Automatic device of rapid gas marker detection array

Abstract

The invention discloses an automatic device of a rapid gas marker detection array. The system comprises a detection array integrated with eight gas sensor modules and used for synchronously detecting eight gas markers in a sample gas mass in real time; the data acquisition unit is used for acquiring analog signals output by the sensor detection array; and the processing display unit is used for receiving the analog signals output by the detection array, storing the analog signals to a local database, performing feature recognition and analysis on the data through a machine learning model, generating effective data and displaying the effective data on a user interaction interface. According to the invention, a detection array covering eight important gas biomarkers is constructed, and an automatic gas inlet, data acquisition and storage processing module matched with detection is created, so that rapid, synchronous and automatic detection of the relative concentration level of the gas marker array in a sample gas mass can be realized.

Description

Technical Field

[0001] This invention relates to an automated device for a rapid gas marker detection array. Background Technology

[0002] Animal exhaled air contains various endogenous volatile organic compounds (VOCs) and inorganic gases, the levels of which are directly affected by various metabolic processes and levels in the body, thus serving as a basis for assessing health status and identifying external stresses. When an animal's health is abnormal, such as due to disease or adverse environmental factors, excessive oxidative stress and inflammatory responses occur, leading to cell structure damage, altered metabolic processes, and changes in the levels of gaseous biomarkers. The driving force behind VOC production is many systemic or organ-specific lipid peroxidation reactions triggered by oxidative stress. Oxygen (O2) and carbon dioxide (CO2) are gases closely related to energy metabolism in the body. Nitric oxide (NO) and carbon monoxide (CO) are typical gaseous biomarkers of lung and airway inflammation and oxidative stress. Hydrogen sulfide (H2S) interacts with NO and CO in lung tissue through regulatory mechanisms, and participates in multiple functions in the liver, including glucose and lipid metabolism, cell differentiation, and regulation of oxidative stress. Ammonia (NH3) is associated with urea and protein metabolism in animals. Hydrogen peroxide (H2O2) is related to the level of reactive oxygen species in the body. Volatile substances produced in situ in the lungs and respiratory tract tissues can be directly expelled with exhaled air, while volatile substances produced by other organs or tissues in the body are carried to the lungs by the circulatory system and released into exhaled air through rapid exchange of substances between blood and gas.

[0003] Therefore, detecting exhaled gas biomarkers can non-invasively reflect multidimensional biochemical processes in animals, indicating normal or disordered metabolic states, and thus indicating potential abnormal health conditions. However, current methods for detecting exhaled gas biomarkers face numerous technical barriers, including high equipment costs, difficult sample collection, slow sample analysis times, and high requirements for subject operation. Furthermore, a technology capable of simultaneously, rapidly, and automatically detecting multiple exhaled gas biomarker arrays is lacking. These issues hinder scientific research on exhaled gas biomarker detection, such as toxicological studies based on experimental animals like rats and epidemiological studies based on large-scale cohorts, and also impede the commercial application of this non-invasive health detection technology. Summary of the Invention

[0004] The purpose of this invention is to provide an automated device for rapid gas marker detection arrays.

[0005] This invention utilizes the release characteristics and change patterns of eight key gaseous biomarkers in target sample air masses (such as animal exhaled air) that are automatically collected and detected in real time online. This system can identify the health status of an organism and the environmental stresses it is subjected to. It is particularly suitable for convenient and non-invasive reflection of possible discomfort in the body, such as metabolic disorders or chronic inflammation. It has high application value for scientific research and the promotion of individual monitoring.

[0006] The present invention provides a detection unit, a data acquisition unit and a processing and display unit connected in sequence, all disposed within the same sealed housing;

[0007] The detection unit includes a power fan, a detection pipeline, a carbon dioxide sensor, an oxygen sensor, a carbon monoxide sensor, a hydrogen peroxide sensor, a hydrogen sulfide sensor, a VOC sensor, a nitric oxide sensor, an ammonia sensor, and a detection inlet. The detection inlet is located at the inlet of the detection pipeline, penetrating the housing and communicating with the environment. The power fan is located outside the detection pipeline and is used to automatically pump the sample gas mass through the detection inlet into the detection pipeline. The carbon dioxide sensor, oxygen sensor, carbon monoxide sensor, hydrogen peroxide sensor, hydrogen sulfide sensor, VOC sensor, nitric oxide sensor, and ammonia sensor are installed inside the detection pipeline to detect the relative concentration of each gaseous marker in the sample gas mass passing through the detection pipeline, generate electrical signals, and transmit them to the data acquisition unit.

[0008] The data acquisition unit includes a data acquisition board, which is used to acquire the analog signals output by each sensor in the detection unit, and send all signals to the processing and display unit through the data acquisition board.

[0009] The processing and display unit includes a host and a screen, and is used to receive data from each sensor uploaded by the data acquisition unit, process the data through a machine learning model mounted on the host, and display the data on the screen.

[0010] The automated device for the rapid gas marker detection array described above further includes a filtration unit. The filtration unit is located at the outlet of the detection pipe in the detection unit and is used to filter the sample gas cloud discharged from the detection pipe to avoid secondary contamination or transmission risks.

[0011] In the aforementioned automated device for rapid gas marker detection array, the filtration unit includes a filter fan, a filter membrane, and a pressure cap. The filter membrane is fixed to the outlet of the filter fan by the pressure cap, and the filter fan is connected to the outlet of the detection pipe.

[0012] In this invention, the filter fan adopts a high-efficiency and low-noise design, and the filter membrane is made of high-efficiency nanomaterials to ensure the filtration effect.

[0013] In the aforementioned automated device for rapid gas marker detection array, the power fan is frequency-controlled and used to automatically pump sample gas clouds into the detection pipeline for detection.

[0014] All sensors use high-precision sensor modules with a measurement range of 0–10 ppm and a resolution of 1 ppb.

[0015] In this invention, the host computer uses a high-performance processor;

[0016] The screen is a high-resolution touchscreen to provide an intuitive user interface.

[0017] In this invention, the data acquisition board uses a high-speed analog-to-digital converter to improve the data acquisition rate and accuracy.

[0018] In the aforementioned automated apparatus for rapid gas marker detection arrays, the processing and display unit is configured or programmed to perform the following steps:

[0019] Receive signal data from the data acquisition unit for the concentration levels of up to eight gaseous markers;

[0020] The signal data is processed by subtracting background values ​​to obtain valid data.

[0021] The effective data is used to generate a time-series dataset of the concentration levels of each gas marker corresponding to the detection time;

[0022] The time series dataset is input into the analysis software on the host computer, automatically stored, and then used for feature recognition and discrimination analysis through three artificial intelligence machine learning models: support vector machine, random forest, and gradient boosting machine. It is then incorporated into a real-time updated gas biomarker array database to construct an animal health status discrimination model.

[0023] In this invention, VOCs, hydrogen peroxide, carbon monoxide, and nitric oxide are related to the level of oxidative stress in organisms; carbon monoxide, nitric oxide, and hydrogen sulfide are related to the inflammatory response in organisms; and oxygen, carbon dioxide, and ammonia are related to the level of energy metabolism in organisms.

[0024] The beneficial effects of this invention are:

[0025] (1) This invention integrates multiple gas sensors and an automatic air intake detection device, which can simultaneously perform automatic, rapid, real-time and non-invasive detection of the release characteristics and change patterns of eight key gaseous biomarkers in sample air masses (such as the exhaled air of an animal), thereby providing users and researchers with multi-dimensional health data.

[0026] (2) Compared with existing gas marker detection methods on the market, this invention does not require pretreatment operations such as concentration and enrichment of sample air masses, nor does it require users to set detection and analysis programs for the instrument. Instead, it adopts an automatic air intake method to directly detect sample air masses, thus having the characteristics of being simple, fast, and non-invasive. Exhaled air detection and analysis can be completed in 2-3 minutes, which can provide users and researchers with high time resolution health information, which is conducive to the development of large-scale experimental animal toxicology research and epidemiological cohort studies.

[0027] (3) Compared with existing exhaled breath detection instruments and equipment on the market, the sensor array, automatic air intake detection device and data acquisition, storage and display module constructed in this invention have low cost, thereby reducing the economic cost required for gas marker detection and facilitating large-scale research and commercial application.

[0028] (4) The invention is uniquely equipped with a filter unit for filtering the sample gas cloud discharged from the detection pipeline, which can effectively avoid the risk of secondary pollution or transmission caused by the discharge of the sample gas cloud after the detection is completed.

[0029] (5) The artificial intelligence machine learning discriminant analysis model paired with this invention is based on a large sample size. It can identify the characteristics and subtle differences in the levels of eight exhaled gas biomarkers, match the characteristic data of different types of users, and automatically update and expand the sample database with each test, so that the prediction model has the ability to identify the category of health effects and assess the degree of health effects. Attached Figure Description

[0030] Figure 1 This invention relates to an automated device for a rapid gas marker detection array.

[0031] Figure 2 This is the result of an application test in a large-scale population cohort epidemiological scientific study, as described in this embodiment of the invention.

[0032] The markings in the diagram are as follows:

[0033] 1. Pressure cap; 2. Filter membrane; 3. Filter fan; 4. Power fan; 5. Detection pipe; 6. Carbon dioxide sensor; 7. Oxygen sensor; 8. Carbon monoxide sensor; 9. Hydrogen peroxide sensor; 10. Detection inlet; 11. Hydrogen sulfide sensor; 12. VOC sensor; 13. Nitric oxide sensor; 14. Ammonia sensor; 15. Housing. Detailed Implementation

[0034] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0035] Unless otherwise specified, all materials and reagents used in the following examples are commercially available.

[0036] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0037] In various scientific studies requiring the detection of indicators of an organism's health status, such as toxicology studies based on laboratory animals like rats and epidemiological studies conducted in cohorts, exhaled breath gas biomarker detection offers significant advantages as a non-invasive method. However, a rapid, low-cost, easy-to-use instrument technology capable of real-time, simultaneous detection of multiple gas biomarkers is still lacking. This invention provides an automated device for rapidly and automatically detecting eight key gaseous biomarkers in a sample air mass. This invention uses an automatic air intake method for air mass collection and sample introduction, eliminating the need for sample pretreatment. Instead, the air mass is directly transmitted to a sensor array for simultaneous detection, and real-time output of the relative concentration signals of each gas biomarker is provided. This provides data on the release characteristics and change patterns of the eight gaseous biomarkers, which are then transmitted in real-time to an onboard computer, stored in a machine learning database, and used to construct an automatically updated discriminant analysis model. This method can be used for laboratory animal toxicology studies and large-scale cohort studies in scientific research, and can also be commercially promoted for individual health monitoring of vulnerable groups.

[0038] like Figure 1 The diagram shows an automated device for the rapid gas marker detection array of the present invention. It includes a filtration unit, a detection unit, a data acquisition unit, and a processing and display unit. All three units are housed within the same sealed housing. The specific structure includes: a pressure cap 1; a filter membrane 2; a filter fan 3; a power fan 4; a detection pipe 5; a carbon dioxide sensor 6; an oxygen sensor 7; a carbon monoxide sensor 8; a hydrogen peroxide sensor 9; a hydrogen sulfide sensor 11; a VOC sensor 12; a nitrogen monoxide sensor 13; a detection inlet 10; an ammonia sensor 14; a main unit; a screen; and a data acquisition board.

[0039] Furthermore, the pressure cap 1, filter fan 3, and filter membrane 2 constitute a filtration unit, located at the rear end of the detection unit. They are used to filter the sample gas mass discharged from the detection pipe 5, preventing secondary contamination or transmission risks. The pressure cap 1 secures the filter membrane 2 to the outlet end of the filter fan 3, which is connected to the outlet of the detection pipe 5. The filter fan 3 extracts the gas mass after detection from the detection pipe 5 and discharges it into the environment. The filter membrane 2 uses highly efficient nanomaterials to filter particulate matter, bacteria, viruses, etc., from the discharged gas mass, ensuring the exhaust is non-toxic and harmless. The pressure cap 1 secures the filter membrane 2 to the outlet end of the filter fan 3.

[0040] Furthermore, the power fan 4, detection pipe 5, carbon dioxide sensor 6, oxygen sensor 7, carbon monoxide sensor 8, hydrogen peroxide sensor 9, hydrogen sulfide sensor 11, VOC sensor 12, nitric oxide sensor 13, ammonia sensor 14, and detection inlet 10 belong to the detection unit and are located at the front end of the filter unit. The detection inlet 10 is located at the inlet of the detection pipe 5, penetrating the housing 15 and communicating with the environment; the power fan 4 is located outside the detection pipe 5. The power fan 4 uses frequency conversion control to automatically pump the sample gas mass through the detection inlet 10 into the detection pipe 5. The carbon dioxide sensor 6, oxygen sensor 7, carbon monoxide sensor 8, hydrogen peroxide sensor 9, hydrogen sulfide sensor 11, VOC sensor 12, nitric oxide sensor 13, and ammonia sensor 14 employ high-precision sensor modules to ensure detection accuracy. They are used to detect the relative concentrations of various gaseous markers (i.e., carbon dioxide, oxygen, carbon monoxide, hydrogen peroxide, sulfur dioxide, VOC, nitric oxide, and ammonia) in the gas mass within the detection pipeline, generating electrical signals and transmitting them to the data acquisition unit.

[0041] Furthermore, the data acquisition board belongs to the data acquisition unit and is located at the front end of the processing and display unit. The data acquisition board adopts a high-speed analog-to-digital converter, which has high data acquisition rate and accuracy. It is used to acquire the analog signals output by carbon dioxide sensor 6, oxygen sensor 7, carbon monoxide sensor 13, hydrogen peroxide sensor 9, hydrogen sulfide sensor 11, VOC sensor 12, nitric oxide sensor 13, and ammonia sensor 14, and send all signals to the processing and display unit.

[0042] Furthermore, the host and screen belong to the processing and display unit, which is located at the back end of the data acquisition unit. The host is a high-performance processor used to receive analog signal data from each sensor uploaded by the data acquisition board, then store the data in a local database, and perform feature recognition and discrimination analysis on the data through the machine learning model on the host, finally generating valid data and displaying it on the screen; the screen is a high-resolution touch screen used to display the gas marker detection array data and provide a user interface for instrument operation.

[0043] Example

[0044] Application testing:

[0045] The system involved in this invention was applied and tested in a large-scale population cohort-based epidemiological study. Using the automated device of the rapid gas biomarker detection array described in Example 1 of this invention, and in collaboration with the Chaoyang District Center for Disease Control and Prevention in Beijing, Beijing Ditan Hospital affiliated with Capital Medical University, Shanghai Public Health Clinical Center, and Jiangsu Provincial Center for Disease Control and Prevention, data on eight gas biomarkers in the exhaled breath of different population groups were collected in Beijing, Shanghai, and Nanjing, Jiangsu Province. In field application, this invention achieved automated collection of exhaled breath samples, rapid synchronous detection by the sensor array, local data storage, and real-time display. It helped researchers quickly and conveniently complete the entire automated process from sampling and detection to data analysis, establishing a large-scale database of relative concentration levels of exhaled gas biomarkers in healthy individuals and patients with various diseases. The results are as follows: Figure 2 As shown, during testing of the automated device for the rapid gas marker detection array of this invention, a comparison was made of the relative concentrations of carbon monoxide (CO), carbon dioxide (CO2), hydrogen peroxide (H2O2), hydrogen sulfide (H2S), ammonia (NH3), nitric oxide (NO), oxygen (O2), and volatile organic compounds (VOCs) in exhaled breath samples from 83 healthy individuals and 194 patients with COVID-19. Figure 2 Data shows that, compared with healthy individuals, the relative concentrations of various gaseous biomarkers in the exhaled breath of COVID-19 patients are significantly increased or decreased. This indicates that COVID-19 infection triggers various metabolic disorders, oxidative inflammation, and inflammatory responses in the body, thus providing researchers with multi-dimensional health information. This has high application value in promoting scientific understanding of the health hazards and physiological mechanisms of various diseases, including COVID-19.

Claims

1. An automated device for detecting rapid gas marker arrays, characterized in that, The detection unit, data acquisition unit, and processing and display unit, which are connected in sequence, are all housed in the same sealed housing. The detection unit includes a power fan, a detection pipeline, a carbon dioxide sensor, an oxygen sensor, a carbon monoxide sensor, a hydrogen peroxide sensor, a hydrogen sulfide sensor, a VOC sensor, a nitric oxide sensor, an ammonia sensor, and a detection inlet. The detection inlet is located at the inlet of the detection pipeline, penetrating the housing and communicating with the environment. The power fan is located outside the detection pipeline and is used to automatically pump the sample gas mass through the detection inlet into the detection pipeline. The carbon dioxide sensor, oxygen sensor, carbon monoxide sensor, hydrogen peroxide sensor, hydrogen sulfide sensor, VOC sensor, nitric oxide sensor, and ammonia sensor are installed inside the detection pipeline to detect the relative concentration of each gaseous marker in the sample gas mass passing through the detection pipeline, generate electrical signals, and transmit them to the data acquisition unit. The data acquisition unit includes a data acquisition board, which is used to acquire the analog signals output by each sensor in the detection unit, and send all signals to the processing and display unit through the data acquisition board. The processing and display unit includes a host and a screen, and is used to receive data from each sensor uploaded by the data acquisition unit, process the data through a machine learning model mounted on the host, and display the data on the screen.

2. The automated device for rapid gas marker detection array according to claim 1, characterized in that, The automated device of the rapid gas marker detection array also includes a filtration unit, which is disposed at the outlet of the detection pipe in the detection unit and is used to filter the sample gas cloud discharged from the detection pipe.

3. The automated device for rapid gas marker detection array according to claim 1 or 2, characterized in that, The filtration unit includes a filter fan, a filter membrane, and a pressure cap. The filter membrane is fixed to the air outlet of the filter fan by the pressure cap. The filter fan is connected to the outlet of the detection pipe.

4. The automated apparatus for a rapid gas marker detection array according to any one of claims 1-3, characterized in that, The power fan is controlled by a frequency converter and is used to automatically pump the sample air mass into the detection pipeline for detection. All sensors use high-precision sensor modules with a measurement range of 0–10 ppm and a resolution of 1 ppb.

5. The automated apparatus for a rapid gas marker detection array according to any one of claims 1-4, characterized in that, The processing display unit is configured or programmed to perform the following steps: Receive signal data from the data acquisition unit for the concentration levels of up to eight gaseous markers; The signal data is processed by subtracting background values ​​to obtain valid data. The effective data is used to generate a time-series dataset of the concentration levels of each gas marker corresponding to the detection time; The time series dataset is input into the analysis software on the host computer, automatically stored, and then used for feature recognition and discrimination analysis through three artificial intelligence machine learning models: support vector machine, random forest, and gradient boosting machine. It is then incorporated into a real-time updated gas biomarker array database to construct an animal health status discrimination model.

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