Breath detection device, method and equipment with oral cavity peeping function and storage medium

Abstract

The invention provides a breath detection device with an oral cavity peeping function, a breath detection method, breath detection equipment and a storage medium. The breath detection device comprises a camera component, a sensing component and an AI main control processor, wherein the camera shooting assembly comprises an endoscopic high-definition camera and an image analysis chip module which are in communication connection with each other; the sensing assembly comprises a breath sensor, a shell with an airflow channel, and a breath analysis chip module, wherein the airflow channel is provided with an air inlet and an air outlet; wherein the breath sensor is arranged in the airflow channel, and the breath sensor is in communication connection with the breath analysis chip module; the AI main control processor is in communication connection with the image analysis chip module and the breath analysis chip module; the oral image information and the breath sample in the oral cavity can be obtained, and the disease information of the user is synthesized, so that the disease diagnosis can be more accurately carried out.

Description

Technical Field

[0001] The present application relates to the field of breath detection, and in particular to a breath detection device, method, equipment and storage medium with oral endoscopy function. Background Art

[0002] Due to the fast-paced modern life, many people's living and eating habits are not healthy. Over time, the body is prone to various problems, and bad breath is one of the very common problems.

[0003] Breath can now be used as a way to check for diseases. The main way to detect breath is to use sensors to collect oral gas and analyze its composition. If there is a certain kind of gas with a specific odor, it is considered to be breath. However, there are many factors that contribute to the formation of breath, such as food residues, oral hygiene, etc. How to accurately use breath to analyze the causes of breath in the body is still a pressing issue. Summary of the invention

[0004] The embodiments of the present application provide a breath detection device, method, equipment and storage medium with an oral endoscopy function, which is conducive to analyzing the causes of breath in the body through breath detection.

[0005] In a first aspect, an embodiment of the present application provides a breath detection device, comprising: a camera component, a sensor component and an AI main control processor; wherein the camera component comprises an endoscopic high-definition camera and an image analysis chip module that are communicatively connected to each other; the sensor component comprises: a breath sensor, a shell with an air flow channel, the air flow channel has an air inlet and an air outlet, and a breath analysis chip module; wherein the breath sensor is arranged in the air flow channel, and the breath sensor and the breath analysis chip module are communicatively connected; the AI ​​main control processor is communicatively connected to the image analysis chip module and the breath analysis chip module; the endoscopic high-definition camera is used to obtain oral image information ; The image analysis chip module is used to analyze the oral image information through a preset oral image analysis model to obtain oral pathological characteristics; according to the pathological characteristics, the first breath component information is obtained, and the first breath component information includes N components in the first breath and the concentrations of the N components; the breath sensor is used to collect breath samples in the oral cavity; the breath analysis chip module is used to perform component analysis on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and the concentrations of the M components; the processor is used to determine the user's disease information based on the first breath component information and the second breath component information.

[0006] Optionally, the image analysis chip module is specifically used to analyze the pathological characteristics through a preset pathological characteristic breath analysis model, and determine the first breath component information generated by the pathological characteristics; if the pathological characteristics include P pathological types, then the P pathological types are analyzed respectively through the preset pathological characteristic breath analysis model, and J breath component information corresponding to the P pathological types are determined respectively, and the J breath component information are calculated through a preset data model to obtain comprehensive breath component information corresponding to the J breath component information, and the comprehensive breath component information is used as the first breath component information.

[0007] Optionally, the AI ​​main control processor includes: a first comparison module, used to compare the N components in the first breath with the M components in the second breath; a first sub-processor, used to determine that a disease exists in the user if the difference component X between the N components in the first breath and the M components in the second breath is a preset component;

[0008] Optionally, the AI ​​main control processor includes: a second comparison module, used to compare the concentrations of N components in the first breath component information with the concentrations of M components in the second breath component information; a second sub-processor, used to determine whether the difference between the concentrations of the N components in the first breath component information and the corresponding concentrations of the M components in the second breath component information exceeds a first preset threshold; if so, determine that there is a disease in the user.

[0009] Optionally, the AI ​​main control processor includes: a third comparison module, used to compare the N components in the first breath with the M components in the second breath; a third sub-processor, used to determine that a disease exists in the user if the distinguishing component X between the N components in the first breath and the M components in the second breath is a preset component and if the concentration value of the distinguishing component X exceeds a second threshold; if so,

[0010] Optionally, the AI ​​master processor is further configured to calculate the concentration difference through a preset model. Calculate the disease value S, and determine the specific type of disease in the user's body based on the disease value S, where S is the disease value, n is the number of components corresponding to the concentration difference, and x i is the concentration difference of the i-th component, w i is the weight of the ith component, f(i) is the dynamic adjustment function of the ith component weight, and f(i) is positively correlated with the concentration difference of the ith component.

[0011] In the second aspect, an embodiment of the present application also provides a breath detection method, including: obtaining oral image information; analyzing the oral image information through a preset oral image analysis model to obtain oral pathological characteristics; obtaining first breath component information based on the pathological characteristics, the first breath component information including N components in the first breath and the concentrations of the N components; collecting a breath sample in the oral cavity; performing component analysis on the breath sample to obtain second breath component information; the second breath component information including M components in the second breath and the concentrations of the M components; determining user disease information based on the first breath component information and the second breath component information.

[0012] In a third aspect, an embodiment of the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the program, a breath detection method as described in the second aspect above is implemented.

[0013] In a fourth aspect, an embodiment of the present application further provides a computer storage medium, wherein a computer program stored in the computer storage medium is used to implement a breath detection method as described in the second aspect above when executed by a computer device.

[0014] In a fifth aspect, an embodiment of the present application further provides a computer program, which, when executed by a computer device, is used to implement the breath detection method as described in the second aspect above.

[0015] It can be seen that in the embodiment of the present application, the breath detection device is connected through its camera component, sensor component and AI main control processor; wherein, the camera component includes an endoscopic high-definition camera and an image analysis chip module that are communicatively connected to each other; the sensor component includes: a breath sensor, a shell with an air flow channel, the air flow channel has an air inlet and an air outlet, and a breath analysis chip module; wherein, the breath sensor is arranged in the air flow channel, and the breath sensor and the breath analysis chip module are communicatively connected; the AI ​​main control processor is communicatively connected with the image analysis chip module and the breath analysis chip module; wherein, the endoscopic high-definition camera is used to obtain oral image information; the image analysis chip module is used to analyze the oral cavity through a preset oral image analysis model. The method comprises the following steps: analyzing the oral cavity image information to obtain oral pathological characteristics; obtaining first breath component information according to the pathological characteristics, wherein the first breath component information includes N components in the first breath and the concentrations of the N components; a breath sensor for collecting breath samples in the oral cavity; a breath analysis chip module for performing component analysis on the breath samples to obtain second breath component information; the second breath component information includes M components in the second breath and the concentrations of the M components; and an AI main control processor for determining user disease information based on the first breath component information and the second breath component information, so that a comprehensive analysis is performed on the breath component information corresponding to the oral pathological characteristics and the component information of the collected breath samples, thereby more accurately diagnosing the disease. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 is a structural schematic diagram of a breath detection device provided by way of example in an embodiment of the present application;

[0018] Figure 2 is a structural schematic diagram of another breath detection device provided by way of example in an embodiment of the present application;

[0019] Figure 3 is a structural schematic diagram of another breath detection device provided by way of example in an embodiment of the present application;

[0020] Figure 4 is a structural schematic diagram of another breath detection device provided by way of example in an embodiment of the present application;

[0021] Figure 5 1 is a flow chart of a breath detection method provided by way of example in an embodiment of the present application;

[0022] Figure 6 is a flow chart of another breath detection method provided by way of example in an embodiment of the present application;

[0023] Figure 7 is a flow chart of another breath detection method provided by way of example in an embodiment of the present application;

[0024] Figure 8 is a flow chart of another breath detection method provided by way of example in an embodiment of the present application;

[0025] Fig. 9 This is a flow chart of another breath detection method provided as an example in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the technical personnel in the technical field better understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is an embodiment of a part of the present invention, not all embodiments. Based on some embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without making creative work should belong to the scope of protection of the present invention. The terms "first", "second" and "third" appearing in the specification, claims and drawings of the present invention are used to distinguish different objects, not to describe a specific order. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system or product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices.

[0027] See also Figure 1 , Figure 1 is a structural diagram of a breath detection device 100 provided by way of example in an embodiment of the present application. Figure 1 As shown, the device 100 includes: a camera component 101, a sensor component 102 and an AI main control processor 103; wherein the camera component 101 includes an endoscopic high-definition camera 1011 and an image analysis chip module 1012 which are communicatively connected to each other; the sensor component 102 includes: a breath sensor 1021, a shell with an air flow channel, the air flow channel has an air inlet and an air outlet, and a breath analysis chip module 1022; wherein the breath sensor is arranged in the air flow channel, and the breath sensor 1021 and the breath analysis chip module 1022 are communicatively connected; the AI ​​main control processor 103 is communicatively connected to the image analysis chip module 1012 and the breath analysis chip module 1022.

[0028] The endoscopic high-definition camera 1011 is used to obtain oral image information, such as images of the inner wall of the oral cavity, teeth, tongue, etc.

[0029] The image analysis chip module 1012 is used to analyze the oral image information through a preset oral image analysis model to obtain oral pathological characteristics; according to the pathological characteristics, the first breath component information is obtained, and the first breath component information includes N components and the concentrations of N components in the first breath; after the image analysis chip module 1012 obtains the oral image information, the image analysis chip module 1012 can analyze the oral image through a preset oral image analysis model, or upload it to a terminal or server connected to the breath detection device for analysis, and the oral image analysis model can be trained and updated through big data or artificial intelligence, so as to obtain the pathological characteristics of the user's oral cavity. The pathological characteristics may include the type of oral pathology, such as oral ulcers, periodontitis, oral smoke stains, oral calculus, oral food residues, etc., and may also include the degree of oral pathology, such as the degree of oral ulcers, the degree of oral smoke stains, the type of oral food residues, etc.

[0030] The breath sensor 1021 is used to collect breath samples in the oral cavity.

[0031] The breath analysis chip module 1022 is used to perform component analysis on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and the concentrations of the M components; the breath analysis chip module can analyze the collected breath sample to obtain the second breath component information of the sample, and the breath component information can include the M component information contained in the above breath sample and the concentrations of the M components.

[0032] It can be understood that the above M and N are positive integers, and M is greater than or equal to N.

[0033] The AI ​​main control processor 103 is used to determine the user's disease information based on the first breath component information and the second breath component information. The AI ​​main control processor 103 comprehensively analyzes and outputs a diagnosis result based on the analysis results of the breath analysis chip module and the image analysis chip module.

[0034] It can be seen that in the embodiment of the present application, the breath detection device 100 is through its camera component 101, sensor component 102 and AI main control processor 103; wherein, the camera component 101 includes an endoscopic high-definition camera 1011 and an image analysis chip module 1012 which are communicatively connected to each other; the sensor component 102 includes: a breath sensor 1021, a shell with an air flow channel, the air flow channel has an air inlet and an air outlet, and a breath analysis chip module 1022; wherein, the breath sensor 1021 is arranged in the air flow channel, and the breath sensor 1021 and the breath analysis chip module 1022 are communicatively connected; the AI ​​main control processor 103 is communicatively connected with the image analysis chip module 1012 and the breath analysis chip module 1022; wherein, the endoscopic high-definition camera 1011 is used to obtain oral image information; image analysis The chip module 1012 is used to analyze the oral image information through a preset oral image analysis model to obtain oral pathological characteristics; obtain first breath component information according to the pathological characteristics, and the first breath component information includes N components in the first breath and the concentrations of the N components; the breath sensor 1021 is used to collect breath samples in the oral cavity; the breath analysis chip module 1022 is used to perform component analysis on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and the concentrations of the M components; the AI ​​main control processor 103 is used to determine the user's disease information based on the first breath component information and the second breath component information, so that the breath component information corresponding to the oral pathological characteristics and the component information of the collected breath samples are comprehensively analyzed, and the disease can be diagnosed more accurately.

[0035] It should be noted that the above-mentioned image analysis chip module can also be specifically used to analyze the pathological characteristics through a preset pathological characteristic breath analysis model to determine the first breath component information generated by the pathological characteristics; if the pathological characteristics include P pathological types, then the P pathological types are analyzed respectively through the preset pathological characteristic breath analysis model to respectively determine the J breath component information corresponding to the P pathological types, and the J breath component information are calculated through a preset mathematical model to obtain the comprehensive breath component information corresponding to the J breath component information, and the comprehensive breath component information is used as the first breath component information and sent to the AI ​​main control processor 103.

[0036] In some preferred embodiments, the AI ​​master processor 103 may also include multiple sub-modules, such as Figure 2 As shown, Figure 2 is a structural schematic diagram of another breath detection device provided by way of example in an embodiment of the present application; Figure 2 As shown, the AI ​​master processor 103 may also include:

[0037] A first comparison module 1031, for comparing the N components in the first breath with the M components in the second breath;

[0038] The first sub-processor 1032 is configured to determine that a disease exists in the user if a distinguishing component X between the N components in the first breath and the M components in the second breath is a preset component.

[0039] In some other preferred embodiments, the AI ​​master processor 103 may also include multiple sub-modules, such as Figure 3 As shown, Figure 3 is a structural schematic diagram of another breath detection device provided by way of example in the embodiment of the present application; Figure 3 As shown, the AI ​​master processor 103 may also include:

[0040] A second comparison module 1033, used to compare the concentrations of the N components in the first breath component information with the concentrations of the M components in the second breath component information;

[0041] The second sub-processor 1034 is configured to: if the difference between the concentrations of the N components in the first breath component information and the concentrations of the M components in the corresponding second breath component information exceeds a first preset threshold;

[0042] If so, it is determined that the user has a disease.

[0043] In some other preferred embodiments, the AI ​​master processor 103 may also include multiple sub-modules, such as Figure 4 As shown, Figure 4 is a structural schematic diagram of another breath detection device provided by way of example in the embodiment of the present application; Figure 4 As shown, the AI ​​master processor 103 may also include:

[0044] A third comparison module 1035, for comparing the N components in the first breath with the M components in the second breath;

[0045] The third sub-processor 1036 is configured to, if a distinguishing component X between the N components in the first breath and the M components in the second breath is a preset component, and if a concentration value of the distinguishing component X exceeds a second threshold;

[0046] If so, it is determined that the user has a disease.

[0047] In some other preferred embodiments, the AI ​​master processor 103 may also include multiple sub-modules, such as Figure 4 As shown, Figure 4 is a structural schematic diagram of another breath detection device provided by way of example in an embodiment of the present application; Figure 4As shown, the AI ​​main control processor 103 can also be used to calculate the concentration difference through a preset model Calculate the disease value S, and determine the specific type of disease in the user's body based on the disease value S, where S is the disease value, n is the number of components corresponding to the concentration difference, and x i is the concentration difference of the i-th component, w i is the weight of the ith component, f(i) is the dynamic adjustment function of the ith component weight, and f(i) is positively correlated with the concentration difference of the ith component.

[0048] See also Figure 5 , Figure 5 A flow chart of a breath detection method provided in an embodiment of the present application is shown in FIG. Figure 1 As an example, the method includes the following steps:

[0049] 501. Obtain oral image information.

[0050] The breath detection device can collect image information of the inside of the oral cavity, such as images of the inner wall of the oral cavity, teeth, tongue, etc., through an external high-definition camera or its built-in high-definition endoscope camera.

[0051] 502. Analyze oral image information through a preset oral image analysis model to obtain oral pathology characteristics.

[0052] After obtaining the oral image information, the oral image can be analyzed by a preset oral image analysis model, or uploaded to a terminal or server connected to the breath detection device for analysis. The oral image analysis model can be trained and updated through big data or artificial intelligence, so as to obtain the pathological characteristics of the user's oral cavity. The pathological characteristics may include the type of oral pathology, such as oral ulcers, periodontitis, oral smoke stains, oral calculus, oral food residues, etc., and may also include the degree of oral pathology, such as the degree of oral ulcers, the degree of oral smoke stains, the type of oral food residues, etc.

[0053] 503. Obtain first breath component information according to the pathological characteristics, wherein the first breath component information includes N components in the first breath and the concentrations of the N components.

[0054] It is understandable that different types of oral pathology will release different types of gases.

[0055] Therefore, based on the pathological characteristics of the user's oral cavity obtained as described above, the first breath component information corresponding to the pathological characteristics can be determined. The component information may include N components contained in the first breath and concentration information of the N components.

[0056] 504. Collect breath samples from the oral cavity.

[0057] The breath sensor can be used to collect breath samples in the oral cavity.

[0058] It is understandable that there is no order restriction for step 504 and the above steps 501 to 503.

[0059] 505. Perform component analysis on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and concentrations of the M components.

[0060] The breath sensor can also be used to analyze the collected breath sample to obtain second breath component information of the sample. The breath component information may include information of M components contained in the breath sample and concentrations of the M components.

[0061] It can be understood that the above M and N are positive integers, and M is greater than or equal to N.

[0062] 506. Determine the user's disease information based on the first breath composition information and the second breath composition information.

[0063] The above-mentioned first breath composition information is the breath composition information that should theoretically be released by the above-mentioned pathological characteristics, and the above-mentioned second breath composition information is the actual breath composition information collected in the oral cavity. In this way, a comprehensive judgment can be made based on the combination of the above-mentioned first breath composition information and the above-mentioned second breath composition information, so as to diagnose the disease.

[0064] In this embodiment, oral image information can be obtained; the obtained oral image information can be analyzed by a preset oral image analysis model; thereby, the pathological characteristics in the oral cavity can be determined; based on the pathological characteristics, breath component information corresponding to the pathological characteristics in the oral cavity can be determined, that is, first breath component information, which includes N components in the first breath and the concentrations of the N components; at the same time, a breath sample in the oral cavity can be collected; a component analysis is performed on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and the concentrations of the M components; based on the above-mentioned first breath component information and the above-mentioned second breath component information, the user's disease information is determined, so that the breath component information corresponding to the oral pathological characteristics and the component information of the collected breath sample can be more clearly known, and the breath component information in the oral cavity and its source can be obtained, so as to perform a comprehensive analysis and further accurately diagnose the disease.

[0065] In some possible implementations, the above-mentioned determination of the first breath component information corresponding to the pathological feature can be performed by querying a pre-stored pathological feature and breath component information correspondence table to obtain the first breath component information corresponding to the pathological feature, or by analyzing the obtained pathological feature through a pre-stored pathological feature breath component analysis model to obtain the first breath component information corresponding to the pathological feature.

[0066] If the above-mentioned pathological characteristics include P pathological types, where P is an integer greater than or equal to 0, the P pathological types can be analyzed separately through a preset pathological characteristic breath analysis model to determine the J breath component information corresponding to the above-mentioned P pathological types, such as the breath component corresponding to pathological type P1 is J1, the breath component corresponding to pathological type P2 is J2, and so on, P = {P1, P2, ... Pp}, J = {J1, J2, ... Jj}, and the data contained in the J breath component information is calculated through a preset mathematical model to obtain comprehensive breath component information of the J breath component information, and then the comprehensive breath component information is used as the first breath component information.

[0067] The above-mentioned preset mathematical model can be a hierarchical analysis method mathematical model, a fuzzy comprehensive evaluation method mathematical model, an entropy method mathematical model, a principal component method mathematical model, etc., which is not limited here.

[0068] In the above embodiment, when the pathological characteristics include multiple pathological types, the breath component information corresponding to the multiple pathological types can be comprehensively calculated according to a preset mathematical model, and the comprehensive breath component information obtained after the calculation can be used as the first breath component information, and the disease diagnosis can be performed together with the above-mentioned second breath component information. This can more accurately and comprehensively determine the impact of various pathological characteristics in the oral cavity on the breath, making the disease diagnosis more accurate.

[0069] See also Figure 6 , Figure 6 A flow chart of another breath detection method provided in an embodiment of the present application. Figure 2 For example, the breath detection method of the embodiment of the present application may specifically include:

[0070] 601. Obtain oral image information.

[0071] The breath detection device can collect image information of the inside of the oral cavity, such as images of the inner wall of the oral cavity, teeth, tongue, etc., through an external high-definition camera or its built-in high-definition endoscope camera.

[0072] 602. Analyze oral image information through a preset oral image analysis model to obtain oral pathology characteristics.

[0073] After obtaining the oral image information, the oral image can be analyzed by a preset oral image analysis model, or uploaded to a terminal or server connected to the breath detection device for analysis. The oral image analysis model can be trained and updated through big data or artificial intelligence, so as to obtain the pathological characteristics of the user's oral cavity. The pathological characteristics may include the type of oral pathology, such as oral ulcers, periodontitis, oral smoke stains, oral calculus, oral food residues, etc., and may also include the degree of oral pathology, such as the degree of oral ulcers, the degree of oral smoke stains, the type of oral food residues, etc.

[0074] 603. Obtain first breath component information according to the pathological characteristics, where the first breath component information includes N components in the first breath and the concentrations of the N components.

[0075] It is understandable that different types of oral pathology will release different types of gases.

[0076] Therefore, based on the pathological characteristics of the user's oral cavity obtained as described above, the first breath component information corresponding to the pathological characteristics can be determined. The component information may include N components contained in the first breath and concentration information of the N components.

[0077] In some possible implementations, the above-mentioned determination of the first breath component information corresponding to the pathological feature can be performed by querying a pre-stored pathological feature and breath component information correspondence table to obtain the first breath component information corresponding to the pathological feature, or by analyzing the obtained pathological feature through a pre-stored pathological feature breath component analysis model to obtain the first breath component information corresponding to the pathological feature.

[0078] If the above-mentioned pathological characteristics include P pathological types, where P is an integer greater than or equal to 0, the P pathological types can be analyzed separately through a preset pathological characteristic breath analysis model to determine the J breath component information corresponding to the above-mentioned P pathological types, such as the breath component corresponding to pathological type P1 is J1, the breath component corresponding to pathological type P2 is J2, and so on, P = {P1, P2, ... Pp}, J = {J1, J2, ... Jj}, and the data contained in the J breath component information is calculated through a preset mathematical model to obtain comprehensive breath component information of the J breath component information, and then the comprehensive breath component information is used as the first breath component information.

[0079] The above-mentioned preset mathematical model can be a hierarchical analysis method mathematical model, a fuzzy comprehensive evaluation method mathematical model, an entropy value method mathematical model, a principal component method mathematical model, etc., which is not limited here.

[0080] 604. Collect breath samples from the oral cavity.

[0081] The breath sensor can be used to collect breath samples in the oral cavity.

[0082] It is understandable that there is no order restriction for step 704 and the above steps 701 to 703.

[0083] 605. Perform component analysis on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and concentrations of the M components.

[0084] The breath sensor can also be used to analyze the collected breath sample to obtain second breath component information of the sample. The breath component information may include information of M components contained in the breath sample and concentrations of the M components.

[0085] It can be understood that the above M and N are positive integers, and M is greater than or equal to N.

[0086] 606. Compare the N components in the first breath with the M components in the second breath. The N components in the first breath may be compared with the M components in the second breath;

[0087] 607. If the distinguishing component X between the N components in the first breath and the M components in the second breath is a preset component, it is determined that the user has a disease.

[0088] The comparison result is determined. If there is a distinguishing component X between the N components in the first breath and the M components in the second breath, the distinguishing component X is determined to be a preset component, and a disease in the user can be diagnosed.

[0089] For example: if the N components in the first breath are water, carbon dioxide, ammonia, and nitrogen, and the M components in the second breath are water, carbon dioxide, ammonia, nitrogen, and acetone, then it can be determined that the distinguishing component X is acetone, and it can be determined that the distinguishing component X acetone is not a breath component secreted by a pathological type in the oral cavity; if the preset components are acetone, hydrogen sulfide, indole, and sulfur dioxide, then it can be determined that the distinguishing component X acetone is the preset component, and it can be further determined that acetone is a gas component exhaled through the respiratory tract of the user's body, indicating that the user has a disease.

[0090] like Figure 7 As shown, in some possible implementations, the breath detection method may further include the following steps:

[0091] 706. Compare the concentrations of the N components in the first breath composition information with the concentrations of the M components in the second breath composition information.

[0092] The concentrations of the N components in the first breath component information may be compared with the concentrations of the M components in the second breath component information.

[0093] 707. Determine whether the difference between the concentrations of the N components in the first breath composition information and the concentrations of the M components in the corresponding second breath composition information exceeds a first preset threshold; if so, determine that the user has a disease.

[0094] Judging the result of the above corresponding comparison, if there is a difference between the concentrations of the N components in the above first breath composition information and the corresponding concentrations of the M components in the above second breath composition information, and the difference exceeds the preset first threshold, it can be determined that the cause of the concentration difference is the gas exhaled from the user's respiratory tract, and it can be further known that there is a disease in the user.

[0095] An example can be given: for example, the N components in the first breath are oxygen, ammonia, carbon dioxide, nitrogen, and sulfur dioxide, and their concentrations are 15%, 78%, 4%, 0.02%, and 0.01%, respectively; the M components in the second breath are oxygen, ammonia, carbon dioxide, nitrogen, and sulfur dioxide, and their concentrations are 15%, 78%, 4%, 0.12%, and 0.09%, respectively. It can be determined that the concentration of the component ammonia in the second breath is 0.1% higher than the concentration of the component ammonia in the first breath, and the concentration of sulfur dioxide is 0.08% higher. If the first threshold is 0.05%, it can be determined that the higher concentration is not caused by pathological characteristics in the oral cavity, and the influence of external air and detection errors are excluded by the first threshold. It can be further confirmed that the gas exhaled from the user's respiratory tract has an impact on the concentration of the component ammonia, and it can be determined that the user has a disease.

[0096] like Figure 8 As shown, in some possible implementations, the breath detection method may further include the following steps:

[0097] 806. Compare the N components in the first breath with the M components in the second breath.

[0098] 807. If the difference component X between the N components in the first breath and the M components in the second breath is a preset component.

[0099] The comparison result is determined. If there is a distinguishing component X between the N components in the first breath and the M components in the second breath, the distinguishing component X is determined to be a preset component.

[0100] 808. If the concentration of the distinguishing component X exceeds a second preset threshold.

[0101] It is determined that the user has a disease.

[0102] For example, if the N components in the first breath are water, carbon dioxide, ammonia, and nitrogen, and the M components in the second breath are water, carbon dioxide, ammonia, nitrogen, and acetone, then it can be determined that the distinguishing component X is acetone, and it can be determined that the distinguishing component X acetone is not a breath component secreted by a pathological type in the oral cavity;

[0103] If the preset components are acetone, hydrogen sulfide, indole, and sulfur dioxide, the distinguishing component X acetone is a component in the preset components.

[0104] If the detected acetone concentration is 0.05% and the second preset threshold is 0.02%, the influence of outside air and detection error is eliminated by the first threshold, and it can be further confirmed that the gas exhaled from the user's respiratory tract has an impact on the concentration of the component ammonia, and it can be determined that the user has a disease.

[0105] Above Figure 2 , Figure 3 , Figure 4 In the illustrated embodiment, by determining the distinguishing component X, or comparing the concentrations of N components in the first breath with the concentrations of M components in the first breath, or determining the distinguishing component X and its concentration, combined with the first threshold or the second threshold, it is possible to further accurately determine whether the component in the breath is the gas exhaled from the user's respiratory tract, thereby more accurately determining whether there is a disease in the user's body.

[0106] like Fig. 9 As shown above Fig. 9 After the steps of the breath detection method shown in the embodiment, the method may further include the following steps:

[0107] 908. According to the concentration difference, by using a preset model Calculate the disease value S.

[0108] According to the concentration difference obtained above, using the preset model The specific disease value S can be calculated comprehensively, where S is the disease value, n is the number of components corresponding to the concentration difference, and x i is the concentration value of the i-th component, w i is the weight of the ith component, f(i) is the dynamic adjustment function of the weight of the ith component, f(i) is positively correlated with the concentration difference of the ith component, and the above weights can be preset.

[0109] 909. Determine the specific type of disease existing in the user according to the disease value S.

[0110] The specific disease type can be determined by querying and comparing the disease value S with the pre-stored disease value and disease type mapping table.

[0111] For example, the N components in the first breath are oxygen, ammonia, carbon dioxide, nitrogen, and sulfur dioxide, and their concentrations are 15%, 78%, 4%, 0.02%, and 0.01%, respectively. The M components in the second breath are oxygen, ammonia, carbon dioxide, nitrogen, and sulfur dioxide, and their concentrations are 15%, 78%, 4%, 0.12%, and 0.09%, respectively. It can be determined that the concentration of ammonia in the second breath is 0.1% higher than that of ammonia in the first breath, and the concentration of sulfur dioxide is 0.08% higher. If the first threshold is 0.05%, assuming that the weight of ammonia is 0.2 and that of sulfur dioxide is 0.25, the function f(i) indicates that the weight of a component increases by 5% for every 0.03% increase in its concentration. Then, the above mathematical model can be used to calculate the disease value S=0.057.

[0112] An example of a disease value and disease type mapping table is as follows:

[0113] Disease value range Disease Type 0.04～0.06 Lung disease 0.06～0.07 Stomach disease 0.08～0.09 Kidney disease

[0114] Therefore, the disease value and disease type mapping table can be queried to find out that the user's disease type is stomach disease.

[0115] The breath detection method shown in the above embodiment can not only detect whether there is a disease risk in the user, but also further accurately detect the specific disease type, making it convenient for the user or doctor to perform further treatment in a timely and accurate manner.

[0116] It is understandable that the above Fig. 9 The breath detection method described in the embodiment shown is the same as the above Figure 6 , Figure 7 , Figure 8 The breath detection methods shown in the illustrated embodiments may be combined and will not be described in detail here.

[0117] It should be noted here that the above-mentioned device provided by the present invention can implement all the method steps implemented by the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects that are the same as the method embodiment in this embodiment will not be described in detail here.

[0118] The present application also provides an electronic device, which may include: a processor, a communications interface, a memory, and a communication bus, wherein the processor, the communications interface, and the memory communicate with each other via the communication bus. The processor may call the logic instructions in the memory to execute any of the breath detection methods provided in the above embodiments.

[0119] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Me mory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0120] It should be noted here that the electronic device provided in the present application can implement all the method steps implemented in the above-mentioned method embodiment and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as the method embodiment will not be described in detail here.

[0121] On the other hand, the present application also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it can implement any of the breath detection methods provided in the above embodiments, the method comprising: obtaining oral image information; analyzing the oral image information through a preset oral image analysis model; obtaining oral pathological characteristics; obtaining first breath component information according to the pathological characteristics, the first breath component information including N components and the concentrations of N components in the first breath; collecting a breath sample in the oral cavity; performing component analysis on the breath sample to obtain second breath component information; the second breath component information including M components and the concentrations of M components in the second breath; determining the user's disease information based on the first breath component information and the second breath component information. It should be noted that the non-transitory computer-readable storage medium provided by the present invention can implement all the method steps implemented in the above method embodiments, and can achieve the same technical effects. The parts and beneficial effects that are the same as those in the method embodiments in this embodiment will not be specifically described here.

[0122] On the other hand, the present application also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute any of the breath detection methods provided in the above embodiments, the method including: obtaining oral image information; analyzing the oral image information through a preset oral image analysis model; obtaining oral pathological characteristics; obtaining first breath component information based on the pathological characteristics, the first breath component information including N components and the concentrations of the N components in the first breath; collecting a breath sample in the oral cavity; performing component analysis on the breath sample to obtain second breath component information; the second breath component information including M components and the concentrations of the M components in the second breath; determining user disease information based on the first breath component information and the second breath component information.

[0123] It should be noted here that the computer program product provided by the present invention can implement all the method steps implemented by the above-mentioned method embodiment, and can achieve the same technical effect. The parts and beneficial effects of this embodiment that are the same as those of the method embodiment will not be described in detail here.

[0124] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0125] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices, units, etc. described above can refer to the corresponding processes in the aforementioned methods or other embodiments and will not be repeated here.

[0126] For the sake of convenience and brevity, the various method embodiments can also be referenced to each other and will not be described in detail. In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0127] The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, the functional units in each embodiment of the present application may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit. If the function is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium, including several instructions for a computer device (such as a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory, a random access memory, a disk or an optical disk.

[0128] The above are only some specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A breath detection device, characterized in that: include: A camera assembly, a sensor assembly and an AI main control processor; wherein the camera assembly includes an endoscopic high-definition camera and an image analysis chip module that are communicatively connected to each other; the sensor assembly includes: a breath sensor, a housing with an air flow channel, the air flow channel has an air inlet and an air outlet, and a breath analysis chip module; wherein the breath sensor is arranged in the air flow channel, and the breath sensor and the breath analysis chip module are communicatively connected; the AI ​​main control processor is communicatively connected to the image analysis chip module and the breath analysis chip module; The endoscopic high-definition camera is used to obtain oral image information; The image analysis chip module is used to analyze the oral image information through a preset oral image analysis model to obtain oral pathological characteristics; according to the pathological characteristics, obtain the first breath component information, wherein the first breath component information includes N components in the first breath and the concentrations of the N components; The breath sensor is used to collect breath samples in the oral cavity; The breath analysis chip module is used to perform component analysis on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and the concentrations of the M components; The AI ​​main control processor is used to determine the user's disease information based on the first breath component information and the second breath component information.

2. The breath detection device according to claim 1, characterized in that: The image analysis chip module is specifically used for: Analyze the pathological feature by using a preset pathological feature breath analysis model to determine the first breath component information generated by the pathological feature; If the pathological characteristics include P pathological types, the P pathological types are analyzed respectively by using a preset pathological characteristic breath analysis model, and J breath component information corresponding to the P pathological types are determined respectively. The J breath component information are calculated by using a preset mathematical model to obtain comprehensive breath component information corresponding to the J breath component information, and the comprehensive breath component information is used as the first breath component information.

3. The breath detection device according to claim 1, characterized in that: The AI ​​master processor includes: A first comparison module, used for comparing the N components in the first breath with the M components in the second breath; The first sub-processor is used to determine that a disease exists in the user if a distinguishing component X between the N components in the first breath and the M components in the second breath is a preset component.

4. The breath detection device according to claim 1, characterized in that: The AI ​​master processor includes: a second comparison module, configured to compare the concentrations of the N components in the first breath component information with the concentrations of the M components in the second breath component information; a second sub-processor, configured to: if a difference between the concentrations of the N components in the first breath component information and the concentrations of the M components in the corresponding second breath component information exceeds a first preset threshold; If so, it is determined that the user has a disease.

5. The breath detection device according to claim 1, characterized in that: The AI ​​master processor includes: A third comparison module, used for comparing the N components in the first breath with the M components in the second breath; a third sub-processor, configured to, if a distinguishing component X between the N components in the first breath and the M components in the second breath is a preset component, and if a concentration value of the distinguishing component X exceeds a second threshold; If so, it is determined that the user has a disease.

6. The breath detection device according to claim 4, characterized in that: The AI ​​master processor is also used for: According to the concentration difference, the preset model Calculate the disease value S, and determine the specific type of disease in the user's body based on the disease value S, where S is the disease value, n is the number of components corresponding to the concentration difference, and x i is the concentration difference of the i-th component, w i is the weight of the ith component, f(i) is the dynamic adjustment function of the ith component weight, and f(i) is positively correlated with the concentration difference of the ith component.

7. A breath detection method, characterized in that: include: Acquire oral image information; Through the preset oral image analysis model, oral image information is analyzed to obtain oral pathology characteristics; According to the pathological characteristics, obtaining first breath component information, wherein the first breath component information includes N components and concentrations of the N components in the first breath; Collect breath samples from the mouth; Performing component analysis on the breath sample to obtain second breath component information; the second breath component information includes M components in the second breath and the concentrations of the M components; Based on the first breath component information and the second breath component information, user disease information is determined.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the breath detection method according to claim 7 is implemented.

9. A computer storage medium, characterized in that The computer program stored in the computer storage medium is used to implement the breath detection method of claim 7 when executed by a computer device.

10. A computer program, characterized in that The computer program is used to implement the breath detection method of claim 7 when executed by a computer device.

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