Double-detector brain blood oxygen measuring system and method and medium

Abstract

The invention discloses a double-detector brain blood oxygen measurement system and method and a medium, belongs to the technical field of brain blood oxygen measurement, and aims to solve the technical problem that the accuracy and reliability of a measurement result are affected due to the fact that an existing brain blood oxygen measurement technology is in a single-detector mode and an obtained deep tissue signal contains a physiological interference signal of a superficial tissue. The system comprises a dual-detector signal acquisition module and a brain blood oxygen information extraction module, the dual-detector signal acquisition module is used for acquiring a superficial tissue signal and a deep tissue signal of the head of a detected person; the brain blood oxygen information extraction module is used for extracting brain blood oxygen information; the dual-detector signal acquisition module at least comprises a dual-wavelength LED light source driving circuit and a dual-detector measurement structure; the double-detector measuring structure is composed of a near-end detector and a far-end detector. The near-end detector is used for detecting light intensity signals scattered by superficial layer tissues of the head of a detected person, and the far-end detector is used for detecting light intensity signals scattered by deep layer tissues of the head of the detected person.

Description

Technical Field

[0001] The present invention relates to the technical field of cerebral blood oxygen measurement, and in particular to a dual-detector cerebral blood oxygen measurement system, method and medium. Background Art

[0002] Brain blood oxygen measurement technology, also known as functional near-infrared spectroscopy (fNIRS), is based on the principle that the main components of blood have good scattering properties for near-infrared light of 600-900nm. It applies a near-infrared light source to the head to obtain changes in the content of oxygenated hemoglobin and deoxygenated hemoglobin during brain activity. In 1977, Jobsis used NIRS technology to detect the hemoglobin concentration in the human brain and successfully captured the changes in blood oxygen in the cerebral cortex when people took deep breaths, demonstrating for the first time the feasibility of using near-infrared light to detect brain activity in living bodies.

[0003] The equipment used in early fNIRS studies was relatively simple, equipped with a small number of observation channels, and could only be measured at a single or a few locations on the head, which greatly limited brain function research. Currently, the commonly used fNIRS devices are all single-detector mode, that is, the distance between the light source and the detector is set to about 3 cm. The detector directly obtains information from the deep layers of the brain and uses this measured information as the final measurement result. The disadvantage of this method is that the obtained deep tissue signal will contain physiological interference signals from the shallow tissue, thus affecting the accuracy and reliability of the final result. Summary of the invention

[0004] The embodiments of the present invention provide a dual-detector cerebral blood oxygen measurement system, method and medium, which are used to solve the following technical problems: the existing cerebral blood oxygen measurement technologies are all single-detector modes, and the deep tissue signals obtained will contain physiological interference signals of shallow tissues, affecting the accuracy and reliability of the measurement results.

[0005] The embodiment of the present invention adopts the following technical solutions:

[0006] On the one hand, an embodiment of the present invention provides a dual-detector cerebral blood oxygen measurement system, the system comprising: a dual-detector signal acquisition module and a cerebral blood oxygen information extraction module; the dual-detector signal acquisition module is used to collect superficial tissue signals and deep tissue signals of the head of the subject; the cerebral blood oxygen information extraction module is used to extract cerebral blood oxygen information from the superficial tissue signals and the deep tissue signals;

[0007] The dual-detector signal acquisition module at least includes a dual-wavelength LED light source driving circuit and a dual-detector measurement structure;

[0008] The dual-wavelength LED light source driving circuit is used to provide a constant current power supply for the dual-wavelength LED light source and control the alternate flashing of the light sources of two wavelengths; the dual-wavelength LED light source irradiates light of two wavelengths onto the head of the subject, and the two wavelengths include red light and near-infrared light;

[0009] The dual-detector measurement structure is composed of a proximal detector and a distal detector;

[0010] The proximal detector is used to detect the light intensity signal scattered by the shallow tissue of the subject's head, that is, the shallow tissue signal;

[0011] The distal detector is used to detect the light intensity signal scattered by the deep tissue of the subject's head, that is, the deep tissue signal.

[0012] In a feasible implementation manner, the dual-detector signal acquisition module further includes: a signal separation circuit, a signal amplification circuit, a lock-in amplification circuit, and a digital-to-analog conversion circuit;

[0013] The signal separation circuit is connected to the output end of the dual-detector measurement structure, and is used to separately separate the shallow tissue signal and the deep tissue signal into red light signals and near-infrared light signals, obtaining four detection signals;

[0014] The signal amplification circuit is connected to the output end of the signal separation circuit, and is used to amplify the four detection signals;

[0015] The lock-in amplification circuit is connected to the output end of the signal amplification circuit, and is used to perform phase modulation on the amplified four detection signals and convert them into DC signals;

[0016] The digital-to-analog conversion circuit is connected to the output end of the lock-in amplification circuit, and is used to convert the DC signal into a digital signal and upload it to the upper computer for further processing.

[0017] In a feasible implementation manner, the dual-detector signal acquisition module further includes a system controller;

[0018] The system controller is used to output a first control signal, a second control signal, a third control signal, and a fourth control signal;

[0019] The first control signal includes two square wave timing signals, both with a duty cycle of 25%, and is used to separate the red light signal and the near-infrared light signal collected by the distal detector;

[0020] The second control signal includes two square wave timing signals, both with a duty cycle of 25%, and is used to separate the red light signal and the near-infrared light signal collected by the proximal detector;

[0021] The third control signal and the fourth control signal each include a square wave timing signal, and the phase difference between the two signals is strictly 180°, and the duty cycle is 50% for both.

[0022] On the other hand, an embodiment of the present invention further provides a dual-detector cerebral blood oxygen measurement method, and the method includes:

[0023] Applying an alternately flashing dual-wavelength light source to the head of the subject, and simultaneously collecting the shallow tissue signal and the deep tissue signal scattered by the head tissue of the subject;

[0024] Performing modal decomposition on the shallow tissue signal and the deep tissue signal respectively, and calculating the spectra of each modal component to obtain the high-frequency components and low-frequency components of the two signals;

[0025] Based on a custom information extraction algorithm, extracting cerebral blood oxygen information from the high-frequency components and low-frequency components of the two signals to obtain the cerebral blood oxygen information of the subject.

[0026] In a feasible implementation manner, applying an alternately flashing dual-wavelength light source to the head of the subject, and simultaneously collecting the shallow tissue signal and the deep tissue signal scattered by the head tissue of the subject specifically includes:

[0027] Placing the light-emitting surface of the dual-wavelength LED light source closely against a preset position on the scalp surface of the subject. At the same time, placing the proximal detector closely against the scalp surface of the subject at a position with a first preset distance from the dual-wavelength LED light source, and placing the distal detector closely against the scalp surface of the subject at a position with a second preset distance from the dual-wavelength LED light source; wherein, the first preset distance is less than the second preset distance; the proximal detector and the distal detector are on the same side of the dual-wavelength LED light source;

[0028] Obtaining an initial shallow tissue signal through the proximal detector, and obtaining an initial deep tissue signal through the distal detector; and separating the initial shallow tissue signal and the deep tissue signal into a red light signal and a near-infrared light signal respectively through a signal separation circuit to obtain four detection signals;

[0029] Performing phase modulation and amplification on the four detection signals respectively, and converting them into digital signals to obtain the processed shallow tissue signal and deep tissue signal.

[0030] In a feasible implementation manner, performing modal decomposition on the shallow tissue signal and the deep tissue signal respectively, and calculating the spectra of each modal component to obtain the high-frequency components and low-frequency components of the two signals specifically includes:

[0031] Analyze the signal components contained in the shallow tissue signal and the deep tissue signal. Based on the analysis results, describe the shallow tissue signal and the deep tissue signal with a mathematical model to obtain corresponding signal expressions;

[0032] Construct an iterative objective function and an iterative termination criterion for modal decomposition based on the standard deviation and excess kurtosis of the shallow tissue signal and the deep tissue signal;

[0033] Perform modal decomposition on the shallow tissue signal and the deep tissue signal respectively, and determine the iterative termination timing based on the iterative termination objective and the iterative termination criterion;

[0034] Calculate the spectral characteristics of each modal component obtained, and distinguish the high-frequency components and low-frequency components of the two signals according to the spectral characteristics.

[0035] In a feasible implementation manner, constructing an iterative objective function and an iterative termination criterion for modal decomposition based on the standard deviation and excess kurtosis of the shallow tissue signal and the deep tissue signal specifically includes:

[0036] Obtain the first envelope mean signal of the shallow tissue signal and the second envelope mean signal of the deep tissue signal;

[0037] Calculate the standard deviation and excess kurtosis of the first envelope mean signal and the second envelope mean signal respectively;

[0038] Construct an iterative objective function for the first envelope mean signal and the second envelope mean signal based on the standard deviation and excess kurtosis;

[0039] Construct the iterative termination criterion as: when the iterative objective function obtained after three consecutive iterations shows an increasing trend, stop the iteration, and output the result of the third-to-last iteration as the final result; or, when the number of iterations reaches the preset maximum number, stop the iteration, and output the result of the last iteration as the final result.

[0040] In a feasible implementation manner, based on a custom information extraction algorithm, extract cerebral blood oxygen information from the high-frequency components and low-frequency components of the two signals to obtain the cerebral blood oxygen information of the subject, specifically including:

[0041] Calculate the sum of the high-frequency components and the sum of the low-frequency components in the shallow tissue signal, and calculate the sum of the high-frequency components and the sum of the low-frequency components in the deep tissue signal;

[0042] Extract the deep brain tissue information of the subject based on the sum of the high-frequency components and the sum of the low-frequency components in the shallow tissue signal and the sum of the high-frequency components and the sum of the low-frequency components in the deep tissue signal;

[0043] Based on the deep brain tissue information, extract the cerebral blood oxygen information of the subject.

[0044] In a feasible implementation, based on the sum of high-frequency components and the sum of low-frequency components in the shallow tissue signal, as well as the sum of high-frequency components and the sum of low-frequency components in the deep tissue signal, extract the deep brain tissue information of the subject, specifically including:

[0045] Normalize the sum of high-frequency components Δx near (t) and the sum of low-frequency components x near (t) to obtain a normalization result and

[0046] Multiply Δx near (t) and x near (t) by a constant k const , and then add them to the sum of high-frequency components Δx far (t) and the sum of low-frequency components x far (t) of the deep tissue signal respectively, and normalize the added results to obtain a normalization result and

[0047] Calculate and And divide the respective calculation results by the corresponding coefficients K A1 and K A2 , add the two results after dividing by the coefficients to obtain the final extraction result, that is, the deep brain tissue information of the subject.

[0048] Finally, the embodiment of the present invention also provides a storage medium, the storage medium is a non-volatile computer-readable storage medium, and the non-volatile computer-readable storage medium stores at least one program, each program includes instructions, and when the instructions are executed by a terminal, the terminal executes the described dual-detector cerebral blood oxygen measurement method.

[0049] Compared with the prior art, a dual-detector cerebral blood oxygen measurement system, method and medium provided by the embodiment of the present invention have the following beneficial effects:

[0050] Existing cerebral blood oxygen content measurement and acquisition systems all adopt a single-detector measurement method. The measurement results obtained by this method include the physiological activity signals of superficial tissues such as the scalp layer and the skull layer. The amplitudes of these signals are often greater than the true cerebral activity signals, which will seriously affect the authenticity and accuracy of the conclusions obtained. In view of this problem, the present invention designs a cerebral blood oxygen measurement and acquisition system based on a dual-detector measurement method on the basis of the dual-detector measurement method. Each measurement channel of this device includes two detectors. The detector closer to the light source measures the physiological signals of superficial tissues such as the scalp and the skull layer, and the detector farther from the light source measures the physiological signals of deep layers such as the cerebral cortex. The two groups of signals are processed by modal decomposition and effective information extraction. Using the interference signals contained in the superficial tissue signals as a reference, the interference signals are removed from the deep tissue signals, so as to obtain accurate and true physiological signals caused by cerebral activity, and reduce the influence of superficial physiological interference on the measurement results. The signal acquisition module in this system is based on a dual-detector measurement method (including a close-range measurement channel and a long-range measurement channel), and adopts a unique circuit design to realize the measurement of superficial tissue information in the close-range channel and the measurement of deep tissue information in the long-range channel. And the number of acquisition channels can be set arbitrarily, and the maximum expandable channel number is 32 channels, which improves the flexibility of the device. The upper computer can set the acquisition and storage parameters of the device, and display and store the acquisition results of each channel in real time, which can meet the requirements in a variety of acquisition scenarios.

[0051] Furthermore, the information extraction module of this system decomposes the two measured signals into different frequency components by modal decomposition respectively, selects the corresponding components as the high-frequency and low-frequency parts in combination with the signal characteristics and spectral characteristics, and then processes them using the information extraction algorithm designed in this application, and then the true cerebral activity information can be obtained, which can effectively suppress the interference components contained in the measurement signals and improve the measurement accuracy. Brief Description of the Drawings

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments recorded in the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings:

[0053] Figure 1 It is a schematic structural diagram of a dual-detector cerebral blood oxygen measurement system provided by an embodiment of the present invention;

[0054] Figure 2 It is a schematic structural diagram of a dual-detector signal acquisition module provided by an embodiment of the present invention;

[0055] Figure 3 A schematic diagram of a structure of a dual detector for collecting brain signals provided by an embodiment of the present invention;

[0056] Figure 4 A timing diagram of a light source and a signal separation circuit provided by an embodiment of the present invention;

[0057] Figure 5 A flow chart of a dual-detector cerebral blood oxygen measurement method provided by an embodiment of the present invention;

[0058] Figure 6 A schematic diagram of the calculation process of a custom information extraction algorithm provided in an embodiment of the present invention.

[0059] Description of reference numerals:

[0060] 1. Host computer; 2. System controller; 3. Dual-wavelength LED light source driving circuit; 4. Dual-detector measurement structure; 5. Signal separation circuit and signal amplification circuit; 6. Phase-locked amplification circuit; 7. Digital-to-analog conversion circuit. DETAILED DESCRIPTION

[0061] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0062] First, an embodiment of the present invention provides a dual-detector cerebral blood oxygen measurement system. Figure 1 A schematic diagram of the structure of a dual-detector cerebral blood oxygen measurement system provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the dual-detector cerebral blood oxygen measurement system 100 includes: a dual-detector signal acquisition module 110 and a cerebral blood oxygen information extraction module 120 .

[0063] The dual detector signal acquisition module 110 is used to acquire the superficial tissue signal and the deep tissue signal of the subject's head. The cerebral blood oxygen information extraction module 120 is used to extract the cerebral blood oxygen information from the superficial tissue signal and the deep tissue signal.

[0064] Further, Figure 2 A schematic diagram of a dual-detector signal acquisition module structure provided by an embodiment of the present invention is shown in FIG. Figure 2 As shown, the dual-detector signal acquisition module 110 at least includes a dual-wavelength LED light source driving circuit 3 and a dual-detector measurement structure 4.

[0065] The dual-wavelength LED light source driving circuit 3 is a two-channel constant current source driving circuit, which is used to provide a constant current power supply for the dual-wavelength LED light source and control the alternating flashing of the light sources of two wavelengths. The dual-wavelength LED light source irradiates the light of two wavelengths onto the head of the subject, and the two wavelengths include red light and near-infrared light.

[0066] As a feasible implementation manner, the wavelengths of the red light and the near-infrared light emitted by the dual-wavelength LED light source are 735nm and 850nm respectively, and the power of the light of both wavelengths is 10mW.

[0067] Further, the dual-detector measurement structure 4 is composed of a proximal detector and a distal detector. The proximal detector is used to detect the light intensity signal scattered by the shallow tissue of the subject's head, that is, the shallow tissue signal. The distal detector is used to detect the light intensity signal scattered by the deep tissue of the subject's head, that is, the deep tissue signal.

[0068] As a feasible implementation manner, Figure 3 is a schematic diagram of a structure for collecting brain signals by a dual-detector provided by an embodiment of the present invention. As Figure 3 shown in the figure, the light source S in the figure is a dual-wavelength LED light source, the detector D1 is a proximal detector for measuring the information of the shallow tissue of the head, and the detector D2 is a distal detector for detecting the information of the deep tissue. Both the detector D1 and the detector D2 are photodiodes with a peak wavelength of 800nm. The light-emitting surface of the light source S is closely attached to the specified detection position on the surface layer of the subject's scalp. The distance between the detector D1 and the light source S is 1cm, and the distance between the detector D2 and the light source S is 3cm, and the detector D1 and the detector D2 are on the same side of the light source S.

[0069] Further, the dual-detector signal acquisition module 110 further includes: a signal separation circuit, a signal amplification circuit 5, a lock-in amplification circuit 6, and an analog-to-digital conversion circuit 7.

[0070] As Figure 2 shown, the signal separation circuit is connected to the output end of the dual-detector measurement structure 4, and includes proximal detector signal separation and distal detector signal separation, which are used to separately separate the shallow tissue signal and the deep tissue signal into red light signals and near-infrared light signals, and obtain four detection signals.

[0071] The signal amplification circuit is connected to the output end of the signal separation circuit and is used to amplify the four detection signals; the lock-in amplification circuit 6 is connected to the output end of the signal amplification circuit and is used to perform phase modulation on the four amplified detection signals and convert them into DC signals.

[0072] The analog-to-digital conversion circuit 7 is connected to the output end of the lock-in amplification circuit 6 and is used to convert the DC signal into a digital signal and upload it to the upper computer 1 for further processing.

[0073] As a feasible implementation, the host computer 1 is a multi-channel data acquisition system developed using LabVIEW and communicates with the ADC acquisition card through the USB transmission protocol. Its functions include displaying and saving the acquisition results, setting acquisition and saving parameters, etc.

[0074] Furthermore, the dual-detector signal acquisition module 110 further includes a system controller 2. The system controller 2 is used to output a first control signal, a second control signal, a third control signal, and a fourth control signal. The first control signal includes two square-wave timing signals, both with a duty cycle of 25%, and is used to separate the red light signal and the near-infrared light signal collected by the distal detector. The second control signal includes two square-wave timing signals, both with a duty cycle of 25%, and is used to separate the red light signal and the near-infrared light signal collected by the proximal detector. The third control signal and the fourth control signal each include a square-wave timing signal, and the phase difference between the two signals is strictly 180°, and the duty cycle of both is 50%.

[0075] As a feasible implementation, the first control signal is Figure 2 the control signal (1) in Figure 2 the second control signal is Figure 2 the control signal (2) in Figure 2 the third control signal is Figure 4 the control signal (3) in Figure 4 the fourth control signal is

[0076] Figure 2 the control signal (4) in. The system controller 2 is a controller based on an ARM or DSP series chip. The system controller 2 outputs six square-wave timing signals. Figure 4 FIG. Figure 4 shows a timing diagram of a light source and a signal separation circuit provided by an embodiment of the present invention. As shown, the third control signal output by the system controller 2 includes a square-wave timing signal IN1, and the fourth control signal includes a square-wave timing signal IN2. The frequencies of the two timing signals are both 1.5KHz, and the duty cycle of both is 50%. The phase difference between the two signals is strictly 180°. The third control signal and the fourth control signal are light source drive signals used to drive the dual-wavelength LED light source to alternately emit red light and near-infrared light. The first control signal is responsible for separating the red light signal and the infrared light signal collected by the distal detector and includes two square-wave timing signals IN3 and IN4 with a frequency of 1.5KHz and a duty cycle of 25% each. The second control signal is responsible for separating the red light signal and the infrared light signal collected by the proximal detector and includes two square-wave timing signals IN5 and IN6 with a frequency of 1.5KHz and a duty cycle of 25% each.

[0076] Further, the lock-in amplifier circuit 6 includes an amplifier circuit and a corresponding phase modulation circuit. Since the signal separation circuit and the signal amplification circuit 5 output four separated signals, the lock-in amplifier circuit 6 includes four lock-in amplification branches. The function of this part is to convert the square wave signal output by the signal amplification circuit into a DC signal. The signals output by the four phase modulation circuits are all sine waves, and their phases are the same as the square wave signals input to each path.

[0077] Further, the digital-to-analog conversion circuit 7 includes a multi-channel signal acquisition card. The ADC resolution of the acquisition card is 16 bits, it has 8 independent single-ended analog input channels, and the maximum supported sampling rate is 200 KSa / s (single channel).

[0078] Based on the above dual-detector cerebral blood oxygen measurement system, an embodiment of the present invention further provides a dual-detector blood oxygen measurement method. Figure 5 The flowchart of a dual-detector blood oxygen measurement method provided by an embodiment of the present invention is shown in Figure 5 As shown, the method specifically includes the following steps:

[0079] S101: Apply an alternately flashing dual-wavelength light source to the head of the subject, and simultaneously collect the shallow tissue signal and the deep tissue signal scattered from the head tissue of the subject.

[0080] Specifically, the light-emitting surface of the dual-wavelength LED light source is closely attached to a preset position on the scalp surface of the subject. At the same time, the proximal detector is closely attached to a position on the scalp surface of the subject and has a first preset distance from the dual-wavelength LED light source, and the distal detector is closely attached to a position on the scalp surface of the subject and has a second preset distance from the dual-wavelength LED light source; wherein, the first preset distance is less than the second preset distance; the proximal detector and the distal detector are on the same side of the dual-wavelength LED light source.

[0081] As a feasible implementation manner, as shown in Figure 3 The light-emitting surface of the dual-wavelength LED light source is closely attached to a preset position on the scalp surface of the subject, and this preset position can be determined according to expert experience or industry regulations. Then, the detector D1 is closely attached to a position 1 cm away from the light source as the proximal detector. The detector D2 is closely attached to a position 3 cm away from the light source as the distal detector. And the proximal detector and the distal detector are on the same side of the light source. Therefore, it can be known that at this time, the distance between the proximal detector and the distal detector is 2 cm.

[0082] Further, an initial shallow tissue signal is obtained through a proximal detector, and an initial deep tissue signal is obtained through a distal detector; and the initial shallow tissue signal and the deep tissue signal are respectively separated into a red light signal and a near-infrared light signal by a signal separation circuit to obtain four detection signals. The four detection signals are respectively phase-modulated and amplified and converted into digital signals to obtain the processed shallow tissue signal and deep tissue signal.

[0083] Since the distance between D1 and the light source S is relatively close, most of the photons obtained by D1 are photons scattered from the scalp surface layer, the skull, and the cerebrospinal fluid layer. Then, the information obtained by D1 is mainly the physiological information of the shallow tissue and the measurement interference. These information are collectively referred to as system interference. The distance between D2 and the light source S is relatively far, and the distance of photon transmission and the depth that can be reached are relatively large. Therefore, the photons obtained by D2 will carry both surface information, deep tissue information, and measurement interference at the same time. Among them, the information in the deep tissue will be used as the component related to brain function activities, which is the effective brain activity signal that needs to be extracted in this application.

[0084] S102. Perform modal decomposition on the shallow tissue signal and the deep tissue signal respectively, and calculate the spectra of each modal component to obtain the high-frequency components and low-frequency components of the two signals.

[0085] Specifically, analyze the signal components included in the shallow tissue signal and the deep tissue signal. Based on the analysis results, describe the shallow tissue signal and the deep tissue signal with a mathematical model to obtain the corresponding signal expressions.

[0086] As a feasible implementation manner, the information measured by the dual detectors can be described by a mathematical model After expanding this mathematical model, the signal expressions are obtained:

[0087] where, y near (t), y far (t) are the shallow tissue signal and the deep tissue signal measured by the detectors D1 and D2 respectively. y sys (t) is the physiological interference signal, and y BFA (t) is the effective brain activity signal. k1, k2, and k3 are three constants representing the coefficients of each signal component, and ε1(t), ε2(t) are the measurement interferences of the two detector channels respectively. Since the proportion of the effective brain activity information detected by the proximal detector is very small, an approximation is made in the mathematical model in this application, that is, it is considered that all the components included in the shallow tissue signal are interference components and do not include effective brain activity information.

[0088] Further, based on the standard deviation and excess kurtosis of the shallow tissue signal and the deep tissue signal, an iterative objective function and an iterative termination criterion for modal decomposition are constructed.

[0089] As a feasible implementation, during the modal decomposition process, the stopping condition determines the number of iterations in each decomposition process. If the number of iterations is too large, a component will be decomposed into multiple decomposition results; if the number of iterations is too small, it will cause multiple components to be included in one decomposition result. Thus, it can be seen that the number of iterations will directly affect the accuracy of the decomposition result. To adaptively select the optimal number of iterations in the decomposition process, the present invention adds a stopping objective function and a stopping criterion to the modal decomposition process to achieve the purpose of obtaining the optimal decomposition times. First, the first envelope mean signal of the shallow tissue signal and the second envelope mean signal of the deep tissue signal are obtained. Then, the standard deviation and excess kurtosis of the first envelope mean signal and the second envelope mean signal are calculated respectively. Based on the standard deviation STD(Q ik [n]) and the excess kurtosis EK(Q ik [n]), an iterative objective function f ik = STD(Q ik [n]) + |EK(Q ik [n])| is constructed; where Q ik [n] is the envelope mean signal.

[0090] Further, the iterative termination criterion is constructed as follows: when the iterative objective function obtained after three consecutive iterations shows an increasing trend, stop the iteration, and output the result of the third-to-last iteration as the final result; or, when the number of iterations reaches the preset maximum number, stop the iteration, and output the result of the last iteration as the final result.

[0091] Further, the shallow tissue signal and the deep tissue signal are respectively subjected to modal decomposition, and based on the iterative termination objective and the iterative termination criterion, the iterative termination timing is determined. The spectral characteristics of each modal component are calculated, and the high-frequency components and low-frequency components of the two signals are distinguished according to the spectral characteristics.

[0092] S103. Based on a custom information extraction algorithm, the high-frequency components and low-frequency components of the two signals are used to extract cerebral blood oxygen information to obtain the cerebral blood oxygen information of the subject.

[0093] Specifically, the sum of the high-frequency components and the sum of the low-frequency components in the shallow tissue signal are calculated, and the sum of the high-frequency components and the sum of the low-frequency components in the deep tissue signal are calculated.

[0094] Extract the deep brain tissue information of the subject based on the sum of the high-frequency components and the sum of the low-frequency components in the shallow tissue signal, as well as the sum of the high-frequency components and the sum of the low-frequency components in the deep tissue signal. Extract the cerebral blood oxygen information of the subject based on the deep brain tissue information.

[0095] As a feasible implementation Figure 6 FIG. is a schematic diagram of the calculation process of a custom information extraction algorithm provided by an embodiment of the present invention, as Figure 6 shown, the specific steps of the custom extraction algorithm are as follows:

[0096] First, perform modal decomposition on the detection signals of the proximal detector and the distal detector respectively, and then calculate the spectra of the respective modal components obtained after decomposition to obtain the low-frequency components and high-frequency components in the spectra.

[0097] Then, normalize the sum of the high-frequency components Δx near (t) and the sum of the low-frequency components x near (t) in the shallow tissue signal to obtain the normalization result and At the same time, multiply Δx near (t) and x near (t) by the constant k const , and then add them to the sum of the high-frequency components Δx far (t) and the sum of the low-frequency components x far (t) in the deep tissue signal respectively, and normalize the sum results to obtain the normalization results and

[0098] Then calculate and And divide the respective calculation results by the corresponding coefficients K A1 and K A2 , and add the two results after dividing by the coefficients to obtain the final extraction result k3y BFA , that is, the deep brain tissue information of the subject.

[0099] Through the above calculation process, the interference signal represented by the shallow tissue signal can be eliminated from the deep tissue signal, so as to obtain a cleaner and interference-free effective brain activity signal and obtain more accurate deep brain tissue information of the subject. Finally, in the deep brain tissue information of the subject, the cerebral blood oxygen information of the subject can be extracted by conventional means.

[0100] It should be noted that the four constants k1, k2, k3, and kconst involved in the algorithm are only used for calculation and do not represent the true values of a certain component. Their values can be arbitrarily selected and will not affect the final extraction result. For the final output result, a filter can be set according to the actual situation to smooth the signal to obtain a clear curve of brain activity information.

[0101] Finally, the embodiment of the present invention also provides a storage medium, which is a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores at least one program, and each program includes instructions. When the instructions are executed by a terminal, the terminal is enabled to execute the described dual-detector brain blood oxygen measurement method.

[0102] The various embodiments in the present invention are described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments.

[0103] The above describes specific embodiments of the present invention. Additionally, the processes depicted in the figures do not necessarily require the specific order or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0104] The above are only the embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, various changes and modifications can be made to the embodiments of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present invention shall be included within the protection scope of the present invention.

Claims

1. A dual-detector cerebral blood oxygen measurement system, characterized in that: The system comprises: a dual-detector signal acquisition module and a cerebral blood oxygen information extraction module; the dual-detector signal acquisition module is used to acquire superficial tissue signals and deep tissue signals of the subject's head; the cerebral blood oxygen information extraction module is used to extract cerebral blood oxygen information from the superficial tissue signals and deep tissue signals; The dual-detector signal acquisition module at least includes a dual-wavelength LED light source driving circuit and a dual-detector measurement structure; The dual-wavelength LED light source driving circuit is used to provide a constant current power supply for the dual-wavelength LED light source and control the light sources of the two wavelengths to flash alternately; the dual-wavelength LED light source irradiates the head of the subject with light of two wavelengths, the two wavelengths including red light and near-infrared light; The dual-detector measurement structure is composed of a proximal detector and a distal detector; The proximal detector is used to detect the light intensity signal scattered by the superficial tissue of the subject's head, that is, the superficial tissue signal; The remote detector is used to detect the light intensity signal scattered by the deep tissue of the head of the subject, that is, the deep tissue signal.

2. A dual-detector cerebral blood oximetry system according to claim 1, characterized in that: The dual-detector signal acquisition module also includes: a signal separation circuit, a signal amplification circuit, a phase-locked amplification circuit and a digital-to-analog conversion circuit; The signal separation circuit is connected to the output end of the dual-detector measurement structure, and is used to separate the shallow tissue signal and the deep tissue signal into a red light signal and a near-infrared light signal, respectively, to obtain four detection signals; The signal amplifying circuit is connected to the output end of the signal separating circuit, and is used to amplify the four detection signals; The phase-locked amplifier circuit is connected to the output end of the signal amplifier circuit, and is used to phase-modulate the amplified four-path detection signal and convert it into a DC signal; The digital-to-analog conversion circuit is connected to the output end of the phase-locked amplifier circuit, and is used to convert the DC signal into a digital signal, and upload it to a host computer for further processing.

3. A dual-detector cerebral blood oximetry system according to claim 1, characterized in that: The dual-detector signal acquisition module also includes a system controller; The system controller is used to output a first control signal, a second control signal, a third control signal and a fourth control signal; The first control signal includes two square wave timing signals, each with a duty cycle of 25%, which are used to separate the red light signal and the near-infrared light signal collected by the remote detector; The second control signal includes two square wave timing signals, each with a duty cycle of 25%, which are used to separate the red light signal and the near-infrared light signal collected by the near-end detector; The third control signal and the fourth control signal each include a square wave timing signal, the phase difference between the two signals is strictly 180°, and the duty cycle is 50%.

4. A dual-detector cerebral blood oximetry method applied to a dual-detector cerebral blood oximetry system as claimed in any one of claims 1 to 3, characterized in that: The method comprises: Apply an alternately flashing dual-wavelength light source to the subject's head, and simultaneously collect the shallow tissue signal and deep tissue signal scattered by the subject's head tissue; Performing modal decomposition on the shallow tissue signal and the deep tissue signal respectively, and calculating the frequency spectrum of each modal component to obtain high-frequency components and low-frequency components of the two signals; Based on a custom information extraction algorithm, brain blood oxygen information is extracted from the high-frequency components and low-frequency components of the two signals to obtain the brain blood oxygen information of the subject.

5. A dual-detector cerebral blood oxygen measurement method according to claim 4, characterized in that: Apply an alternately flashing dual-wavelength light source to the subject's head, and collect shallow tissue signals and deep tissue signals scattered by the subject's head tissue at the same time, specifically including: The light-emitting surface of the dual-wavelength LED light source is closely attached to a preset position on the surface of the scalp of the subject, and at the same time, the proximal detector is closely attached to a position on the surface of the scalp of the subject at a first preset distance from the dual-wavelength LED light source, and the distal detector is closely attached to a position on the surface of the scalp of the subject at a second preset distance from the dual-wavelength LED light source; wherein the first preset distance is smaller than the second preset distance; and the proximal detector and the distal detector are on the same side of the dual-wavelength LED light source; The initial shallow tissue signal is obtained through the proximal detector, and the initial deep tissue signal is obtained through the distal detector; and the initial shallow tissue signal and the deep tissue signal are separated into a red light signal and a near-infrared light signal respectively through a signal separation circuit to obtain four detection signals; The four detection signals are phase modulated and amplified respectively, and converted into digital signals to obtain processed shallow tissue signals and deep tissue signals.

6. A dual-detector cerebral blood oxygen measurement method according to claim 4, characterized in that: Performing modal decomposition on the shallow tissue signal and the deep tissue signal respectively, and calculating the frequency spectrum of each modal component to obtain high-frequency components and low-frequency components of the two signals, specifically including: Analyzing the signal components contained in the superficial tissue signal and the deep tissue signal, and based on the analysis results, describing the superficial tissue signal and the deep tissue signal with a mathematical model to obtain corresponding signal expressions; Based on the standard deviation and excess kurtosis of the shallow tissue signal and the deep tissue signal, construct an iterative objective function and an iterative termination criterion for modal decomposition; Performing modal decomposition on the shallow tissue signal and the deep tissue signal respectively, and determining an iteration termination timing based on the iteration termination target and the iteration termination criterion; The frequency spectrum characteristics of each modal component are calculated, and the high-frequency components and low-frequency components of the two signals are distinguished according to the frequency spectrum characteristics.

7. A dual-detector cerebral blood oxygen measurement method according to claim 6, characterized in that: Based on the standard deviation and excess kurtosis of the shallow tissue signal and the deep tissue signal, an iterative objective function and an iterative termination criterion of modal decomposition are constructed, specifically including: Acquire a first envelope mean signal of the shallow tissue signal and a second envelope mean signal of the deep tissue signal; Calculating the standard deviation and the excess kurtosis of the first envelope mean signal and the second envelope mean signal respectively; Based on the standard deviation and the excess kurtosis, constructing an iterative objective function of the first envelope mean signal and the second envelope mean signal; The iteration termination criterion is constructed as follows: when the iterative objective function obtained after three consecutive iterations shows an increasing trend, the iteration is stopped, and the result of the third-to-last iteration is output as the final result; or, when the number of iterations reaches a preset maximum number, the iteration is stopped, and the result of the last iteration is output as the final result.

8. A dual-detector cerebral blood oxygen measurement method according to claim 4, characterized in that: Based on a custom information extraction algorithm, brain blood oxygen information is extracted from the high-frequency components and low-frequency components of the two signals to obtain the brain blood oxygen information of the subject, specifically including: Calculating the sum of the high frequency components and the sum of the low frequency components in the shallow tissue signal, and calculating the sum of the high frequency components and the sum of the low frequency components in the deep tissue signal; Extracting deep brain tissue information of the subject based on the sum of the high-frequency components and the sum of the low-frequency components in the superficial tissue signal and the sum of the high-frequency components and the sum of the low-frequency components in the deep tissue signal; Based on the deep brain tissue information, the brain blood oxygen information of the subject is extracted.

9. A dual-detector cerebral blood oxygen measurement method according to claim 8, characterized in that: Extracting the deep brain tissue information of the subject based on the sum of the high frequency components and the sum of the low frequency components in the superficial tissue signal, and the sum of the high frequency components and the sum of the low frequency components in the deep tissue signal, specifically includes: The sum of the high-frequency components of the shallow tissue signal Δx near (t) and the sum of the low-frequency components x near (t) Perform normalization processing to obtain the normalized result and Δx near (t) and x near (t) multiplied by the constant k const , and then respectively with the sum of the high-frequency components of the deep tissue signal Δx far (t), the sum of low-frequency components x far (t) are added, and the result of the addition is normalized to obtain the normalized result and calculate as well as And divide each calculation result by the corresponding coefficient K A1 With K A2 , the two results after division by the coefficient are added together to obtain the final extraction result, i.e., the deep brain tissue information of the subject.

10. A storage medium, characterized in that: The storage medium is a non-volatile computer-readable storage medium, and the non-volatile computer-readable storage medium stores at least one program, each of which includes instructions, and when the instructions are executed by the terminal, the terminal executes a dual-detector cerebral blood oxygen measurement method according to any one of claims 4-9.

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