Cross-platform full-automatic electrochemical luminescence analysis system

Abstract

The invention discloses a cross-platform full-automatic electrochemical luminescence analysis system, which relates to an electrochemical luminescence detection technology, and comprises: an electrochemical luminescence signal acquisition subsystem, which is used for acquiring an ECL image signal; the cloud server analysis subsystem is used for analyzing and processing the ECL image signal received by the cloud server analysis subsystem so as to obtain an ECL intensity value and a light-emitting image; the man-machine interaction subsystem is used for controlling the electrochemical luminescence signal acquisition subsystem to acquire ECL image signals and uploading the ECL image signals acquired by the electrochemical luminescence signal acquisition subsystem to the cloud server analysis subsystem; and the ECL intensity value returned by the cloud server analysis subsystem and the ECL image signal corresponding to the ECL intensity value are displayed. According to the invention, collection, processing, analysis and storage of ECL signals can be efficiently and automatically realized, and detection requirements in different application scenes can be met.

Description

Technical Field

[0001] The present invention relates to electrochemiluminescence detection technology, and more particularly to a cross-platform fully automatic electrochemiluminescence analysis system. Background Art

[0002] Electrochemiluminescence (ECL) analysis technology, with its advantages of high sensitivity, low background signal, and easy control, has been increasingly applied in fields such as biological monitoring, environmental monitoring, and medical diagnostics. It cleverly combines the dual advantages of electrochemical triggering and chemiluminescence signal readout, enabling rapid response and high-sensitivity detection. Typically, an ECL analysis system consists of multiple modules, including an acquisition module, an analysis module, and a human-computer interface module, which are often integrated to maximize overall effectiveness.

[0003] Most existing ECL analysis systems rely on embedded systems or dedicated terminals for localized analysis, a model with significant limitations. For one thing, their processing speed is relatively slow, making it difficult to meet the efficiency requirements of large-scale data detection. Furthermore, most analysis systems utilize custom applications (APPs) or embedded human-computer interaction, which not only limits system portability but also significantly increases ongoing system maintenance costs.

[0004] Currently, the operating procedures of existing ECL analysis systems are often lacking standardization, which leads to a significant impact of human factors during the operation. For example, different laboratories or operators may have differences in sample processing, reagent addition, reaction condition control, and other aspects. These differences will directly affect the accuracy and repeatability of the test results, thereby increasing the coefficient of variation of the test results, making it difficult to ensure the reliability and consistency of the test results. It is precisely because of these limitations that the application potential of existing ECL analysis systems in scenarios such as homes, communities, and primary healthcare institutions is greatly limited. In these scenarios, the professional level and operating experience of operators may vary greatly. Non-standardized operating procedures may further amplify these differences, resulting in more unstable and unreliable test results. Therefore, in order to improve the applicability and promotion of ECL analysis systems, standardized automatic detection processes are needed to reduce interference from human factors and improve the stability and consistency of test results. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to address the shortcomings of the existing technology and provide a cross-platform fully automatic electrochemiluminescence analysis system that can efficiently and automatically realize the acquisition, processing, analysis and storage of ECL signals, and can meet the detection needs in different application scenarios.

[0006] The cross-platform fully automatic electrochemiluminescence analysis system of the present invention comprises:

[0007] Electrochemiluminescence signal acquisition subsystem, used to collect ECL image signals;

[0008] A cloud server analysis subsystem, configured to analyze and process the received ECL image signal to obtain an ECL intensity value and a luminescence image;

[0009] The human-computer interaction subsystem is network-connected to the electrochemiluminescence signal acquisition subsystem and the cloud server analysis subsystem, and is used to control the electrochemiluminescence signal acquisition subsystem to acquire ECL image signals, and to upload the ECL image signals acquired by the electrochemiluminescence signal acquisition subsystem to the cloud server analysis subsystem, and to display the ECL intensity values ​​and their corresponding ECL image signals transmitted back by the cloud server analysis subsystem.

[0010] Preferably, the human-computer interaction subsystem includes a human-computer interaction communication module, a real-time preview module, a parameter control module, a data upload module, and a data display module; the real-time preview module, parameter control module, data upload module, and data display module are all electrically connected to the human-computer interaction communication module.

[0011] Preferably, the electrochemiluminescence signal acquisition subsystem includes a camera acquisition module, an electrochemical excitation module, and a signal acquisition communication module; the camera acquisition module is electrically connected to the signal acquisition communication module through the electrochemical excitation module, and the signal acquisition communication module is network-connected to the human-computer interaction communication module.

[0012] Preferably, the cloud server analysis subsystem includes a cloud server communication module and a cloud server analysis and processing module; the cloud server analysis and processing module is used to analyze and process the ECL image signal, the cloud server communication module is electrically connected to the cloud server analysis and processing module, and the cloud server communication module is network-connected to the human-computer interaction communication module.

[0013] Preferably, the cloud server analysis subsystem further includes a data storage module, and the data storage module is electrically connected to the cloud server communication module and the cloud server analysis and processing module at the same time.

[0014] Preferably, the human-computer interaction subsystem further includes a data download module, and the data download module is electrically connected to the human-computer interaction communication module.

[0015] Preferably, the ECL analysis process of the electrochemiluminescence analysis system includes the following steps:

[0016] S101: issuing a start detection instruction through the human-computer interaction subsystem to enable the electrochemiluminescence signal acquisition subsystem to execute an ECL image signal acquisition program;

[0017] S102: After receiving the start detection instruction, the electrochemiluminescence signal acquisition subsystem automatically sends a command to apply an electrochemical excitation voltage after a set delay time, so that the ECL detector starts to perform the ECL reaction of the sample and simultaneously acquires the ECL image signal;

[0018] S103: After the ECL reaction has completed the set reaction time, the acquisition of the ECL image signal is stopped, and the ECL image signal is transmitted to the cloud server analysis and processing module through the human-computer interaction subsystem for analysis and processing;

[0019] S104: After the cloud server analysis processing module completes the analysis, the cloud server analysis subsystem transmits the ECL intensity value and the corresponding luminescence image obtained by the analysis to the human-computer interaction subsystem for display.

[0020] Preferably, the steps of analyzing and processing the ECL image signal are:

[0021] S201: Create a thread pool;

[0022] S202: Utilizing multiple threads in the thread pool to simultaneously and in parallel process the ECL image signal to save the ECL image signal, extracting the ECL image signal into pictures frame by frame, and recording the number of pictures; automatically identifying luminous areas in the pictures, and cutting and saving the luminous areas in the pictures;

[0023] S203: performing noise filtering on the cut image using a median filter image algorithm, and then converting the image into grayscale;

[0024] S204: Traverse the grayscale image and accumulate the grayscale value of each pixel as the grayscale value of the image;

[0025] S205: Repeat the above steps S202 to S204 for all images to obtain the grayscale values ​​of all images;

[0026] S206: Sort the grayscale values ​​of all images by size, output the maximum grayscale value and the corresponding image as the ECL intensity value and luminescence image respectively;

[0027] S207: Archiving and storing the ECL intensity value and the luminescence image;

[0028] S208: Close the thread pool.

[0029] Preferably, the human-computer interaction subsystem is deployed on nginx.

[0030] Preferably, the cloud server analysis subsystem is packaged into a war package through javaweb and deployed on tomcat.

[0031] Beneficial effects

[0032] The advantages of the present invention are:

[0033] 1. The present invention constructs a fully automatic detection process and establishes an end-to-end closed-loop control system to achieve one-click automatic detection from signal acquisition, data transmission to cloud analysis and result feedback, thereby greatly reducing the deviation caused by manual operation.

[0034] 2. The present invention adopts cloud data analysis and deploys the data analysis module on the cloud server, making full use of its high-performance computing resources and breaking through the computing power bottleneck of traditional local processing.

[0035] 3. This invention adopts a cross-platform interactive system, and the developed open interactive interface supports multi-terminal access such as computers, tablets and mobile phones. The compatibility test covers iOS, Android, Harmony, and Windows systems, which greatly reduces development and maintenance costs and improves the versatility of the system.

[0036] 4. The data analysis and processing module uses multi-threaded algorithms for parallel analysis, further improving analysis efficiency.

[0037] 5. The data analysis and processing module uses ffmpeg, which can efficiently perform data analysis of ECL signals and improve the efficiency of data processing.

[0038] 6. The data display module outputs the results on terminal devices (such as mobile phones, tablets, computers, etc.), providing an intuitive user interaction experience.

[0039] 7. The data storage module stores data in the cloud, further reducing the storage pressure of terminal devices while ensuring the security and accessibility of experimental data. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a structural block diagram of the cross-platform fully automatic electrochemiluminescence analysis system of the present invention.

[0041] Figure 2 1 is a flow chart of the ECL analysis of the present invention.

[0042] Figure 3 It is an analysis flow chart of the cloud server analysis and processing module of the present invention.

[0043] Figure 4 It is a closed bipolar ECL chip Ru(bpy)3 2+ ECL intensity value curve at concentrations of 0.1mM, 0.5mM, 1mM, 2.5mM, and 5mM.

[0044] Figure 5 This is a curve of ECL intensity values ​​when the TPA concentrations on the closed bipolar ECL chip are 0.1mM, 0.5mM, 1mM, 2.5mM, and 5mM.

[0045] Figure 6 This is a curve of ECL intensity values ​​when the H2O2 concentration is 0.1mM, 0.5mM, 1mM, 2.5mM, 5mM, and 10mM on a closed bipolar ECL chip.

[0046] Figure 7 This is a graph showing the relationship between luteinizing hormone (LH) concentration and ECL intensity value during closed bipolar ECL chip immunoassay. DETAILED DESCRIPTION

[0047] The present invention will be further described below in conjunction with the embodiments, but this does not constitute any limitation to the present invention. Any limited number of modifications made by anyone within the scope of the claims of the present invention are still within the scope of the claims of the present invention.

[0048] See Figure 1 The present invention provides a cross-platform, fully automatic electrochemiluminescence analysis system, comprising an electrochemiluminescence signal acquisition subsystem 1, a human-computer interaction subsystem 2, and a cloud server analysis subsystem 3. The electrochemiluminescence signal acquisition subsystem 1 includes a camera acquisition module 11, an electrochemical excitation module 12, and a signal acquisition and communication module 13; the human-computer interaction subsystem 2 includes a human-computer interaction and communication module 21, a real-time preview module 22, a parameter control module 23, a data upload module 24, a data display module 25, and a data download module 26; and the cloud service analysis subsystem 3 includes a cloud server communication module 31, a cloud server analysis and processing module 32, and a data storage module 33.

[0049] The electrochemiluminescence signal acquisition subsystem 1 is connected to the human-computer interaction subsystem 2 through a network. Specifically, the signal acquisition and communication module 13 is connected to the human-computer interaction communication module 21 through a network. The human-computer interaction communication module 21 is also electrically connected to the real-time preview module 22 and the parameter control module 23. The electrochemical excitation module 12 is also electrically connected to the camera acquisition module 11 and the signal acquisition and communication module 13.

[0050] In the electrochemiluminescence signal acquisition subsystem 1, the camera acquisition module 11 transmits the ECL image signal to the signal acquisition and communication module 13 via the electrochemical excitation module 12. The signal acquisition and communication module 13 transmits the ECL image signal to the real-time preview module 22 via the human-computer interaction communication module 21. The parameter control module 23 transmits the camera parameter control signal and the electrochemical excitation voltage parameter control signal to the signal acquisition and communication module 13 via the human-computer interaction communication module 21.

[0051] The human-computer interaction subsystem 2 is connected to the cloud server analysis subsystem 3 through a network. Specifically, the human-computer interaction communication module 21 is connected to the cloud service communication module 31 through a network. The data upload module 24, data display module 25, and data download module 26 are all electrically connected to the human-computer interaction communication module 21. The cloud service communication module 31 is connected to the cloud server analysis and processing module 32 through a network. The data storage module 33 is electrically connected to both the cloud service communication module 31 and the cloud server analysis and processing module 32.

[0052] In the human-computer interaction subsystem 2, the parameter control module 23 receives the specific parameter signal input by the user through the keyboard or the like and transmits the signal to the human-computer interaction communication module 21, and then the signal is transmitted to the signal acquisition communication module 13; the real-time preview module 22 receives the ECL image signal transmitted in real time by the signal acquisition communication module 13 through the human-computer interaction communication module 21; the data upload module 24 uploads the ECL image signal to the cloud server analysis subsystem 3 through the human-computer interaction communication module 21; the data display module 25 is used to display the luminescence image processed by the cloud server analysis subsystem 3 and its corresponding ECL intensity value; the data download module 26 is used to download the required luminescence image and its corresponding ECL intensity value from the data storage module 33.

[0053] In the cloud server analysis subsystem 3, the cloud server communication module 31 receives the ECL image signal transmitted through the human-computer interaction communication module 21; the cloud server analysis and processing module 32 analyzes the ECL image signal transmitted by the cloud server communication module 31; the data storage module 33 stores the luminescent image and its corresponding ECL intensity value, that is, the analysis result of the cloud server analysis and processing module 32.

[0054] Furthermore, the signal acquisition communication module 13, the human-computer interaction communication module 21, and the cloud server communication module 31 all use wireless networks for data transmission, such as 4G / 5G networks, WiFi networks, Bluetooth networks, etc.

[0055] Furthermore, the parameter control module 23 can adjust the camera's contrast, brightness, saturation, exposure time, white balance, sharpness, gain, gamma value and other parameters as well as the electrochemical excitation voltage parameters.

[0056] Furthermore, the real-time preview module 22 can preview the ECL image in real time and control it through the control buttons on the interactive interface of the human-computer interaction subsystem 2;

[0057] Furthermore, the interactive interface of the human-computer interaction subsystem 2 can be displayed on a variety of terminal devices (such as mobile phones, tablets, computers, etc.); the interactive interface of the human-computer interaction subsystem 2 is highly adaptable and compatible with different terminal devices.

[0058] Furthermore, the cloud server analysis subsystem 3 is implemented by Java, wherein the cloud server analysis processing module 32 is implemented by the FFmpeg data processing program.

[0059] Furthermore, the cloud server analysis subsystem 3 is packaged into a war package through javaweb and deployed on tomcat.

[0060] Furthermore, the real-time preview module 22 , the parameter control module 23 , the data display module 25 and the data download module 26 are implemented by writing programs based on HTML, CSS and JavaScript, and the luminous image can be previewed in real time on the interactive interface of the human-computer interaction subsystem 2 .

[0061] Furthermore, the human-computer interaction subsystem 2 is deployed on nginx;

[0062] Furthermore, data storage is performed on a cloud server, where the video data collected by the camera acquisition module 11 and the luminescent image and its corresponding ECL intensity value obtained by the cloud server system analysis and processing module 32 are stored on the cloud server. These data can be downloaded to different terminal devices via the Internet.

[0063] like Figure 2 As shown, the ECL analysis process based on the above-mentioned cross-platform fully automatic electrochemiluminescence analysis system is as follows:

[0064] S101: The user clicks the "Start Detection" button on the interactive interface of the human-computer interaction subsystem 2, which automatically starts recording the ECL image signal (video);

[0065] S102: After a few seconds (e.g., 2 seconds), a command to apply an electrochemical excitation voltage is automatically sent;

[0066] S103: After the ECL reacts for a period of time, the system will automatically stop recording, and the recorded video will be transmitted to the cloud server analysis and processing module 32 for analysis and processing;

[0067] S104: After the cloud server analysis processing module 32 completes the analysis, the luminescence image and its corresponding ECL intensity value obtained by analysis are transmitted to the data display module 25 via the cloud server communication module 31 and the human-computer interaction communication module 21;

[0068] S105: The fully automatic ECL analysis ends.

[0069] Furthermore, if Figure 3 As shown, the analysis process of the cloud server analysis and processing module 32 is as follows:

[0070] S201: Create a thread pool;

[0071] S202: Utilize multiple threads in the thread pool to process in parallel to save the uploaded ECL image signal (i.e., recorded video), extract it frame by frame into pictures, and record the number of pictures; automatically identify the luminous area in the picture, cut out the luminous area in the picture, and save it;

[0072] S203: performing noise filtering on the cut image using a median filter image algorithm, and then converting the image into grayscale;

[0073] S204: Traverse the grayscale image and accumulate the grayscale value of each pixel as the grayscale value of the image;

[0074] S205: Repeat the above steps S202 to S204 for all images to obtain the grayscale values ​​of all images. These operations are completed in parallel through the thread pool, and the high-performance computing resources of the cloud server are used to efficiently complete the parallel analysis.

[0075] S206: sorting the grayscale values ​​of all images by size, outputting the maximum grayscale value and the corresponding image, thereby realizing data analysis of the ECL signal;

[0076] S207: Archiving and storing the analysis results.

[0077] S208: Close the thread pool.

[0078] The following is an example based on the specific application of the above system:

[0079] Application Example 1

[0080] The cross-platform fully automatic ECL analysis system in this example is based on Ru(bpy)3 2+ / TPA system, detecting Ru(bpy)3 by closed bipolar ECL chip 2+ .

[0081] 1) First, use PBS to prepare 5mM TPA solution, and then use purified water to prepare 0.1mM, 0.5mM, 1mM, 2.5mM, and 5mM Ru(bpy)3 2+ solution, and the configured Ru(bpy)3 2+ The solution was mixed with 5 mM TPA solution in equal volumes to obtain the test solution.

[0082] 2) Place the closed bipolar ECL chip into the fully automated ECL analysis system.

[0083] 3) Open the human-computer interaction subsystem 2 interface and set the camera brightness to 120, contrast to 96, saturation to 180, white balance to 4650, sharpness to 120, and exposure time to 2500.

[0084] 4) Analyze according to the above ECL analysis process (waiting time is 2s, electrochemical excitation voltage parameter is 13V), the analysis results are as follows Figure 4 shown.

[0085] from Figure 4 It can be seen that the fully automatic ECL analysis system of the present invention is used, and as Ru(bpy)3 2+ As the concentration increases, the ECL intensity value also increases accordingly, and Ru(bpy)3 2+ There is a good linear relationship between the concentration and the ECL intensity value. The linear fitting equation is Y=10.5899X+12.574, and the correlation coefficient is R 2 is 0.9975 (n=5). Therefore, the cross-platform fully automatic ECL analysis system based on wireless network communication and cloud server of the present invention can be applied to Ru(bpy)3 2+ / TPA system for quantitative detection of Ru(bpy)3 2+ .

[0086] Application Example 2

[0087] This example of a cross-platform fully automated ECL analysis system based on Ru(bpy)3 2+ / TPA system, TPA is detected by closed bipolar ECL chip.

[0088] 1) First use PBS to prepare 5mM Ru(bpy)3 2+ solution, and then use purified water to prepare 0.1mM, 0.5mM, 1mM, 2.5mM, and 5mM TPA solutions, and mix the prepared TPA solutions with 5mM Ru(bpy)3 2+ Equal volumes were mixed to obtain the test solution.

[0089] 2) Place the closed bipolar ECL chip into the fully automated ECL analysis system.

[0090] 3) Open the human-computer interaction subsystem 2 interface and set the camera brightness to 120, contrast to 96, saturation to 180, white balance to 4650, sharpness to 120, and exposure time to 2500.

[0091] 4) Analyze according to the above ECL analysis process (waiting time is 2s, electrochemical excitation voltage parameter is 13V), the analysis results are as follows Figure 5 shown.

[0092] from Figure 5It can be seen that, using the fully automatic ECL analysis system of the present invention, as the TPA concentration increases, the ECL intensity value also increases accordingly, and there is a good linear relationship between the TPA concentration and the ECL intensity value. The linear fitting equation is Y=1.381X+1.779, and the correlation coefficient R 2 is 0.9959 (n=5). Therefore, the cross-platform fully automatic ECL analysis system based on wireless network communication and cloud server of the present invention can be applied to Ru(bpy)3 2+ / TPA system for quantitative detection of TPA.

[0093] Application Example 3

[0094] The cross-platform fully automated ECL analysis system in this example is based on a luminol / hydrogen peroxide (H2O2) detection system and detects H2O2 using a closed bipolar ECL chip.

[0095] 1) First, use CBS (carbonate buffer) to prepare 5mM luminol solution, then use purified water to prepare 0.1mM, 0.5mM, 1mM, 2.5mM, 5mM, and 10mM H2O2 solutions. Then, mix equal volumes of the prepared H2O2 solution and 5mM luminol solution to obtain the test solution.

[0096] 2) Place the closed bipolar ECL chip into the fully automated ECL analysis system.

[0097] 3) Open the human-computer interaction subsystem 2 interface and set the camera brightness to 120, contrast to 96, saturation to 180, white balance to 4650, sharpness to 120, and exposure time to 2500.

[0098] 4) Analyze according to the above-mentioned fully automatic ECL analysis process (waiting time is 2s, electrochemical excitation voltage parameter is 13V), and the analysis results are as follows Figure 6 shown.

[0099] from Figure 6 It can be seen that with the full-automatic ECL analysis system of the present invention, as the H2O2 concentration increases, the ECL intensity value also increases accordingly, and there is a good linear relationship between the H2O2 concentration and the ECL intensity value. The linear fitting equation is Y=0.377X+0.405, and the correlation coefficient R 2 The cross-platform fully automatic ECL analysis system based on wireless network communication and cloud server of the present invention can be applied to the luminol / H2O2 system to quantitatively detect H2O2.

[0100] Application Example 4

[0101] In this example, immunoassay was performed using a cross-platform fully automated ECL analysis system. The immunoassay target was LH, and a closed bipolar ECL chip was used.

[0102] 1) Preparation of closed bipolar ECL immunochip An existing closed bipolar ECL immunochip was used, and its preparation process was similar to that of invention patent ZL202410829788.0.

[0103] 2) Place the prepared closed bipolar ECL chip into a fully automatic ECL analysis system.

[0104] 3) Open the human-computer interaction subsystem 2 interface and set the camera brightness to 120, contrast to 96, saturation to 180, white balance to 4650, sharpness to 120, and exposure time to 2500.

[0105] 4) Analyze according to the above-mentioned fully automatic ECL analysis process (waiting time is 2s, electrochemical excitation voltage parameter is 13V), and the analysis results are as follows Figure 7 shown.

[0106] from Figure 7 It can be seen that using the cross-platform fully automatic ECL analysis system based on wireless network communication and cloud server of the present invention, as the LH concentration increases, the ratio of the ECL intensity value on the chip T line to the ECL intensity value on the C line (i.e., T / C) also increases accordingly, and there is a good linear relationship between the logarithm of LH concentration and T / C. The linear fitting equation is Y=1.194X+0.285, and the correlation coefficient R 2 The cross-platform fully automatic ECL analysis system of the present invention can be applied to the ECL immunoassay of LH, and can also be applied to the immunoassay of biomarkers of other diseases and other physiological activities.

[0107] The above is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present invention. These modifications and improvements will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A cross-platform fully automatic electrochemiluminescence analysis system, characterized in that: include: An electrochemiluminescence signal acquisition subsystem (1), for acquiring ECL image signals; A cloud server analysis subsystem (3) is used to analyze and process the received ECL image signal to obtain an ECL intensity value and a luminescence image; The human-computer interaction subsystem (2) is simultaneously connected to the electrochemiluminescence signal acquisition subsystem (1) and the cloud server analysis subsystem (3) through a network, and is used to control the electrochemiluminescence signal acquisition subsystem (1) to acquire ECL image signals, and to upload the ECL image signals acquired by the electrochemiluminescence signal acquisition subsystem (1) to the cloud server analysis subsystem (3), and to display the ECL intensity value and the corresponding ECL image signal transmitted back by the cloud server analysis subsystem (3).

2. A cross-platform fully automatic electrochemiluminescence analysis system according to claim 1, characterized in that: The human-computer interaction subsystem (2) comprises a human-computer interaction communication module (21), a real-time preview module (22), a parameter control module (23), a data upload module (24), and a data display module (25); the real-time preview module (22), the parameter control module (23), the data upload module (24), and the data display module (25) are all electrically connected to the human-computer interaction communication module (21).

3. A cross-platform fully automatic electrochemiluminescence analysis system according to claim 2, characterized in that: The electrochemiluminescence signal acquisition subsystem (1) comprises a camera acquisition module (11), an electrochemical excitation module (12), and a signal acquisition communication module (13); the camera acquisition module (11) is electrically connected to the signal acquisition communication module (13) via the electrochemical excitation module (12), and the signal acquisition communication module (13) is network-connected to the human-computer interaction communication module (21).

4. A cross-platform fully automatic electrochemiluminescence analysis system according to claim 2, characterized in that: The cloud server analysis subsystem (3) comprises a cloud server communication module (31) and a cloud server analysis and processing module (32); the cloud server analysis and processing module (32) is used to analyze and process ECL image signals, the cloud server communication module (31) is electrically connected to the cloud server analysis and processing module (32), and the cloud server communication module (31) is network-connected to the human-computer interaction communication module (21).

5. A cross-platform fully automatic electrochemiluminescence analysis system according to claim 4, characterized in that: The cloud server analysis subsystem (3) further includes a data storage module (33), and the data storage module (33) is electrically connected to the cloud server communication module (31) and the cloud server analysis and processing module (32).

6. A cross-platform fully automatic electrochemiluminescence analysis system according to claim 5, characterized in that: The human-computer interaction subsystem (2) further includes a data download module (26), and the data download module (26) is electrically connected to the human-computer interaction communication module (21).

7. A cross-platform fully automatic electrochemiluminescence analysis system according to claim 4, characterized in that: The ECL analysis process of the electrochemiluminescence analysis system includes the following steps: S101: issuing a start detection instruction through the human-computer interaction subsystem (2) to enable the electrochemiluminescence signal acquisition subsystem (1) to execute an ECL image signal acquisition program; S102: After receiving the start detection instruction, the electrochemiluminescence signal acquisition subsystem (1) automatically sends a command to apply an electrochemical excitation voltage after a set delay time, so that the ECL detector starts to perform the ECL reaction of the sample and collects the ECL image signal at the same time; S103: After the ECL reaction reaches the set reaction time, the collection of the ECL image signal is stopped, and the ECL image signal is transmitted to the cloud server analysis and processing module (32) through the human-computer interaction subsystem (2) for analysis and processing; S104: After the cloud server analysis processing module (32) completes the analysis, the cloud server analysis subsystem (3) transmits the ECL intensity value obtained from the analysis and its corresponding luminescence image to the human-computer interaction subsystem (2) for display.

8. A cross-platform fully automatic electrochemiluminescence analysis system according to claim 1, 4 or 7, characterized in that: The steps of analyzing and processing the ECL image signal are as follows: S201: Create a thread pool; S202: Utilizing multiple threads in the thread pool to simultaneously and in parallel process the ECL image signal to save the ECL image signal, extracting the ECL image signal into pictures frame by frame, and recording the number of pictures; automatically identifying luminous areas in the pictures, and cutting and saving the luminous areas in the pictures; S203: performing noise filtering on the cut image using a median filter image algorithm, and then converting the image into grayscale; S204: Traverse the grayscale image and accumulate the grayscale value of each pixel as the grayscale value of the image; S205: Repeat the above steps S202 to S204 for all images to obtain the grayscale values ​​of all images; S206: Sort the grayscale values ​​of all images by size, output the maximum grayscale value and the corresponding image as the ECL intensity value and luminescence image respectively; S207: Archiving and storing the ECL intensity value and the luminescence image; S208: Close the thread pool.

9. The cross-platform fully automatic electrochemiluminescence analysis system according to claim 1, characterized in that: The human-computer interaction subsystem (2) is deployed on nginx.

10. The cross-platform fully automatic electrochemiluminescence analysis system according to claim 1, characterized in that: The cloud server analysis subsystem (3) is packaged into a war package through javaweb and deployed on tomcat.

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