Real-time analysis method and device for measuring chemical substances of living brain

Abstract

The invention provides a real-time analysis method for measuring chemical substances in a brain of a living body. The real-time analysis method comprises the following steps: setting test parameters, and calculating the number of times of cyclic measurement; de-noising, checking, caching and measuring the collected original data by adopting a multi-thread working mode based on the number of cyclic measurement times; and verifying the clean data for the second time by using the verification algorithm, and comparing whether the data of the verification interval after the second verification is consistent with the original data of the same interval. High time resolution is realized; performing dynamic monitoring; real-time data processing; performing multi-parameter analysis; long-term monitoring; accumulating data; the sensitivity is high.

Description

Technical Field

[0001] The present invention belongs to the field of material analysis, and in particular relates to a real-time analysis method and device for measuring chemical substances in living brain. Background Art

[0002] Electrophysiological equipment plays an important role in biomedical research. Researchers use electrophysiological equipment to test and record the electrophysiological activities in vivo. Accordingly, each electrophysiological equipment has a corresponding set of measurement, display and analysis systems. This type of system has powerful data analysis functions and can perform various processing and analysis on experimental data; it has good visualization functions and can intuitively display experimental results; it is usually equipped with various electrophysiological experimental modules, which are suitable for different types of research.

[0003] However, the existing measurement systems have different shortcomings, and none of them can combine the above advantages while taking into account the test performance.

[0004] Microdialysis measurement systems, such as Microdialysis Coupled with Electrochemical Detection, can provide long-term continuous monitoring, but the time resolution is low.

[0005] For example, Chenhua's electrochemical workstation has multiple research methods and high sensitivity, but it is unable to process and analyze the data being measured.

[0006] For example, MT100 can perform simple data processing and analysis during testing, but when the amount of test data is very large, the data must be displayed in segments, and it is impossible to fully observe the data changes. During the test, MT100 software can only perform simple analysis on the currently displayed data, and many functions can only be used after the test is completed. In addition, the interface becomes more and more stuck as the amount of data increases.

[0007] In order to more realistically reflect the physiological and pathological processes in living organisms, researchers now need to analyze and monitor the real-time concentration changes of chemical substances in the brain tissue of living organisms through in vivo experiments. Therefore, the demand for test equipment and its measurement system is increasing. The existing electrophysiological analysis and measurement system cannot meet the needs of researchers to conduct long-term real-time analysis of chemical substances in living brains.

[0008] Existing technical problems:

[0009] (1) Studying the chemical substances in living brains requires long-term observation. A live experiment can last up to a week or even longer. During this period, data must be collected and recorded. The whole process will inevitably generate a large amount of data. The larger the amount of data, the more it will affect the stability and compatibility of the measurement and analysis system. The current measurement system cannot stably perform long-term tests and record data completely.

[0010] (2) In order for researchers to understand the changes in chemical substances in the living brain, real-time data needs to be continuously displayed and processed during the test to achieve the purpose of real-time monitoring of changes in the concentration of chemical substances in the brain. Currently, this cannot be tested, the data cannot be displayed in real time, and the data cannot be processed in real time. Summary of the invention

[0011] The purpose of the present invention is to overcome the above problems and provide a real-time analysis method and device for measuring chemical substances in living brains. The present invention solves the problem that the measurement system cannot stably perform long-term testing and completely record data and the test data cannot be displayed in real time.

[0012] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0013] In one aspect, a real-time analysis method for measuring chemical substances in the living brain is provided, wherein the server side of the method comprises the following steps:

[0014] Set the test parameters and calculate the number of cycle measurements, where the calculation formula for the number of cycle tests is:

[0015]

[0016] In the formula, N represents the number of cycle tests, C represents the number of turns, and n represents the bit length for storing the number of turns; N is an integer, and if it is not an integer, it is calculated as an integer. For example, if the formula calculates N = 3.1, the actual value of N is 4.

[0017] Based on the number of cyclic measurements, a multi-threaded working mode is used to denoise, verify, cache and measure the collected raw data; wherein, the multi-threaded working mode is used to denoise, verify, cache and measure the collected raw data, including collecting raw data, denoising the raw data using a smoothing filter algorithm, verifying the denoised clean data for the first time using a verification algorithm, and storing the denoised clean data simultaneously;

[0018] The clean data is verified for a second time using the verification algorithm to compare the data of the verification interval after the second verification with the original data of the same interval to see if they are consistent; wherein, if the data of the two are consistent, the measurement data in the data storage disk is sent to the client.

[0019] As a further improvement, the server side further includes the following steps:

[0020] The data model and the data stored in the data storage disk in real time are bound using a data binding framework, and the updated measurement data is sent to the client in real time.

[0021] As a further improvement, the first verification of the denoised clean data using the verification algorithm includes the following steps:

[0022] Verify the uint16 value obtained by adding each byte from the byte after the frame length to the byte before the terminator as unsigned uint8 and then taking the modulo 65536.

[0023] As a further improvement, the storing of the clean data after denoising includes the following steps:

[0024] The clean data after denoising is placed in a cache file, and after the measurement is completed, the cache file is converted into an actual file.

[0025] As a further improvement, sending the updated measurement data to the client in real time includes the following steps:

[0026] Declare data binding relationships, and the data binding framework automatically updates data and sends the updated data to the client.

[0027] On the other hand, a real-time analysis method for measuring chemical substances in living brain is also provided, and its client comprises the following steps:

[0028] Receive measurement data sent by the server;

[0029] Multi-threaded off-screen rendering technology is used to render images of the measurement data, and to display and update the data in real time.

[0030] As a further improvement, the image rendering of the measurement data using multi-threaded off-screen rendering technology includes the following steps:

[0031] Divide the rendering task into multiple subtask blocks;

[0032] By using multi-threading technology, the rendering tasks of the plurality of sub-task blocks are assigned to a plurality of threads for parallel rendering, thereby obtaining rendering results of the plurality of threads;

[0033] The rendering results of the multiple threads are combined and spliced ​​into a display image.

[0034] As a further improvement, the image rendering of the measurement data using the multi-threaded off-screen rendering technology further includes the following steps:

[0035] Create a framebuffer object for off-screen rendering and create and initialize an OpenGL context.

[0036] As a further improvement, the Direct2D rendering API is used in the parallel rendering.

[0037] On the other hand, the present invention also provides a real-time analysis system for measuring chemical substances in living brains, the system comprising at least one processor and a memory storing instructions, which, when executed by at least one processor, implement the method in the above technical solution.

[0038] A computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method described in the steps of the above technical solution.

[0039] A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method described in the steps of the above technical solution is implemented.

[0040] The beneficial effects of the present invention are:

[0041] High temporal resolution: The real-time analysis system of living brain chemicals can capture the dynamic changes of chemicals in the brain with a temporal resolution of milliseconds;

[0042] Dynamic monitoring: Real-time analysis systems can monitor changes in concentrations of chemicals in the brain in real time, providing immediate feedback and helping researchers better understand the relationship between neural activity and behavior;

[0043] Real-time data processing: In vivo brain chemical real-time analysis systems are usually equipped with powerful data processing capabilities to quickly analyze and display data;

[0044] Multi-parameter analysis: The real-time analysis system can be used to conduct two different electrophysiological experiments, and can simultaneously monitor and analyze the concentration changes of multiple chemical substances (it can simultaneously monitor two (because only two experiments can be done at the same time) and analyze the concentration changes of multiple chemical substances (it can analyze multiple because the software can also open the previous test data for processing during the test);

[0045] Long-term monitoring: The real-time analysis system of living brain chemicals can monitor for a long time, helping researchers understand long-term neural activity and behavioral patterns;

[0046] Data accumulation: Long-term testing can accumulate a large amount of data, providing rich information for subsequent in-depth analysis;

[0047] High sensitivity: Real-time analysis systems of living brain chemicals usually have higher sensitivity and can detect small changes in chemical concentrations;

[0048] Versatility: The real-time analysis system can not only monitor the changes in chemical substances, but also combine electrophysiological signals for comprehensive analysis.

[0049] In summary, it can be seen that the real-time analysis system of living brain chemicals has obvious advantages in real-time analysis, data processing, long-term testing and comprehensive performance, and can provide more comprehensive and in-depth support for neuroscience research. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The present invention has the following accompanying drawings:

[0051] Figure 1 is a flowchart of a real-time analysis method for measuring chemical substances in the living brain according to some specific embodiments of the present invention;

[0052] Figure 2 It is a schematic diagram of the structure of a real-time analysis device for measuring chemical substances in the living brain in some specific embodiments of the present invention;

[0053] Figure 3 It is a structural schematic diagram of a real-time analysis system for measuring chemical substances in living brain of the present invention;

[0054] Figure 4 A schematic diagram of a real-time analysis system for measuring chemical substances in the living brain of the present invention. DETAILED DESCRIPTION

[0055] The following examples further illustrate the content of the present invention, but should not be construed as limiting the present invention. Without departing from the spirit and substance of the present invention, modifications or substitutions made to the methods, steps or conditions of the present invention all fall within the scope of the present invention.

[0056] Embodiment 1:

[0057] like Figure 1 As shown, the present invention provides a real-time analysis method for measuring chemical substances in living brain, and the server side thereof includes the following steps:

[0058] Step S11: setting test parameters and calculating the number of cycle measurements;

[0059] For example, the test steps are:

[0060] When establishing an experimental project, the system will first initialize the backend module. At this time, it will establish the environment and configuration to ensure that the subsequent development and operating environment work properly; load necessary resources to ensure that the backend module can run normally and access the required resources; pre-process data to ensure the normal operation of subsequent functions; check whether the configuration is correct and whether the dependencies are complete, etc., which will help to discover potential problems in advance and deal with them; reduce system startup time and improve response speed to avoid unnecessary delays during operation.

[0061] Continue to set parameters and select whether to run for a long time in the parameters. If a long-term test is set, the system will use a cyclic test. The formula for calculating the number of cyclic tests is: C / (2^n-1), where C is the number of cycles set by the user, and n is the bit length allocated by the system to store the number of cycles. In this system, n=16.

[0062] The system calculates the number of cycles and then starts the measurement.

[0063] Among them, the calculation formula for the number of cycle tests is:

[0064]

[0065] In the formula, N represents the number of cycle tests, C represents the number of turns, and n represents the bit length for storing the number of turns;

[0066] For example, continue to set parameters and select whether to run for a long time in the parameters. If a long-term test is set, the system uses a cyclic test. The formula for calculating the number of cyclic tests is: Where C is the number of laps set by the user, and n is the bit length assigned by the system to store the number of laps. In this system, n=16. After the system calculates the number of cycles, it starts the measurement (if N is greater than 1, the system will perform a cyclic test. After clicking Start Measurement, a file save interface will pop up to allow the customer to save in advance. Only cyclic tests will have files saved in advance to prevent accidental data loss during long-term tests. If the test stops responding unexpectedly before the end, the data can also be found in the cache file, so the experiment will not be in vain). At the same time, the system needs to collect data. The system continuously collects data through the serial port, and the data transmission speed is not limited.

[0067] Step S12: based on the number of cyclic measurements, denoising, verifying, caching and measuring the collected raw data by a multi-threaded working mode; wherein the denoising, verifying, caching and measuring the collected raw data by a multi-threaded working mode includes collecting raw data, denoising the raw data by a smoothing filter algorithm, verifying the denoised clean data for the first time by a verification algorithm and storing the denoised clean data simultaneously;

[0068] For example, the system starts measuring after calculating the number of cycles, and the system needs to collect data at the same time. The system continuously collects data through the serial port, and the data transmission speed is not limited.

[0069] The longer the measurement time, the larger the amount of data collected. In order to process data quickly and have sufficient storage space, this system uses multi-threaded processing, and each thread is an independent execution path, that is, data is collected and stored at the same time.

[0070] The collected data is placed in a cache file. After the measurement is completed, the cache file is saved and converted into an actual file. The file is mapped into a memory area by means of memory mapping file. Therefore, the file size is not limited and is only related to the size of the hard disk where the file is stored.

[0071] Large amounts of data require more computing resources to process and analyze. In order to ensure the computing and processing efficiency of the system, this system uses parallel processing and multi-threaded parallel working mode to store data while using smoothing filters to process data.

[0072] A large amount of data may contain a large amount of noise data or invalid data. In order to ensure the accuracy and credibility of the system data analysis, this system designs a verification algorithm. From the frame length (excluding the frame length byte) to the byte before the terminator, each byte is accumulated as unsigned uint8 and then modulo 65536 (the reason for modulo 65536 is: the check bit length is two bytes, "accumulate each byte from the byte after the frame length to the byte before the terminator as unsigned uint8", if the accumulated value is greater than 65536, the data will overflow. In order to prevent data overflow, the modulo needs to be calculated), and the obtained uint16 value is verified to ensure data accuracy.

[0073] Through the above means, unnecessary data flooding and waste of resources can be avoided to ensure the efficiency, security and maintainability of the system.

[0074] Step S13: Use the verification algorithm to verify the clean data for the second time, and compare the data of the verification interval after the second verification with the original data of the same interval to see if they are consistent; if the data of the two intervals are consistent, send the measurement data in the data storage disk to the client.

[0075] For example, displaying the collected data on the user interface (UI) requires coordination from multiple aspects to realize the function.

[0076] For scientific research experiments, data accuracy is crucial. Data may change or be lost during transmission, storage, and processing, so before displaying the collected data on the UI, the data must be confirmed to ensure that the collected data has been correctly processed and stored. The accuracy of the data has been confirmed during collection, and the system needs to use the same verification algorithm to recalculate before display to ensure that the data displayed on the UI is consistent with the actual collected data. After confirming that the data is correct, the system directly reads the data in the hard disk according to the parameters.

[0077] In some embodiments of the present invention, the server further comprises the following steps:

[0078] Step S10: Bind the data model and the data stored in the data storage disk in real time using a data binding framework, and send the updated measurement data to the client in real time.

[0079] For example, when setting up an experimental project, the system will first initialize the backend module, at which point it will establish the environment and configuration to ensure that subsequent development and operating environments work properly; load necessary resources to ensure that the backend module can run normally and access required resources; pre-process data to ensure that subsequent functions run normally; check whether the configuration is correct and whether the dependencies are complete, etc., to help identify potential problems in advance and deal with them; reduce system startup time and improve response speed to avoid unnecessary delays during runtime.

[0080] In some embodiments of the present invention, the first verification of the denoised clean data using a verification algorithm includes the following steps:

[0081] Verify the uint16 value obtained by adding each byte from the byte after the frame length to the byte before the terminator as unsigned uint8 and then taking the modulo 65536.

[0082] In some embodiments of the present invention, storing the clean data after denoising comprises the following steps:

[0083] Put the denoised clean data in a cache file (the system comes with a temporary cache folder. During the test, a file named after the test time will be automatically generated in the folder. These files always exist, and all test data can be found, unless the user enters this folder to delete the cache file. These cache files exist independently and do not affect the user's own file saving. If the software test is interrupted unexpectedly or the current test data is not saved due to improper operation, the data can be found in the temporary cache folder. This function is very important for long-term testing to avoid the loss of important data and reduce the time for repeated experiments). After the measurement, convert the cache file into an actual file.

[0084] In some embodiments of the present invention, sending the updated measurement data to the client in real time includes the following steps:

[0085] Declare data binding relationships, and the data binding framework automatically updates data and sends the updated data to the client.

[0086] For example, the UI of the system should be clear and easy to understand, so that users can quickly find key information. When data is updated, ensure that the UI can be updated and displayed in time. This system design uses the data binding framework to declare the data binding relationship. The framework automatically handles the update between data and the interface so that data changes can be automatically reflected on the interface. Bind the data model with the real-time data source to realize the display and update of real-time data.

[0087] On the other hand, a real-time analysis method for measuring chemical substances in living brain is also provided, and its client comprises the following steps:

[0088] Receive measurement data sent by the server;

[0089] Multi-threaded off-screen rendering technology is used to render images of the measurement data, and to display and update the data in real time.

[0090] For example, this system uses multi-threaded off-screen rendering, which is an advanced graphics programming technique that involves rendering images off-screen and using multi-threading technology to improve rendering efficiency. By assigning rendering tasks to multiple threads, you can take full advantage of multi-core processors, significantly improve rendering performance, and avoid the bottleneck of a single thread. Multi-threaded rendering can reduce the load on a single thread and make the application respond faster to user input.

[0091] The image rendering of the measurement data is performed using a multi-threaded off-screen rendering technology, including the following steps:

[0092] Divide the rendering task into multiple subtask blocks;

[0093] By using multi-threading technology, the rendering tasks of the plurality of sub-task blocks are assigned to a plurality of threads for parallel rendering, thereby obtaining rendering results of the plurality of threads;

[0094] The rendering results of the multiple threads are combined and spliced ​​into a display image.

[0095] The image rendering of the measurement data using multi-threaded off-screen rendering technology may also include the following steps:

[0096] a) Divide the overall rendering task into multiple subtask blocks;

[0097] b) using multi-threading technology, assigning these sub-task blocks to multiple independent threads to perform rendering in parallel;

[0098] c) Collect and integrate the rendering results of each thread;

[0099] d) The integrated rendering results are synthesized into the final display image.

[0100] For example, the key steps to implement multi-threaded off-screen rendering are:

[0101] Initialize the rendering context: Create the frame buffer object (FBO) required for off-screen rendering. Create and initialize the OpenGL context for each thread, ensuring that these contexts share the necessary resources.

[0102] Task division: Divide the rendering task into multiple sub-task blocks, and each thread is responsible for rendering a part of it. Task division can be based on factors such as screen space and scene complexity.

[0103] Parallel rendering: Use multithreading technology (such as C++'s std::thread or other parallel programming frameworks) to assign rendering tasks to multiple threads for parallel execution. This system uses the Direct2D rendering API for high-performance 2D graphics rendering, supports multiple graphic elements such as vector graphics, bitmaps, text, etc., and can be compatible with other graphics APIs such as Windows GDI and GDI+.

[0104] Merge results: After all threads complete their respective rendering tasks, the rendering results of each part are merged into the final image.

[0105] In some embodiments of the present invention, the image rendering of the measurement data using the multi-threaded off-screen rendering technology further includes the following steps:

[0106] Create a framebuffer object for off-screen rendering and create and initialize an OpenGL context.

[0107] In some embodiments of the present invention, the parallel rendering is performed using a Direct2D rendering API (Direct2D is a high-performance 2D graphics rendering API (application programming interface) developed by Microsoft).

[0108] like Figure 2 As shown, a real-time analysis device for measuring chemical substances in living brain is also provided, including a long-term test and data acquisition module and a real-time data display and processing module, and its server side includes:

[0109] The calculation module is used to set the test parameters and calculate the number of cycle measurements, wherein the calculation formula for the number of cycle tests is:

[0110]

[0111] In the formula, N represents the number of cycle tests, C represents the number of turns, and n represents the bit length for storing the number of turns;

[0112] The measurement module is used for denoising, verifying, caching and measuring the collected raw data in a multi-threaded working mode based on the number of cyclic measurements; wherein the denoising, verifying, caching and measuring the collected raw data in a multi-threaded working mode includes collecting raw data, denoising the raw data by a smoothing filter algorithm, verifying the denoised clean data for the first time by a verification algorithm and storing the denoised clean data simultaneously;

[0113] A comparison module, used to use the verification algorithm to verify the clean data for a second time, and to compare whether the data in the verification interval after the second verification is consistent with the original data in the same interval;

[0114] The first sending module is used to send the measurement data in the data storage disk to the client if the data of the two are consistent.

[0115] In some embodiments of the present invention, the server side further includes:

[0116] The second sending module is used to bind the data model and the data stored in the data storage disk in real time by using a data binding framework, and send the updated measurement data to the client in real time.

[0117] In some embodiments of the present invention, the first verification of the denoised clean data using a verification algorithm includes:

[0118] Verify the uint16 value obtained by adding each byte from the byte after the frame length to the byte before the terminator as unsigned uint8 and then taking the modulo 65536.

[0119] In some embodiments of the present invention, storing the clean data after denoising includes:

[0120] The conversion module is used to place the clean data after denoising in a cache file, and after the measurement is completed, convert the cache file into an actual file.

[0121] In some embodiments of the present invention, sending the updated measurement data to the client in real time includes:

[0122] Declare data binding relationships, and the data binding framework automatically updates data and sends the updated data to the client.

[0123] On the other hand, a real-time analysis device for measuring chemical substances in living brain is also provided, and its client comprises:

[0124] A receiving module, used for receiving measurement data sent by the server;

[0125] The data updating module is used for rendering the image of the measurement data, displaying the data in real time and updating the data by using multi-threaded off-screen rendering technology.

[0126] In some embodiments of the present invention, the image rendering of the measurement data using a multi-threaded off-screen rendering technology includes:

[0127] A division module, used to divide the rendering task into multiple sub-task blocks;

[0128] A rendering module, used to use multi-threading technology to assign the plurality of sub-task block rendering tasks to a plurality of threads to perform rendering in parallel, thereby obtaining rendering results of the plurality of threads;

[0129] The synthesis module is used to merge and splice the rendering results of the multiple threads into a display image.

[0130] In some embodiments of the present invention, the rendering of the image of the measurement data using a multi-threaded off-screen rendering technology further includes:

[0131] Create a framebuffer object for off-screen rendering and create and initialize an OpenGL context.

[0132] In some embodiments of the present invention, the parallel rendering is performed using a Direct2D rendering API.

[0133] like Figure 3 As shown, a real-time analysis system for measuring living brain chemical substances includes a long-term test and data acquisition module and a real-time data display and processing module. The present invention is a system that can be used for long-term collection of living brain chemical substances and real-time display and analysis, and adopts a modular design. According to the function, it is divided into a long-term test and data acquisition module and a real-time data display and processing module.

[0134] A large amount of data may contain a large amount of noise data or invalid data. In order to ensure the accuracy and credibility of the system data analysis, this system designs a verification algorithm (for example, the verification code: "From the frame length (excluding the frame length byte) to the byte before the terminator, each byte is accumulated as unsigned uint8 and then modulo 65536, and the uint16 value obtained is verified to ensure data accuracy."), from the frame length (excluding the frame length byte) to the byte before the terminator, each byte is accumulated as unsigned uint8 and then modulo 65536, and the uint16 value obtained is verified to ensure data accuracy.

[0135] While collecting data, the system also needs to display the collected data in real time and process the data from time to time to achieve the purpose of real-time monitoring of changes in concentrations of chemical substances in the brain.

[0136] For example, the details of monitoring the concentration changes of chemicals in the brain are as follows: imagine the brain chemicals as a variable resistor; the device applies a certain voltage, and the concentration of brain chemicals changes, which will cause the measured current signal to change; and constantly changing data will be received.

[0137] Displaying the collected data on the user interface (UI) requires coordination from multiple aspects to realize the function.

[0138] The UI interface of the system should be clear and easy to understand, so that users can quickly find key information. When the data is updated, ensure that the UI can be updated and displayed in time. This system design uses the data binding framework to declare data binding relationships (types of data binding: One-way data binding: One-way data binding means that data can only flow from the data source to the user interface. That is, when the data source is updated, these updates will be reflected in the user interface, but changes in the user interface will not affect the data source. This type of data binding is simple to understand and implement, and is common in simple data display scenarios. Two-way data binding: Two-way data binding not only allows data to flow from the data source to the user interface, but also allows changes in the user interface to be fed back to the data source. This means that if an element on the user interface is modified by the user, the corresponding data source will also be updated. Two-way data binding is particularly suitable for highly interactive applications, such as forms or editors, where user input can be reflected in the data model in real time. Technologies for implementing data binding: Desktop application development: .NET framework: WPF (Windows Presentation Technologies such as JavaFX and Swing support powerful data binding capabilities. Java: JavaFX and Swing provide data binding tools to help developers synchronize UI and data when creating desktop applications. Advantages of data binding: Reduce the amount of code: Automatically handle the synchronization of UI and data, reducing the code for manual operation of DOM or interface. Improve efficiency: The fast and real-time synchronization of data and UI improves the responsiveness and user experience of the application. Easy to maintain: The separation of data logic and interface logic makes the code more modular, easy to maintain and expand. Data binding is an important concept in modern software development, and it plays a key role in improving development efficiency and improving user experience. Correctly understanding and utilizing data binding can help developers build more powerful and flexible applications), the framework will automatically handle updates between data and interface so that changes in data can be automatically reflected in the interface. Bind the data model to the real-time data source to display and update real-time data.

[0139] Through this method and device, the following are achieved:

[0140] High temporal resolution: The real-time analysis system of living brain chemicals can capture the dynamic changes of chemicals in the brain with a temporal resolution of milliseconds;

[0141] Dynamic monitoring: Real-time analysis systems can monitor changes in concentrations of chemicals in the brain in real time, providing immediate feedback and helping researchers better understand the relationship between neural activity and behavior;

[0142] Real-time data processing: In vivo brain chemical real-time analysis systems are usually equipped with powerful data processing capabilities to quickly analyze and display data;

[0143] Multi-parameter real-time analysis: The real-time analysis system can be used with two different electrophysiological experiments, and can simultaneously monitor and analyze changes in the concentrations of multiple chemical substances; it can simultaneously monitor two (because only two experiments can be done at the same time) and analyze changes in the concentrations of multiple chemical substances (it can analyze multiple because the software can also open previous test data for processing during testing).

[0144] Long-term monitoring: The real-time analysis system of living brain chemicals can monitor for a long time, helping researchers understand long-term neural activity and behavioral patterns;

[0145] Data accumulation: Long-term testing can accumulate a large amount of data, providing rich information for subsequent in-depth analysis;

[0146] High sensitivity: Real-time analysis systems of living brain chemicals usually have higher sensitivity and can detect small changes in chemical concentrations;

[0147] Versatility: The real-time analysis system can not only monitor the changes in chemical substances, but also combine electrophysiological signals for comprehensive analysis.

[0148] In summary, it can be seen that the real-time analysis system of living brain chemicals has obvious advantages in real-time analysis, data processing, long-term testing and comprehensive performance, and can provide more comprehensive and in-depth support for neuroscience research.

[0149] In some specific embodiments, Figure 4 As shown, a real-time analysis system for measuring chemical substances in the living brain is provided. The system includes at least one processor and a memory storing instructions for implementing any one of the real-time analysis methods for measuring chemical substances in the living brain in the above technical solutions.

[0150] In some specific embodiments, a computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps in the above technical solution.

[0151] In some specific embodiments, a computer program product is provided, the computer program product includes a computer program, and when the computer program is executed by a processor, the method of implementing the steps in the above technical solution is implemented.

[0152] The embodiments and functional operations of the subject matter described in this specification may be implemented in: digital electronic circuitry, tangibly implemented computer software or firmware, computer hardware, including the structures disclosed in this specification and their structural equivalents, or a combination of more than one of the above. The embodiments of the subject matter described in this specification may be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on one or more tangible non-transitory program carriers, for execution by a data processing device or to control the operation of a data processing device.

[0153] Alternatively or additionally, the program instructions may be encoded on an artificially generated propagation signal, such as a machine-generated electrical, optical, or electromagnetic signal, which is generated to encode information for transmission to an appropriate receiver device for execution by a data processing device. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of the above devices.

[0154] A computer program (which may also be referred to or described as a program, software, software application, module, software module, script or code) may be written in any form of programming language, including compiled or interpreted languages ​​or declarative or procedural languages, and the computer program may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program may be stored in a portion of a file that stores other programs or data, for example, one or more scripts stored in the following: in a markup language document; in a single file dedicated to a related program; or in multiple collaborative files, for example, files storing one or more modules, subroutines or code portions. A computer program may be deployed to execute on one or more computers, the computers being located in one place or distributed to multiple locations and interconnected by a communication network.

[0155] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0156] Although the present invention has been described in detail above by general description, specific implementation methods and experiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A real-time analysis method for measuring chemical substances in living brain, characterized in that: The server side includes the following steps: Set the test parameters and calculate the number of cycle measurements, where the calculation formula for the number of cycle tests is: In the formula, N represents the number of cycle tests, C represents the number of turns, and n represents the bit length for storing the number of turns; Based on the number of cyclic measurements, a multi-threaded working mode is used to denoise, verify, cache and measure the collected raw data; wherein, the multi-threaded working mode is used to denoise, verify, cache and measure the collected raw data, including collecting raw data, denoising the raw data using a smoothing filter algorithm, verifying the denoised clean data for the first time using a verification algorithm, and storing the denoised clean data simultaneously; The clean data is verified for a second time using the verification algorithm to compare the data of the verification interval after the second verification with the original data of the same interval to see if they are consistent; wherein, if the data of the two are consistent, the measurement data in the data storage disk is sent to the client.

2. A real-time analysis method for measuring chemical substances in living brain according to claim 1, characterized in that: The server side also includes the following steps: The data model and the data stored in the data storage disk in real time are bound using a data binding framework, and the updated measurement data is sent to the client in real time.

3. A real-time analysis method for measuring chemical substances in living brain according to claim 1, characterized in that: The first verification of the denoised clean data using the verification algorithm includes the following steps: Verify the uint16 value obtained by adding each byte from the byte after the frame length to the byte before the terminator as unsigned uint8 and then taking the modulo 65536.

4. A real-time analysis method for measuring chemical substances in living brain according to claim 1, characterized in that: The storing of the clean data after denoising comprises the following steps: The clean data after denoising is placed in a cache file, and after the measurement is completed, the cache file is converted into an actual file.

5. A real-time analysis method for measuring chemical substances in living brain according to claim 2, characterized in that: The step of sending the updated measurement data to the client in real time comprises the following steps: Declare data binding relationships, and the data binding framework automatically updates data and automatically sends the updated data to the client.

6. A real-time analysis method for measuring chemical substances in living brain, characterized in that: The client includes the following steps: Receive measurement data sent by the server; Multi-threaded off-screen rendering technology is used to render images of the measurement data, and to display and update the data in real time.

7. A real-time analysis method for measuring chemical substances in living brain according to claim 6, characterized in that: The method of using multi-threaded off-screen rendering technology to render the image of the measurement data includes the following steps: Divide the rendering task into multiple subtask blocks; By using multi-threading technology, the rendering tasks of the plurality of sub-task blocks are assigned to a plurality of threads for parallel rendering, thereby obtaining rendering results of the plurality of threads; The rendering results of the multiple threads are combined and spliced ​​into a display image.

8. A real-time analysis method for measuring chemical substances in living brain according to claim 6, characterized in that: The image rendering of the measurement data using the multi-threaded off-screen rendering technology also includes the following steps: Create a framebuffer object for off-screen rendering and create and initialize an OpenGL context.

9. A real-time analysis method for measuring chemical substances in living brain according to claim 7, characterized in that: In the parallel rendering, Direct2D rendering API is used.

10. A real-time analysis device for measuring chemical substances in the brain of a living body, the device comprising at least one processor and a memory storing instructions, which, when executed by at least one processor, implements a real-time analysis method for measuring chemical substances in the brain of a living body as described in any one of claims 1-9.

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