CN103340635B - Optical parameter and blood glucose concentration three-dimensional correlation calculation method based on OCT - Google Patents
Optical parameter and blood glucose concentration three-dimensional correlation calculation method based on OCT Download PDFInfo
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Abstract
The invention relates to an optical parameter and blood glucose concentration three-dimensional correlation calculation method based on the OCT. The method includes the following steps that blood glucose concentration changes of a measured target are controlled; a plurality of blood glucose concentration values at different times and OCT three-dimensional data of the skin tissue are acquired; the OCT three-dimensional data of the skin tissue acquired at different times form OCT three-dimensional data vectors, and the blood glucose concentration values form blood glucose concentration value vectors; the OCT three-dimensional data vectors are aligned to obtain OCT three-dimensional data aligned vectors; an optical parameter three-dimensional distribution vector of the skin is calculated; according to the optical parameter three-dimensional distribution vector of the skin and the blood glucose concentration value vectors, the three-dimensional correlation between the optical parameters of the skin and the blood glucose concentration value is calculated. According to the optical parameter and blood glucose concentration three-dimensional correlation calculation method based on the OCT, the three-dimensional correlation between the optical parameters of the skin tissue and the blood glucose concentration value can be calculated and is used for guiding detecting area selecting of the OCT noninvasive blood glucose detection technology, and accuracy of an OCT noninvasive blood glucose concentration detection system is improved.
Description
Technical field
The present invention relates to measurement of blood sugar concentration field, particularly relate to the computational methods of a kind of optical parametric based on OCT and blood sugar concentration three-dimensional correlation.
Background technology
Diabetes are frequently-occurring diseases of mid-aged population, and along with the raising of people's living standard, the sickness rate of diabetes also rises day by day, and diabetes, tumor are classified as worldwide three disaster diseases by World Health Organization (WHO) together with cardiovascular and cerebrovascular disease.Find a kind of method that blood sugar concentration detects the prevention and therapy of diabetes is had very great significance.Current blood sugar concentration detection method is most widely used is have wound to measure.The method having wound to detect main application relies on electrochemical method to refer to that blood detects the blood glucose concentration value obtaining patient to patient.The method can realize detecting the blood glucose concentration value in a certain moment, but equally also there are some shortcomings.Such as, extraction refers to that blood is more painful, measure blood sugar concentration and needs consumptive material etc.Also have some Wicresoft's detection methods in addition, Wicresoft's detection method mainly detects blood sugar concentration by detecting the tissue fluid extracted from skin, and the method can alleviate the misery of patient, but causes certain wound to patient equally.To sum up, the device of Non-invasive detection blood sugar concentration and correlation method are highly significant.
Research shows, utilizes optical means can detect the corresponding relation of the intensity of the light of returning from skin reflex and the scattering coefficient of skin histology, and the inner blood glucose concentration value of the scattering coefficient of skin histology and biological tissue is closely related.Following single scattered light strength formula can the corresponding relation of the approximate description intensity of light of returning from skin reflex and the scattering coefficient of skin histology:
I
R＝I
oexp[-(μ
a+μ
s)L]
Wherein I
rfor the light intensity of returning from skin reflex, I
ofor projecting the light intensity of skin, μ
afor the absorptance of skin histology, μ
sfor the scattering coefficient of skin histology, L is the total optical path of light transdermal.As can be seen from the above equation, the intensity of the light of returning from skin reflex is the exponential damping with scattering coefficient and absorptance.
In skin histology, the refractive index of body fluid and the refractive index of organelle there are differences.This difference can cause skin histology to scattering of light phenomenon.Glucose is the main ingredient of of body fluid, and when blood sugar concentration changes, the refractive index of body fluid also can change thereupon, and this can cause tissue scatter's coefficient to change.At near infrared band, the scattering coefficient change that glucose causes wants the change of specific absorptivity much bigger, and therefore the change of blood sugar concentration mainly causes the change of skin histology scattering coefficient instead of the change of absorptance.As can be seen here, optical detection skin histology scattering coefficient can as of a noninvasive dynamics monitoring important means.
Skin histology is from organizational structure, comprise a lot of sweat glands, oils and fats gland and blood vessel, these organizational structuries are very strong for the absorption of infrared light, therefore at use OCT(Optical Coherence Tomography, optical coherence tomography) when gathering relevant to skin histology data, can very weak or disappearance at these organizational structure regional signals.When making optically to carry out blood glucose concentration value detection, need to consider that these strong absorptive tissue parts are on the impact on blood sugar test precision of whole signal.Therefore, be necessary to find the rule that in skin histology, different tissues structural region changes by blood glucose concentration value, thus strong absorptive tissue structure is avoided when Non-invasive detection blood glucose, obtain the measurement data with the highly sensitive tissue of change of blood sugar, realize the method for being penetrated the change of skin detection blood sugar concentration by illumination.
OCT is continue ultra sonic imaging, X ray CT (Computed Tomography, computed tomography), MRI(Magnetic Resonance Imaging, nuclear magnetic resonance) after biomedical imaging technology of new generation, low coherence interference technology, the product that combines of confocal microscope principle and superhet Detection Techniques, non-intruding can be realized, high sensitivity, high-resolution carry out imaging to tissue.The ultimate principle that it utilizes low-coherent light to interfere, accurately can be measured amplitude and the relative phase of reflected light to the backscatter signals of the low-coherent light of incidence by detection biological tissue different depth aspect, obtain the microstructure features on organization internal depth direction, pass through horizontal scanning again, data and the image of biological tissue's two dimension or three dimensional structure can be obtained.By scanning the OCT two dimension that obtains or three-dimensional data can use single scattered light strength formula to calculate scattering coefficient with change in depth.
There is the method about adopting OCT to carry out Woundless blood sugar measurement of concetration at present, but measured in blood sugar concentration technology at existing OCT, only had the technology adopting stratiform Information Monitoring to carry out blood sugar concentration analysis.Prior art thinks that skin is layer structure, in an aspect, its blood sugar concentration is consistent, so, existing OCT technology measures the method for blood sugar concentration, is by skin in certain search coverage, carries out measurement layer by layer and obtain optical parametric, then the optical parametric set of every one deck is formed the curve that an optical parametric changes with skin depth, judged the change of blood sugar concentration by the change of this curve; That is, prior art is just carried out optical parametric accumulation and detects the Changing Pattern of optical parametric along with blood glucose on skin depth direction, but skin histology is not a kind of simple layer structure, but a kind of labyrinth in three dimensions, therefore the method for existing this Woundless blood sugar measurement of concetration cannot obtain dependency Changing Pattern in three dimensions between optical parametric and blood sugar concentration.
Summary of the invention
Based on this, be necessary that providing a kind of can obtain the optical parametric based on OCT of dependency Changing Pattern in three dimensions and the computational methods of blood sugar concentration three-dimensional correlation between optical parametric and blood sugar concentration.
Based on the optical parametric of OCT and computational methods for blood sugar concentration three-dimensional correlation, comprise the steps:
The blood sugar concentration change of step (1), control measurand;
Step (2), in the blood sugar concentration change procedure of measurand, gather the OCT three-dimensional data of several not blood glucose concentration value in the same time and skin histologies;
Step (3), the OCT three-dimensional data of skin histology do not gathered in the same time is formed OCT three-dimensional data vector, blood glucose concentration value forms blood glucose concentration value vector;
Step (4), obtain OCT three-dimensional data alignment vector according to skin surface characteristic information alignment OCT three-dimensional data vector;
Step (5), according to OCT three-dimensional data alignment vector calculation skin optical parameter distributed in three dimensions vector;
Step (6), go out the three-dimensional correlation of skin optical parameter and blood glucose concentration value according to skin optical parameter distributed in three dimensions vector sum blood glucose concentration value vector calculation.
Wherein in an embodiment, in the blood sugar concentration conversion step of described control measurand, the blood sugar concentration change controlling measurand takes in glucose or feed realization by making measurand.
Wherein in an embodiment, form in OCT three-dimensional data vector step in the described OCT three-dimensional data by the skin histology do not gathered in the same time, also comprise the steps:
Described OCT three-dimensional data vector and blood glucose concentration value are formed OCT three-dimensional data vector right with blood glucose concentration value vector.
Wherein in an embodiment, described according in OCT three-dimensional data alignment vector calculation skin optical parameter distributed in three dimensions vector step, comprise the steps:
Step a, the OCT three-dimensional data elements selected in OCT three-dimensional data alignment vector;
Step b, selection three-dimensional rectangle frame size;
Step c, coordinate points P(x at skin histology, y, z) place, use selected three-dimensional rectangle frame from this OCT three-dimensional data elements, take the three-dimensional subdata of an OCT;
Steps d, in the three-dimensional subdata of OCT, along degree of depth Z-direction, the three-dimensional subdata of OCT is averaged in the XOY plane parallel with skin surface, obtain the position coordinates of one dimension OCT data and correspondence thereof;
Step e, calculate P(x, y, z according to the position coordinates of one dimension OCT data and correspondence thereof) the skin optical parameter put;
Step f, repeatedly repeat step c, steps d and step e, choose different coordinate points P ' (x ', y ', z ') at every turn, obtain the skin optical parameter on all three-dimensional coordinates of skin histology and form skin three-dimensional optical parameter;
Repeat step c to step f after other OCT three-dimensional data elements in step g, selection OCT three-dimensional data alignment vector, obtain the skin three-dimensional optical parameter of all elements in OCT three-dimensional data alignment vector and form skin optical parameter distributed in three dimensions vector.
Wherein in an embodiment, in described step e, least-squares linear regression method is adopted to calculate P(x, y, z) put the skin optical parameter of position.
Wherein in an embodiment, go out in the three-dimensional correlation step of skin optical parameter and blood glucose concentration value according to skin optical parameter distributed in three dimensions vector calculation described, comprise the steps:
Step (1), select skin optical parameter distributed in three dimensions vector at coordinate points P(x, y, z) the optical parametric vector at place;
Step (2), coordinates computed point P(x, y, z) the optical parametric vector at place and blood glucose concentration value vectorial between dependency, and be kept in three-dimensional correlation data;
Step (3), repetition step (1) and step (2), travel through the three-dimensional correlation that all coordinate points obtain skin optical parameter and blood glucose concentration value.
Wherein in an embodiment, in described step (2), according to Pearson correlation calculate optical parametric vector and blood glucose concentration value vectorial between dependency.
The computational methods of the above-mentioned optical parametric based on OCT and blood sugar concentration three-dimensional correlation, acquire several not blood glucose concentration value in the same time and skin histology OCT three-dimensional data and to constitute OCT three-dimensional data vector right with blood glucose concentration value vector, by obtaining skin optical parameter distributed in three dimensions vector to OCT three-dimensional data vector and the vectorial right further process of blood glucose concentration value, and finally calculate the three-dimensional correlation of skin optical parameter and blood glucose concentration value.The computational methods of the above-mentioned optical parametric based on OCT and blood sugar concentration three-dimensional correlation can obtain the optical parametric of skin histology in three dimensions and distribute, obtain the three-dimensional correlation between skin histology optical parametric and blood glucose concentration value, this three-dimensional correlation may be used for the selection instructing OCT noninvasive dynamics monitoring technology for detection region simultaneously.
Accompanying drawing explanation
Fig. 1 is skin optical parameter and the blood glucose concentration value three-dimensional correlation algorithm flow chart of an embodiment;
Fig. 2 is that the OCT three-dimensional data vector of an embodiment is vectorial to schematic diagram with blood glucose concentration value;
Fig. 3 is the list group OCT three-dimensional data alignment front and back contrast of an embodiment, and left figure is schematic diagram before alignment, and right figure is the rear schematic diagram of alignment;
Fig. 4 is the skin optical parameter distributed in three dimensions vector calculation flow chart of an embodiment;
Fig. 5 is that the three-dimensional rectangle frame of an embodiment takes the three-dimensional subdata schematic diagram of an OCT;
Fig. 6 is that the OCT three-dimensional data taken by three-dimensional rectangle frame of an embodiment obtains one-dimensional signal schematic diagram at XY orientation average;
Fig. 7 is skin optical parameter and the blood glucose concentration value three-dimensional correlation calculation flow chart of an embodiment;
Fig. 8 is that the single coordinate points dependency of an embodiment describes schematic diagram;
Fig. 9 is the three-dimensional correlation schematic diagram of the skin optical parameter that obtains of the experiment of an embodiment and blood glucose concentration value.
Detailed description of the invention
In order to the method solving current Woundless blood sugar measurement of concetration cannot obtain the problem of dependency Changing Pattern in three dimensions between optical parametric and blood sugar concentration, present embodiments provide for the computational methods of a kind of optical parametric based on OCT and blood sugar concentration three-dimensional correlation and measure the device of blood sugar concentration.Below in conjunction with specific embodiment, be specifically described based on the optical parametric of OCT and the computational methods of blood sugar concentration three-dimensional correlation.
Please refer to Fig. 1, the computational methods of the optical parametric based on OCT that present embodiment provides and blood sugar concentration three-dimensional correlation, comprise the steps:
Step S110: the blood sugar concentration change controlling measurand.In this step, can allow measurand oral glucose or feed, the blood glucose concentration value controlling measurand changes.
Step S120: in the blood sugar concentration change procedure of measurand, gathers the OCT three-dimensional data of several not blood glucose concentration value in the same time and skin histologies.T1 in blood glucose concentration value change procedure, t2 ..., the tn moment gathers OCT three-dimensional data T1 respectively successively, T2 ..., Tn and blood glucose concentration value G1, G2 ..., Gn.The skin histology that OCT three-dimensional data specifically just refers to measurand in three dimensions each point to the reflex strength of light.
Step S130: the OCT three-dimensional data of the skin histology do not gathered in the same time is formed OCT three-dimensional data vector, blood glucose concentration value forms blood glucose concentration value vector, and it is right with blood glucose concentration value vector that OCT three-dimensional data vector and blood glucose concentration value are formed OCT three-dimensional data vector.Please refer to Fig. 2, by t1, t2 ..., the OCT three-dimensional data T1 that the tn moment collects respectively successively, T2 ..., Tn and blood glucose concentration value G1, G2 ..., Gn formation OCT three-dimensional data vector T1, T2 ..., Tn } and blood glucose concentration value vector G1, G2 ..., Gn }.Meanwhile, in order to by OCT three-dimensional data vector T1, T2 ..., Tn } and blood glucose concentration value vector G1, G2 ..., Gn } and keep the corresponding relation of synchronization, they can be formed OCT three-dimensional data vector right with blood glucose concentration value vector.
Step S140: obtain OCT three-dimensional data alignment vector according to skin surface characteristic information alignment OCT three-dimensional data vector.Due to OCT three-dimensional data vector { T1, T2,, Tn } in element be collected in not in the same time, and not in the same time, inevitably there is the phenomenon of position movement in measurand, although this position move can by take some measures control to very small, even if move also can to OCT three-dimensional data vector { T1, T2 in position small again,, Tn } in data cause serious impact.Therefore, we be necessary by OCT three-dimensional data vector T1, T2 ..., Tn } in the data that comprise of all elements carry out " registration process ".So-called " registration process " process is as follows:
(a), from OCT three-dimensional data vector T1, T2 ..., Tn } and a middle selection element T
k, use image processing method to find this OCT three-dimensional data T
kin the skin surface position of each A-Scan.Wherein A-Scan data refer at T
kone-dimensional data when middle X Y-coordinate is fixed in degree of depth Z-direction.
(b), according to skin surface positional information, the skin surface of each A-Scan is snapped to A-Scan first Data Position, obtains OCT three dimensional alignment data T'
k.
(c), repeat step (a) and step (b) obtain OCT three-dimensional data alignment vector T'1, T'2 ..., T'n }.
Please refer to Fig. 3, OCT three-dimensional data vector T1, T2 ..., Tn } obtain after " registration process " OCT three-dimensional data alignment vector T'1, T'2 ..., T'n }.
Step S150: according to OCT three-dimensional data alignment vector calculation skin optical parameter distributed in three dimensions vector.Please refer to Fig. 4, this step comprises the steps: further
Step a, the OCT three-dimensional data elements T' selected in OCT three-dimensional data alignment vector
m.
Step b, selection three-dimensional rectangle frame size.Here the size of rectangle frame, comprises length l, width w and height h.
Step c, coordinate points P(x at skin histology, y, z) place, use selected three-dimensional rectangle frame from this OCT three-dimensional data elements, take the three-dimensional subdata of an OCT.Please refer to Fig. 5, sentencing coordinate points P at coordinate points P (x, y, z) is that three-dimensional data selects the center of rectangle frame R to take the three-dimensional subdata T' of OCT
mp.
Steps d, in the three-dimensional subdata of OCT, along degree of depth Z-direction, the three-dimensional subdata of OCT is averaged in the XOY plane parallel with skin surface, obtain the position coordinates of one dimension OCT data and correspondence thereof.And obtain the corresponding relation of one dimension OCT data and position coordinates further.Wherein one dimension OCT data S can be expressed as s1, s2 ..., s
h, obtain simultaneously space, S place Z-direction coordinate position z1, z2 ..., z
h.Please refer to Fig. 6, according to one dimension OCT data S=s1, s2 ..., s
hand z1, z2 ..., z
hthe curve that the three-dimensional subdata meansigma methods of OCT changes with skin histology degree of depth Z can be obtained.
Step e, calculate P(x, y, z according to the position coordinates of one dimension OCT data and correspondence thereof) the skin optical parameter put.Carry out least-squares linear regression according to one dimension OCT data S and obtain the optical parametric (that is scattering coefficient) of slope value as this coordinate position, formula is as follows:
Wherein, slope value is b, and intercept is a,
for the average of S,
for coordinate position average.
Step f, repeatedly repeat step c, steps d and step e, choose different coordinate points P ' (x ', y ', z ') at every turn, obtain the skin optical parameter on all three-dimensional coordinates of skin histology and form skin three-dimensional optical parameter O
m.
Step c is repeated to step f after other OCT three-dimensional data elements in step g, selection OCT three-dimensional data alignment vector, obtain the skin three-dimensional optical parameter of all elements in OCT three-dimensional data alignment vector and form skin optical parameter distributed in three dimensions vector { O1, O2 ..., On }.
Step S160: the three-dimensional correlation going out skin optical parameter and blood glucose concentration value according to skin optical parameter distributed in three dimensions vector sum blood glucose concentration value vector calculation.Please refer to Fig. 7, Fig. 8 and Fig. 9, this step comprises the steps: further
Step (1), select skin optical parameter distributed in three dimensions vector O1, O2 ..., On } at coordinate points P(x, y, z) place optical parametric vector Up=O1p, O2p ..., Onp };
The optical parametric vector at step (2), coordinates computed point (x, y, z) place and blood glucose concentration value vectorial between dependency, and to be kept in correlation data.According to Pearson correlation, during dependency here between calculating optical parameter vector and blood glucose concentration value vector, make use of following formula:
Wherein, R
pfor optical parametric vector and blood glucose concentration value vectorial between dependency, O
ipfor skin optical parameter distributed in three dimensions vector O
iat coordinate points P(x, y, z) the optical parametric vector at place, G
ipfor blood glucose concentration value vector G
iat coordinate points P(x, y, z) blood glucose concentration value at place.
Step (3), repetition step (1) and step (2), travel through the three-dimensional correlation that all coordinate points obtain skin optical parameter and blood glucose concentration value.
The computational methods of the above-mentioned optical parametric based on OCT and blood sugar concentration three-dimensional correlation acquire several not blood glucose concentration value in the same time and skin histology OCT three-dimensional data and to constitute OCT three-dimensional data vector right with blood glucose concentration value vector, by obtaining skin optical parameter distributed in three dimensions vector to OCT three-dimensional data vector and the vectorial right further process of blood glucose concentration value, and finally calculate the three-dimensional correlation of skin optical parameter and blood glucose concentration value.The computational methods of the above-mentioned optical parametric based on OCT and blood sugar concentration three-dimensional correlation can obtain the optical parametric of skin histology in three dimensions and distribute, obtain the three-dimensional correlation between skin histology optical parametric and blood glucose concentration value, this three-dimensional correlation may be used for the selection instructing OCT noninvasive dynamics monitoring technical calibration stage surveyed area simultaneously.
The above embodiment only have expressed several embodiment of the present invention, and it describes comparatively concrete and detailed, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (7)
1., based on the optical parametric of OCT and computational methods for blood sugar concentration three-dimensional correlation, it is characterized in that, comprise the steps:
The blood sugar concentration change of step (1), control measurand;
Step (2), in the blood sugar concentration change procedure of measurand, gather the OCT three-dimensional data of several not blood glucose concentration value in the same time and skin histologies;
Step (3), the OCT three-dimensional data of skin histology do not gathered in the same time is formed OCT three-dimensional data vector, blood glucose concentration value forms blood glucose concentration value vector;
Step (4), obtain OCT three-dimensional data alignment vector according to skin surface characteristic information alignment OCT three-dimensional data vector;
Step (5), according to OCT three-dimensional data alignment vector calculation skin optical parameter distributed in three dimensions vector;
Step (6), go out the three-dimensional correlation of skin optical parameter and blood glucose concentration value according to skin optical parameter distributed in three dimensions vector sum blood glucose concentration value vector calculation.
2. the computational methods of the optical parametric based on OCT according to claim 1 and blood sugar concentration three-dimensional correlation, it is characterized in that, in the blood sugar concentration conversion step of described control measurand, the blood sugar concentration change controlling measurand takes in glucose or feed realization by making measurand.
3. the computational methods of the optical parametric based on OCT according to claim 1 and blood sugar concentration three-dimensional correlation, it is characterized in that, form in OCT three-dimensional data vector step in the described OCT three-dimensional data by the skin histology do not gathered in the same time, also comprise the steps:
Described OCT three-dimensional data vector and blood glucose concentration value are formed OCT three-dimensional data vector right with blood glucose concentration value vector.
4. the computational methods of the optical parametric based on OCT according to claim 1 and blood sugar concentration three-dimensional correlation, is characterized in that, described according in OCT three-dimensional data alignment vector calculation skin optical parameter distributed in three dimensions vector step, comprise the steps:
Step a, the OCT three-dimensional data elements selected in OCT three-dimensional data alignment vector;
Step b, selection three-dimensional rectangle frame size;
Step c, coordinate points P (x, y, z) place at skin histology, use selected three-dimensional rectangle frame from this OCT three-dimensional data elements, take the three-dimensional subdata of an OCT;
Steps d, in the three-dimensional subdata of OCT, along degree of depth Z-direction, the three-dimensional subdata of OCT is averaged in the XOY plane parallel with skin surface, obtain the position coordinates of one dimension OCT data and correspondence thereof;
Step e, to calculate the skin optical parameter that P (x, y, z) puts according to the position coordinates of one dimension OCT data and correspondence thereof;
Step f, repeatedly repeat step c, steps d and step e, choose different coordinate points P ' (x ', y ', z ') at every turn, obtain the skin optical parameter on all three-dimensional coordinates of skin histology and form skin three-dimensional optical parameter;
Repeat step c to step f after other OCT three-dimensional data elements in step g, selection OCT three-dimensional data alignment vector, obtain the skin three-dimensional optical parameter of all elements in OCT three-dimensional data alignment vector and form skin optical parameter distributed in three dimensions vector.
5. the computational methods of the optical parametric based on OCT according to claim 4 and blood sugar concentration three-dimensional correlation, it is characterized in that, in described step e, adopt least-squares linear regression method to calculate P (x, y, z) put the skin optical parameter of position.
6. the computational methods of the optical parametric based on OCT according to claim 1 and blood sugar concentration three-dimensional correlation, it is characterized in that, go out in the three-dimensional correlation step of skin optical parameter and blood glucose concentration value according to skin optical parameter distributed in three dimensions vector calculation described, comprise the steps:
Step (1), the optical parametric vector of selection skin optical parameter distributed in three dimensions vector at coordinate points P (x, y, z) place;
The optical parametric vector at step (2), coordinates computed point P (x, y, z) place and blood glucose concentration value vectorial between dependency, and be kept in three-dimensional correlation data;
Step (3), repetition step (1) and step (2), travel through the three-dimensional correlation that all coordinate points obtain skin optical parameter and blood glucose concentration value.
7. the computational methods of the optical parametric based on OCT according to claim 6 and blood sugar concentration three-dimensional correlation, it is characterized in that, in described step (2), according to Pearson correlation calculate optical parametric vector and blood glucose concentration value vectorial between dependency, Pearson correlation computing formula is as follows:
Wherein, R
pfor optical parametric vector and blood glucose concentration value vectorial between dependency, O
ipfor optical parametric distributed in three dimensions vector O
ioptical parametric vector at coordinate points P (x, y, z) place, G
ipfor the blood glucose concentration value of blood glucose concentration value vector Gi at coordinate points P (x, y, z) place.
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| CN104188664B (en) * | 2014-09-01 | 2016-03-30 | 苏州光环科技有限公司 | Blood sugar test scaling method and system |
| CN104657576B (en) * | 2014-09-28 | 2017-09-22 | 东软熙康健康科技有限公司 | The rendering method and equipment of a kind of change of blood sugar |
| DE102015006406A1 (en) * | 2015-05-19 | 2016-12-08 | SAMTD GmbH & Co. KG | Method and device for the non-invasive determination of a measurand of an analyte in a biological body |
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