Oxygen flow dynamic conveying control method and system

Abstract

The invention provides an oxygen flow dynamic conveying control method and system, and the method comprises the steps: obtaining the current driving road information of an ambulance and the current body sign data of a user, and recognizing the current road condition information of a vehicle driving route of the ambulance based on the current driving road information of the ambulance; identifying current physical sign data distribution information of each physical sign data type of the user based on the current physical sign data of the user, and identifying an oxygen demand range of the user through an oxygen delivery amount analysis model based on the current physical sign data distribution information of each physical sign data type; and based on the current road condition information of the vehicle driving route of the ambulance and the oxygen demand range of the user, current dynamic oxygen supply distribution information of the user is generated through an oxygen supply analysis model, and based on the current dynamic oxygen supply distribution information, a current oxygen supply dynamic control strategy of the oxygen tank is generated. By adopting the scheme, the supply dynamic adaptation degree of oxygen supply for the user can be comprehensively improved.

Description

Technical Field

[0001] The present invention relates to the field of dynamic oxygen adjustment and intelligent medical technology, and in particular to a method and system for dynamic oxygen flow delivery control. Background Art

[0002] Oxygen supply to patients is one of the primary methods for maintaining a user's vital signs, ensuring their life, and assisting them with meeting their normal oxygen needs. This is especially true for critically ill patients, those in coma, and those whose consciousness is unclear. Effective oxygen supply can ensure the user maintains their current condition and even escapes life-threatening danger. This is especially true during ambulance travel, which is often the golden rescue period for the user. However, due to excessive speed, vehicle deviation, bumps, acceleration and deceleration, etc., the user's actual vital signs can vary greatly, and traditional stable oxygen supply alone is often unable to meet the user's vital sign maintenance needs. Therefore, improving oxygen delivery under dynamic environmental conditions is a current research focus.

[0003] The traditional supply and delivery method is to fix the valve size and provide steady-state supply to users. However, when encountering bumpy roads, vehicle turns, vehicle acceleration and deceleration, and vehicle deviation, vehicle supply often results in oxygen supply interruption, oxygen oversupply, oxygen undersupply, etc., affecting the user's vital signs, resulting in a low dynamic adaptability of the oxygen supply. Summary of the Invention

[0004] The main purpose of the present invention is to provide a method and system for dynamic oxygen flow delivery control, aiming to solve the problem in the prior art that when encountering bumpy roads, vehicle turns, vehicle acceleration and deceleration, and vehicle deviation, vehicle supply often suffers from oxygen supply interruption, oxygen oversupply, oxygen undersupply, etc., affecting the maintenance of the user's vital signs, thereby resulting in low dynamic adaptability of oxygen supply.

[0005] To achieve the above object, the present invention provides a method for dynamically controlling oxygen flow rate, the method comprising:

[0006] Acquiring current driving road information of the ambulance and current physical sign data of the user, and identifying current road condition information of the ambulance's driving route based on the current driving road information of the ambulance;

[0007] identifying, based on the current physical sign data of the user, current physical sign data distribution information of each physical sign data type of the user, and identifying, based on the current physical sign data distribution information of each physical sign data type, an oxygen demand range of the user using an oxygen delivery analysis model;

[0008] Based on the current road condition information of the ambulance's route and the user's oxygen demand range, the user's current dynamic oxygen supply distribution information is generated through an oxygen supply analysis model, and based on the current dynamic oxygen supply distribution information, a current oxygen supply dynamic control strategy for the oxygen tank is generated.

[0009] Optionally, the identifying current road condition information of the ambulance's driving route based on the current driving road information of the ambulance includes:

[0010] identifying current road data of a vehicle driving route of the ambulance based on current driving road information of the ambulance;

[0011] Based on the current road data, identifying road condition data distribution information of each road condition type of the vehicle driving route, and based on the vehicle driving route, extracting route feature data of the vehicle driving route through a route feature extraction network;

[0012] The road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route are used as the current road condition information of the vehicle driving route of the ambulance.

[0013] Optionally, the identifying, based on the current physical sign data of the user, current physical sign data distribution information of each physical sign data type of the user includes:

[0014] Splitting the current body sign data into indicator data distribution information of each sign indicator type;

[0015] The indicator data distribution information of each of the physical sign indicator types is subjected to data conversion processing to obtain current physical sign data distribution information of each of the physical sign data types.

[0016] Optionally, the oxygen delivery analysis model includes an oxygen demand analysis model and an oxygen demand prediction model, and identifying the user's oxygen demand range through the oxygen delivery analysis model based on the current vital sign data distribution information of each vital sign data type includes:

[0017] Based on the current vital sign data distribution information of each of the vital sign data types, identifying the data distribution characteristics of each of the vital sign data types and the data trend characteristics of each of the vital sign data types;

[0018] Based on the data distribution characteristics of each of the vital sign data types, the oxygen demand analysis model is used to identify a first oxygen demand range of the user; and based on the data trend characteristics of each of the vital sign data types, the oxygen demand prediction model is used to identify a second oxygen demand range of the user;

[0019] An oxygen requirement range of the user is identified based on the first oxygen requirement range of the user and the second oxygen requirement range of the user.

[0020] Optionally, the generating of the user's current dynamic oxygen supply distribution information by an oxygen supply analysis model based on the current road condition information of the ambulance's route and the user's oxygen demand range includes:

[0021] Based on the road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route, identifying the interference data distribution information of each road condition interference type in each road section area of ​​the vehicle driving route through a road condition index analysis strategy;

[0022] For each road section area, based on the interference data distribution information of each road interference type in the road section area, predicting the vital sign data change information of each vital sign data type of the user through a vital sign data prediction network;

[0023] Based on the vital sign data change information of each vital sign data type and the oxygen demand range of the user, the actual oxygen supply demand range corresponding to the road section area is identified, and the actual oxygen supply demand range corresponding to all road section areas is used as the current dynamic oxygen supply distribution information of the user.

[0024] Optionally, the interference data distribution information of each road interference type in the road section area, and predicting the vital sign data change information of each vital sign data type of the user through a vital sign data prediction network, include:

[0025] Fitting an interference data variation curve diagram of each of the road condition interference types based on the interference data distribution information of each of the road condition interference types;

[0026] Obtaining a weighted value of the influence of each road interference type on the physical sign change, and identifying a physical sign change influence curve corresponding to each road interference type based on the interference data change curve of each road interference type and the weighted value of the influence of each road interference type on the physical sign change;

[0027] Based on the physical sign change influence curve diagram corresponding to each of the road interference types, the physical sign data change information of each of the physical sign data types of the user is predicted through a physical sign data prediction network.

[0028] In addition, to achieve the above-mentioned purpose, the present invention also provides an oxygen flow dynamic delivery control system, which includes:

[0029] an acquisition module, configured to acquire information about the current travel route of the ambulance and the current physical sign data of the user, and identify current road condition information of the vehicle travel route of the ambulance based on the information about the current travel route of the ambulance;

[0030] an identification module, configured to identify, based on the current physical sign data of the user, current physical sign data distribution information of each physical sign data type of the user, and identify, based on the current physical sign data distribution information of each physical sign data type, an oxygen demand range of the user using an oxygen delivery analysis model;

[0031] The generation module is used to generate the user's current dynamic oxygen supply distribution information based on the current road condition information of the ambulance's vehicle route and the user's oxygen demand range through an oxygen supply analysis model, and generate a current oxygen supply dynamic control strategy for the oxygen tank based on the current dynamic oxygen supply distribution information.

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

[0033] identifying current road data of a vehicle driving route of the ambulance based on current driving road information of the ambulance;

[0034] Based on the current road data, identifying road condition data distribution information of each road condition type of the vehicle driving route, and based on the vehicle driving route, extracting route feature data of the vehicle driving route through a route feature extraction network;

[0035] The road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route are used as the current road condition information of the vehicle driving route of the ambulance.

[0036] Optionally, the identification module is specifically configured to:

[0037] Splitting the current body sign data into indicator data distribution information of each sign indicator type;

[0038] The indicator data distribution information of each of the physical sign indicator types is subjected to data conversion processing to obtain current physical sign data distribution information of each of the physical sign data types.

[0039] Optionally, the identification module is specifically configured to:

[0040] Based on the current vital sign data distribution information of each of the vital sign data types, identifying the data distribution characteristics of each of the vital sign data types and the data trend characteristics of each of the vital sign data types;

[0041] Based on the data distribution characteristics of each of the vital sign data types, the oxygen demand analysis model is used to identify a first oxygen demand range of the user; and based on the data trend characteristics of each of the vital sign data types, the oxygen demand prediction model is used to identify a second oxygen demand range of the user;

[0042] An oxygen requirement range of the user is identified based on the first oxygen requirement range of the user and the second oxygen requirement range of the user.

[0043] Optionally, the generating module is specifically configured to:

[0044] Based on the road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route, identifying the interference data distribution information of each road condition interference type in each road section area of ​​the vehicle driving route through a road condition index analysis strategy;

[0045] For each road section area, based on the interference data distribution information of each road interference type in the road section area, predicting the vital sign data change information of each vital sign data type of the user through a vital sign data prediction network;

[0046] Based on the vital sign data change information of each vital sign data type and the oxygen demand range of the user, the actual oxygen supply demand range corresponding to the road section area is identified, and the actual oxygen supply demand range corresponding to all road section areas is used as the current dynamic oxygen supply distribution information of the user.

[0047] Optionally, the generating module is specifically configured to:

[0048] Fitting an interference data variation curve diagram of each of the road condition interference types based on the interference data distribution information of each of the road condition interference types;

[0049] Obtaining a weighted value of the influence of each road interference type on the physical sign change, and identifying a physical sign change influence curve corresponding to each road interference type based on the interference data change curve of each road interference type and the weighted value of the influence of each road interference type on the physical sign change;

[0050] Based on the physical sign change influence curve diagram corresponding to each of the road interference types, the physical sign data change information of each of the physical sign data types of the user is predicted through a physical sign data prediction network.

[0051] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the methods described in the first aspect when executing the computer program.

[0052] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0053] In a fifth aspect, the present application provides a computer program product, wherein the computer program product comprises 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.

[0054] The present invention provides a method and system for dynamic oxygen flow delivery control, the method comprising: obtaining current driving road information of an ambulance and current physical sign data of a user, and identifying current road condition information of the ambulance's vehicle driving route based on the current physical sign data of the ambulance; identifying current physical sign data distribution information of each physical sign data type of the user based on the current physical sign data of the user, and identifying the user's oxygen demand range through an oxygen delivery volume analysis model based on the current physical sign data distribution information of each physical sign data type; generating the user's current dynamic oxygen supply distribution information through an oxygen supply analysis model based on the current road condition information of the ambulance's vehicle driving route and the user's oxygen demand range, and generating a current oxygen supply dynamic control strategy for an oxygen tank based on the current dynamic oxygen supply distribution information. This solution first performs intelligent analysis on the user's current vital sign data to identify the current vital sign data distribution information of each vital sign data type of the user, thereby analyzing the user's oxygen demand range, and effectively controlling the oxygen supply of the oxygen tank to maintain it within the user's oxygen demand range, ensuring the user's normal oxygen needs. Then, this solution combines the ambulance's current driving route information and current road condition information to analyze the impact of changing road conditions on the user's vital sign data (bumping, acceleration / braking, turning, uphill and downhill). Then, based on the user's supply demand range, this solution ensures that the oxygen supply can be adjusted in real time as the user's vital signs change when the vehicle bumps, accelerates / decelerates, turns, and goes uphill and downhill, thereby dynamically and real-time meeting the user's oxygen needs, ensuring the effective maintenance of the user's vital signs, and comprehensively improving the dynamic adaptability of the user's oxygen supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the solutions in this application, a brief introduction will be given below to the drawings required for use in the description of the embodiments of this application. Obviously, the drawings described below are some embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0056] Figure 1is a flow chart of a method for dynamic oxygen flow delivery control provided by an embodiment of the present invention;

[0057] Figure 2 Schematic diagram of the structure of the oxygen flow dynamic delivery control system provided by an embodiment of the present invention;

[0058] Figure 3 This is a diagram of the internal structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The oxygen flow dynamic delivery control method provided by the embodiment of the present invention is applied to the oxygen flow dynamic delivery control system. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly 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.

[0060] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0061] 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.

[0062] The oxygen flow dynamic delivery control method provided in the embodiments of the present application can be applied in an oxygen flow dynamic delivery control application environment. The method can be applied to a terminal, a server, or a system including a terminal and a server, and implemented through interaction between the terminal and the server. The terminal can be, but is not limited to, various personal computers, laptop computers, and the like. Among them, the terminal first performs intelligent analysis on the user's current physical sign data to identify the current physical sign data distribution information of each physical sign data type of the user, thereby analyzing the user's oxygen demand range, and effectively controlling the oxygen supply of the oxygen tank to maintain it within the user's oxygen demand range, ensuring the user's normal oxygen demand. Then, this solution combines the vehicle route of the ambulance's current driving road information and current road condition information to analyze the impact of road condition changes on the user's physical sign data (bumping, acceleration / braking, turning, uphill and downhill). Then, based on the user's supply demand range, it ensures that when the vehicle bumps, accelerates / decelerates, turns, and goes uphill and downhill, the oxygen supply can be adjusted in real time as the user's physical signs change, thereby dynamically and in real time meeting the user's oxygen demand, ensuring that the user's vital signs are effectively maintained, and comprehensively improving the dynamic adaptability of the user's oxygen supply.

[0063] In one embodiment, Figure 1 As shown, a method for dynamic oxygen flow delivery control is provided, which is described by taking the application of the method to a terminal as an example, and includes the following steps:

[0064] Step S101 , obtaining the current driving road information of the ambulance and the current physical sign data of the user, and identifying the current road condition information of the ambulance's vehicle driving route based on the current driving road information of the ambulance.

[0065] In this embodiment, the terminal receives real-time road condition information transmitted by the ambulance's navigation device to obtain the ambulance's current route information. Furthermore, a physical sign data collection device (physical sign detection device) mounted on the user's body surface collects real-time indicator data for various types of the user's physical signs to obtain the user's current physical sign data. This road condition information includes the ambulance's route and the road conditions along the route (e.g., congested, normal, uphill and downhill, turning, road grade, and speed limit). Finally, based on the ambulance's current route information, the terminal identifies the current road condition information for the ambulance's route. This current road condition information includes distribution information for each road condition type and route feature data for the route. Road condition types include congestion type and speed limit type, while route feature data includes, but is not limited to, road grade feature data, road turning feature data, and uphill and downhill feature data. The image recognition process will be described in detail later.

[0066] Step S102: Based on the user's current physical sign data, current physical sign data distribution information of each physical sign data type of the user is identified, and based on the current physical sign data distribution information of each physical sign data type, the user's oxygen demand range is identified through an oxygen delivery analysis model.

[0067] In this embodiment, the terminal identifies the current vital sign data distribution information for each of the user's vital sign data types based on the user's current physical sign data. Based on this current vital sign data distribution information for each of the vital sign data types, the terminal uses an oxygen delivery analysis model to identify the user's oxygen requirement range. Vital sign data types include, but are not limited to, heart rate type, blood pressure type, respiratory status type, etc. The oxygen delivery analysis model is a deep learning-based artificial neural network that combines the current vital sign data distribution information for each of the vital sign data types to identify the user's oxygen requirement range. The specific identification process will be described in detail later.

[0068] Step S103, based on the current road condition information of the ambulance's route and the user's oxygen demand range, the user's current dynamic oxygen supply distribution information is generated through the oxygen supply analysis model, and based on the current dynamic oxygen supply distribution information, the current oxygen supply dynamic control strategy of the oxygen tank is generated.

[0069] In this embodiment, the terminal generates the user's current dynamic oxygen supply distribution information based on the current road condition information of the ambulance's route and the user's oxygen demand range through an oxygen supply analysis model. Based on this dynamic oxygen supply distribution information, the terminal generates a dynamic oxygen supply control strategy for the oxygen tank. The oxygen supply analysis model is a convolutional neural network based on an attention mechanism. The terminal converts the current dynamic oxygen supply distribution information into dynamic supply instructions, which it then sends to a preset oxygen control device to dynamically control the current dynamic oxygen supply control strategy for the oxygen tank. In actual application, this solution will iterate the above steps, collecting real-time information about the ambulance's current route and the user's current physical sign data, thereby dynamically adjusting the current dynamic oxygen supply control strategy to ensure that the oxygen tank's current oxygen supply meets the real-time and dynamic user needs.

[0070] Based on the above solution, by first performing intelligent analysis on the user's current vital sign data, the current vital sign data distribution information of each type of the user's vital sign data is identified, and the user's oxygen demand range is analyzed, thereby effectively controlling the oxygen supply of the oxygen tank to maintain it within the user's oxygen demand range, ensuring the user's normal oxygen demand. Then, this solution combines the ambulance's current driving route information and the vehicle's current road condition information to analyze the degree of impact of road condition changes on the user's vital sign data (bumping, acceleration / braking, turning, uphill and downhill). Then, based on the user's supply demand range, it is ensured that the oxygen supply can be adjusted in real time as the user's vital signs change when the vehicle bumps, accelerates / decelerates, turns, and goes uphill and downhill, thereby dynamically and real-time meeting the user's oxygen demand, ensuring the effective maintenance of the user's vital signs, and comprehensively improving the dynamic adaptability of the user's oxygen supply.

[0071] Optionally, based on the current driving road information of the ambulance, the current road condition information of the ambulance's vehicle driving route is identified, including: based on the current driving road information of the ambulance, the current road data of the ambulance's vehicle driving route is identified; based on the current road data, the road condition data distribution information of each road condition type of the vehicle driving route is identified, and based on the vehicle driving route, the route feature data of the vehicle driving route is extracted through a route feature extraction network; the road condition data distribution information of each road condition type and the route feature data of the vehicle driving route are used as the current road condition information of the ambulance's vehicle driving route.

[0072] In this embodiment, the terminal identifies the current road data of the ambulance's vehicle driving route based on the current road information of the ambulance. Then, based on the current road data, the terminal identifies the road condition data distribution information of each road condition type of the vehicle's driving route, and extracts the route feature data of the vehicle's driving route through a route feature extraction network based on the vehicle's driving route. The vehicle's driving route is the navigation information of the vehicle, and the navigation information includes the speed limit, turns, uphill and downhill, road grade, etc. of different road sections where the vehicle is traveling. The route feature extraction network is a convolutional neural network based on deep learning, which is used to extract features from the road condition data distribution information of the vehicle's driving route, thereby obtaining route feature data of different road sections of the road. The road condition data distribution information of each road condition type is a road condition data distribution table that is distributed and sorted according to the driving order of the road section area.

[0073] Finally, the terminal uses the road condition data distribution information of each road condition type and the route characteristic data of the vehicle's driving route as the current road condition information of the ambulance's driving route.

[0074] Based on the above solution, by effectively identifying the distribution of road condition data and route characteristics of the vehicle's driving road, the comprehensiveness of road information recognition is improved, and the comprehensiveness of the analysis of the impact of road conditions on users' vital signs data is effectively improved.

[0075] Optionally, based on the user's current physical sign data, the current physical sign data distribution information of each physical sign data type of the user is identified, including: splitting the current physical sign data into indicator data distribution information of each physical sign indicator type; performing data conversion processing on the indicator data distribution information of each physical sign indicator type to obtain the current physical sign data distribution information of each physical sign data type.

[0076] In this embodiment, the terminal splits the current body vital sign data into indicator data distribution information for each vital sign indicator type, and then performs data conversion processing on the indicator data distribution information for each vital sign indicator type to obtain current vital sign data distribution information for each vital sign data type. Each vital sign data type represents the vital sign status of the user, and each vital sign indicator type corresponds to a vital sign data type. The terminal presets different vital sign indicator types, corresponding relationships between them and the vital sign data types, and a data conversion program. Based on the corresponding relationships and the data conversion program, the terminal converts the data to obtain current vital sign data distribution information for each vital sign data type.

[0077] Based on the above solution, by combining the types of vital sign indicators and analyzing the data distribution information of different vital sign data, the accuracy of the analysis of user vital signs is improved.

[0078] Optionally, the oxygen delivery analysis model includes an oxygen demand analysis model and an oxygen demand prediction model. Based on the current vital sign data distribution information of each vital sign data type, the oxygen delivery analysis model is used to identify the user's oxygen demand range, including: identifying the data distribution characteristics of each vital sign data type and the data trend characteristics of each vital sign data type based on the current vital sign data distribution information of each vital sign data type; identifying the user's first oxygen demand range through the oxygen demand analysis model based on the data distribution characteristics of each vital sign data type, and identifying the user's second oxygen demand range through the oxygen demand prediction model based on the data trend characteristics of each vital sign data type; identifying the user's oxygen demand range based on the user's first oxygen demand range and the user's second oxygen demand range.

[0079] In this embodiment, the terminal identifies the data distribution characteristics and data trend characteristics of each vital sign data type based on the current vital sign data distribution information of each vital sign data type. The data trend characteristics are identified using a linear trend prediction network, while the data distribution characteristics are identified using a linear feature extraction network.

[0080] The terminal then uses an oxygen demand analysis model to identify the user's first oxygen demand range based on the data distribution characteristics of each vital sign data type. It also uses an oxygen demand prediction model to identify the user's second oxygen demand range based on the data trend characteristics of each vital sign data type. The first oxygen demand range corresponds to the user's current vital sign, while the second oxygen demand range corresponds to the predicted oxygen demand range for changes in the user's vital sign. By identifying these two oxygen demand ranges, the adaptability of oxygen supply is effectively improved.

[0081] Then, the terminal identifies the user's oxygen requirement range based on the user's first oxygen requirement range and the user's second oxygen requirement range, wherein the oxygen requirement range is the oxygen requirement range obtained by summarizing the first oxygen requirement range and the second oxygen requirement range.

[0082] Based on the above solution, by identifying the oxygen demand range corresponding to the user's current vital signs and predicting the oxygen demand range corresponding to the user's future vital signs, the patient's actual oxygen demand range is identified, thereby improving the adaptability of oxygen supply to the patient's actual needs.

[0083] Optionally, based on the current road condition information of the ambulance's route and the user's oxygen demand range, the user's current dynamic oxygen supply distribution information is generated through an oxygen supply analysis model, including: based on the road condition data distribution information of each road condition type and the route characteristic data of the vehicle's route, identifying the interference data distribution information of each road condition interference type for each road section area of ​​the vehicle's route through a road condition index analysis strategy; for each road section area, based on the interference data distribution information of each road condition interference type in the road section area, predicting the user's vital data change information of each vital sign data type through a vital sign data prediction network; based on the vital data change information of each vital sign data type and the user's oxygen demand range, identifying the actual oxygen supply demand range corresponding to the road section area, and using the actual oxygen supply demand range corresponding to all road section areas as the user's current dynamic oxygen supply distribution information.

[0084] In this embodiment, the terminal uses a road condition index analysis strategy to identify interference data distribution information for each road condition interference type for each road section of the vehicle's route based on road condition data distribution information for each road condition type and route characteristic data for the vehicle's route. Road condition interference types include, but are not limited to, vehicle bump interference types (combined with vehicle speed and road grade information for the road section in which the vehicle is located) and vehicle offset interference types (combined with information such as vehicle turns, uphill and downhill driving, etc.). The interference data distribution information for each road condition interference type is identified by the terminal using a road condition index analysis strategy based on the preset road condition types and route characteristic data corresponding to each road condition interference type. The terminal then distributes and arranges the interference data ranges according to different location ranges within the road section to obtain interference data distribution information for each road condition interference type. The road condition index analysis strategy includes a corresponding relationship between the interference data ranges for different road condition interference types and the road condition data ranges and route characteristic data ranges for each road condition type corresponding to the road condition interference type.

[0085] For each road section, the terminal uses the vital sign data prediction network to predict the user's vital sign data change information for each vital sign data type based on the interference data distribution information of each road condition interference type in the road section. The specific prediction process will be described in detail later.

[0086] Finally, based on the vital sign data change information of each vital sign data type and the user's oxygen demand range, the terminal identifies the actual oxygen supply demand range corresponding to the road section area, and uses the actual oxygen supply demand range corresponding to all road section areas as the user's current dynamic oxygen supply distribution information.

[0087] Based on the above scheme, by combining the road condition data distribution information of each road condition type and the route characteristic data of the vehicle's driving route, the interference data distribution information of each road condition interference type is analyzed, and then the impact of the road information currently traveled by the vehicle on the user's vital signs is predicted, thereby improving the comprehensiveness and accuracy of the analysis of changes in user vital signs.

[0088] Optionally, based on the interference data distribution information of each road condition interference type in the road section area, the vital sign data change information of each vital sign data type of the user is predicted through the vital sign data prediction network, including: fitting the interference data change curve diagram of each road condition interference type based on the interference data distribution information of each road condition interference type; obtaining the influence weight value of each road condition interference type on the vital sign change, and based on the interference data change curve diagram of each road condition interference type, identifying the vital sign change influence curve diagram corresponding to each road condition interference type through the influence weight value of each road condition interference type on the vital sign change; based on the vital sign change influence curve diagram corresponding to each road condition interference type, predicting the vital sign data change information of each vital sign data type of the user through the vital sign data prediction network.

[0089] In this embodiment, the terminal fits the interference data change curve diagram for each road interference type based on the interference data distribution information of each road interference type. The fitting method is to perform linear fitting processing on the interference data distribution information of each road interference type using a linear fitting algorithm corresponding to the linear fitting technology to obtain the interference data change curve diagram for each road interference type.

[0090] Then, the terminal obtains the weighted value of the impact of each road condition interference type on the change of vital signs, and based on the interference data change curve of each road condition interference type, identifies the vital sign change impact curve corresponding to each road condition interference type through the weighted value of the impact of each road condition interference type on the change of vital signs. Specifically, based on the weighted value of the impact of each road condition interference type on the change of vital signs, the terminal performs data weighting processing on the interference data change curve of each road condition interference type to obtain the vital sign change impact curve corresponding to each road condition interference type. Among them, the impact weight value includes sub-influence weight values ​​corresponding to different vital sign data types. The terminal performs weighted processing on each road condition interference type according to the sub-influence weight values ​​corresponding to different vital sign data types, and obtains the vital sign change impact curve corresponding to the road condition interference type corresponding to the different vital sign data types.

[0091] Finally, based on the vital sign change impact curves corresponding to each road interference type, the terminal uses the vital sign data prediction network to predict the vital sign data change information for each type of user's vital sign data. The vital sign data prediction network is a convolutional neural network based on the attention mechanism.

[0092] Based on this solution, by performing a linear fit and then weighting the interference data distribution information for each road interference type, the impact of discrete data on the overall interference data analysis accuracy is avoided. Furthermore, the weighted processing effectively improves the accuracy of the actual interference information of each vital sign data type based on the interference data of different road interference types. This effectively improves the accuracy of the predicted vital sign data change information for each vital sign data type for the user.

[0093] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0094] Based on the same inventive concept, embodiments of the present application also provide an oxygen flow dynamic delivery control system for implementing the aforementioned oxygen flow dynamic delivery control method. The solution provided by this system is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the oxygen flow dynamic delivery control system provided below can be found in the above-described limitations of the oxygen flow dynamic delivery control method and will not be further elaborated here.

[0095] Further references Figure 2 , as a response to the above Figure 1 To implement the method shown, the present application provides an embodiment of an oxygen flow dynamic delivery control system 200, which includes an acquisition module 210, an identification module 220, and a generation module 230, wherein:

[0096] an acquisition module 210 for acquiring information about the current travel route of the ambulance and the current physical sign data of the user, and identifying current road condition information of the ambulance's vehicle route based on the information about the current travel route of the ambulance;

[0097] an identification module 220 for identifying, based on the current physical sign data of the user, current physical sign data distribution information of each physical sign data type of the user, and identifying, based on the current physical sign data distribution information of each physical sign data type, an oxygen demand range of the user using an oxygen delivery analysis model;

[0098] The generation module 230 is used to generate the user's current dynamic oxygen supply distribution information based on the current road condition information of the ambulance's vehicle route and the user's oxygen demand range through an oxygen supply analysis model, and generate the current oxygen supply dynamic control strategy of the oxygen tank based on the current dynamic oxygen supply distribution information.

[0099] Optionally, the acquisition module 210 is specifically configured to:

[0100] identifying current road data of a vehicle driving route of the ambulance based on current driving road information of the ambulance;

[0101] Based on the current road data, identifying road condition data distribution information of each road condition type of the vehicle driving route, and based on the vehicle driving route, extracting route feature data of the vehicle driving route through a route feature extraction network;

[0102] The road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route are used as the current road condition information of the vehicle driving route of the ambulance.

[0103] Optionally, the identification module 220 is specifically configured to:

[0104] Splitting the current body sign data into indicator data distribution information of each sign indicator type;

[0105] The indicator data distribution information of each of the physical sign indicator types is subjected to data conversion processing to obtain current physical sign data distribution information of each of the physical sign data types.

[0106] Optionally, the identification module 220 is specifically configured to:

[0107] Based on the current vital sign data distribution information of each of the vital sign data types, identifying the data distribution characteristics of each of the vital sign data types and the data trend characteristics of each of the vital sign data types;

[0108] Based on the data distribution characteristics of each of the vital sign data types, the oxygen demand analysis model is used to identify a first oxygen demand range of the user; and based on the data trend characteristics of each of the vital sign data types, the oxygen demand prediction model is used to identify a second oxygen demand range of the user;

[0109] An oxygen requirement range of the user is identified based on the first oxygen requirement range of the user and the second oxygen requirement range of the user.

[0110] Optionally, the generating module 230 is specifically configured to:

[0111] Based on the road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route, identifying the interference data distribution information of each road condition interference type in each road section area of ​​the vehicle driving route through a road condition index analysis strategy;

[0112] For each road section area, based on the interference data distribution information of each road interference type in the road section area, predicting the vital sign data change information of each vital sign data type of the user through a vital sign data prediction network;

[0113] Based on the vital sign data change information of each vital sign data type and the oxygen demand range of the user, the actual oxygen supply demand range corresponding to the road section area is identified, and the actual oxygen supply demand range corresponding to all road section areas is used as the current dynamic oxygen supply distribution information of the user.

[0114] Optionally, the generating module 230 is specifically configured to:

[0115] Fitting an interference data variation curve diagram of each of the road condition interference types based on the interference data distribution information of each of the road condition interference types;

[0116] Obtaining a weighted value of the influence of each road interference type on the physical sign change, and identifying a physical sign change influence curve corresponding to each road interference type based on the interference data change curve of each road interference type and the weighted value of the influence of each road interference type on the physical sign change;

[0117] Based on the physical sign change influence curve diagram corresponding to each of the road interference types, the physical sign data change information of each of the physical sign data types of the user is predicted through a physical sign data prediction network.

[0118] Each module in the above-mentioned oxygen flow dynamic delivery control system can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0119] 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, memory, a communication interface, a display screen, and an input system connected via a system bus. 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 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 computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal via wired or wireless communication. The wireless communication can be achieved via Wi-Fi, a mobile cellular network, NFC (near-field communication), or other technologies. When executed by the processor, the computer program implements a method for dynamic oxygen flow delivery control. The display screen of the computer device can be a liquid crystal display or an electronic ink display. The input system of the computer device can be a touch layer covering the display screen, keys, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse.

[0120] 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 shown in the figure, or combine certain components, or have a different component arrangement.

[0121] In one embodiment, a computer device is provided, comprising 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.

[0122] 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.

[0123] In one embodiment, a computer program product is provided, comprising a computer program, which implements the steps of any one of the methods of the first aspect when executed by a processor.

[0124] 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.

[0125] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. 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 above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this 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), magnetic 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. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0126] The technical features of the above embodiments can 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.

[0127] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for dynamic oxygen flow delivery control, characterized in that: The method comprises: Acquiring current driving road information of the ambulance and current physical sign data of the user, and identifying current road condition information of the ambulance's driving route based on the current driving road information of the ambulance; identifying, based on the current physical sign data of the user, current physical sign data distribution information of each physical sign data type of the user, and identifying, based on the current physical sign data distribution information of each physical sign data type, an oxygen demand range of the user using an oxygen delivery analysis model; Based on the current road condition information of the ambulance's route and the user's oxygen demand range, the user's current dynamic oxygen supply distribution information is generated through an oxygen supply analysis model, and based on the current dynamic oxygen supply distribution information, a current oxygen supply dynamic control strategy for the oxygen tank is generated.

2. The method according to claim 1, characterized in that The identifying of the current road condition information of the ambulance's vehicle driving route based on the current driving road information of the ambulance includes: identifying current road data of a vehicle driving route of the ambulance based on current driving road information of the ambulance; Based on the current road data, identifying road condition data distribution information of each road condition type of the vehicle driving route, and based on the vehicle driving route, extracting route feature data of the vehicle driving route through a route feature extraction network; The road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route are used as the current road condition information of the vehicle driving route of the ambulance.

3. The method according to claim 1, characterized in that The identifying, based on the current physical sign data of the user, current physical sign data distribution information of each physical sign data type of the user includes: Splitting the current body sign data into indicator data distribution information of each sign indicator type; The indicator data distribution information of each of the physical sign indicator types is subjected to data conversion processing to obtain current physical sign data distribution information of each of the physical sign data types.

4. The method according to claim 1, wherein The oxygen delivery analysis model includes an oxygen demand analysis model and an oxygen demand prediction model. The oxygen demand range of the user is identified by the oxygen delivery analysis model based on the current vital sign data distribution information of each vital sign data type, including: Based on the current vital sign data distribution information of each of the vital sign data types, identifying the data distribution characteristics of each of the vital sign data types and the data trend characteristics of each of the vital sign data types; Based on the data distribution characteristics of each of the vital sign data types, the oxygen demand analysis model is used to identify a first oxygen demand range of the user; and based on the data trend characteristics of each of the vital sign data types, the oxygen demand prediction model is used to identify a second oxygen demand range of the user; An oxygen requirement range of the user is identified based on the first oxygen requirement range of the user and the second oxygen requirement range of the user.

5. The method according to claim 2, characterized in that The generating of the user's current dynamic oxygen supply distribution information based on the current road condition information of the ambulance's route and the user's oxygen demand range through an oxygen supply analysis model includes: Based on the road condition data distribution information of each road condition type and the route characteristic data of the vehicle driving route, identifying the interference data distribution information of each road condition interference type in each road section area of ​​the vehicle driving route through a road condition index analysis strategy; For each road section area, based on the interference data distribution information of each road interference type in the road section area, predicting the vital sign data change information of each vital sign data type of the user through a vital sign data prediction network; Based on the vital sign data change information of each vital sign data type and the oxygen demand range of the user, the actual oxygen supply demand range corresponding to the road section area is identified, and the actual oxygen supply demand range corresponding to all road section areas is used as the current dynamic oxygen supply distribution information of the user.

6. The method according to claim 5, characterized in that The interference data distribution information of each road interference type in the road section area is used to predict the vital sign data change information of each vital sign data type of the user through a vital sign data prediction network, including: Fitting an interference data variation curve diagram of each of the road condition interference types based on the interference data distribution information of each of the road condition interference types; Obtaining a weighted value of the influence of each road interference type on the physical sign change, and identifying a physical sign change influence curve corresponding to each road interference type based on the interference data change curve of each road interference type and the weighted value of the influence of each road interference type on the physical sign change; Based on the physical sign change influence curve diagram corresponding to each of the road interference types, the physical sign data change information of each of the physical sign data types of the user is predicted through a physical sign data prediction network.

7. An oxygen flow dynamic delivery control system, characterized in that: The system comprises: an acquisition module, configured to acquire information about the current travel route of the ambulance and the current physical sign data of the user, and identify current road condition information of the vehicle travel route of the ambulance based on the information about the current travel route of the ambulance; an identification module, configured to identify, based on the current physical sign data of the user, current physical sign data distribution information of each physical sign data type of the user, and identify, based on the current physical sign data distribution information of each physical sign data type, an oxygen demand range of the user using an oxygen delivery analysis model; The generation module is used to generate the user's current dynamic oxygen supply distribution information based on the current road condition information of the ambulance's vehicle route and the user's oxygen demand range through an oxygen supply analysis model, and generate a current oxygen supply dynamic control strategy for the oxygen tank based on the current dynamic oxygen supply distribution information.

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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