CN1223842C - Method and system in diffused light for scatheless monitoring blood-oxygen metabolizability of biologic tissue - Google Patents

Abstract

The non-destructive monitoring method and system of biological tissue blood oxygen metabolism based on diffuse light belong to the technical field of biomedical engineering, and it is characterized in that: it makes light-emitting diodes at three different positions and each of which can emit two wavelengths of light in sequence within less than Sequentially emit light within a time interval of 0.5ms, and then a photodetector located on one side of the above-mentioned three light-emitting diodes sequentially detects the light intensity of the diffused light from the above-mentioned three light-emitting diodes through deep tissue, and calculates the The optical density OD and the blood oxygen saturation of the tissue to be measured can be accurately given, and the system structure is simple and more suitable for practical requirements.

Description

Method and system for non-destructive monitoring of biological tissue blood oxygen metabolism by diffuse light

technical field

The non-destructive monitoring method of biological tissue blood oxygen metabolism based on diffuse light belongs to the fields of spectral technology application and biomedical engineering.

Background technique

Monitor the blood supply of local tissues (including brain and muscle), and observe its changes over time, and monitor the survival rate of patients during surgery, critically ill patients and infants with hypoxic-ischemic encephalopathy and tissue transplantation There's important meaning.

To determine the oxygen metabolism status of local tissues, there are mainly direct measurement methods of invasive tissue oxygen partial pressure based on electrochemical principles and non-destructive detection methods based on optical measurement. The optical method can realize non-invasive monitoring, which is convenient, safe, stable and reliable. The present invention belongs to one of optical methods. The method described in the document with the publication number CN1365649A is based on the classic Lambert-Beer law. This classic law is for the case of no scattering. For the human body and other biological tissues with strong scattering optical properties, this law must be corrected in this case before use. In principle, directly applying the classical Lambert-Beer law under strong scattering cannot obtain any correct results. The method used in the publication number US005632273A is based on a semi-infinite homogeneous medium, and the steady-state spatial resolution calculation algorithm adopted by it has an impact on the blood oxygen saturation of the deep tissue detected when there is an outer layer of tissue. The patents of the publication numbers CN1333011A and CN1331953A The method used in the method has no deterministic algorithm steps and detection values, and cannot accurately detect tissue blood oxygen saturation, and the weak signal affects the detection accuracy, and the system structure is complex. Compared with Publication Nos. US005632273A, CN1333011A and CN1331953A, the present invention differs from them in that: (1) this patent clearly detects tissue blood oxygen saturation rather than generally referring to "blood oxygen parameters". (2) The method of using multiple light sources and single detectors in this patent is different from the method of single light source and multiple detectors, which has high signal-to-noise ratio, high detection accuracy, and simple system structure. (3) The present invention provides an available empirical formula for accurately detecting tissue blood oxygen saturation under the condition of outer tissue. Figure 1 shows the detection schematic diagram of the existing patent, where a is a light source, b is a detector, c is a probe, d is a detector, e is a deep tissue to be tested, and f is an outer tissue.

Contents of the invention

Compared with the previous method and the current domestic patented technology, the present invention application has its characteristics and advantages in that firstly, it clearly provides the absolute value of the blood oxygen saturation to be measured rather than the vague concept of "blood oxygen parameter". Knowing the absolute value of tissue oxygen saturation can accurately determine whether the patient's blood supply status is normal, so this parameter has more clinical significance. Second, the thickness of the outer tissue is often an important factor causing errors in blood oxygen parameters, but the method of this patent can eliminate this effect. In terms of implementation methods, although the absorption spectrum of oxyhemoglobin and reduced hemoglobin is common to many testing techniques in this field, the characteristics of this patent are: first, multiple The method of a light source and a single detector, which can improve the detection accuracy and facilitate adjustment; second, considering the high scattering of biological tissues, a semi-empirical formula is proposed, which are different from the schemes proposed in existing patents at home and abroad. .

In Figure 2, 1 is the light source LS1 at a distance r1 from the optical sensor OPSU, 2 is the light source LS2 at a distance r2 from the optical sensor OPUS, 3 is the light source LS3 at a distance r3 from the optical sensor OPUS, and 4 is the optical sensor OPSU, 5 is the first layer of tissue and is represented by T1, 6 is the second layer of tissue and is represented by T2, 7 is the third layer of tissue and is represented by T3, in the tissue model of human muscle tissue oximetry, T1 is skin, T2 muscle subcutaneous T3 is muscle tissue; in the tissue model of human cerebral oximetry, T1 is skin, T2 is skull, and T3 is brain tissue (gray and white matter). b1, b2, b3 are the trajectories of photon migration. To detect tissues at different depths, place the LS at different distances from the optical sensor OPUS, the LS3 light is mainly detected by OPUS is the information of the T1 layer, the LS2 light is detected by the OPUS is the information of the T1 and T2 layers, and the LS1 light is detected by the OPUS OPUS detects mainly the information of T1, T2 and T3 layers. The distances from the light sources LS1, LS2, LS3 to the OPUS are r ₁ , r ₂ , r ₃ .

The method for detecting blood oxygen saturation of biological tissues with near-infrared light sources proposed by the present invention is characterized in that: it makes light-emitting diodes (LEDs) at three different positions and each of which can emit light of two wavelengths sequentially within a time of less than 0.5ms Sequentially emit light in the interval, and then a photodetector located on one side of the above-mentioned three light-emitting diodes sequentially detects the light intensity of the diffused light from the above-mentioned three light-emitting diodes through the deep structural tissue, and thus calculates the optical density value OD To calculate the blood oxygen saturation of the deep local tissue to be measured, this nondestructive monitoring method contains the following steps in sequence:

(1) Detect and save the optical density OD _k of the photodetector at different detection distances by using the formula of optical density through the computer.

(1.1) Fix the three light sources at three different positions.

(1.2) Under the control of the microcontroller, each light source is driven to emit light sequentially, and the value corresponding to the scattered light intensity is measured sequentially.

(1.3) Use the following optical density formula to calculate the optical density OD _k at different detection distances from the photodetector:

${\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; log</span>}\frac{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}}{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; kr</span>}}}<span\; class="notranslate">\; ,</span>$

Among them, k=1, 2, 3, representing the subscripts of three different light sources;

I _kr is the reflected light intensity detected by the photodetector after the light emitted by the light source at different positions is scattered inside the tissue,

I _k is the light intensities emitted by the three light sources;

(2) Calculate, display and save the oxygen saturation rSO ₂ of the deep local tissue to be tested according to the above test results;

(2.1) Subtract the optical densities detected at different detection distances in the same detection cycle and find the difference:

$\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; OD</span>}}_{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; ,</span>$

$\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="3"\; label="OD"\; filenames="C20031010305300113.png"\; state="\{\{state\}\}">OD</figure-callout></span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; o</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span>$

Among them, j=1, 2, respectively represent different wavelengths, that is, λ ₁ and λ ₂ respectively represent the wavelengths of light waves at different wavelengths:

ΔOD ₂ ^λj represents the difference between the optical density of light with wavelength λ _j emitted by the second light source and the optical density of light with wavelength λ _j emitted by the first light source;

ΔOD ₁ ^λj represents the difference between the optical density of the light with wavelength λ _j emitted by the third light source and the optical density of light with wavelength λ _j emitted by the second light source:

(2.2) Use the following empirical formula to calculate the oxygen saturation rSO ₂ of the deep local tissue to be measured by computer:

$\mathrm{<span\; class="notranslate">\; R</span>}{\mathrm{<span\; class="notranslate">\; o</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; C</span>}{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}}{\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Delta;OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}}{\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}}{\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; A</span>}$

Among them: C: 0.16～0.25; B ₁ : -1.66～-2.5

B ₂ : -0.13 to -0.25; A: 1.8 to 2.7.

2. The three light sources and photodetectors are on the same straight line.

3. The center-to-center distance between two adjacent light sources is between 5 mm and 10 mm, and the center-to-center distance between the photodetector and all light sources is between 30 mm and 50 mm.

4. The light sources described can emit red light and near-infrared light respectively.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 Schematic diagram of the general monitoring method.

Figure 2 is a schematic diagram of the monitoring method of the present invention.

Figure 3 Absorption spectrum of hemoglobin.

Figure 4 is a flow chart of the program for detecting blood oxygen metabolism in biological tissues proposed by the present invention.

Figure 5 is a structural diagram of the hardware device.

Figure 6 Appearance of the sensor.

Figure 7 is the appearance diagram of the hardware device of the present invention.

Figure 8 Experimental results.

Detailed ways:

It contains 3 infrared light sources LS distributed at different distances from the photodetector, and 1 photodetector OPUS, which are arranged linearly to form a probe 8, as shown in Figure 6. According to the multiple optical density values measured at different positions, the present invention performs algebraic operation on the given empirical formula to obtain the tissue oxygen saturation in the local area. The system consists of sensors, preamplifier circuits, A/D converters, embedded microcontrollers, external SRAM, liquid crystal displays and touch screens, as shown in Figure 5. The microcontroller is AT89C52, the OPUS used is a silicon photocell, the liquid crystal display has a resolution of 320*240 and a touch screen of 1024*1024. The appearance is shown in Figure 7, the probe 8 connects the plug 9 to the instrument 10, 11 is the liquid crystal and touch screen, and 12 is the reset button.

A typical hardware device designed based on the principle of diffused light is shown in Figure 5. The light source LS uses 3 LEDs and 1 OPUS at different distances (in a line, LEDs respectively), and the photodetector OPUS of the 3 LEDs is 30mm, 35mm, 40mm apart, and the photodetector OPUS detects the light intensity change. The silicon photocell OPUS is connected to the preamplifier TLC27L4, the microcontroller AT89C52 controls the work of the sample holder LF398 and starts the A/D TLC2543 conversion, and reads and records the sampling value of the conversion result. The microcontroller drives the light source LS to emit light, and saves the A/D conversion value of the OPUS detection value to the memory chip 6264. The above advantages: the consistency of the channels is very good, making the data comparable.

There are 3 LEDs in the probe of the device in the present invention, and the 2 LEDs at r ₂ and r ₃ are used to correct the influence of outer tissue. In the whole tissue, because the absorption of biological tissue has certain characteristics, only by selecting the appropriate wavelength can the changes of local tissue oxygen saturation and blood oxygen concentration be better calculated. There are some differences in the selection of wavelengths in the measurement of different tissues. Muscle blood oxygen detection is 700/880nm, and the head is 780nm/840nm. We use 700/880, 780nm/840nm component LEDs. In order not to cause any damage to biological tissues, the optical power of the LED should be less than 10mW.

Through the introduction of the above hardware structure and working principle, the signal flow of the system can be summarized as follows: (1) The microcontroller sends a control signal to the LS drive unit, and the 3 LEDs emit light sequentially (2) Light through the organization (5T1, 6T2 in Figure 2 , 7T3) Exit from the detection part (3) OPUS detection light intensity is connected to the preamplifier (4) 1 channel sample holder to sample and hold the signal, the A/D converter converts, and the conversion result is read into SRAM saves. (5) Calculate and display the local tissue oxygen saturation rSO2 in the microcontroller.

Calculate the OD values at three distances in the microcontroller, and use the formula to solve rSO2.

Experimental effect

Utilize the present invention to test the basic value of tissue oxygen saturation in normal infants and infants suffering from encephalopathy in a quiet state; when there is an outer layer tissue in the blood model, the blood oxygen saturation change value detected by the present invention is the same as that used in the publication number US005632273A For method comparison, the method used in US005632273A has a limited measurement range of 18%-98%, as shown in FIG. 8 .

The effects brought by the implementation of the invention of this patent can be summarized as follows: (1) It is non-destructive and quantitative at the same time, and accurately reflects the blood oxygen saturation when there is an outer layer of tissue. (2) The parameter of the absolute value of tissue blood oxygen saturation provided by the present invention is the main index for judging whether the blood supply state of the tissue is normal (compared with the variation of other blood oxygen indexes).

Main features of the present invention:

1. The detection method of local tissue oxygen saturation is proposed, and the empirical formula for accurately detecting tissue oxygen saturation under the condition of outer tissue is given. The result is accurate and does not need to be calibrated.

2. The method according to 1 adopts three light sources and one photodetector for detection, and each light source is linearly arranged at different distances from the photodetector. The signal-to-noise ratio is high, the detection accuracy is high, and the system structure is simple.

Claims (4)

1. The method for non-destructive monitoring of biological tissue blood oxygen metabolism based on diffuse light includes the steps of using a light source located on the surface of the deep tissue to be measured and detecting the diffuse light from the deep local tissue to be measured, characterized in that: it makes three different positions and each A light-emitting diode LED that can emit light of two wavelengths sequentially emits light sequentially within a time interval of less than 0.5ms, and then a photodetector located on one side of the above-mentioned three light-emitting diodes sequentially detects the light from the above-mentioned three light-emitting diodes. The light intensity is diffused through the deep structural tissue, and the blood oxygen saturation of the deep local tissue to be measured is calculated by calculating the optical density value OD. This non-destructive monitoring method contains the following steps in sequence: (1) Detect and save the optical density ODk of the photodetector at different detection distances by using the formula of optical density through the computer. (1.1) Fix the three light sources at three different positions. (1.2) Under the control of the microcontroller, each light source is driven to emit light sequentially, and the value corresponding to the scattered light intensity is measured sequentially. (1.3) Use the following optical density formula to calculate the optical density OD _k at different detection distances from the photodetector: $\mathrm{<span\; class="notranslate">\; o</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; log</span>}\frac{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}}{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; kr</span>}}}<span\; class="notranslate">\; ,</span>$ Among them, k=1, 2, 3, representing the subscripts of three different light sources; I _kr is the reflected light intensity detected by the photodetector after the light emitted by the light source at different positions is scattered inside the tissue, I _k is the light intensities emitted by the three light sources; (2) Calculate, display and save the oxygen saturation rSO ₂ of the deep local tissue to be tested according to the above test results; (2.1) Subtract the optical densities detected at different detection distances in the same detection period and find the difference: $\mathrm{<span\; class="notranslate">\; \&Delta;O</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; OD</span>}}_{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; ,</span>$ $\mathrm{<span\; class="notranslate">\; \&Delta;O</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 3</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; ,</span>$ Among them, j=1, 2, respectively represent different wavelengths, that is, λ ₁ and λ ₂ respectively represent the wavelengths of light waves at different wavelengths:

Indicates the difference between the optical density of the light with wavelength _λj emitted by the second light source and the optical density of light with wavelength _λj emitted by the first light source;

Indicates the difference between the optical density of the light with wavelength λ _j emitted by the third light source and the optical density of light with wavelength λ _j emitted by the second light source: (2.2) Use the following empirical formula to calculate the oxygen saturation rSO ₂ of the deep local tissue to be measured by computer: ${\mathrm{<span\; class="notranslate">\; rSO</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; C</span>}{<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}}{{\mathrm{<span\; class="notranslate">\; \&Delta;OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Delta;OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}}{{\mathrm{<span\; class="notranslate">\; \&Delta;OD</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; B</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; \&Delta;OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}}}{{\mathrm{<span\; class="notranslate">\; \&Delta;OD</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}^{{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; A</span>}$ Among them: C: 0.16～0.25; B ₁ : -1.66～-2.5 B ₂ : -0.13 to -0.25; A: 1.8 to 2.7. 2. The non-destructive monitoring method of biological tissue blood oxygen metabolism based on diffuse light according to claim 1, characterized in that the three light sources and the photodetector are on the same straight line. 3. The blood oxygen metabolism monitoring method of biological tissue based on diffuse light according to claim 1, characterized in that: the center-to-center distance between two adjacent light sources is between 5 mm and 10 mm, and the center-to-center distance between the photodetector and all light sources is 30 mm ~50mm. 4. The blood oxygen metabolism monitoring method of biological tissue based on diffuse light according to detection requirement 1, characterized in that said light sources can respectively emit red light and near-infrared light.

Images