, smart phone, tablet PC, laptop computer, personal digital assistant (PDA), portable multimedia player (PMP), navigation device, MP3 player, digital camera, wearable device, etc.; examples of the wearable device may include: watch-type wearable device, wristband-type wearable device, ring-type wearable device, belt-type wearable device, necklace-type wearable device, ankle-band-type wearable device, thigh-band-type wearable device, forearm-band-type wearable device, etc. However, the electronic device is not limited to the above examples, and the wearable device is also not limited to the above examples.

[0143] Referring to Figure 6 , the device 600 for estimating the analyte concentration includes an optical sensor 110, a processor 120, an input interface 610, a storage device 620, a communication interface 630, and an output interface 640. Here, the optical sensor 110 and the processor 120 are substantially the same or similar to those described above with reference to Figures 1 to 5 and thus, their detailed descriptions will be omitted.

[0144] The input interface 610 can receive the input of various operation signals from the user. In one exemplary embodiment, the input interface 610 may include a keyboard, dome switch, touchpad (e.g., static pressure and / or capacitive touchpad), roller, roller switch, hardware (H / W) button, etc. A touchpad forming a layer structure with the display may be referred to as a touch screen.

[0145] The storage device 620 may store programs or commands for operating the device 600 for estimating analyte concentration, and may store data input to the device 600 for estimating analyte concentration and / or data output from the device 600 for estimating analyte concentration. In addition, the storage device 620 may store data processed by the device 600 for estimating analyte concentration, data for performing data processing of the device 600 for estimating analyte concentration (e.g., various models), and the like.

[0146] The storage device 620 may include at least one of the following storage media: flash memory type, hard disk type, multimedia card micro memory, card type memory (e.g., secure digital (SD) memory, extreme digital (XD) memory, etc.), random access memory (RAM), static random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), magnetic memory, magnetic disk, and optical disk, etc. In addition, the device 600 for estimating analyte concentration may operate in association with an external storage medium (such as a network storage device that performs the storage function of the storage device 620 on the Internet).

[0147] The communication interface 630 may communicate with an external device. For example, the communication interface 630 may send data used by the device 600 for estimating analyte concentration, processing result data of the device 600 for estimating analyte concentration, etc. to the external device, or may receive various data useful for generating a model and / or estimating analyte concentration from the external device.

[0148] In this case, the external device may be a medical device that uses data used by the device 600 for estimating analyte concentration, processing result data of the device 600 for estimating analyte concentration, etc., a printer that prints results, or a display for displaying results. In addition, the external device may be a digital television (TV), desktop computer, cellular phone, smart phone, tablet PC, laptop computer, personal digital assistant (PDA), portable multimedia player (PMP), navigation device, MP3 player, digital camera, wearable device, etc., but the external device is not limited thereto.

[0149] The communication interface 630 can communicate with external devices by using one or more of the following communication methods: Bluetooth communication, Bluetooth Low Energy (BLE) communication, Near Field Communication (NFC), Wireless Local Area Network (WLAN) communication, Zigbee communication, Infrared Data Association (IrDA) communication, Wi-Fi Direct (WFD) communication, Ultra-Wideband (UWB) communication, Ant+ communication, WI-FI communication, Radio Frequency Identification (RFID) communication, Third Generation (3G) communication, Fourth Generation (4G) communication, Fifth Generation (5G) communication, etc. However, these are only examples and are not intended to be limiting.

[0150] The output interface 640 can output data used by the device 600 for estimating analyte concentration, processing result data of the device 600 for estimating analyte concentration, etc. In one exemplary embodiment, the output interface 640 can output data used by the device 600 for estimating analyte concentration, processing result data of the device 600 for estimating analyte concentration, etc. by using at least one of an acoustic method, a visual method, and a tactile method. To this end, the output interface 640 can include a display, a speaker, a vibrator, etc.

[0151] Figure 7 is a flowchart showing a method for generating a scatter correction model according to an exemplary embodiment. Figure 7 The method for generating the scatter correction model can be performed by Figure 1 the device 100 for estimating analyte concentration and Figure 6 either of the device 600 for estimating analyte concentration.

[0152] Referring to Figure 7 , in 710, the device for estimating analyte concentration can emit light towards an object and receive the light reflected from the object.

[0153] In 720, the device for estimating analyte concentration can obtain the ratio of the absorption coefficient to the scattering coefficient based on the received light. For example, the device for estimating analyte concentration can obtain the reflectance of the object by using the amount of the received light, and can obtain the albedo of the object based on the obtained reflectance by using Equation 1. In addition, the device for estimating analyte concentration can obtain the ratio of the absorption coefficient to the scattering coefficient based on the obtained albedo by using Equation 2.

[0154] After obtaining the ratio of the absorption coefficient to the scattering coefficient, in 730, the device for estimating analyte concentration can obtain the first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient. For example, the device for estimating analyte concentration can calculate the absorbance of the object by using the absorbance calculation equation of Equation 5, and can obtain the first absorption spectrum based on the calculated absorbance.

[0155] In 740, the device for estimating analyte concentration can generate multiple candidate scatter correction models by changing the coefficients of a function representing the change in optical path length with wavelength. For example, the device for estimating analyte concentration can generate multiple candidate scatter correction models by changing the coefficients E, F, and m in Equation 7.

[0156] In 750, by using the multiple generated candidate scatter correction models to eliminate the scatter correction spectrum indicating the influence of the non-linear change of the scattering coefficient according to wavelength from the first absorption spectrum, the device for estimating analyte concentration can obtain multiple second absorption spectra. For example, the device for estimating analyte concentration can obtain multiple second absorption spectra by using various dimensionality reduction algorithms (such as principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NMF), singular value decomposition (SVD), etc.) to eliminate the influence of the scatter correction spectrum from the first absorption spectrum.

[0157] In 760, the device for estimating analyte concentration can estimate the analyte concentration for each second absorption spectrum by using the default concentration estimation model. For example, the device for estimating analyte concentration can estimate the analyte concentration for each second absorption spectrum by using the default concentration estimation model represented by Equation 9.

[0158] In 770, the device for estimating analyte concentration can select, from among the multiple candidate scatter correction models, the candidate scatter correction model used to obtain such a second absorption spectrum as the final scatter correction model, under which the difference between the estimated concentration and the actual concentration is minimized.

[0159] Figure 8 is a flowchart showing a method for generating a concentration estimation model according to an exemplary embodiment. Figure 8 The method for generating the concentration estimation model can be performed by Figure 1 the device 100 for estimating analyte concentration of Figure 6 and any one of the device 600 for estimating analyte concentration of

[0160] Refer to Figure 8, in 810, the device for estimating analyte concentration can obtain a second absorption spectrum when the concentration of the analyte in the object is the first concentration. For example, when the concentration of the analyte in the object is the first concentration, the device for estimating analyte concentration can emit light towards the object, receive the light reflected from the object, and obtain the ratio of the absorption coefficient to the scattering coefficient based on the received light. In addition, the device for estimating analyte concentration can obtain the first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient. Further, based on the scattering correction model, by using various dimensionality reduction algorithms (such as principal component analysis (PCA), independent component analysis (ICA), non - negative matrix factorization (NMF), singular value decomposition (SVD), etc.) to eliminate the influence of the scattering correction spectrum from the first absorption spectrum, the device for estimating analyte concentration can obtain the second absorption spectrum when the concentration of the analyte in the object is the first concentration.

[0161] In 820, the device for estimating analyte concentration can obtain a second absorption spectrum when the concentration of the analyte in the object is the second concentration. For example, when the concentration of the analyte in the object is the second concentration, the device for estimating analyte concentration can emit light towards the object, receive the light reflected from the object, and obtain the ratio of the absorption coefficient to the scattering coefficient based on the received light. In addition, the device for estimating analyte concentration can obtain the first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient. Further, based on the scattering correction model, by using various dimensionality reduction algorithms (such as principal component analysis (PCA), independent component analysis (ICA), non - negative matrix factorization (NMF), singular value decomposition (SVD), etc.) to eliminate the influence of the scattering correction spectrum from the first absorption spectrum, the device for estimating analyte concentration can obtain the second absorption spectrum when the concentration of the analyte in the object is the second concentration.

[0162] In 830, the device for estimating analyte concentration can obtain the pure component spectrum of the analyte based on the second absorption spectrum when the concentration of the analyte in the object is the first concentration and the second absorption spectrum when the concentration of the analyte in the object is the second concentration. For example, the device for estimating analyte concentration can obtain the pure component spectrum of the analyte by using Equation 10.

[0163] In 840, by using the obtained pure component spectrum of the analyte, the device for estimating analyte concentration can generate a concentration estimation model. For example, the device for estimating analyte concentration can generate a concentration estimation model as represented by Equation 11.

[0164] Figure 9 is a flowchart showing a method for estimating the concentration of an analyte. Figure 9 The method for estimating analyte concentration can be performed by Figure 1 the device 100 for estimating analyte concentration ofFigure 6 is performed by any one of the devices 600 for estimating analyte concentration.

[0165] In 910, the device for estimating analyte concentration can emit light toward an object and receive the light reflected from the object.

[0166] In 920, the device for estimating analyte concentration can obtain a ratio of an absorption coefficient to a scattering coefficient based on the received light. For example, the device for estimating analyte concentration can obtain a reflectance of the object by using an amount of the received light, and can obtain an albedo of the object based on the obtained reflectance by using Equation 1. In addition, the device for estimating analyte concentration can obtain the ratio of the absorption coefficient to the scattering coefficient based on the obtained albedo by using Equation 2.

[0167] After obtaining the ratio of the absorption coefficient to the scattering coefficient, in 930, the device for estimating analyte concentration can obtain a first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient. For example, the device for estimating analyte concentration can obtain the first absorption spectrum by using an absorbance calculation equation of Equation 5 that is represented as a function of the ratio of the absorption coefficient to the scattering coefficient.

[0168] By using a scattering correction model to eliminate an influence of a scattering correction spectrum indicating a non-linear change of the scattering coefficient according to wavelength from the first absorption spectrum, in 940, the device for estimating analyte concentration can obtain a second absorption spectrum. For example, based on the scattering correction model represented by Equation 8, by using various dimensionality reduction algorithms (such as, principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NMF), singular value decomposition (SVD), etc.), the device for estimating analyte concentration can obtain the second absorption spectrum from the first absorption spectrum.

[0169] After obtaining the second absorption spectrum, in 950, the device for estimating analyte concentration can estimate the analyte concentration by using the second absorption spectrum and a concentration estimation model. In this case, the device for estimating analyte concentration according to an exemplary embodiment can estimate the analyte concentration by using various dimensionality reduction algorithms (such as, principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NMF), singular value decomposition (SVD), etc.). The concentration estimation model can be represented by Equation 9 or Equation 11.

[0170] Figure 10 is a diagram showing a wrist-wearable device according to an exemplary embodiment.

[0171] Referring to Figure 10 , the wrist-wearable device 1000 includes a band 1010 and a body 1020.

[0172] The strap 1010 can be connected to both ends of the main body 1020 so as to be fixedly attached in a detachable manner, or can be integrally formed with the main body 1020 as a smart strap. The strap 1010 can be made of a flexible material to wrap around the user's wrist so that the main body 1020 can be worn on the wrist.

[0173] The main body 1020 can include any one of the aforementioned devices 100 and 600 for estimating analyte concentration. In addition, the main body 1020 can include a battery that powers the wrist-wearable device 1000 and any one of the devices 100 and 600 for estimating analyte concentration.

[0174] The biosensor can be mounted on the main body 1020 (e.g., on the rear surface of the main body 1020) to be exposed to the user's wrist. Thus, when the user wears the wrist-wearable device 1000, the biosensor can naturally come into contact with the user's skin.

[0175] The wrist-wearable device 1000 can also include a display 1021 and an input interface 1022 mounted on the main body 1020. The display 1021 can display data processed by the wrist-wearable device 1000 and any one of the devices 100 and 600 for estimating analyte concentration, their processed result data, etc. The input interface 1022 can receive various operation signals from the user.

[0176] The disclosure can be implemented as computer-readable code written on a computer-readable recording medium. A computer programming person of ordinary skill in the art can easily derive the code and code segments required to implement the disclosure. The computer-readable recording medium can be any type of recording device that stores data in a computer-readable manner. Examples of the computer-readable recording medium include: ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical disk, etc. In addition, the computer-readable recording medium can be distributed on multiple computer systems connected to a network so that the computer-readable recording medium is written therein and executed therefrom in a distributed manner.

[0177] Example embodiments have been described. However, it will be clear to those skilled in the art that various changes and modifications can be made without departing from the inventive concept of the disclosure. Therefore, it should be understood that the above example embodiments are not intended to limit the disclosure, but include various modifications and equivalents included within the spirit and scope of the appended claims.

Claims

1. An apparatus for estimating the concentration of an analyte, the apparatus comprising: an optical sensor configured to: emit light toward an object and receive light reflected from the object; as well as The processor is configured to: The ratio of the absorption coefficient to the scattering coefficient is obtained based on the received light, obtaining a first absorption spectrum of the object based on the obtained ratio, obtaining a second absorption spectrum by eliminating a scattering correction spectrum from the first absorption spectrum, the scattering correction spectrum corresponding to a nonlinear change in a scattering coefficient according to a wavelength of emitted light, and The concentration of the analyte is estimated based on the second absorbance spectrum.

2. The device according to claim 1, wherein The processor is also configured to: obtain the reflectivity of the object based on the received light, obtaining the albedo of the object based on the obtained reflectivity, and The ratio of the absorption coefficient to the scattering coefficient is obtained based on the obtained albedo.

3. The device according to claim 1, wherein The processor is further configured to obtain a first absorption spectrum based on a function of a ratio of the absorption coefficient to the scattering coefficient.

4. The device according to claim 1, wherein The scatter-corrected spectrum is expressed as a function representing a change in the length of the optical path according to the wavelength of the emitted light; and The processor is further configured to obtain a second absorption spectrum by using a scatter correction model based on the function.

5. The device according to claim 4, wherein The processor is also configured to: generating a plurality of candidate scatter correction models by varying the coefficients of the function, obtaining a plurality of second absorption spectra by using the first absorption spectrum and the plurality of candidate scatter correction models; estimating the concentration of the analyte for each second absorbance spectrum of the plurality of second absorbance spectra, and A candidate scatter correction model having the smallest difference between the estimated concentration and the actual concentration of the analyte is selected from among the plurality of candidate scatter correction models as the scatter correction model.

6. The apparatus according to claim 1, wherein The processor is further configured to estimate the concentration of the analyte by using the second absorbance spectrum and the pure component spectrum of the analyte.

7. The apparatus according to claim 6, wherein Pure component spectra of the analytes are set as default values or acquired and set in calibration mode.

8. The apparatus according to claim 7, wherein The processor is further configured to, in the calibration mode, obtain a pure component spectrum of the analyte based on a difference between a second absorption spectrum obtained when the concentration of the analyte in the subject is a first concentration and a second absorption spectrum obtained when the concentration of the analyte in the subject is a second concentration.

9. The apparatus according to claim 1, wherein The processor is further configured to obtain a second absorption spectrum by eliminating the scattering correction spectrum from the first absorption spectrum using one of principal component analysis, independent component analysis, non-negative matrix decomposition, and singular value decomposition.

10. The apparatus according to claim 1, wherein The analyte includes at least one of glucose, triglyceride, urea, uric acid, lactic acid, protein, cholesterol, antioxidants, and ethanol.

11. A method for estimating the concentration of an analyte, the method comprising: emitting light toward an object and receiving light reflected from the object; obtaining a ratio of an absorption coefficient to a scattering coefficient based on the received light; obtaining a first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient; obtaining a second absorption spectrum by eliminating a scattering correction spectrum from the first absorption spectrum, the scattering correction spectrum corresponding to a nonlinear change in a scattering coefficient according to a wavelength of emitted light; as well as The concentration of the analyte is estimated based on the second absorbance spectrum.

12. The method according to claim 11, wherein The steps of obtaining the ratio include: obtaining a reflectivity of the object based on the received light; obtaining an albedo of the object based on the obtained reflectivity; and The ratio of the absorption coefficient to the scattering coefficient is obtained based on the obtained albedo.

13. The method according to claim 11, wherein The step of obtaining the first absorption spectrum includes obtaining the first absorption spectrum based on a function of a ratio of an absorption coefficient to a scattering coefficient.

14. The method according to claim 11, wherein The scatter-corrected spectrum is expressed as a function representing the change in length of the optical path according to the wavelength of the emitted light; and The step of obtaining the second absorption spectrum includes obtaining the second absorption spectrum by using a scattering correction model based on the function.

15. The method according to claim 11, wherein The estimating step includes estimating the concentration of the analyte by using the second absorption spectrum and a pure component spectrum of the analyte.

16. The method according to claim 15, wherein Pure component spectra of the analytes are set as default values or acquired and set in calibration mode.

17. The method according to claim 11, wherein The step of obtaining the second absorption spectrum includes obtaining the second absorption spectrum by eliminating the scattering correction spectrum from the first absorption spectrum using one of principal component analysis, independent component analysis, non-negative matrix decomposition, and singular value decomposition.

18. The method according to claim 11, wherein The analyte includes at least one of glucose, triglyceride, urea, uric acid, lactic acid, protein, cholesterol, antioxidants, and ethanol.

19. A method of calibrating an apparatus for estimating the concentration of an analyte, the method comprising: emitting light toward an object and receiving light reflected from the object; obtaining a ratio of an absorption coefficient to a scattering coefficient based on the received light; obtaining a first absorption spectrum of the object from the obtained ratio of the absorption coefficient to the scattering coefficient; generating a plurality of candidate scatter correction models by varying coefficients of a function representing a change in the length of the optical path according to the wavelength of emitted light; obtaining a plurality of second absorption spectra by using the first absorption spectrum and the plurality of candidate scatter correction models; estimating a concentration of an analyte for each second absorbance spectrum in the plurality of second absorbance spectra; as well as A candidate scatter correction model having the smallest difference between the estimated concentration and the actual concentration of the analyte is selected from among the plurality of candidate scatter correction models as the scatter correction model.

20. The method according to claim 19, wherein The steps of obtaining the ratio include: obtaining a reflectivity of the object based on the received light; obtaining an albedo of the object based on the obtained reflectivity; and The ratio of the absorption coefficient to the scattering coefficient is obtained based on the obtained albedo.

21. The method according to claim 19, wherein The step of obtaining the first absorption spectrum includes obtaining the first absorption spectrum based on a function of a ratio of an absorption coefficient to a scattering coefficient.

22. The method according to claim 19, wherein The estimating step includes estimating the concentration of the analyte for each of the plurality of second absorption spectra by using each of the plurality of second absorption spectra and a pure component spectrum of the analyte.

23. The method according to claim 19, wherein The step of obtaining the plurality of second absorption spectra includes obtaining the plurality of second absorption spectra by using one of principal component analysis, independent component analysis, non-negative matrix decomposition, and singular value decomposition.

24. The method according to claim 19, wherein The analyte includes at least one of glucose, triglyceride, urea, uric acid, lactic acid, protein, cholesterol, antioxidants, and ethanol.

25. A method of calibrating an apparatus for estimating the concentration of an analyte, the method comprising: emitting a first light toward an object and receiving a second light reflected from the object, the concentration of an analyte in the object being a first concentration; obtaining a first ratio of an absorption coefficient to a scattering coefficient based on the received second light; obtaining a first absorption spectrum of the object from the obtained first ratio; obtaining a second absorption spectrum by eliminating a first scattering correction spectrum from the first absorption spectrum, the first scattering correction spectrum corresponding to a nonlinear change in a scattering coefficient according to a wavelength of the emitted first light; emitting a third light toward an object and receiving a fourth light reflected from the object, the concentration of the analyte in the object being a second concentration; obtaining a second ratio of the absorption coefficient to the scattering coefficient based on the received fourth light; obtaining a third absorption spectrum of the object from the obtained second ratio; obtaining a fourth absorption spectrum by eliminating a second scattering correction spectrum from the third absorption spectrum, the second scattering correction spectrum corresponding to a nonlinear change in a scattering coefficient according to a wavelength of the emitted third light; as well as Based on the obtained second absorption spectrum and the obtained fourth absorption spectrum, a pure component spectrum of the analyte is obtained.

26. The method according to claim 25, wherein The step of obtaining a pure component spectrum of the analyte includes obtaining a pure component spectrum of the analyte by using a difference between the fourth absorption spectrum and the second absorption spectrum and a difference between the second concentration and the first concentration.

27. The method according to claim 25, further comprising: A concentration estimation model is generated by using the obtained pure component spectra of the analyte.

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