A device for measuring the oxygen state of cerebral cortex tissue with high precision

Abstract

This invention discloses a device for high-precision measurement of blood oxygenation status in cerebral cortex tissue, comprising a light source module containing multiple near-infrared light sources, each of which emits three different wavelengths of near-infrared light into the brain tissue; a signal acquisition module containing multiple signal acquisition groups, each forming long and short-distance channels for acquiring near-infrared light signals emitted from the brain tissue by a single near-infrared light source; and a signal processing module that calculates the long and short optical path lengths of near-infrared light in the brain tissue, constructs expressions for the optical density changes of the long and short-distance channels based on the optical path lengths, eliminates the brain surface tissue absorption term in the optical density change of the long-distance channel by subtracting the two expressions, and obtains the noise-reduced optical density change expression. The noise-reduced optical density change expressions for the three near-infrared wavelengths are then solved to obtain the blood oxygenation status of the cerebral cortex tissue.

Description

Technical Field

[0001] This invention belongs to the field of brain signal acquisition and processing technology, specifically relating to a device for high-precision measurement of blood oxygenation status in cerebral cortex tissue. Background Technology

[0002] Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical imaging technique widely used in fields such as brain functional imaging and brain-computer interfaces. Based on the principle of neurovascular coupling, this technique indirectly reflects neural activity by detecting changes in the concentrations of local oxyhemoglobin (HbO2) and deoxyhemoglobin (HbR) caused by hemodynamic changes in brain tissue due to neuronal metabolic activity. Due to its portability, high spatial resolution, and relatively small motion artifact interference, it has wide applications in brain science research and clinical physiological monitoring.

[0003] However, due to various physiological noises and computational errors, there are many challenges in accurately measuring changes in blood oxygen concentration in the cerebral cortex using fNIRS, as follows:

[0004] (1) Because near-infrared light passes through four layers of structure—scalp, skull, cerebrospinal fluid, and cerebral cortex—before being received by the detector, the obtained fNIRS signal contains noise from local hemodynamic changes in the non-cortical brain surface tissues. These local blood flow changes in the brain surface tissues include not only systemic activities of the body (such as changes in blood pressure and skin blood flow), but can also be generated by tasks such as cognitive behavior and emotional changes. These task-related components are important sources of interference and noise.

[0005] (2) In addition to hemoglobin, changes in the concentration of substances such as water and cytochrome in the cerebral cortex can also cause changes in optical density. Therefore, the obtained fNIRS signal contains noise caused by changes in background absorption.

[0006] (3) The total path length of near-infrared light varies in different layers of brain tissue. In fact, the total path length is not only determined by the distance between the light source and the detector, but also influenced by the optical properties and structure of the tissue. For long-distance and short-distance near-infrared channels, the total optical path length and the functional relationship between the light source and the detector differ due to the different tissue layers through which the light passes. Traditional methods use the same path length correction factor (DPF) multiplied by the distance between the light source and the detector to calculate the total optical path length, treating only the total optical path length as a function of the distance between the light source and the detector, which will introduce calculation errors.

[0007] Among existing techniques for measuring changes in blood oxygen concentration in the cerebral cortex, the BRS-1 brain oximeter, disclosed in Juanning Si et al.'s 2022 paper "Cerebral tissue oximeter suitable for real-time regional oxygensaturation monitoring in multiple clinical settings," uses two photodetectors at distances of 30mm and 40mm from the light source to subtract the effects of light attenuation in superficial brain tissue. However, the proposed algorithm assumes that the blood oxygen concentration in the cerebral cortex changes uniformly between the two channels, which introduces errors in actual calculations.

[0008] A near-infrared optical detection method for local venous blood flow parameters, disclosed in patent publication number CN112386253A, uses three measurement wavelengths. It simultaneously subtracts the optical density change of a reference wavelength from the optical density changes of two measurement wavelengths to eliminate the influence of background absorption on the measurement results. However, this algorithm is inaccurate when the change in total blood oxygen concentration (ΔHbT) in the local tissue is not zero.

[0009] The cerebral cortex blood oxygenation signal acquisition device disclosed in patent publication number CN107080543A uses long and short distance near-infrared channels to separate scalp blood oxygenation signals and cerebral cortex blood oxygenation signals. However, the algorithm makes a large approximation of the optical path length, and the near-infrared signals of the corresponding oxygenated hemoglobin / deoxygenated hemoglobin obtained by separation do not take into account the absorption effects of other hemoglobins and other components.

[0010] US Patent 20230026344 discloses a method for removing noise from changes in cortical blood oxygen concentration based on baseline signals and a scaling factor. This algorithm uses the amplitude ratio between the long-range and short-range baseline signals as a scaling factor, and subtracts the product of the short-range signal and the scaling factor from the long-range signal for subtraction. However, this algorithm requires a long baseline signal acquisition time and relies on task-oriented frequency calculations, which limits its application in routine monitoring outside of tasks. Summary of the Invention

[0011] In view of the above, the purpose of this invention is to provide a device for high-precision measurement of blood oxygenation status in cerebral cortex tissue, which takes into account the differences in blood oxygen concentration between channels, the differences in total optical path length between channels, and the absorption effect of different light-absorbing substances, so as to achieve a real-time, task-independent, high-precision measurement of changes in blood oxygen concentration in the cerebral cortex.

[0012] To achieve the above-mentioned objectives, this invention provides a device for high-precision measurement of blood oxygenation status in cerebral cortex tissue, comprising:

[0013] The light source module contains multiple near-infrared light sources, and each near-infrared light source is controlled to emit three different wavelengths of near-infrared light toward the brain tissue.

[0014] The signal acquisition module contains multiple signal acquisition groups. Each signal acquisition group contains two acquisition units at long and short distances from the light source group, forming long and short distance channels respectively, which are used to acquire near-infrared light signals emitted from a single near-infrared light source from brain tissue.

[0015] The signal processing module calculates the long and short optical path lengths of near-infrared light in brain tissue based on the long and short distances between each signal acquisition group and the light source. It constructs expressions for the optical density changes of the long and short distance channels based on the long and short optical path lengths according to the Lambert-Beer law. By subtracting these two expressions to eliminate the absorption term of the brain surface tissue in the optical density change of the long distance channel, it obtains the noise-reduced optical density change expression. Based on the actual optical density changes of the long and short distance channels calculated from the near-infrared light signals, it solves the noise-reduced optical density change expressions for the three near-infrared wavelengths to obtain the blood oxygenation status of the cerebral cortex.

[0016] Preferably, the three different wavelength ranges of near-infrared light emitted by each near-infrared light source to the brain tissue are 690-760nm, 800-810nm, and 830-850nm, respectively.

[0017] Preferably, the distance between the long-distance acquisition unit and the light source group is 30-40mm, and the distance between the short-distance acquisition unit and the light source group is 10-15mm.

[0018] Preferably, the light source module further includes a light source driving unit, which enables the near-infrared channels of different near-infrared light sources according to a certain timing standard, and asynchronously switches the different emission wavelengths of each near-infrared light source to ensure that near-infrared light of different wavelengths in the same near-infrared channel is emitted at different times, and that there is no crosstalk between the near-infrared light of different near-infrared channels.

[0019] The emission time of each wavelength of near-infrared light is adjustable from 1ms to 20ms, and the enable time of each near-infrared channel is adjustable from 3ms to 100ms.

[0020] Preferably, each signal acquisition group uses two photodetectors for its long and short distance acquisition units, which are used to receive near-infrared light signals emitted from brain tissue and convert the near-infrared light signals into current signals.

[0021] The signal acquisition module also includes a detector control unit, which controls the operation of the photodetector, converts the current signal obtained by the photodetector into a voltage signal, performs analog-to-digital conversion on the voltage signal, and sends the conversion result to the signal processing module.

[0022] Preferably, each near-infrared light source includes three wavelength light-emitting diodes with lenses, and each photodetector employs an avalanche diode;

[0023] It also includes a fixed module, with the light source module and signal acquisition module fixed on the fixed module, and the signal processing module located on the host computer.

[0024] Preferably, the calculation of the long and short optical path lengths of near-infrared light in brain tissue based on the long and short distances between each signal acquisition group and the light source includes:

[0025] First, based on the partial path length (PPL) of near-infrared light in the scalp and skull layers... S Partial path length of the cerebrospinal fluid layer (PPL) CSF And the partial path length (PPL) of the gray matter layer of the cerebral cortex Gray The calculation formula and the long and short distances between the acquisition group and the light source are used to calculate the partial path length PPL corresponding to the long-distance channel. S′ PPL CSF′ PPL Gray′ Partial path length (PPL) corresponding to short-distance channels S″ PPL CSF″ and PPL Gray″ ;

[0026]

[0027]

[0028]

[0029] Where l represents the distance between the acquisition unit and the near-infrared light source;

[0030] Then, for long-distance channels, based on the partial path length PPL S′ PPL CSF′ and PPL Gray′ Calculate the long optical path length L of brain surface tissue in a long-distance channel. LS and the long optical path length L of the cerebral cortex LD , represented as:

[0031] L LS =PPL S′ (4)

[0032] L LD =PPLCSF′ +PPL Gray′ (5)

[0033] For short-distance channels, based on the partial path length PPL S″ PPL CSF″ and PPL Gray″ Calculate the short optical path length L of brain surface tissue in short-distance channels. SS and the short optical path length L of the cerebral cortex SD , represented as:

[0034] L SS =PPL S″ (6)

[0035] L SD =PPL CSF″ +PPL Gray″ (7).

[0036] Preferably, assuming that scalp hemodynamics is uniform between long and short channels, the expression for the change in optical density between long and short channels constructed according to the Lambert-Beer law, based on the lengths of the long and short optical paths, is as follows:

[0037] △OD L =△μ S ·L LS +△μ LD ·L LD (8)

[0038] △OD S =△μ S ·L SS +△μ SD ·L SD (9)

[0039] Among them, △OD L , △OD s These represent the changes in optical density in the long and short channels, respectively, Δμ S Δμ represents the sum of the products of the absorption coefficients and concentration changes of each component in the brain surface tissue. LD Δμ represents the sum of the products of the absorption coefficients and concentration changes of various components in the cerebral cortex tissue over long distances. SD L represents the sum of the products of the absorption coefficients and concentration changes of various components in the cerebral cortex tissue during short-distance pathways. LS and L LD L represents the length of the long optical path in the surface tissues of the brain and the length of the long optical path in the cerebral cortex of the brain in a long-distance channel. SS and L SD Δμ represents the short optical path length of the superficial brain tissue and the cerebral cortex tissue in the short-distance channel.S ·L LS This indicates the absorption of brain surface tissues in long-distance pathways.

[0040] Preferably, the expression for eliminating noise-reduced optical density change by subtracting the two expressions to eliminate the brain surface tissue absorption term in the optical density change of long-distance channels is as follows:

[0041]

[0042] For short-distance channels, 10 ≤ l ≤ 15. According to equations (2), (3), and (7), we can derive...

[0043] L SD =0 (11)

[0044] Therefore, equation (10) can be rewritten as follows:

[0045]

[0046] Preferably, the step of calculating the actual optical density changes of the long and short-distance channels based on the near-infrared light signals, and then solving the expression for the optical density changes after noise reduction for the three near-infrared wavelengths to obtain the blood oxygenation status of the cerebral cortex includes:

[0047] When considering the absorption of oxygenated hemoglobin HbO2, deoxyhemoglobin HbR, and other components in the cerebral cortex, Δμ LD It can be represented as:

[0048] △μ LD =ε HbO2 ·△C HbO2 +ε HbR ·△C HbR +ε other ·△C other (13)

[0049] According to equation (13), equation (12) can be rewritten as follows:

[0050]

[0051] △C other )·L LD (14)

[0052] Where, ε HbO2 ,ε HbR ,ε other ΔC represents the absorption coefficients of oxygenated hemoglobin, deoxygenated hemoglobin, and other components in the cerebral cortex, respectively. HbO2 , △C HbRLet ΔC represent the changes in the concentrations of oxygenated hemoglobin and deoxygenated hemoglobin in the cerebral cortex, respectively. other Indicates the change in concentration of other components;

[0053] The actual optical density changes ΔOD in the long and short distance channels were calculated based on two near-infrared light signals at each wavelength and the optical density value at the baseline time. L and △OD s ;

[0054] The actual optical density change ΔOD corresponding to the three wavelengths L and △OD s and the ε corresponding to the three wavelengths HbO2 ,ε HbR ,ε other Substituting into equation (14) and solving the simultaneous equations, we obtain △C. HbO2 , △C HbR .

[0055] Compared with the prior art, the beneficial effects of the present invention include at least the following:

[0056] (1) The interference of changes in blood oxygen concentration in the brain surface tissue on the measurement results is eliminated, resulting in a high signal-to-noise ratio for near-infrared signals. Based on the principle that near-infrared light penetrates human tissue to different depths at different light source-acquisition group distances, this invention designs a short-range near-infrared channel that can only penetrate the brain surface tissue and a long-range near-infrared channel that can penetrate to the cerebral cortex tissue. Then, a brain surface tissue noise subtraction method based on the long and short-range channels is used to eliminate the interference of changes in blood oxygen concentration in the brain surface tissue on the measurement results, greatly improving the signal-to-noise ratio of near-infrared signals and the measurement accuracy of changes in blood oxygen concentration in the cerebral cortex. In this respect, the difference between this invention and the paper "Cerebral tissueoximeter suitable for real-time regional oxygen saturation monitoring in multiple clinical settings" published by Juanning Si et al. in 2022 is that this invention takes into account the non-uniformity of hemodynamics in the cerebral cortex between the two channels. By controlling the distance between the light source and the detector, the penetration depth of near-infrared light in the short-distance channel cannot reach the cerebral cortex. The advantage of doing so is that the changes in optical density caused by the absorption of the brain surface tissue can be more accurately subtracted without affecting the changes in optical density caused by the cerebral cortex.

[0057] (2) The interference of concentration changes of components other than hemoglobin in the cerebral cortex on the measurement results is removed, further improving the measurement accuracy. Compared with the previous dual-wavelength fNIRS system, this invention uses three wavelengths of near-infrared light for measurement, and uses three wavelengths to jointly calculate and subtract the interference of components other than hemoglobin in the cerebral cortex on the measurement results. In this respect, the difference between patent application CN112386253A and this invention is that this invention analyzes the material components corresponding to background absorption and subtracts the optical density change value caused by the corresponding material components from the total optical density change value. The advantage of doing so is that when the local tissue total blood oxygen concentration change value (ΔHbT) is not zero, the optical density change caused by background absorption can be subtracted more accurately.

[0058] (3) A method for calculating the total optical path length based on partial optical path lengths makes the calculation of the total optical path length more accurate. Compared with the previous method of calculating the path length by multiplying the constant path length correction factor (DPF) by the distance between the light source and the acquisition group, this invention calculates the total optical path length by superimposing partial path lengths based on the partial path lengths in different layers of brain tissue. In this respect, the difference between patent application CN107080543A and this patent is that this invention takes into account the differences in partial path lengths between different layers of the human brain. Based on the actual brain layers through which near-infrared light passes in long and short distance channels, it uses the method of superimposing partial path lengths to calculate the total optical path length. The advantage of doing so is that a more accurate optical path length can be obtained, thereby more accurately calculating the change value of blood oxygen concentration. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This is a schematic diagram of the device for high-precision measurement of blood oxygenation status in cerebral cortex tissue provided in the embodiment;

[0061] Figure 2 This is a schematic diagram of the near-infrared light source and its corresponding acquisition group provided in the embodiment;

[0062] Figure 3 This is a combined schematic diagram of the light source module and the signal acquisition module provided in the embodiment;

[0063] Figure 4 This is a schematic diagram of signal processing in the signal processing module provided in the embodiment;

[0064] Figure 5This is a schematic diagram of the fixing device provided in the embodiment;

[0065] Figure 6 This is a comparison chart of the changes in oxygenated hemoglobin concentration in the left prefrontal cortex calculated by the device of the present invention and the conventional two-wavelength algorithm, provided in the embodiment. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of this invention.

[0067] The inventive concept of this invention is as follows: Addressing the problems of existing devices for measuring changes in blood oxygen concentration in the cerebral cortex, which collect signals containing various physiological noise interferences such as changes in blood oxygen concentration in the surface tissues of the brain and absorption by other tissue components in the cerebral cortex besides hemoglobin, as well as the issues of existing algorithms for measuring changes in blood oxygen concentration in the cerebral cortex failing to simultaneously consider differences in blood oxygen concentration between channels, differences in total optical path length between channels, and the absorption effects of different light-absorbing substances, this invention provides a device for high-precision measurement of the blood oxygen status of cerebral cortex tissues.

[0068] The device provided by this invention is based on a three-wavelength near-infrared light source and long and short-range fNIRS channels, comprehensively considering various sources of noise and error when measuring blood oxygen concentration in the cerebral cortex using near-infrared technology. Unlike existing papers and patent applications that approximate various aspects such as optical path length and absorption by different light-absorbing substances, this invention accurately calculates the variables that have undergone approximation in existing algorithms through three techniques: partial path superposition, separation of non-hemoglobin light-absorbing substances, and spatial resolution of near-infrared channels. This significantly improves the signal-to-noise ratio of the near-infrared signal and enables precise measurement of blood oxygen status information in the cerebral cortex.

[0069] Based on the above inventive concept, such as Figure 1 As shown in the figure, the device for high-precision measurement of blood oxygenation status in cerebral cortex tissue provided in this embodiment of the invention includes a light source module, a signal acquisition module, and a signal processing module.

[0070] like Figure 3 As shown, the light source module includes multiple near-infrared light sources and a light source driving unit. Each near-infrared light source includes three wavelength light-emitting diodes with lenses. The light source driving unit controls each near-infrared light source to emit three different wavelengths of near-infrared light into the brain tissue. The three different wavelengths are 690-760nm, 800-810nm, and 830-850nm, respectively, and the emission time of each wavelength of near-infrared light is adjustable within 1ms-20ms.

[0071] To ensure that the near-infrared light received by each signal acquisition group at any given time comes from only one near-infrared light source, and to ensure that only one wavelength of a single near-infrared light source is lit at any given time, the light source driving unit enables the near-infrared channels of different near-infrared light sources according to a certain timing standard, and asynchronously switches the different emission wavelengths of each near-infrared light source. This ensures that there is no crosstalk between different wavelengths of near-infrared light in the same near-infrared channel, and no crosstalk between near-infrared light in different near-infrared channels. The enable time of each near-infrared channel is adjustable within the range of 3ms-100ms.

[0072] like Figure 3 As shown, the signal acquisition module comprises multiple signal acquisition groups and a detector control unit. Each signal acquisition group corresponds to a near-infrared light source, collectively forming an fNIRS measurement unit. Specifically, each signal acquisition group includes long-distance and short-distance acquisition units from the light source group, corresponding to long-distance and short-distance channels used to acquire near-infrared light signals emitted from brain tissue by a single near-infrared light source. The long-distance acquisition unit is 30-40 mm from the light source group, and the short-distance acquisition unit is 10-15 mm from the light source group. More specifically, as... Figure 2 As shown, each signal acquisition group employs two photodetectors in its long-range and short-range acquisition units: a long-range channel photodetector and a short-range channel photodetector. These two photodetectors are positioned at the same horizontal level as the infrared light source to receive near-infrared light signals emitted from brain tissue and convert them into current signals. Each photodetector uses an avalanche diode (APD) to achieve higher photoelectric sensitivity.

[0073] The detector control unit controls the operation of the photodetector, converts the current signal obtained by the photodetector into a voltage signal, performs analog-to-digital conversion on the voltage signal, and sends the conversion result to the signal processing module. Both the detector control unit and the light source driving unit can use integrated analog front-end chips (AFEs), such as... Figure 3 As shown, these two units can also be integrated into a single AFE. The detector control unit converts the photocurrent signal into an analog voltage signal via a transimpedance amplifier (TIA) integrated in the AFE, and then the analog voltage signal is converted into a digital voltage signal by an analog-to-digital converter (ADC) module in the AFE. The AFE and the main control MCU configure the module's functions and read and transmit the near-infrared emitted signal via the IIC bus.

[0074] like Figure 1 and Figure 3As shown, the device provided in this embodiment of the invention also includes a main control module, which can be an MCU, used to power and control the operation of the light source module and the signal acquisition module. It is also responsible for communicating with the signal processing module located on the host computer, sending the near-infrared light signal acquired by the signal acquisition module to the signal processing module. The two can communicate via WiFi.

[0075] The signal processing module is mainly used to achieve high-precision measurement of the blood oxygenation status of the cerebral cortex by using the acquired near-infrared light signal and subtracting interference from changes in blood oxygen concentration in the brain surface tissue and changes in the concentration of other components in the cerebral cortex besides hemoglobin. For example... Figure 4 As shown, the specific process is as follows:

[0076] (a) Calculate the long and short optical path lengths of near-infrared light in brain tissue based on the long and short distances of each signal acquisition group.

[0077] The long and short optical path lengths of near-infrared light in brain tissue include the long optical path length L in the surface tissues of the brain within long-distance channels. LS The length of the long optical path L in the cerebral cortex tissue of a long-distance channel LD The short optical path length L of the brain surface tissue in the short-distance channel SS The short optical path length L of the cerebral cortex in short-distance channels SD The brain surface tissues include the skull and scalp, while the cerebral cortex tissues include the cerebrospinal fluid layer and the gray matter layer. Because near-infrared light penetrates to different depths in brain tissues, the calculation of L... SS L SD L LS L LD To determine the actual brain tissue layers through which near-infrared light passes, the optical path lengths of some of these brain tissue layers should be calculated first, and then the total optical path length should be obtained by superposition.

[0078] Based on conclusions from previous literature, the partial path length PPL of near-infrared light in the scalp and skull layer was obtained. S Partial path length of the cerebrospinal fluid layer (PPL) CSF Partial path length of the gray matter layer of the cerebral cortex (PPL) Gray The calculation formulas are formulas (1)-(3), depending on the specific long or short distance l (for example, such as...). Figure 2 The 30mm and 15mm values ​​shown indicate the calculation of the partial path length PPL corresponding to the long-distance channel. S′ PPL CSF′ and PPL Gray′ ', the partial path length PPL corresponding to the short-distance channel S″ PPL CSF″ and PPL Gray″ ;

[0079]

[0080]

[0081]

[0082] Where l represents the distance between the acquisition unit and the near-infrared light source;

[0083] For long-distance channels, based on the partial path length L S '、L CSF 'and L GM 'Calculate the long optical path length L of brain surface tissue in a long-distance channel' LS and the long optical path length L of the cerebral cortex LD , represented as:

[0084] L LS =PPL S′ (4)

[0085] L LD =PPL CSF′ +PPL Gray′ (5)

[0086] For short-distance channels, based on the partial path length L S “、L CSF "and L GM "Calculate the short optical path length L of brain surface tissue in short-distance channels" SS and the short optical path length L of the cerebral cortex SD , represented as:

[0087] L SS =PPL S″ (6)

[0088] L SD =PPL CSF″ +PPL Gray″ (7).

[0089] (b) Based on the Lambert-Beer law, construct expressions for the changes in optical density of long and short-distance channels, based on the lengths of long and short optical paths.

[0090] Specifically, assuming that scalp hemodynamics are uniform between long and short channels, the expression for the change in optical density according to the Lambert-Beer law is as follows:

[0091] △OD L =△μ S ·L LS +△μ LD ·L LD(8)

[0092] △OD S =△μ S ·L SS +△μ SD ·L SD (9)

[0093] Among them, △OD L , △OD s These represent the changes in optical density in the long and short channels, respectively, Δμ S Δμ represents the sum of the products of the absorption coefficients and concentration changes of each component in the brain surface tissue. LD Δμ represents the sum of the products of the absorption coefficients and concentration changes of various components in the cerebral cortex tissue over long distances. SD Δμ represents the sum of the products of the absorption coefficients and concentration changes of various components in the cerebral cortex tissue during short-distance pathways. S ·L LS This indicates the absorption of brain surface tissues in long-distance pathways.

[0094] (c) Based on the difference between the two expressions, the absorption term of the brain surface tissue in the optical density change of the long-distance channel is eliminated to obtain the expression for the optical density change after noise elimination.

[0095] To deduct △OD L Midbrain surface tissue absorption Δμ S ·L LS The effect of Δμ needs to be eliminated in equation (8). S ·L LS Item. Order (8) The expression for the change in optical density after noise removal is as follows:

[0096]

[0097] For short-distance channels, 10 ≤ l ≤ 15. According to equations (2), (3), and (7), we can derive...

[0098] L SD =0 (11)

[0099] Therefore, equation (10) can be rewritten as:

[0100]

[0101] (d) Based on the actual optical density changes of the long and short distance channels calculated from the near-infrared light signals, the expression for the optical density changes after noise elimination of the three near-infrared wavelengths is solved to obtain the blood oxygenation status of the cerebral cortex.

[0102] In the near-infrared band, when considering the absorption of oxygenated hemoglobin HbO2, deoxyhemoglobin HbR, and other components such as water H2O in the cerebral cortex, Δμ LD It can be represented as:

[0103] △μ LD =ε HbO2 ·△C HbO2 +ε HbR ·△C HbR +ε H2O ·△C H2O (13)

[0104] According to equation (13), equation (12) can be rewritten as:

[0105]

[0106] △C H2O )·L LD (14)

[0107] Where, ε HbO2 ,ε HbR ,ε H2O ΔC represents the absorption coefficients of oxygenated hemoglobin, deoxygenated hemoglobin, and water in the cerebral cortex, respectively. HbO2 , △C HbR Let and represent the changes in concentration of oxygenated hemoglobin and deoxygenated hemoglobin in the cerebral cortex, respectively, and let ΔC be the value to be solved. H2O Indicates the change in water concentration;

[0108] The actual optical density changes ΔOD in the long and short distance channels were calculated based on two near-infrared light signals at each wavelength and the optical density value at the baseline time. L and △OD s , using △OD= The optical density change ΔOD was obtained. The baseline time was 5 seconds before the start of the measurement. The subject remained resting at the baseline time, and the average of the optical density data collected over 5 seconds was used as the baseline optical density value. The actual optical density changes ΔOD corresponding to the three wavelengths were then calculated. L and △OD s and the ε corresponding to the three wavelengths HbO2 ,ε HbR ,ε H2O Substituting into equation (14) and solving the simultaneous equations, we obtain △C. HbO2 , △C HbR .

[0109] In specific measurements, for example, with a long distance of 30mm and a short distance of 15mm, a near-infrared light source is controlled to emit near-infrared light of three wavelengths: 735nm, 805nm, and 850nm. Then, in a single fNIRS measurement unit, the following can be obtained through formula (14):

[0110]

[0111]

[0112]

[0113] By solving the system of equations (15)-(17), we can obtain the following:

[0114]

[0115] Equation (18) represents the change in concentration of oxygenated hemoglobin and deoxygenated hemoglobin in the cerebral cortex after deducting the influence of the surface tissue of the brain and other substances in the cerebral cortex (water in this embodiment).

[0116] When the above-mentioned device is materialized, such as Figure 5 As shown, the device also includes a fixing module, which comprises a housing and straps. The housing is made of flexible TPU material, which fits snugly against the scalp for high comfort. The housing has pre-drilled holes for housing a light source and photodetector. A single housing can be used to form at least four (…). Figure 5 For example, there are 4 long-distance channels and at least 4 ( Figure 5 (Example: 4 short-range channels) The outer shell also has pre-drilled holes next to the channels for placing EEG electrodes, which can easily increase the number of EEG channels and expand the system to EEG-near-infrared dual-modal acquisition. The strap is made of flexible material to fix the outer shell to the forehead and also ensure good contact between the light source, detector and scalp. In this device, the outer shell is made of flexible material, which allows the light source module and signal acquisition to conform as closely as possible to the curvature of the human brain surface, resulting in high comfort and minimal ambient light interference. The site design incorporates EEG electrode expansion, which can be extended to whole-brain acquisition of EEG-near-infrared dual-modal signals.

[0117] Figure 6 In a cognitive experiment involving alternating between a resting and a cognitive task state for a total of 140 seconds, the device proposed in this invention and a traditional two-wavelength algorithm were used to calculate the changes in oxygenated hemoglobin concentration in the left prefrontal cortex. The solid line represents the blood oxygen concentration change curve obtained under the traditional algorithm, while the dashed line represents the blood oxygen concentration change curve processed by the device proposed in this invention. It can be clearly seen that after removing noise from the surface brain tissue and interference from non-hemoglobin components of the cerebral cortex, the signal has significantly reduced noise, and the blood oxygen concentration curve is smoother.

[0118] The specific embodiments described above illustrate the technical solution and beneficial effects of the present invention in detail. It should be understood that the above description is only the most preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, additions, and equivalent substitutions made within the scope of the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A device for measuring the oxygen state of cerebral cortex tissue with high precision, characterized in that, include: The light source module contains multiple near-infrared light sources, and each near-infrared light source is controlled to emit three different wavelengths of near-infrared light toward the brain tissue. The signal acquisition module contains multiple signal acquisition groups. Each signal acquisition group contains two acquisition units at long and short distances from the light source group, forming long and short distance channels respectively, which are used to acquire near-infrared light signals emitted from a single near-infrared light source from brain tissue. The signal processing module calculates the long and short optical path lengths of near-infrared light in brain tissue based on the long and short distances between each signal acquisition group and the light source. Specifically, it includes: First, based on the partial path length of near-infrared light in the scalp and skull layers... Partial path length of the cerebrospinal fluid layer and the partial path length of the gray matter layer of the cerebral cortex The calculation formula and the long and short distances between the signal acquisition group and the light source are used to calculate the partial path length corresponding to the long-distance channel. , as well as Partial path length corresponding to short-distance channels , as well as : （1） （2） （3） in, This indicates the distance between the acquisition unit and the near-infrared light source; Then, for long-distance channels, based on the partial path length , as well as Calculate the length of the long optical path in the brain surface tissue of a long-distance channel. and the long optical path length of the cerebral cortex , represented as: （4） （5） For short-distance channels, based on partial path length 、 as well as Calculate the short optical path length of brain surface tissue in short-distance channels. and the short optical path length of the cerebral cortex , represented as: （6） （7） Based on the Lambert-Beer law, the expressions for the changes in optical density in long and short-distance channels, based on the lengths of the long and short optical paths, are as follows: （8） （9） in, , These represent the changes in optical density for the long and short channels, respectively. This represents the sum of the products of the absorption coefficients of each component in the brain surface tissue and their concentration changes. This represents the sum of the products of the absorption coefficients and concentration changes of various components in the cerebral cortex tissue during long-distance pathways. This represents the sum of the products of the absorption coefficients and concentration changes of various components in the cerebral cortex tissue during short-distance pathways. This indicates the absorption of brain surface tissues in long-distance pathways; By subtracting the two expressions to eliminate the brain surface tissue absorption term in the optical density change of long-distance channels, for short-distance channels, 10 ≤ l ≤15, the expression for the change in optical density after noise removal is: （10） in, , These represent the actual changes in optical density for the long and short distance channels, respectively. and This indicates the length of the long optical path for the surface tissues of the brain and the length of the long optical path for the cerebral cortex tissues in a long-distance channel. This indicates the length of the short optical path in the surface tissues of the brain within a short-distance channel. This represents the sum of the products of the absorption coefficients and concentration changes of various components in the cerebral cortex tissue during long-distance pathways. Based on the actual optical density changes of the long and short-range channels calculated from the near-infrared light signals, the expressions for the optical density changes after noise reduction at the three near-infrared wavelengths are solved to obtain the blood oxygenation status of the cerebral cortex, including: When considering simultaneously oxygenated hemoglobin HbO2, deoxyhemoglobin HbR, and other components of the cerebral cortex When the absorption situation is as follows, Represented as: （11） in, These represent the absorption coefficients of oxygenated hemoglobin, deoxygenated hemoglobin, and other components in the cerebral cortex, respectively. , The values ​​to be solved represent the changes in the concentrations of oxygenated hemoglobin and deoxygenated hemoglobin in the cerebral cortex. This represents the change in concentration of other components; it also represents the change in actual optical density corresponding to the three wavelengths. and and the three wavelengths corresponding to Substituting into the formula and solving simultaneously, we get... , .

2. The device for high-precision measurement of blood oxygenation status in cerebral cortex tissue according to claim 1, characterized in that, The three different wavelength ranges of near-infrared light emitted by each near-infrared light source into the brain tissue are 690-760nm, 800-810nm, and 830-850nm.

3. The device for high-precision measurement of blood oxygenation status in cerebral cortex tissue according to claim 1, characterized in that, The distance between the long-distance acquisition unit and the light source group is 30-40mm, and the distance between the short-distance acquisition unit and the light source group is 10-15mm.

4. The device for high-precision measurement of blood oxygenation status in cerebral cortex tissue according to claim 1, characterized in that, The light source module also includes a light source driving unit, which enables the near-infrared channels of different near-infrared light sources according to a certain timing standard, and asynchronously switches the different emission wavelengths of each near-infrared light source to ensure that near-infrared light of different wavelengths in the same near-infrared channel is emitted at different times, and that there is no crosstalk between the near-infrared light of different near-infrared channels. The emission time of each wavelength of near-infrared light is adjustable from 1ms to 20ms, and the enable time of each near-infrared channel is adjustable from 3ms to 100ms.

5. The device for high-precision measurement of blood oxygenation status in cerebral cortex tissue according to claim 1, characterized in that, Each signal acquisition group uses two photodetectors for its long and short distance acquisition units. These detectors are used to receive near-infrared light signals emitted from brain tissue and convert the near-infrared light signals into current signals. The signal acquisition module also includes a detector control unit, which controls the operation of the photodetector, converts the current signal obtained by the photodetector into a voltage signal, performs analog-to-digital conversion on the voltage signal, and sends the conversion result to the signal processing module.

6. The device for high-precision measurement of blood oxygenation status in cerebral cortex tissue according to claim 1, characterized in that, Each near-infrared light source includes three wavelength light-emitting diodes with lenses, and each photodetector uses an avalanche diode; It also includes a fixed module, with the light source module and signal acquisition module fixed on the fixed module, and the signal processing module located on the host computer.

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