Intelligent gastric lavage auxiliary guiding method and system

Abstract

The invention provides an intelligent gastric lavage auxiliary guiding method and system, and the method comprises the steps: obtaining a current gastric lavage mode, gastric lavage extract detection data, and current body detection data of a user, and recognizing the current gastric lavage degree and the current gastric damage degree; identifying the current body state and the current breathing state of the user, and analyzing the abnormal degree of gastric lavage of the user; based on the above information, through a gastric lavage adjustment strategy, generating gastric lavage adjustment guidance information of the current gastric lavage mode, and re-collecting new body detection data and new gastric lavage extract detection data; and generating target gastric lavage guide information based on the new gastric lavage extract detection data and the difference value, sending the target gastric lavage guide information to a display terminal of gastric lavage equipment, guiding a worker to adjust a current gastric lavage mode, and returning to execute the above steps until a gastric lavage task is completed. By adopting the scheme, the injury avoidance accuracy in the gastric lavage process can be improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence and equipment-assisted guidance technology, and in particular to an intelligent gastric lavage-assisted guidance method and system. Background Art

[0002] Gastric lavage is a procedure in which a gastric tube is inserted into the stomach through the mouth or nose through the esophagus, and a large amount of solution is used to flush the stomach cavity using the principle of gravity and siphon action, in order to remove harmful substances in the stomach, or to clean the substances in the stomach to complete the preparation before the examination. However, there are potential risks in the gastric lavage process, which may cause serious complications such as acute gastric dilatation, gastric perforation, water intoxication, electrolyte and acid-base imbalance, and even aspiration or suffocation, which may cause secondary harm or more serious harm to the patient. Therefore, how to guide the gastric lavage process through auxiliary guidance means to avoid secondary harm of gastric lavage is the current research focus.

[0003] The traditional gastric lavage guidance method is highly dependent on professional medical staff. Based on historical gastric lavage experience, the gastric lavage process is manually guided to avoid secondary injuries during the gastric lavage process. However, the accuracy of manual guidance is low, and in actual operations, the damage caused by abnormal operations is instantaneous. Therefore, the timeliness of manual guidance is also low, resulting in low accuracy in avoiding damage during the gastric lavage process. Summary of the invention

[0004] The main purpose of the present invention is to provide an intelligent gastric lavage auxiliary guidance method and system, aiming to solve the problem that the accuracy of manual guidance in the prior art is low, and in the actual operation process, the damage caused by abnormal operation is instantaneous, so the timeliness of manual guidance is also low, resulting in low accuracy in avoiding damage during the gastric lavage process.

[0005] To achieve the above object, the present invention provides an intelligent gastric lavage auxiliary guidance method, the method comprising:

[0006] Obtaining the current gastric lavage method, gastric lavage extract test data, and the user's current body test data, and identifying the current gastric cleaning degree and the current gastric damage degree based on the gastric lavage extract data;

[0007] Based on the current body detection data of the user, identifying the current body state of the user and the current breathing state of the user, and analyzing the abnormal degree of gastric lavage of the user based on the current body state of the user and the current breathing state of the user;

[0008] Based on the user's gastric lavage abnormality, the current gastric cleaning degree, and the current gastric damage degree, gastric lavage adjustment guidance information of the current gastric lavage method is generated through a gastric lavage adjustment strategy, and the gastric lavage adjustment guidance information is sent to the display terminal of the gastric lavage device to guide the staff to adjust the current gastric lavage method and re-collect new body test data and new gastric lavage extract test data of the user;

[0009] When the difference between the new gastric lavage abnormality degree corresponding to the new body test data of the user and the gastric lavage abnormality degree is lower than the difference value threshold, based on the new gastric lavage extract test data and the difference value, the gastric lavage adjustment guidance information is adjusted through the gastric lavage adjustment strategy to generate target gastric lavage guidance information, and the target gastric lavage guidance information is sent to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and the step of returning to execute the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then re-collecting the new body test data of the user and the new gastric lavage extract test data until the gastric lavage task is completed.

[0010] Optionally, the identifying the current degree of gastric cleansing and the current degree of gastric damage based on the gastric lavage extraction data includes:

[0011] Based on the gastric lavage extraction data, identifying each gastric extraction component of the user and the component concentration of each gastric extraction component, and selecting a first component concentration of a blood extraction component and a second component concentration of a target extraction component from among the component concentrations of each gastric extraction component;

[0012] Based on the concentration of the first component of the blood extraction component, identifying the current degree of stomach damage through a stomach damage identification strategy;

[0013] Initial sampling information of the target extraction component of the user is collected, and based on the initial sampling information of the target extraction component and the second component concentration of the target extraction component, a current stomach cleansing degree is calculated.

[0014] Optionally, the identifying the current physical state of the user and the current breathing state of the user based on the current physical detection data of the user includes:

[0015] Splitting the current body detection data of the user into current physiological detection data and current breathing detection data, and analyzing the current body state of the user through a body state analysis network based on the detection index values ​​of each physiological detection type in the current physiological detection data;

[0016] Based on the current breathing detection data of the user, the breathing detection value of each breathing detection type of the user is identified, and based on the breathing detection value of each breathing detection type, the current breathing state of the user is identified through a breathing detection graph.

[0017] Optionally, analyzing the abnormality degree of gastric lavage of the user based on the current physical state of the user and the current breathing state of the user includes:

[0018] Based on the current physical state of the user, query the user's physical function abnormality information in a physical state database, and based on the current breathing state of the user, query the user's breathing abnormality information in a breathing response database;

[0019] Based on the body function abnormality information and the user's breathing abnormality information, a gastric lavage abnormality degree of the user's gastric lavage abnormality type is analyzed through a gastric lavage abnormality analysis strategy.

[0020] Optionally, the generating of gastric lavage adjustment guidance information of the current gastric lavage method through a gastric lavage adjustment strategy based on the gastric lavage abnormality degree of the user, the current gastric cleaning degree, and the current gastric damage degree includes:

[0021] Based on the gastric cleansing degree and the initial sampling information of the target extraction component, identifying the current remaining component capacity of the target extraction component, and based on the current gastric damage degree, identifying the first physical tolerance range of each gastric lavage condition type of the user;

[0022] Based on the gastric lavage abnormality degree of the gastric lavage abnormality type of the user, identifying the second body tolerance range of each gastric lavage condition type of the user, and based on the first body tolerance range of each gastric lavage condition type and the second body tolerance range of each gastric lavage condition type, identifying the target body tolerance range of each gastric lavage condition type;

[0023] Based on the current remaining component capacity of the target extracted component and the target body tolerance range of each gastric lavage condition type, gastric lavage adjustment guidance information of the user is generated through a gastric lavage planning network.

[0024] Optionally, adjusting the gastric lavage adjustment guidance information based on the new gastric lavage extract detection data and the difference value through the gastric lavage adjustment strategy to generate target gastric lavage guidance information includes:

[0025] Calculating a difference deviation value between the difference value and the difference threshold, and calculating a new target body tolerance range for each gastric lavage condition type based on the difference deviation value;

[0026] Based on the new gastric lavage extract detection data, the new remaining component capacity of the target extraction component is identified, and based on the new remaining component capacity and the new target body tolerance range of each gastric lavage condition type, the user's target gastric lavage guidance information is generated through the gastric lavage planning network.

[0027] In addition, to achieve the above-mentioned purpose, the present invention also provides an intelligent gastric lavage auxiliary guidance system, the intelligent gastric lavage auxiliary guidance system comprising:

[0028] An acquisition module, used to acquire the current gastric lavage method, gastric lavage extract test data, and the user's current body test data, and to identify the current gastric cleaning degree and the current gastric damage degree based on the gastric lavage extract data;

[0029] an analysis module, configured to identify the current physical state of the user and the current breathing state of the user based on the current physical detection data of the user, and to analyze the abnormal degree of gastric lavage of the user based on the current physical state of the user and the current breathing state of the user;

[0030] A generating module, configured to generate gastric lavage adjustment guidance information of a current gastric lavage method based on the gastric lavage abnormality degree of the user, the current gastric cleaning degree, and the current gastric damage degree through a gastric lavage adjustment strategy, and send the gastric lavage adjustment guidance information to a display terminal of a gastric lavage device to guide the staff to adjust the current gastric lavage method and then re-collect new body test data and new gastric lavage extract test data of the user;

[0031] An iterative module is used to adjust the gastric lavage adjustment guidance information based on the new gastric lavage extract detection data and the difference value through the gastric lavage adjustment strategy, generate target gastric lavage guidance information, and send the target gastric lavage guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, return to execute the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then re-collect the new body detection data of the user and the new gastric lavage extract detection data, until the gastric lavage task is completed.

[0032] Optionally, the acquisition module is specifically used to:

[0033] Based on the gastric lavage extraction data, identifying each gastric extraction component of the user and the component concentration of each gastric extraction component, and selecting a first component concentration of a blood extraction component and a second component concentration of a target extraction component from among the component concentrations of each gastric extraction component;

[0034] Based on the concentration of the first component of the blood extraction component, identifying the current degree of stomach damage through a stomach damage identification strategy;

[0035] Initial sampling information of the target extraction component of the user is collected, and based on the initial sampling information of the target extraction component and the second component concentration of the target extraction component, a current stomach cleansing degree is calculated.

[0036] Optionally, the analysis module is specifically used to:

[0037] Splitting the current body detection data of the user into current physiological detection data and current breathing detection data, and analyzing the current body state of the user through a body state analysis network based on the detection index values ​​of each physiological detection type in the current physiological detection data;

[0038] Based on the current breathing detection data of the user, the breathing detection value of each breathing detection type of the user is identified, and based on the breathing detection value of each breathing detection type, the current breathing state of the user is identified through a breathing detection graph.

[0039] Optionally, the analysis module is specifically used to:

[0040] Based on the current physical state of the user, query the user's physical function abnormality information in a physical state database, and based on the current breathing state of the user, query the user's breathing abnormality information in a breathing response database;

[0041] Based on the body function abnormality information and the user's breathing abnormality information, a gastric lavage abnormality degree of the user's gastric lavage abnormality type is analyzed through a gastric lavage abnormality analysis strategy.

[0042] Optionally, the generating module is specifically used for:

[0043] Based on the gastric cleansing degree and the initial sampling information of the target extraction component, identifying the current remaining component capacity of the target extraction component, and based on the current gastric damage degree, identifying the first physical tolerance range of each gastric lavage condition type of the user;

[0044] Based on the gastric lavage abnormality degree of the gastric lavage abnormality type of the user, identifying the second body tolerance range of each gastric lavage condition type of the user, and based on the first body tolerance range of each gastric lavage condition type and the second body tolerance range of each gastric lavage condition type, identifying the target body tolerance range of each gastric lavage condition type;

[0045] Based on the current remaining component capacity of the target extracted component and the target body tolerance range of each gastric lavage condition type, gastric lavage adjustment guidance information of the user is generated through a gastric lavage planning network.

[0046] Optionally, the iteration module is specifically used for:

[0047] Calculating a difference deviation value between the difference value and the difference threshold, and calculating a new target body tolerance range for each gastric lavage condition type based on the difference deviation value;

[0048] Based on the new gastric lavage extract detection data, the new remaining component capacity of the target extraction component is identified, and based on the new remaining component capacity and the new target body tolerance range of each gastric lavage condition type, the user's target gastric lavage guidance information is generated through the gastric lavage planning network.

[0049] In a third aspect, the present application provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0051] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0052] The present invention provides an intelligent gastric lavage auxiliary guidance method and system, the method comprising: obtaining the current gastric lavage method, gastric lavage extract detection data, and the user's current body detection data, and identifying the current gastric cleaning degree and the current gastric damage degree based on the gastric lavage extraction data; identifying the user's current body state and the user's current breathing state based on the user's current body detection data, and analyzing the user's gastric lavage abnormality degree based on the user's current body state and the user's current breathing state; based on the user's gastric lavage abnormality degree, the current gastric cleaning degree, and the current gastric damage degree, generating gastric lavage adjustment guidance information of the current gastric lavage method through a gastric lavage adjustment strategy, and sending the gastric lavage adjustment guidance information to a display terminal of a gastric lavage device, indicating After guiding the staff to adjust the current gastric lavage method, the new body examination data and the new gastric lavage extract examination data of the user are collected again; when the difference between the new gastric lavage abnormality degree corresponding to the new body examination data of the user and the gastric lavage abnormality degree is lower than the difference value threshold, based on the new gastric lavage extract examination data and the difference value, the gastric lavage adjustment guidance information is adjusted through the gastric lavage adjustment strategy to generate target gastric lavage guidance information, and the target gastric lavage guidance information is sent to the display terminal of the gastric lavage device to guide the staff to adjust the current gastric lavage method, and the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage device to guide the staff to adjust the current gastric lavage method is returned to execute, and the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage device to guide the staff to adjust the current gastric lavage method and the step of collecting the new body examination data and the new gastric lavage extract examination data of the user again is performed until the gastric lavage task is completed. This solution starts from multiple angles such as the current gastric lavage method, gastric lavage extract detection, and current body detection, and comprehensively analyzes the user's current gastric cleaning degree, gastric damage degree, and gastric lavage abnormality degree during gastric lavage, so as to perform multi-angle detection and analysis of the user's gastric lavage process in real time, so as to comprehensively judge whether the gastric lavage process causes secondary damage to the user's stomach and the user's body, and then generates the user's gastric lavage adjustment degree through the identified gastric cleaning degree and gastric damage degree, thereby improving the timeliness of the user's gastric lavage method adjustment and the accuracy of gastric lavage adjustment. Afterwards, the terminal analyzes the effect of gastric lavage adjustment by comparing the changes in the user's gastric lavage abnormality degree, and iteratively guides the staff to adjust the current gastric lavage method when the effect is not obvious / poor, so as to ensure that the user's gastric lavage abnormality degree is effectively and timely reduced. This makes this solution not only able to monitor the user's physical state in real time and comprehensively during the gastric lavage process, but also able to timely adjust the user's gastric lavage method and guide it, avoiding the low timeliness and low precision of manual guidance, thereby effectively improving the accuracy of damage avoidance during the gastric lavage process. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 is a flow chart of an intelligent gastric lavage auxiliary guidance method provided by an embodiment of the present invention;

[0055] Figure 2 is a structural schematic diagram of an intelligent gastric lavage auxiliary guidance system provided by an embodiment of the present invention;

[0056] Figure 3 An internal structure diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The intelligent gastric lavage auxiliary guidance method provided in the embodiment of the present invention is applied to the intelligent gastric lavage auxiliary guidance system. Unless otherwise defined, all technical and scientific terms used in this document have the same meaning as those generally understood by technicians in the technical field of this application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of this application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0058] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0059] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0060] The intelligent gastric lavage auxiliary guidance method provided in the embodiment of the present application can be applied to the application environment of auxiliary guidance of gastric lavage equipment. The method can be applied to a terminal, a server, or a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, etc. Among them, the terminal comprehensively analyzes the current gastric cleaning degree, gastric damage degree, and gastric lavage abnormality degree of the user during gastric lavage from multiple angles such as the current gastric lavage method, gastric lavage extract detection, and current body detection, so as to perform multi-angle detection and analysis on the gastric lavage process of the user in real time, so as to comprehensively judge whether the gastric lavage process causes secondary damage to the user's stomach and the user's body, and then generate the user's gastric lavage adjustment degree through the identified gastric cleaning degree and gastric damage degree, so as to improve the timeliness of the gastric lavage method adjustment and the accuracy of gastric lavage adjustment for the user. After that, the terminal analyzes the effect of gastric lavage adjustment by comparing the changes in the abnormal degree of gastric lavage of the user, and iteratively guides the staff to adjust the current gastric lavage method when the effect is not obvious / poor, so as to ensure that the abnormal degree of gastric lavage of the user is effectively and timely reduced. This solution not only monitors the user's physical condition in real time and comprehensively during the gastric lavage process, but also can promptly adjust and guide the user's gastric lavage method, avoiding the low timeliness and low precision of manual guidance, thereby effectively improving the accuracy of damage avoidance during the gastric lavage process.

[0061] In one embodiment, Figure 1 As shown, an intelligent gastric lavage auxiliary guidance method is provided, which is described by taking the application of the method to a terminal as an example, and includes the following steps:

[0062] Step S101, obtaining the current gastric lavage method, gastric lavage extract detection data, and the user's current body detection data, and identifying the current gastric cleaning degree and the current gastric damage degree based on the gastric lavage extraction data.

[0063] In this embodiment, the terminal acquires the current gastric lavage method of the gastric lavage device by collecting the current gastric lavage data of the gastric lavage device, and then performs real-time detection on the gastric lavage extract to obtain the gastric lavage extract detection data. Finally, the current body detection data of the user is collected by the body detection instrument set on the user's body surface. Among them, the current gastric lavage method is the gastric lavage solution data, flushing rate, single flushing volume, flushing and extraction frequency, etc. when the gastric lavage device currently lavages the user's stomach. The gastric lavage extract detection data includes the detection results obtained by detecting the components of each extract. Among them, the current body detection data includes but is not limited to physiological detection data and respiratory detection data. The physiological detection data includes detection index values ​​of various physiological detection types, and the physiological monitoring types include but are not limited to electrocardiogram detection data, pulse detection data, and body temperature detection data. The respiratory detection data includes respiratory monitoring values ​​of various respiratory detection types, and the respiratory detection types include but are not limited to respiratory frequency data, respiratory volume data, respiratory volume ratio data, respiratory rate data, etc. Finally, the terminal identifies the current degree of stomach cleaning and the current degree of stomach damage based on the gastric lavage extraction data. The specific identification process will be described in detail later.

[0064] Step S102, based on the user's current body detection data, identifying the user's current body state and the user's current breathing state, and analyzing the user's gastric lavage abnormality based on the user's current body state and the user's current breathing state.

[0065] In this embodiment, the terminal identifies the user's current physical state and the user's current breathing state based on the user's current physical detection data, and analyzes the user's gastric lavage abnormality based on the user's current physical state and the user's current breathing state. The gastric lavage abnormality degree includes gastric lavage abnormality degrees of different abnormal types, such as suffocation abnormality type, heart rate abnormality type, etc. The specific analysis process will be described in detail later. Among them, the current physical state includes but is not limited to normal state, epileptic state, low heart rate state, high heart rate state, etc., and the current breathing state includes but is not limited to normal state, respiratory rate disorder state, high respiratory rate state, low respiratory volume state, etc.

[0066] Step S103, based on the user's gastric lavage abnormality, current gastric cleaning degree, and current gastric damage degree, gastric lavage adjustment guidance information of the current gastric lavage method is generated through the gastric lavage adjustment strategy, and the gastric lavage adjustment guidance information is sent to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method and re-collect the user's new body test data and new gastric lavage extract test data.

[0067] In this embodiment, the terminal generates gastric lavage adjustment guidance information of the current gastric lavage method based on the user's gastric lavage abnormality, the current gastric cleaning degree, and the current gastric damage degree through the gastric lavage adjustment strategy, and sends the gastric lavage adjustment guidance information to the display terminal of the gastric lavage device to guide the staff to adjust the current gastric lavage method and re-collect the user's new body detection data and new gastric lavage extract detection data. Among them, the gastric lavage adjustment strategy is a guidance suggestion generation strategy for adjusting the gastric lavage solution data, flushing rate, single flushing volume, and flushing and extraction frequency of the current gastric lavage method. The specific generation process will be described in detail later.

[0068] Step S104, when the difference between the new gastric lavage abnormality degree corresponding to the user's new body test data and the gastric lavage abnormality degree is lower than the difference value threshold, based on the new gastric lavage extract test data and the difference value, the gastric lavage adjustment guidance information is adjusted through the gastric lavage adjustment strategy to generate target gastric lavage guidance information, and the target gastric lavage guidance information is sent to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and the gastric lavage adjustment guidance information is sent to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then the step of returning to execute the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then re-collecting the user's new body test data and new gastric lavage extract test data until the gastric lavage task is completed.

[0069] In this embodiment, when the difference between the new gastric lavage abnormality degree corresponding to the new body detection data of the user and the gastric lavage abnormality degree is lower than the difference value threshold, the terminal adjusts the gastric lavage adjustment guidance information based on the new gastric lavage extract detection data and the difference value through the gastric lavage adjustment strategy, generates the target gastric lavage guidance information, and sends the target gastric lavage guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, returns to execute the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then re-collects the user's new body detection data and the new gastric lavage extract detection data until the gastric lavage task is completed. When judging whether the gastric lavage task is completed, the current gastric cleaning degree can be identified for judgment. When the current gastric cleaning degree is 100% complete, it is determined that the gastric lavage task is completed.

[0070] Based on the above scheme, by starting from multiple angles such as the current gastric lavage method, gastric lavage extract detection, and current body detection, the current gastric cleaning degree, gastric damage degree, and gastric lavage abnormality of the user during gastric lavage are comprehensively analyzed, so as to perform multi-angle detection and analysis on the gastric lavage process of the user in real time, so as to comprehensively judge whether the gastric lavage process causes secondary damage to the user's stomach and the user's body, and then generate the gastric lavage adjustment degree of the user through the identified gastric cleaning degree and gastric damage degree, thereby improving the timeliness of the adjustment of the gastric lavage method and the accuracy of the gastric lavage adjustment. Afterwards, the terminal analyzes the effect of the gastric lavage adjustment by comparing the changes in the abnormal degree of the user's gastric lavage, and iteratively guides the staff to adjust the current gastric lavage method when the effect is not obvious / poor, so as to ensure that the abnormal degree of the user's gastric lavage is effectively and timely reduced. This scheme not only enables real-time and comprehensive monitoring of the user's physical state during the gastric lavage process, but also enables timely adjustment guidance of the user's gastric lavage method, avoiding the low timeliness and low precision of manual guidance, thereby effectively improving the accuracy of damage avoidance during the gastric lavage process.

[0071] Optionally, based on the gastric lavage extraction data, the current degree of gastric cleaning and the current degree of gastric damage are identified, including: based on the gastric lavage extraction data, identifying the user's various gastric extraction components and the component concentration of each gastric extraction component, and screening the first component concentration of the blood extraction component and the second component concentration of the target extraction component among the component concentrations of each gastric extraction component; based on the first component concentration of the blood extraction component, identifying the current degree of gastric damage through a gastric damage identification strategy; collecting the initial sampling information of the user's target extraction component, and calculating the current degree of gastric cleaning based on the initial sampling information of the target extraction component and the second component concentration of the target extraction component.

[0072] In this embodiment, the terminal identifies the user's various gastric extraction components and the component concentration of each gastric extraction component based on the gastric lavage extraction data, and screens the first component concentration of the blood extraction component and the second component concentration of the target extraction component among the component concentrations of each gastric extraction component.

[0073] The blood extraction components are blood components in the gastric extraction components, wherein the blood components include red blood cell components, white blood cell components, platelet components, etc. The target extraction components are the material components required for the current gastric lavage.

[0074] The terminal identifies the current degree of stomach damage based on the concentration of the first component of the blood extraction component through a stomach damage identification strategy. The stomach damage identification strategy includes the degree of stomach damage corresponding to the concentration range of each subcomponent in the blood extraction component, and then the terminal identifies the concentration range of each subcomponent through the collected component concentration to determine the user's stomach damage degree.

[0075] Afterwards, the terminal collects the initial sampling information of the user's target extraction component, and calculates the current stomach cleaning degree based on the initial sampling information of the target extraction component and the second component concentration of the target extraction component. Among them, the initial sampling information is the initial component concentration of the target extraction component in the stomach, and the calculated predicted total component content of the target extraction component. Then, the terminal calculates the deviation value between the initial component concentration and the second component concentration to obtain the first cleaning degree, and calculates the current extraction amount of the target extraction component based on the second component concentration and the extraction amount of all current gastric lavage extracts. Finally, the terminal calculates the ratio between the current extraction amount and the predicted total component content to obtain the second cleaning degree. The terminal uses the first cleaning degree and the second cleaning degree as the current stomach cleaning degree of the target extraction component.

[0076] Based on the above scheme, the degree of stomach damage and stomach cleansing of the user can be identified through component splitting analysis, which can not only accurately identify the user's stomach damage, but also effectively detect the current stomach cleansing process.

[0077] Optionally, based on the user's current body detection data, the user's current body state and the user's current breathing state are identified, including: splitting the user's current body detection data into current physiological detection data and current breathing detection data, and analyzing the user's current body state through a body state analysis network based on the detection index values ​​of each physiological detection type in the current physiological detection data; based on the user's current breathing detection data, identifying the user's breathing detection values ​​of each breathing detection type, and based on the breathing detection values ​​of each breathing detection type, identifying the user's current breathing state through a breathing detection graph.

[0078] In this embodiment, the terminal splits the user's current body detection data into current physiological detection data and current breathing detection data, and analyzes the user's current body state through a body state analysis network based on the detection index values ​​of each physiological detection type in the current physiological detection data. The body state analysis network is a classifier based on a reinforcement learning neural network, in which the detection index value range of each physiological detection type corresponding to each body state is preset, and then the classifier determines the user's current body state by identifying the detection index value range to which the detection index value of each physiological detection type in the current detection data belongs.

[0079] Based on the user's current breathing detection data, the breathing detection value of each breathing detection type of the user is identified, and based on the breathing detection value of each breathing detection type, the user's current breathing state is identified through the breathing detection graph. The breathing monitoring graph is a knowledge graph for judging the breathing state preset in the terminal by the staff, wherein the knowledge graph includes the detection value range corresponding to the breathing detection value of each breathing detection type and the association information between each breathing state. Then, the terminal queries the knowledge graph through the breathing detection value of each breathing detection type in the current breathing detection data to obtain the current breathing state of the user.

[0080] Based on the above solution, different recognition strategies are used to determine the user's current physical state and current breathing state, thereby improving the accuracy and comprehensiveness of the determination.

[0081] Optionally, based on the user's current physical state and the user's current breathing state, the degree of gastric lavage abnormality of the user is analyzed, including: based on the user's current physical state, querying the user's abnormal body function information in a body state database, and based on the user's current breathing state, querying the user's abnormal breathing information in a breathing response database; based on the abnormal body function information and the user's abnormal breathing information, analyzing the degree of gastric lavage abnormality of the user's gastric lavage abnormality type through a gastric lavage abnormality analysis strategy.

[0082] In this embodiment, the terminal queries the user's body function abnormality information in the body state database based on the user's current body state, and queries the user's breathing abnormality information in the breathing reaction database based on the user's current breathing state. The body state database includes body function abnormality information corresponding to different body states, and the breathing reaction database includes breathing abnormality information corresponding to each breathing state. For example, the body function abnormality information, the body function abnormality information corresponding to the high heart rate state is gastric dilatation abnormality, etc., the body function abnormality information corresponding to the epileptic state is gastric perforation abnormality, etc., the breathing frequency disorder state corresponds to breathing abnormality information as obstructed breathing, and the breathing volume state corresponds to breathing abnormality information as suffocation abnormality.

[0083] The terminal analyzes the gastric lavage abnormality degree of the gastric lavage abnormality type of the user based on the body function abnormality information and the user's breathing abnormality information through the gastric lavage abnormality analysis strategy. Among them, the gastric lavage abnormality analysis strategy includes the body function abnormality information range and the breathing abnormality information range corresponding to each gastric lavage abnormality type. The gastric lavage abnormality degree of each gastric lavage abnormality type corresponds to the abnormality degree range of each body function abnormality information and the abnormality degree range corresponding to the breathing abnormality information.

[0084] Based on the above scheme, after analyzing the abnormal body function information and the abnormal breathing information, the abnormal gastric lavage type and the degree of abnormal gastric lavage of the user are determined, thereby improving the accuracy and comprehensiveness of the determination.

[0085] Optionally, based on the user's gastric lavage abnormality level, current gastric cleaning level, and current gastric damage level, gastric lavage adjustment guidance information for the current gastric lavage method is generated through a gastric lavage adjustment strategy, including: based on the gastric cleaning level and the initial sampling information of the target extracted components, identifying the current remaining component capacity of the target extracted components, and based on the current gastric damage level, identifying the first body tolerance range of each gastric lavage condition type of the user; based on the gastric lavage abnormality level of the user's gastric lavage abnormality type, identifying the second body tolerance range of each gastric lavage condition type of the user, and based on the first body tolerance range of each gastric lavage condition type and the second body tolerance range of each gastric lavage condition type, identifying the target body tolerance range of each gastric lavage condition type; based on the current remaining component capacity of the target extracted components and the target body tolerance range of each gastric lavage condition type, generating the user's gastric lavage adjustment guidance information through a gastric lavage planning network.

[0086] In this embodiment, the terminal identifies the current remaining component capacity of the target extraction component based on the degree of gastric cleaning and the initial sampling information of the target extraction component, and identifies the first body tolerance range of each gastric lavage condition type of the user based on the current degree of gastric damage. Among them, each gastric lavage condition type includes but is not limited to a gastric lavage solution data type, a flushing rate type, a single flushing volume type, and a flushing and extraction frequency type, and the first body tolerance range of each gastric lavage condition type includes the gastric lavage solution data, the proportion of the content of the cleaning solution substance in all solution volumes, the flushing rate range, the single flushing volume range, and the flushing and extraction frequency range, etc.

[0087] The terminal identifies the second body tolerance range of each gastric lavage condition type of the user based on the gastric lavage abnormality degree of the gastric lavage abnormality type of the user. The terminal stores the corresponding relationship between each gastric lavage abnormality type and the body tolerance range of each gastric lavage condition type. Then, the terminal adjusts the range size of each body tolerance range based on the gastric lavage abnormality degree of the gastric lavage abnormality type to obtain the second body tolerance range of each gastric lavage condition type. The adjustment method is to multiply the percentage value corresponding to the gastric lavage abnormality degree by each range value of the body tolerance range to obtain the second body tolerance range.

[0088] Then, the terminal identifies the target body tolerance range of each gastric lavage condition type based on the first body tolerance range of each gastric lavage condition type and the second body tolerance range of each gastric lavage condition type, wherein the target body tolerance range is the overlapped range of the first body tolerance range and the second body tolerance range.

[0089] Finally, the terminal generates gastric lavage adjustment guidance information for the user through the gastric lavage planning network based on the current remaining component capacity of the target extraction component and the target body tolerance range of each gastric lavage condition type. The gastric lavage planning network is a convolutional neural network based on the self-attention mechanism, which is used to screen the gastric lavage guidance data with the highest gastric lavage efficiency within the target body tolerance range of each gastric lavage condition type based on the current remaining component capacity and the target body tolerance range of each gastric lavage condition type.

[0090] Based on the above scheme, the user's gastric lavage adjustment guidance information is comprehensively analyzed based on the gastric lavage abnormality type, the degree of gastric lavage abnormality, and the current degree of stomach damage. This ensures that when performing gastric lavage on the user, the efficiency of gastric lavage can be ensured and the degree of stomach absorption of target extracted components can be reduced, while also improving the accuracy of damage avoidance during the gastric lavage process.

[0091] Optionally, based on the new gastric lavage extract detection data and the difference value, the gastric lavage adjustment guidance information is adjusted through the gastric lavage adjustment strategy to generate target gastric lavage guidance information, including: calculating the difference value, the difference deviation value between the difference threshold, and calculating the new target body tolerance range of each gastric lavage condition type based on the difference deviation value; based on the new gastric lavage extract detection data, identifying the new remaining component capacity of the target extraction component, and based on the new remaining component capacity and the new target body tolerance range of each gastric lavage condition type, generating the user's target gastric lavage guidance information through the gastric lavage planning network.

[0092] In this embodiment, the terminal calculates the difference value and the difference deviation value between the difference value and the difference threshold, and calculates the new target body tolerance range of each gastric lavage condition type based on the difference deviation value. The calculation method is to return to the above steps to regenerate the new target body tolerance range of each gastric lavage condition type by the gastric lavage abnormality degree corresponding to each difference deviation value.

[0093] Finally, the terminal identifies the new remaining component capacity of the target extraction component based on the new gastric lavage extract detection data, and generates the user's target gastric lavage guidance information through the gastric lavage planning network based on the new remaining component capacity and the new target body tolerance range of each gastric lavage condition type. The planning process of the gastric lavage planning network is the same as the planning process described above, and no redundant description is given here.

[0094] Based on the above solution, through real-time detection and real-time adjustment of gastric lavage guidance, the gastric lavage guidance effect and accuracy for users are improved.

[0095] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0096] Based on the same inventive concept, the embodiment of the present application also provides an intelligent gastric lavage auxiliary guidance system for implementing the intelligent gastric lavage auxiliary guidance method involved above. The implementation solution provided by the system to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more intelligent gastric lavage auxiliary guidance system embodiments provided below can refer to the limitations of the intelligent gastric lavage auxiliary guidance method above, and will not be repeated here.

[0097] Further references Figure 2 , as a response to the above Figure 1 In order to realize the method shown in the figure, the present application provides an embodiment of an intelligent gastric lavage auxiliary guidance system 200, which includes an acquisition module 210, an analysis module 220, a generation module 230 and an iteration module 240, wherein:

[0098] The acquisition module 210 is used to acquire the current gastric lavage method, gastric lavage extract test data, and the user's current body test data, and identify the current gastric cleaning degree and the current gastric damage degree based on the gastric lavage extract data;

[0099] An analysis module 220, configured to identify the current physical state of the user and the current respiratory state of the user based on the current physical detection data of the user, and analyze the abnormal degree of gastric lavage of the user based on the current physical state of the user and the current respiratory state of the user;

[0100] The generating module 230 is used to generate gastric lavage adjustment guidance information of the current gastric lavage method based on the gastric lavage abnormality degree of the user, the current gastric cleaning degree, and the current gastric damage degree through the gastric lavage adjustment strategy, and send the gastric lavage adjustment guidance information to the display terminal of the gastric lavage device to guide the staff to adjust the current gastric lavage method and re-collect new body test data and new gastric lavage extract test data of the user;

[0101] Iterative module 240 is used to adjust the gastric lavage adjustment guidance information based on the new gastric lavage extract detection data and the difference value through the gastric lavage adjustment strategy, generate target gastric lavage guidance information, and send the target gastric lavage guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, return to execute the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then re-collect the new body detection data of the user and the new gastric lavage extract detection data, until the gastric lavage task is completed.

[0102] Optionally, the acquisition module 210 is specifically configured to:

[0103] Based on the gastric lavage extraction data, identifying each gastric extraction component of the user and the component concentration of each gastric extraction component, and selecting a first component concentration of a blood extraction component and a second component concentration of a target extraction component from among the component concentrations of each gastric extraction component;

[0104] Based on the concentration of the first component of the blood extraction component, identifying the current degree of stomach damage through a stomach damage identification strategy;

[0105] Initial sampling information of the target extraction component of the user is collected, and based on the initial sampling information of the target extraction component and the second component concentration of the target extraction component, a current stomach cleansing degree is calculated.

[0106] Optionally, the analysis module 220 is specifically used for:

[0107] Splitting the current body detection data of the user into current physiological detection data and current breathing detection data, and analyzing the current body state of the user through a body state analysis network based on the detection index values ​​of each physiological detection type in the current physiological detection data;

[0108] Based on the current breathing detection data of the user, the breathing detection value of each breathing detection type of the user is identified, and based on the breathing detection value of each breathing detection type, the current breathing state of the user is identified through a breathing detection graph.

[0109] Optionally, the analysis module 220 is specifically used for:

[0110] Based on the current physical state of the user, query the user's physical function abnormality information in a physical state database, and based on the current breathing state of the user, query the user's breathing abnormality information in a breathing response database;

[0111] Based on the body function abnormality information and the user's breathing abnormality information, a gastric lavage abnormality degree of the user's gastric lavage abnormality type is analyzed through a gastric lavage abnormality analysis strategy.

[0112] Optionally, the generating module 230 is specifically configured to:

[0113] Based on the gastric cleansing degree and the initial sampling information of the target extraction component, identifying the current remaining component capacity of the target extraction component, and based on the current gastric damage degree, identifying the first physical tolerance range of each gastric lavage condition type of the user;

[0114] Based on the gastric lavage abnormality degree of the gastric lavage abnormality type of the user, identifying the second body tolerance range of each gastric lavage condition type of the user, and based on the first body tolerance range of each gastric lavage condition type and the second body tolerance range of each gastric lavage condition type, identifying the target body tolerance range of each gastric lavage condition type;

[0115] Based on the current remaining component capacity of the target extracted component and the target body tolerance range of each gastric lavage condition type, gastric lavage adjustment guidance information of the user is generated through a gastric lavage planning network.

[0116] Optionally, the iteration module 240 is specifically configured to:

[0117] Calculating a difference deviation value between the difference value and the difference threshold, and calculating a new target body tolerance range for each gastric lavage condition type based on the difference deviation value;

[0118] Based on the new gastric lavage extract detection data, the new remaining component capacity of the target extraction component is identified, and based on the new remaining component capacity and the new target body tolerance range of each gastric lavage condition type, the user's target gastric lavage guidance information is generated through the gastric lavage planning network.

[0119] Each module in the above intelligent gastric lavage auxiliary guidance system can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0120] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input system connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an intelligent gastric lavage auxiliary guidance method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0121] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0122] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of any one of the methods in the first aspect are implemented.

[0123] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0124] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0125] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0126] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0127] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0128] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An intelligent gastric lavage auxiliary guidance method, characterized in that: The method comprises: Obtaining the current gastric lavage method, gastric lavage extract test data, and the user's current body test data, and identifying the current gastric cleaning degree and the current gastric damage degree based on the gastric lavage extract data; Based on the current body detection data of the user, identifying the current body state of the user and the current breathing state of the user, and analyzing the abnormal degree of gastric lavage of the user based on the current body state of the user and the current breathing state of the user; Based on the user's gastric lavage abnormality, the current gastric cleaning degree, and the current gastric damage degree, gastric lavage adjustment guidance information of the current gastric lavage method is generated through a gastric lavage adjustment strategy, and the gastric lavage adjustment guidance information is sent to the display terminal of the gastric lavage device to guide the staff to adjust the current gastric lavage method and re-collect new body test data and new gastric lavage extract test data of the user; When the difference between the new gastric lavage abnormality degree corresponding to the new body test data of the user and the gastric lavage abnormality degree is lower than the difference value threshold, based on the new gastric lavage extract test data and the difference value, the gastric lavage adjustment guidance information is adjusted through the gastric lavage adjustment strategy to generate target gastric lavage guidance information, and the target gastric lavage guidance information is sent to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and the step of returning to execute the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then re-collecting the new body test data of the user and the new gastric lavage extract test data until the gastric lavage task is completed.

2. The method according to claim 1, characterized in that The method of identifying the current degree of gastric cleansing and the current degree of gastric damage based on the gastric lavage extraction data includes: Based on the gastric lavage extraction data, identifying each gastric extraction component of the user and the component concentration of each gastric extraction component, and selecting a first component concentration of a blood extraction component and a second component concentration of a target extraction component from among the component concentrations of each gastric extraction component; Based on the concentration of the first component of the blood extraction component, identifying the current degree of stomach damage through a stomach damage identification strategy; Initial sampling information of the target extraction component of the user is collected, and based on the initial sampling information of the target extraction component and the second component concentration of the target extraction component, a current stomach cleansing degree is calculated.

3. The method according to claim 2, characterized in that The identifying the current physical state of the user and the current breathing state of the user based on the current physical detection data of the user includes: Splitting the current body detection data of the user into current physiological detection data and current breathing detection data, and analyzing the current body state of the user through a body state analysis network based on the detection index values ​​of each physiological detection type in the current physiological detection data; Based on the current breathing detection data of the user, the breathing detection value of each breathing detection type of the user is identified, and based on the breathing detection value of each breathing detection type, the current breathing state of the user is identified through a breathing detection graph.

4. The method according to claim 3, characterized in that: The analyzing the abnormality degree of the user's gastric lavage based on the user's current physical state and the user's current breathing state includes: Based on the current physical state of the user, query the user's physical function abnormality information in a physical state database, and based on the current breathing state of the user, query the user's breathing abnormality information in a breathing response database; Based on the body function abnormality information and the user's breathing abnormality information, a gastric lavage abnormality degree of the user's gastric lavage abnormality type is analyzed through a gastric lavage abnormality analysis strategy.

5. The method according to claim 4, characterized in that The generating of gastric lavage adjustment guidance information of the current gastric lavage method through a gastric lavage adjustment strategy based on the gastric lavage abnormality degree of the user, the current gastric cleaning degree, and the current gastric damage degree includes: Based on the gastric cleansing degree and the initial sampling information of the target extraction component, identifying the current remaining component capacity of the target extraction component, and based on the current gastric damage degree, identifying the first physical tolerance range of each gastric lavage condition type of the user; Based on the gastric lavage abnormality degree of the gastric lavage abnormality type of the user, identifying the second body tolerance range of each gastric lavage condition type of the user, and based on the first body tolerance range of each gastric lavage condition type and the second body tolerance range of each gastric lavage condition type, identifying the target body tolerance range of each gastric lavage condition type; Based on the current remaining component capacity of the target extracted component and the target body tolerance range of each gastric lavage condition type, gastric lavage adjustment guidance information of the user is generated through a gastric lavage planning network.

6. The method according to claim 5, characterized in that The step of adjusting the gastric lavage adjustment guidance information based on the new gastric lavage extract detection data and the difference value through the gastric lavage adjustment strategy to generate target gastric lavage guidance information includes: Calculating a difference deviation value between the difference value and the difference threshold, and calculating a new target body tolerance range for each gastric lavage condition type based on the difference deviation value; Based on the new gastric lavage extract detection data, the new remaining component capacity of the target extraction component is identified, and based on the new remaining component capacity and the new target body tolerance range of each gastric lavage condition type, the user's target gastric lavage guidance information is generated through the gastric lavage planning network.

7. An intelligent gastric lavage auxiliary guidance system, characterized in that: The system comprises: An acquisition module, used to acquire the current gastric lavage method, gastric lavage extract test data, and the user's current body test data, and to identify the current gastric cleaning degree and the current gastric damage degree based on the gastric lavage extract data; an analysis module, configured to identify the current physical state of the user and the current breathing state of the user based on the current physical detection data of the user, and to analyze the abnormal degree of gastric lavage of the user based on the current physical state of the user and the current breathing state of the user; A generating module, configured to generate gastric lavage adjustment guidance information of a current gastric lavage method based on the gastric lavage abnormality degree of the user, the current gastric cleaning degree, and the current gastric damage degree through a gastric lavage adjustment strategy, and send the gastric lavage adjustment guidance information to a display terminal of a gastric lavage device to guide the staff to adjust the current gastric lavage method and then re-collect new body test data and new gastric lavage extract test data of the user; An iterative module is used to adjust the gastric lavage adjustment guidance information based on the new gastric lavage extract detection data and the difference value through the gastric lavage adjustment strategy, generate target gastric lavage guidance information, and send the target gastric lavage guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, return to execute the step of sending the gastric lavage adjustment guidance information to the display terminal of the gastric lavage equipment to guide the staff to adjust the current gastric lavage method, and then re-collect the new body detection data of the user and the new gastric lavage extract detection data, until the gastric lavage task is completed.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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