Artificial intelligence-based dermatological nursing scene analysis system and method

Abstract

The invention relates to the technical field of artificial intelligence, in particular to a dermatological nursing scene analysis system and method based on artificial intelligence. Skin vulnerability analysis is performed based on patient skin damage position image data and patient skin damage data; nursing process injury assessment is performed based on patient skin data, movement of a nursing position and nursing pressure value data, nursing process abnormity analysis is performed based on a skin vulnerability analysis result and a nursing process injury assessment result, and nursing action early warning is performed according to a nursing process abnormity analysis result. According to the application, the skin abnormity of the patient is quantitatively analyzed by combining the recovery condition and the damage condition of the skin damaged area of the patient, and meanwhile, the nursing action damage is accurately evaluated by combining the nursing action and the influence of acupoint pressing on the movement of the skin of the patient, so that the accuracy of matching analysis of the nursing action and the skin damage of the patient is improved; and the secondary injury of the patient is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial intelligence, and particularly to a dermatological care scenario analysis system and method based on artificial intelligence. Background Art

[0002] Most dermatological patients have their skin damaged to varying degrees. When performing dermatological treatments, in order to promote blood circulation and remove blood stasis, a nursing method of massaging designated acupoints with designated intensity and movements is usually adopted for the care near the damaged area. However, when performing the nursing actions, the combined effects of the vulnerability of the patient's skin and abnormalities in the nursing process are ignored. It is impossible to comprehensively analyze the quantification of the patient's skin abnormalities based on the recovery and damage conditions of the damaged area of the patient's skin. At the same time, it is impossible to comprehensively consider the impact of nursing actions and acupoint pressing on the movement of the patient's skin and then accurately evaluate the damage caused by the nursing actions, resulting in the inability to perform the matching analysis between the nursing actions and the patient's skin damage. Existing technologies, such as the intelligent auxiliary system and method for dermatological rehabilitation care disclosed in the Chinese patent with the application publication number CN119049642A, which relates to the technical field of dermatological rehabilitation care, includes a symptom recognition module for obtaining image data of the patient's skin through an image acquisition device and multi-spectral imaging technology, and is also used for identifying dermatological symptoms. This intelligent auxiliary system and method for dermatological rehabilitation care, through the processing of the image preprocessing and enhancement unit, improves the quality and authenticity of the images, provides a reliable basis for accurately identifying dermatological symptoms, and can more accurately generate symptom data by comparing and identifying with machine learning algorithms and a dermatological symptom database. It can identify the potential impact of the patient's living habits on skin symptoms at multiple levels, provides a scientific basis for formulating personalized rehabilitation, and can dynamically adjust in combination with the patient's living habit data, improving the pertinence and effectiveness of rehabilitation, but there are the technical problems proposed in this application.

[0003] To solve the technical problems proposed in this application, the present application designs a dermatological care scenario analysis system and method based on artificial intelligence. Summary of the Invention

[0004] In order to overcome the defects and deficiencies of the existing technologies, the present invention provides an artificial-intelligence-based dermatological care scenario analysis system and method, which performs skin vulnerability analysis based on the image data of the damaged positions of a patient's skin and the patient's skin damage data, performs damage assessment during the care process based on the patient's skin data, the movement of the care position, and the care pressure value data, performs abnormal analysis of the care process based on the results of the skin vulnerability analysis and the damage assessment during the care process, and issues a warning for care actions according to the results of the abnormal analysis of the care process. This application comprehensively quantifies the skin abnormalities of the patient based on the recovery and damage conditions of the damaged areas of the patient's skin, and at the same time comprehensively considers the impact of care actions and acupoint pressing on the movement of the patient's skin to accurately assess the damage caused by care actions, improving the accuracy of the matching analysis between care actions and patient skin damage and avoiding secondary damage to the patient.

[0005] To achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides an artificial-intelligence-based dermatological care scenario analysis method, including the following steps: S1. Obtain the image data of the damaged positions of the patient's skin and the patient's skin data, and at the same time obtain the care position and the care pressure value data during the care process; S2. Perform skin vulnerability analysis based on the image data of the damaged positions of the patient's skin and the patient's skin damage data; S3. Perform damage assessment during the care process based on the patient's skin data, the movement of the care position, and the care pressure value data; S4. Perform abnormal analysis of the care process based on the results of the skin vulnerability analysis and the damage assessment during the care process; S5. Issue a warning for care actions according to the results of the abnormal analysis of the care process.

[0006] In an implementation manner of the present invention, the step of obtaining the image data of the damaged positions of the patient's skin and the patient's skin data, and at the same time obtaining the care position and the care pressure value data during the care process includes the following specific steps: S101. Obtain the image data of the damaged skin area and the hardness data of the damaged skin area, import the image data of the damaged skin area into image processing software to obtain the hue values of each pixel point in the damaged skin area, and at the same time obtain the elasticity data of the skin near the damaged area; S102. Obtain the corresponding contact positions for performing care actions, and at the same time obtain the distance data between the corresponding contact positions of each action and the damaged skin area; S103. Obtain the care pressure value data of the corresponding contact positions for performing care actions, and store the obtained data in a storage module.

[0007] In an implementation manner of the present invention, in step S2, skin vulnerability analysis is performed based on the image data of the damaged position of the patient's skin and the damaged data of the patient's skin, including the following specific steps: S201. Obtain the hue values of each pixel point in the corresponding skin damaged area and the hardness data of each point in the skin damaged area, and analyze the scabbing degree of each point in the skin damaged area based on the hue values of each pixel point in the skin damaged area and the hardness data of each point in the skin damaged area; S202. Analyze the scabbing situation of the corresponding skin damaged area based on the average value and the fluctuation degree of the scabbing degree of each point in the corresponding skin damaged area; S203. Perform damage abnormality analysis based on the damaged area of the corresponding skin damaged area and the damage depth of each point. Among them, the damage abnormality analysis method is: Integrate the damage depth of each point in the dimension of the damaged area and then divide by a set standard value to obtain a damage abnormality analysis value after standardization; S204. Obtain the scabbing situation of the corresponding skin damaged area, and at the same time obtain the damage abnormality analysis value of the corresponding skin damaged area. Divide the damage abnormality analysis value of the corresponding skin damaged area by the scabbing situation of the corresponding skin damaged area to obtain the skin vulnerability analysis result of the corresponding skin damaged area.

[0008] In an implementation manner of the present invention, in step S3, damage assessment during the nursing process is performed based on the patient's skin data, the movement of the nursing position, and the nursing pressure value data, including the following specific steps: S301. Obtain the distance between the skin damaged area and the nursing position and the elasticity data of the skin; S302. Perform nursing abnormality analysis based on the movement situation of the nursing position, the nursing pressure value data, and the distance between the skin damaged area and the nursing position. Among them, the nursing abnormality analysis formula is: , where n is the number of nursing positions, Li is the movement path of the nursing position during the i-th nursing action, fil is the pressure value when the distance of the movement path l of the nursing position during the i-th nursing action, fm is the standard pressure value, dl is the distance integral constant, and Di is the average value of the shortest distance from the movement path of the nursing position during the i-th nursing action to the skin damaged area; S303. Obtain the nursing abnormality analysis result and the elasticity data of the skin between the skin damaged area and the nursing position. Divide the nursing abnormality analysis result by the standardized elasticity data of the skin between the skin damaged area and the nursing position to obtain the damage assessment result during the nursing process.

[0009] In an implementation manner of the present invention, in step S4, nursing process abnormality analysis is performed based on the skin vulnerability analysis result and the damage assessment result during the nursing process, including the following specific steps: S401. Obtain the skin vulnerability analysis result corresponding to the skin damaged area and the nursing process injury assessment result corresponding to the corresponding nursing action; S402. Perform weighted summation on the obtained skin vulnerability analysis result corresponding to the skin damaged area and the nursing process injury assessment result corresponding to the corresponding nursing action to obtain the nursing process anomaly analysis result.

[0010] In an implementation manner of the present invention, in step S5, warning of nursing actions is performed according to the nursing process anomaly analysis result, including the following specific contents: Obtain the corresponding nursing process anomaly analysis result, subtract it from the set nursing process anomaly analysis threshold to obtain a difference. If the obtained difference is greater than or equal to 0, it means that the nursing process anomaly analysis result is greater than or equal to the set nursing process anomaly analysis threshold, that is, the nursing action does not match the skin damaged position, and the nursing action is likely to cause secondary injury to the skin damaged position, and warning of the nursing action is performed. If the obtained difference is less than 0, it means that the nursing process anomaly analysis result is less than the set nursing process anomaly analysis threshold, that is, the nursing action matches the skin damaged position, and the nursing action does not cause secondary injury to the skin damaged position.

[0011] In a second aspect, the present invention also provides a dermatology nursing scenario analysis system based on artificial intelligence, including: A data acquisition module, configured to acquire image data of the skin damaged position of a patient and the skin data of the patient, and at the same time acquire the nursing position and nursing pressure value data during the nursing process; A skin vulnerability analysis module, which performs skin vulnerability analysis based on the image data of the skin damaged position of the patient and the skin damaged data of the patient; A nursing process injury assessment module, which performs nursing process injury assessment based on the skin data of the patient, the movement of the nursing position, and the nursing pressure value data; A nursing process anomaly analysis module, which performs nursing process anomaly analysis based on the skin vulnerability analysis result and the nursing process injury assessment result; An action warning module, which warns of nursing actions according to the nursing process anomaly analysis result.

[0012] In a third aspect, an electronic device provided by the present invention includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory, and the processor executes the dermatology nursing scenario analysis method based on artificial intelligence by calling the computer program stored in the memory.

[0013] In a fourth aspect, a computer-readable storage medium provided by the present invention stores instructions, and when the instructions run on a computer, the computer is caused to execute the dermatology nursing scenario analysis method based on artificial intelligence.

[0014] Compared with the prior art, the present invention has the following advantages and beneficial effects: Based on the image data of the damaged position of the patient's skin and the damaged data of the patient's skin, the present invention performs skin vulnerability analysis. Based on the patient's skin data, the movement of the nursing position, and the nursing pressure value data, it evaluates the damage during the nursing process. Based on the results of the skin vulnerability analysis and the damage assessment results during the nursing process, it analyzes the abnormalities during the nursing process, and issues a warning for nursing actions according to the analysis results of the abnormalities during the nursing process. This application comprehensively quantifies the skin abnormalities of the patient based on the recovery and damage conditions of the damaged area of the patient's skin. At the same time, it comprehensively considers the impact of nursing actions and acupoint pressing on the movement of the patient's skin, and then accurately evaluates the damage caused by nursing actions, improving the accuracy of the matching analysis between nursing actions and patient skin damage, and avoiding secondary damage to the patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent: Figure 1 It is a schematic diagram of the overall process of the method embodiment of the present invention; Figure 2 It is a flowchart of the operation of S2 in the method embodiment of the present invention; Figure 3 It is a flowchart of the operation of S3 in the method embodiment of the present invention; Figure 4 It is a schematic diagram of the structure of the system embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The technical solution of the present invention will be described in detail below with reference to the drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. Without conflict, the technical features in the embodiments of the present invention and the embodiments can be combined with each other.

[0017] Embodiment 1 Embodiment 1 provides a method embodiment of the technical solution.

[0018] As Figures 1 to 3 shown, this embodiment provides a method for analyzing dermatological care scenarios based on artificial intelligence, which specifically includes the following steps: S1. Obtain the image data of the damaged position of the patient's skin and the patient's skin data, and at the same time obtain the nursing position and nursing pressure value data during the nursing process; In a specific embodiment, the obtaining of the image data of the damaged position of the patient's skin and the patient's skin data, and at the same time obtaining the nursing position and nursing pressure value data during the nursing process includes the following specific steps: S101. Obtain the image data of the skin damaged area and the hardness data of the skin damaged area. Import the image data of the skin damaged area into image processing software to obtain the hue values of each pixel point in the skin damaged area. At the same time, obtain the elasticity data of the skin near the damaged area. The way to obtain the elasticity data of the skin is as follows: 1. Non-contact measurement device: Laser scanning: Use laser technology to non-contact measure the deformation of the skin, so as to calculate the hardness and elasticity of the skin; Ultrasonic measurement: Evaluate the hardness and elasticity of the skin through the reflection of ultrasonic signals; Advantage: Non-invasive, suitable for measuring skin damage or sensitive areas; 2. Skin elastometer: A device with a measurement probe, press it gently on the skin surface, measure the rebound time and pressure value of the skin, and can quantify the elasticity and hardness of the skin; S102. Obtain the corresponding contact positions for the nursing actions to be performed, and at the same time obtain the distance data between the corresponding contact positions of each action and the skin damaged area; In this embodiment, the ways to obtain the contact positions and the distance data are all conventional acquisition means, and the relevant data of the nursing actions are stored in the storage of the nursing actions and can be directly called when in use; S103. Obtain the nursing pressure value data of the corresponding contact positions for the nursing actions to be performed, and store the obtained data in the storage module; S2. Perform skin vulnerability analysis based on the image data of the patient's skin damaged position and the patient's skin damaged data; In a specific embodiment, in step S2, performing skin vulnerability analysis based on the image data of the patient's skin damaged position and the patient's skin damaged data includes the following specific steps: S201. Obtain the hue values of each pixel point in the corresponding skin damaged area and the hardness data of each point in the skin damaged area. Analyze the scabbing degree of each point in the skin damaged area based on the hue values of each pixel point in the skin damaged area and the hardness data of each point in the skin damaged area, which can be calculated through the scabbing degree calculation formula. Among them, the scabbing degree calculation formula for the z-th point is: , where xz is the hue value of the z-th point, xm is the average value of the scabbing hue values, exp() represents the power of the natural constant e. If the number in the exp() parentheses is greater than 0, that is, the hue value of the z-th point is greater than or equal to the average value of the scabbing hue values, it means that the color of the z-th point is darker than the scab, indicating a high possibility of scabbing. If the number in the exp() parentheses is less than 0, it means that the color of the z-th point is lighter than the scab, indicating a low possibility of scabbing. Pz is the hardness of the z-th point, and Pm is the average hardness of the scab; S202. Analyze the scabbing situation of the corresponding skin damaged area based on the average value and the fluctuation degree of the scabbing degree of each point in the corresponding skin damaged area. Among them, the scabbing situation analysis calculation formula for the corresponding skin damaged area is: , where a is the average proportion weight, Js is the average degree of scabbing at each point, and Jr is the variance of the degree of scabbing at each point; S203. Perform damage anomaly analysis based on the damaged area of the corresponding skin damaged area and the damage depth at each point. Among them, the damage anomaly analysis method is: Integrate the damage depth at each point in the dimension of the damaged area and then divide by a set standard value to obtain the damage anomaly analysis value after standardization; S204. Obtain the scabbing condition of the corresponding skin damaged area, and at the same time obtain the damage anomaly analysis value of the corresponding skin damaged area. Divide the damage anomaly analysis value of the corresponding skin damaged area by the scabbing condition of the corresponding skin damaged area to obtain the skin vulnerability analysis result of the corresponding skin damaged area; S3. Perform damage assessment during the nursing process based on patient skin data, movement of the nursing position, and nursing pressure value data; In a specific embodiment, the damage assessment during the nursing process based on patient skin data, movement of the nursing position, and nursing pressure value data in step S3 includes the following specific steps: S301. Obtain the distance between the skin damaged area and the nursing position and the elasticity data of the skin; S302. Perform nursing anomaly analysis based on the movement condition of the nursing position, nursing pressure value data, and the distance between the skin damaged area and the nursing position. Among them, the nursing anomaly analysis formula is: , where n is the number of nursing positions. Taking massage nursing as an example, the number of nursing positions is the number of contacts between the medical staff's fingers and the patient during massage. Li is the movement path of the nursing position during the i-th nursing action. Still taking massage nursing as an example, the movement path of the nursing position is the movement path when the medical staff's fingers press and rub on the patient's skin. fil is the pressure value at the distance l of the movement path of the nursing position during the i-th nursing action, fm is the standard pressure value, dl is the distance integration constant, and Di is the average value of the shortest distance from the movement path of the nursing position during the i-th nursing action to the skin damaged area; S303. Obtain the nursing anomaly analysis result and the elasticity data of the skin between the skin damaged area and the nursing position. Divide the nursing anomaly analysis result by the standardized elasticity data of the skin between the skin damaged area and the nursing position to obtain the damage assessment result during the nursing process; Because if the skin elasticity is large, it will affect the transmission of the pulling force and reduce the damage to the damaged position caused by the pulling force during rubbing; S4. Perform nursing process anomaly analysis based on the skin vulnerability analysis result and the damage assessment result during the nursing process; In a specific embodiment, the nursing process anomaly analysis based on the skin vulnerability analysis result and the damage assessment result during the nursing process in step S4 includes the following specific steps: S401. Obtain the skin vulnerability analysis result corresponding to the skin damaged area and the nursing process injury assessment result corresponding to the corresponding nursing action; S402. Perform weighted summation on the obtained skin vulnerability analysis result corresponding to the skin damaged area and the nursing process injury assessment result corresponding to the corresponding nursing action to obtain the nursing process anomaly analysis result; S5. Issue a warning for the nursing action according to the nursing process anomaly analysis result; In a specific embodiment, the warning for the nursing action according to the nursing process anomaly analysis result in step S5 includes the following specific content: Obtain the corresponding nursing process anomaly analysis result, subtract it from the set nursing process anomaly analysis threshold to obtain a difference value. If the obtained difference value is greater than or equal to 0, it means that the nursing process anomaly analysis result is greater than or equal to the set nursing process anomaly analysis threshold, that is, the nursing action does not match the skin damaged position, and the nursing action is likely to cause secondary damage to the skin damaged position, and a warning for the nursing action is issued. If the obtained difference value is less than 0, it means that the nursing process anomaly analysis result is less than the set nursing process anomaly analysis threshold, that is, the nursing action matches the skin damaged position, and the nursing action does not cause secondary damage to the skin damaged position.

[0019] In this embodiment, it should be noted that the acquisition method of the set parameters (such as the proportion weights of each weighted sum, threshold, etc.) in this embodiment is obtained by experiments by those skilled in the art. The specific experimental method is as follows: Obtain the image data of the skin damaged positions of several groups of historical patients and the skin data of the patients, and at the same time obtain the nursing position and nursing pressure value data during the nursing process, substitute them into each step of this embodiment to calculate the nursing process anomaly analysis result, and at the same time obtain the judgment result of whether secondary damage is caused to the skin damaged position after nursing. Based on the nursing process anomaly analysis result and the judgment result of whether secondary damage is caused to the skin damaged position, import them into a fitting software (preferably matlab) for iterative fitting of the data, and output the set parameter value that meets the maximum evaluation sorting accuracy rate.

[0020] In this embodiment, it should be noted that this embodiment has the following advantages: Perform skin vulnerability analysis based on the image data of the patient's skin damaged position and the patient's skin damaged data, perform nursing process injury assessment based on the patient's skin data, the movement of the nursing position, and the nursing pressure value data, perform nursing process anomaly analysis based on the skin vulnerability analysis result and the nursing process injury assessment result, issue a warning for the nursing action according to the nursing process anomaly analysis result, comprehensively quantify the patient's skin anomaly based on the recovery and damage conditions of the patient's skin damaged area, and at the same time comprehensively consider the influence of the nursing action and acupoint pressing on the movement of the patient's skin to accurately evaluate the injury of the nursing action, improve the accuracy of the matching analysis between the nursing action and the patient's skin injury, and avoid secondary injury to the patient.

[0021] Example 2 As Figure 4 shown, this embodiment provides an artificial intelligence-based dermatological care scenario analysis system, including: A data acquisition module for acquiring image data of the damaged location of the patient's skin, the patient's skin data, and at the same time acquiring the care location and care pressure value data during the care process; a skin vulnerability analysis module for performing skin vulnerability analysis based on the image data of the damaged location of the patient's skin and the patient's skin damage data; a care process injury assessment module for performing care process injury assessment based on the patient's skin data, the movement of the care location, and the care pressure value data; a care process anomaly analysis module for performing care process anomaly analysis based on the skin vulnerability analysis result and the care process injury assessment result; and an action warning module for warning care actions according to the care process anomaly analysis result. For the parameters, steps of each unit module in the above artificial intelligence-based dermatological care scenario analysis system of the present invention to achieve corresponding functions, and the corresponding effects, reference can be made to the parameters and steps in the embodiments of the artificial intelligence-based dermatological care scenario analysis method in the above text, which will not be elaborated here.

[0022] Example 3 An electronic device according to an embodiment of the present invention includes: a processor and a memory. Among them, the memory stores a computer program that can be called by the processor, and the processor executes an artificial intelligence-based dermatological care scenario analysis method by calling the computer program stored in the memory. It should be noted that: all computer programs of the artificial intelligence-based dermatological care scenario analysis method are implemented using the C language. Among them, the data acquisition module, the pollutant intrusion degree analysis module, the damage degree analysis module, the stain diffusion degree analysis module, the stain risk assessment module, the book processing warning module, and the control module are all controlled by a remote server.

[0023] Example 4 This embodiment proposes a computer-readable storage medium, on which a rewritable computer program is stored; When the computer program runs on a computer device, the computer device is enabled to execute the above artificial intelligence-based dermatological care scenario analysis method.

[0024] Each embodiment in the present invention is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments. In particular, for the embodiments of the Internet of Things devices and media, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0025] The system, medium, and method provided by the embodiments of the present invention correspond one by one. Therefore, the system and medium also have beneficial technical effects similar to those of their corresponding methods. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the system and medium will not be elaborated here.

[0026] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0027] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0028] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the specified functions in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0029] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0030] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0031] A computer-readable medium includes both permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0032] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or apparatus comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or apparatus. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising the element.

[0033] The above are only embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. An artificial intelligence-based dermatology nursing scenario analysis method, characterized in that: The steps include: S1. Obtain image data of the damaged skin position of the patient and the patient's skin data, and simultaneously obtain the nursing position and nursing pressure value data during the nursing process; S2, performing skin vulnerability analysis based on the image data of the patient's skin damage location and the patient's skin damage data; S3, perform nursing process damage assessment based on patient skin data, movement of nursing position, and nursing pressure value data; S4. Perform nursing process abnormality analysis based on skin vulnerability analysis results and nursing process damage assessment results; S5. Provide early warning for nursing actions based on abnormal analysis results of the nursing process.

2. The artificial intelligence-based dermatology nursing scenario analysis method according to claim 1, characterized in that: The skin vulnerability analysis based on the patient's skin damage location image data and the patient's skin damage data includes the following specific steps: The hue value of each pixel point corresponding to the damaged skin area and the hardness data of each point in the damaged skin area are obtained, and the scab degree of each point in the damaged skin area is analyzed based on the hue value of each pixel point in the damaged skin area and the hardness data of each point in the damaged skin area. The calculation formula for the scab degree of the zth point is: , where xz is the hue value of the z-th point, xm is the average hue value of the scab, exp() represents the power of the natural constant e, if the number in the bracket of exp() is greater than 0, Pz is the hardness of the z-th point, and Pm is the average hardness of the scab; The scab situation of the corresponding skin damaged area was analyzed based on the average value and fluctuation degree of the scab degree at each point of the corresponding skin damaged area.

3. The artificial intelligence-based dermatology nursing scenario analysis method according to claim 2, characterized in that: The skin vulnerability analysis based on the patient's skin damage position image data and the patient's skin damage data also includes the following specific steps: The damage abnormality analysis is performed based on the damage area of ​​the corresponding skin damaged area and the damage depth of each point, wherein the damage abnormality analysis method is: the damage depth of each point is integrated in the damage area dimension and then divided by the set standard value to obtain the damage abnormality analysis value; The scab situation of the corresponding skin damaged area is obtained, and the damage abnormality analysis value of the corresponding skin damaged area is obtained at the same time. The damage abnormality analysis value of the corresponding skin damaged area is divided by the scab situation of the corresponding skin damaged area to obtain the skin vulnerability analysis result of the corresponding skin damaged area.

4. The artificial intelligence-based dermatology nursing scenario analysis method according to claim 3 is characterized in that: The nursing process injury assessment based on the patient's skin data, the movement of the nursing position and the nursing pressure value data includes the following specific steps: Obtain the distance between the damaged skin area and the care location and the skin elasticity data; Perform nursing abnormality analysis based on the movement of the nursing position, nursing pressure value data, and the distance between the damaged skin area and the nursing position; The nursing abnormality analysis results and the elasticity data of the skin between the damaged skin area and the nursing position are obtained, and the nursing process damage assessment result is obtained by dividing the nursing abnormality analysis results by the standardized elasticity data of the skin between the damaged skin area and the nursing position.

5. The artificial intelligence-based dermatology nursing scenario analysis method according to claim 4, characterized in that: The nursing process abnormality analysis based on the skin vulnerability analysis results and the nursing process damage assessment results includes the following specific steps: Obtain skin vulnerability analysis results corresponding to the skin damaged area and nursing process damage assessment results corresponding to the nursing action; The obtained skin vulnerability analysis results of the corresponding skin damaged area and the nursing process damage assessment results of the corresponding nursing actions are weightedly summed to obtain the nursing process abnormality analysis results.

6. The artificial intelligence-based dermatology nursing scenario analysis method according to claim 5, characterized in that: The early warning of nursing actions according to the abnormal analysis results of the nursing process includes the following specific contents: Obtain the corresponding nursing process abnormality analysis result, subtract it from the set nursing process abnormality analysis threshold to get the difference; if the difference is greater than or equal to 0, the nursing action does not match the damaged skin location, and the nursing action is likely to cause secondary damage to the damaged skin location, and an early warning of the nursing action is issued; if the difference is less than 0, the nursing action matches the damaged skin location, and the nursing action does not cause secondary damage to the damaged skin location.

7. The artificial intelligence-based dermatology nursing scenario analysis method according to claim 6, characterized in that: The method of obtaining the image data of the damaged skin position of the patient and the skin data of the patient, and simultaneously obtaining the nursing position and nursing pressure value data during the nursing process comprises the following specific steps: Obtain image data of the damaged skin area and hardness data of the damaged skin area, import the image data of the damaged skin area into image processing software to obtain the hue value of each pixel point in the damaged skin area, and simultaneously obtain elasticity data of the skin near the damaged area; Obtaining the corresponding contact position of the care action that needs to be performed, and at the same time obtaining the distance data between the corresponding contact position of each action and the damaged skin area; The nursing pressure value data of the corresponding contact position where the nursing action needs to be performed is obtained, and the obtained data is stored in the storage module.

8. The artificial intelligence-based dermatology nursing scenario analysis method according to claim 7, characterized in that: The nursing abnormality analysis formula is: , where n is the number of nursing positions, Li is the moving path of the nursing position during the i-th nursing action, fil is the pressure value at a distance l from the moving path of the nursing position during the i-th nursing action, fm is the standard pressure value, dl is the distance integral constant, and Di is the average value of the shortest distance from the moving path of the nursing position during the i-th nursing action to the damaged skin area.

9. An artificial intelligence-based dermatology care scenario analysis system, which is implemented based on the method according to any one of claims 1 to 8, characterized in that: The system comprises: A data acquisition module is used to obtain image data of the damaged skin position of the patient and the patient's skin data, and to obtain the nursing position and nursing pressure value data during the nursing process; A skin vulnerability analysis module, which performs skin vulnerability analysis based on the patient's skin damage location image data and the patient's skin damage data; Nursing process damage assessment module, which conducts nursing process damage assessment based on patient skin data, movement of nursing position, and nursing pressure value data; Nursing process abnormality analysis module, which performs nursing process abnormality analysis based on skin vulnerability analysis results and nursing process injury assessment results; The action warning module provides early warning of nursing actions based on the abnormal analysis results of the nursing process.

10. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the method according to any one of claims 1 to 8 by calling the computer program stored in the memory.

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