Intelligent hemodialysis auxiliary nursing method and system based on dynamic environment perception

Abstract

The present invention discloses an intelligent hemodialysis auxiliary nursing method and system based on dynamic environmental perception, which relates to the field of medical data processing technology. The method includes: sensing and collecting an array of environmental feature information in a hemodialysis environment, analyzing and obtaining blood pressure influencing parameters and dialysis influencing parameters; performing comfort impact analysis and obtaining perceived comfort influencing parameters; collecting a perception image array for actual comfort analysis, and analyzing and obtaining the environmental comfort impact ratio, combining the dialysis influencing parameters and the perceived comfort influencing parameters, to optimize the auxiliary nursing plan and perform auxiliary nursing. The present invention solves the technical problem that traditional hemodialysis nursing in the prior art often ignores environmental impacts and differences in environmental sensitivity among different patients, resulting in low adaptability and comfort of the nursing plan, and achieves the technical effect of optimizing the nursing plan through dynamic environmental perception and intelligent analysis technology, and improving the adaptability and comfort of the nursing plan.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data processing, and in particular to an intelligent hemodialysis auxiliary nursing method and system based on dynamic environment perception. Background Art

[0002] Hemodialysis is a commonly used renal replacement therapy, mainly used for patients with renal failure to artificially remove metabolic waste and excess fluid from the body. With the advancement of medical technology, the effectiveness and safety of hemodialysis have been significantly improved. However, traditional hemodialysis care often ignores the impact of environmental factors (such as temperature and humidity) on dialysis effects and user comfort, resulting in unstable care effects. In addition, different patients have different sensitivities to environmental changes, and traditional care methods are difficult to provide personalized care plans. Summary of the invention

[0003] The present application provides an intelligent hemodialysis assisted care method and system based on dynamic environmental perception, which is used to solve the technical problem in the prior art that traditional hemodialysis care often ignores environmental impacts and differences in environmental sensitivity among different patients, resulting in low adaptability and comfort of care plans.

[0004] In a first aspect of the present application, an intelligent hemodialysis auxiliary care method based on dynamic environmental perception is provided, the method comprising: sensing and collecting an environmental characteristic information array in a hemodialysis environment through a sensing device, wherein the environmental characteristic information array includes a humidity information array and a temperature information array, and the sensing device includes a sensor array configured at multiple sensing points around a dialysis position; performing a blood pressure impact analysis on a dialysis user according to the humidity information array and the temperature information array, obtaining blood pressure impact parameters, and classifying and obtaining dialysis impact parameters; performing a comfort impact analysis on the dialysis user according to the humidity information array and the temperature information array, obtaining perceived comfort impact parameters; collecting a perception image array of the dialysis user at the multiple sensing points, performing a comfort analysis, obtaining actual comfort impact parameters, and performing an environmental comfort impact ratio analysis in combination with the perceived comfort impact parameters, obtaining an environmental comfort impact ratio; optimizing an auxiliary care plan based on the dialysis impact parameters, obtaining an optimal auxiliary care plan, and performing auxiliary care, wherein the optimal auxiliary care plan includes an optimal temperature adjustment plan and an optimal humidity adjustment plan in the dialysis environment.

[0005] The second aspect of the present application provides an intelligent hemodialysis auxiliary care system based on dynamic environment perception, the system comprising: an environmental characteristic information acquisition module, the environmental characteristic information acquisition module is used to perceive and collect an environmental characteristic information array in the hemodialysis environment through a sensing device, wherein the environmental characteristic information array includes a humidity information array and a temperature information array, and the sensing device includes a sensor array configured at multiple sensing points around the dialysis position; a blood pressure impact analysis module, the blood pressure impact analysis module is used to perform blood pressure impact analysis on the dialysis user according to the humidity information array and the temperature information array, obtain blood pressure impact parameters, and classify the dialysis impact parameters; a comfort impact analysis module, the comfort impact analysis module is used to analyze the blood pressure of the dialysis user according to the humidity information array and the temperature information array, obtain blood pressure impact parameters, and classify the dialysis impact parameters; A module for analyzing the comfort impact of the dialysis user to obtain perceived comfort impact parameters; an environmental comfort impact ratio analysis module for collecting the perceived image array of the dialysis user at the plurality of perception points, performing comfort analysis, obtaining actual comfort impact parameters, and performing environmental comfort impact ratio analysis in combination with the perceived comfort impact parameters to obtain environmental comfort impact ratios; and an auxiliary care program optimization module for optimizing the auxiliary care program based on the dialysis impact parameters, the perceived comfort impact parameters, and the environmental comfort impact ratio to obtain an optimal auxiliary care program and perform auxiliary care, wherein the optimal auxiliary care program includes an optimal temperature adjustment program and an optimal humidity adjustment program in the dialysis environment.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] The intelligent hemodialysis auxiliary care method and system based on dynamic environmental perception provided in the present application relate to the field of medical data processing technology. The environmental feature information array in the hemodialysis environment is sensed and collected, dialysis influencing parameters are obtained through analysis, comfort impact analysis is performed, perceived comfort impact parameters are obtained, and a perception image array is collected for actual comfort analysis. The environmental comfort impact ratio is obtained through analysis, and the dialysis influencing parameters and perceived comfort impact parameters are combined to optimize auxiliary care plans and provide auxiliary care. The technical problem that traditional hemodialysis care in the prior art often ignores environmental impacts and differences in environmental sensitivity among different patients, resulting in low adaptability and comfort of the care plans, is solved. The technical effect of auxiliary optimization of care plans and improving the adaptability and comfort of care plans is achieved through dynamic environmental perception and intelligent analysis technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic diagram of a flow chart of an intelligent hemodialysis auxiliary nursing method based on dynamic environment perception provided in an embodiment of the present application;

[0010] Figure 2 A schematic diagram of a process for obtaining the environmental comfort impact ratio in the intelligent hemodialysis auxiliary care method based on dynamic environmental perception provided in an embodiment of the present application;

[0011] Figure 3 A schematic diagram of the structure of an intelligent hemodialysis auxiliary care system based on dynamic environment perception provided in an embodiment of the present application.

[0012] Explanation of the reference numerals: environmental characteristic information acquisition module 11, blood pressure impact analysis module 12, comfort impact analysis module 13, environmental comfort impact ratio analysis module 14, auxiliary nursing program optimization module 15. DETAILED DESCRIPTION

[0013] The present application provides an intelligent hemodialysis assisted care method and system based on dynamic environmental perception, which is used to solve the technical problem in the prior art that traditional hemodialysis care often ignores environmental impacts and differences in environmental sensitivity among different patients, resulting in low adaptability and comfort of care plans.

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0015] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices.

[0016] Embodiment 1

[0017] like Figure 1 As shown, the present application provides an intelligent hemodialysis auxiliary care method based on dynamic environment perception, the method comprising:

[0018] P10: The environmental characteristic information array in the hemodialysis environment is sensed and collected through a sensing device, wherein the environmental characteristic information array includes a humidity information array and a temperature information array, and the sensing device includes a sensor array configured at multiple sensing points around the dialysis position.

[0019] Specifically, by configuring a sensor array at multiple sensing points in the hemodialysis environment, the environmental feature information array in the dialysis environment is sensed and collected in real time. Specifically, the sensor array in the sensing device usually includes high-precision temperature sensors and humidity sensors, which are distributed at multiple key points around the dialysis location, such as near the patient's head and limbs. Through these sensors, the system can accurately detect changes in temperature and humidity at these locations.

[0020] The environmental characteristic information array refers to a set of environmental variable data collected by multiple sensors, including a humidity information array and a temperature information array. The temperature information array refers to a set of temperature data at each sensing point collected by the sensor array, which can reflect the temperature distribution in different areas of the dialysis environment. Similarly, the humidity information array is a set of humidity data at each sensing point, which can provide detailed information about humidity changes in the dialysis environment.

[0021] These environmental feature information arrays can provide basic data support for blood pressure impact analysis and comfort impact analysis in subsequent steps. Through this multi-point sensing layout, the system can capture subtle changes in the environment and provide the necessary data support for accurately adjusting the temperature and humidity in the dialysis environment, thereby improving the dialysis effect and comfort of patients.

[0022] P20: According to the humidity information array and the temperature information array, the blood pressure impact analysis of the dialysis user is performed to obtain blood pressure impact parameters, and the dialysis impact parameters are obtained by classification.

[0023] Furthermore, step P20 of the embodiment of the present application further includes:

[0024] P21: Based on historical hemodialysis data, a sample humidity information array set and a sample temperature information array set are collected, and according to the parameters of blood pressure changes in the blood pressure test data, a sample blood pressure influencing parameter set is annotated to obtain a sample blood pressure influencing parameter set; P22: The sample humidity information array set, the sample temperature information array set and the sample blood pressure influencing parameter set are used to train an environmental blood pressure influencing analysis channel; P23: Based on the environmental blood pressure influencing analysis channel, a blood pressure influencing analysis is performed on the humidity information array and the temperature information array to obtain blood pressure influencing parameters; P24: Based on historical hemodialysis data, a sample dialysis influencing parameter set is collected; P25: Based on the sample blood pressure influencing parameter set and the sample dialysis influencing parameter set, a dialysis influencing classification channel is constructed; P26: The blood pressure influencing parameters are input into the dialysis influencing analysis channel to obtain dialysis influencing parameters through classification.

[0025] It should be understood that in this step, the potential impact of the humidity information array and the temperature information array on the blood pressure of dialysis users is deeply analyzed, aiming to accurately quantify the specific effects of these environmental factors on the dialysis effect through a data-driven approach.

[0026] First, based on historical hemodialysis data, sample humidity information array sets and sample temperature information array sets are collected. These sample sets come from a large amount of historical dialysis case data, covering the changes in humidity and temperature under different dialysis environments. At the same time, the blood pressure change parameters recorded in the blood pressure test data of the same period are used to annotate these data and generate a sample blood pressure influencing parameter set. This set contains the specific numerical parameters that affect the blood pressure of dialysis users under different environmental conditions.

[0027] Next, the sample humidity information array set, the sample temperature information array set, and the sample blood pressure impact parameter set are used to train the environmental blood pressure impact analysis channel using machine learning algorithms, such as neural networks or random forests. The core of the training is to learn and understand the complex relationship between humidity, temperature, and blood pressure changes, so that when new data is input, the potential impact of environmental factors on blood pressure can be accurately predicted. The accuracy and robustness of the environmental blood pressure impact analysis channel are ensured through repeated iterations and optimization of the training process.

[0028] Then, based on the trained environmental blood pressure impact analysis channel, the humidity information array and temperature information array in the current dialysis environment are analyzed for blood pressure impact. Through this analysis process, the blood pressure impact parameters under the current environmental conditions are obtained. These parameters quantitatively describe the potential impact of the current environment on the patient's blood pressure.

[0029] In order to more comprehensively evaluate the dialysis effect, we continue to collect sample dialysis effect parameter sets from historical hemodialysis data. These parameter sets are obtained by analyzing historical dialysis data and include specific indicators of the impact of different dialysis environmental conditions on dialysis effects, such as dialysis clearance, electrolyte balance, etc.

[0030] Furthermore, the sample blood pressure influencing parameter set is combined with the sample dialysis influencing parameter set to construct a dialysis influencing classification channel. The dialysis influencing classification channel is an analytical model used to classify different blood pressure influencing parameters into corresponding dialysis effect categories, which can help identify and distinguish the specific impacts on the dialysis process under different environmental conditions, that is, identify which dialysis influencing parameters are significantly affected by environmental factors, thereby providing more accurate guidance for the subsequent optimization of auxiliary care plans.

[0031] Finally, the currently obtained blood pressure impact parameters are input into the dialysis impact analysis channel and classified to obtain the dialysis impact parameters. Through this classification process, the specific impact of the current environmental conditions on the dialysis effect can be accurately evaluated, providing a scientific basis for subsequent nursing optimization.

[0032] P30: Performing a comfort impact analysis on the dialysis user according to the humidity information array and the temperature information array to obtain a perceived comfort impact parameter.

[0033] Furthermore, step P30 of the embodiment of the present application further includes:

[0034] P31: Based on the data records of the user in the hemodialysis environment, a sample humidity information array set and a sample temperature information array set are collected, and based on the user's comfort query data, a sample perceived comfort influence parameter set is annotated to obtain; P32: The sample humidity information array set, the sample temperature information array set and the sample perceived comfort influence parameter set are used to train a perceived comfort influence analysis channel; P33: Based on the perceived comfort influence analysis channel, the humidity information array and the temperature information array are subjected to a comfort influence analysis on the dialysis user to obtain perceived comfort influence parameters.

[0035] Optionally, based on the humidity information array and the temperature information array, a comfort impact analysis is performed on the dialysis users, that is, the specific impact of humidity and temperature in the hemodialysis environment on the comfort of the dialysis users is evaluated, the effect of these environmental factors on the user's comfort experience is quantified, and finally the perceived comfort impact parameters are obtained.

[0036] First, relying on historical data records, especially the environmental data of users during hemodialysis, sample humidity information array sets and sample temperature information array sets are collected. These sets reflect in detail the humidity and temperature conditions of the user's surrounding environment under different dialysis environments. At the same time, the user's comfort inquiry data in the same time period is collected. These data directly reflect the user's subjective feeling of comfort in the current environment. By matching these comfort data with the corresponding environmental data, the set of sample perceived comfort influencing parameters is annotated. This process ensures that the data set contains both environmental feature information and the comfort influencing information associated with it, providing strong data support for subsequent model training.

[0037] Next, machine learning algorithms, such as support vector machines, decision trees, or deep learning models, are used to train the perceived comfort impact analysis channel, the core of which is to learn and understand the complex relationship between humidity, temperature, and user comfort, so that when new data is input, the potential impact of environmental factors on user comfort can be accurately predicted. Through a large amount of sample data training and verification, the prediction accuracy and generalization ability of the perceived comfort impact analysis channel are ensured, so that it can be applied to comfort impact analysis under different users and environmental conditions.

[0038] Finally, the trained perceptual comfort impact analysis channel is used to analyze the comfort impact of the real-time collected humidity information array and temperature information array. According to the input environmental characteristic information, the corresponding perceptual comfort impact parameters are automatically calculated. These parameters quantitatively describe the specific impact of the current environment on the user's comfort, providing an important reference for the subsequent optimization of auxiliary nursing plans. Through the implementation of this step, the impact of environmental factors on user comfort can be more accurately grasped, so as to formulate a more personalized nursing plan and improve the patient's dialysis experience.

[0039] P40: At the plurality of perception points, the perception image array of the dialysis user is collected to perform comfort analysis to obtain actual comfort impact parameters, and an environmental comfort impact ratio analysis is performed in combination with the perceived comfort impact parameters to obtain the environmental comfort impact ratio.

[0040] Further, such as Figure 2 As shown, step P40 of the embodiment of the present application also includes:

[0041] P41: At the multiple perception points, the perception image array of the dialysis user is collected; P42: According to the user's comfort analysis data, a sample perception image set is collected, and according to the user's comfort in each sample perception image, a sample actual comfort impact parameter set is annotated to obtain; P43: Using the sample perception image set and the sample actual comfort impact parameter set, based on the convolutional neural network, an actual comfort impact analysis channel is trained; P44: Using the actual comfort impact analysis channel, multiple perception images in the perception image array are identified to obtain multiple actual comfort impact analysis results, and actual comfort impact parameters are calculated. P45: The ratio of the perceived comfort impact parameter to the actual comfort impact parameter is calculated to obtain the environmental comfort impact ratio.

[0042] In a possible embodiment of the present application, the system analyzes the user's comfort by collecting a perception image array of the dialysis user at multiple perception points to obtain actual comfort impact parameters, and performs environmental comfort impact ratio analysis in combination with the previously obtained perception comfort impact parameters to ultimately obtain the environmental comfort impact ratio.

[0043] First, at multiple sensing points in the dialysis environment, sensor arrays are used to collect sensor image arrays of the dialysis user. These sensor image arrays refer to real-time image data of the user during the dialysis process obtained through multiple cameras or image sensors. These images can capture the user's facial expressions, posture, skin condition, blood vessel color and other visual features, providing external visible clues about the user's comfort.

[0044] Next, using the user comfort analysis data in the historical data, a set of sample perception images is collected. These sample images cover the user status at different comfort levels, providing rich data support for subsequent model training. According to the user's comfort status in each sample image, the sample actual comfort influencing parameter set is annotated and obtained. The sample perception image set here comes from historical image data in different dialysis environments. These images are annotated to associate the user's subjective comfort perception with its external performance in the image, and generate a set of actual comfort influencing parameters.

[0045] Furthermore, the actual comfort impact analysis channel is trained based on the convolutional neural network (CNN) using the sample perception image set and the sample actual comfort impact parameter set. The convolutional neural network is a deep learning model that is particularly suitable for image recognition and analysis. Through training on a large amount of sample data, it can automatically extract and learn features in the image, thereby accurately identifying the factors affecting the user's actual comfort.

[0046] Subsequently, the trained actual comfort impact analysis channel is used to identify and analyze the currently acquired perception image array, thereby generating multiple actual comfort impact analysis results. Based on these analysis results, the actual comfort impact parameter of the current dialysis user is further calculated. This parameter reflects the user's actual comfort status in the current dialysis environment and is an objective assessment of the user's physiological and psychological comfort.

[0047] Finally, the environmental comfort impact ratio is obtained by calculating the ratio of the perceived comfort influencing parameters to the actual comfort influencing parameters. The environmental comfort impact ratio is a key indicator to measure the impact of the dialysis environment on user comfort. By comparing the perceived comfort influencing parameters (prediction based on environmental conditions) with the actual comfort influencing parameters (real evaluation based on image analysis), the proportion of user comfort caused by environmental factors can be determined. If this ratio is small, it means that the user's comfort is more affected by other factors (such as psychological state or health status) rather than environmental conditions; conversely, a large ratio indicates that environmental factors are the main cause of comfort, and environmental adjustments need to be made in subsequent optimization to optimize the nursing process.

[0048] P50: Based on the dialysis influencing parameters, perceived comfort influencing parameters and environmental comfort influencing ratio, the auxiliary care plan is optimized to obtain the optimal auxiliary care plan and perform auxiliary care, wherein the optimal auxiliary care plan includes the optimal temperature adjustment plan and the optimal humidity adjustment plan in the dialysis environment.

[0049] Furthermore, step P50 of the embodiment of the present application also includes:

[0050] P51: Based on the dialysis influencing parameters, the perceived comfort influencing parameters and the environmental comfort influencing ratio, an auxiliary care function is constructed as follows:

[0051] ;

[0052] Among them, ANF is nursing adaptability, and are dialysis weight and comfort weight respectively, and The sum of is 1, To obtain the dialysis impact parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, is the dialysis influencing parameter, is the impact ratio of environmental comfort, To calculate the perceived comfort influencing parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, is the perceived comfort influencing parameter; P52: obtaining the temperature adjustment range and humidity adjustment range of the hemodialysis environment, and constructing an auxiliary care plan space; P53: randomly generating a first auxiliary care plan in the auxiliary care plan space, and performing blood pressure impact analysis and classification on the dialysis user according to the first temperature adjustment plan and the first humidity adjustment plan in the first auxiliary care plan, and obtaining the first dialysis influencing parameter; P54: performing a comfort impact analysis according to the first temperature adjustment plan and the first humidity adjustment plan, and obtaining the first perceived comfort influencing parameter, and combining the first dialysis influencing parameter, based on the auxiliary care function, calculating and obtaining the first nursing fitness; P55: adjusting the first temperature adjustment plan and the first humidity adjustment plan, generating a second auxiliary care plan, and analyzing and calculating and obtaining the second nursing fitness; P56: distinguishing according to the second nursing fitness and the first nursing fitness, and retaining the first dialysis influencing parameter or the second dialysis influencing parameter; P57: continuing to adjust and iteratively optimize the retained auxiliary care plan according to the auxiliary care function in the auxiliary care plan space until convergence, and outputting the optimal auxiliary care plan with the largest nursing fitness.

[0053] It should be understood that by comprehensively considering the dialysis influencing parameters, the perceived comfort influencing parameters, and the environmental comfort influencing ratio, the optimal auxiliary care plan that can maximize the patient's dialysis effect and comfort can be formulated by constructing and optimizing the auxiliary care function. This process not only involves the precise control of the temperature and humidity in the dialysis environment, but also makes full use of data-driven methods to improve the pertinence and effectiveness of care.

[0054] Specifically, first, a function for optimizing the auxiliary care plan is constructed based on the dialysis influencing parameters, the perceived comfort influencing parameters and the environmental comfort influencing ratio, which is called the auxiliary care function. The goal of the auxiliary care function is to maximize the nursing fitness (ANF), where the dialysis weight and the comfort weight are used to balance the importance of the dialysis effect and the user's comfort in the care plan, respectively, and the sum of these two weights is 1. The specific form of the function is as follows:

[0055] ;

[0056] Among them, ANF is nursing adaptability, and are dialysis weight and comfort weight respectively, and The sum of is 1, To obtain the dialysis impact parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, is the dialysis influencing parameter, is the impact ratio of environmental comfort, To calculate the perceived comfort influencing parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, is the parameter affecting the perceived comfort.

[0057] Next, the temperature adjustment range and humidity adjustment range of the current hemodialysis environment are obtained, and an auxiliary care plan space is constructed based on these ranges. The auxiliary care plan space represents all possible combinations of temperature and humidity adjustments, which will be used as possible care plans to be selected during the system optimization process. Then, an initial auxiliary care plan, namely the first auxiliary care plan, is randomly generated in the auxiliary care plan space. According to the temperature adjustment and humidity adjustment recommended in this plan, the blood pressure of the dialysis user is analyzed, and the first dialysis influencing parameter is obtained by classification.

[0058] Further, a comfort impact analysis is performed according to the first temperature adjustment scheme and the first humidity adjustment scheme to obtain a first perceived comfort impact parameter. Then, in combination with the first dialysis impact parameter, a first nursing fitness is calculated based on the aforementioned auxiliary nursing function. The nursing fitness reflects the overall performance of the auxiliary nursing scheme in balancing the dialysis effect and the user's comfort.

[0059] Next, the first temperature adjustment scheme and the first humidity adjustment scheme are fine-tuned to generate the second auxiliary nursing scheme, and the above analysis and calculation process is repeated to obtain the second nursing fitness. Then, by comparing the first nursing fitness and the second nursing fitness, it is decided which dialysis influencing parameter to retain (i.e., which scheme is better). If the second nursing fitness is higher, the second dialysis influencing parameter and the corresponding second auxiliary nursing scheme are retained; otherwise, the first dialysis influencing parameter and the first auxiliary nursing scheme are retained.

[0060] Finally, iterative optimization is continued in the auxiliary care plan space according to the auxiliary care function and the currently retained auxiliary care plan. The temperature adjustment plan and the humidity adjustment plan are continuously adjusted, and the nursing fitness is recalculated until the optimal auxiliary care plan that maximizes the nursing fitness is found. This plan takes into account the optimal combination of dialysis effect and user comfort, and optimizes the dialysis environment by adjusting temperature and humidity, ultimately providing users with the best auxiliary care services.

[0061] Furthermore, step P56 of the embodiment of the present application also includes:

[0062] P56-1: When it is determined that the second nursing fitness is greater than the first nursing fitness, the second auxiliary nursing plan is retained; P56-2: When it is determined that the second nursing fitness is not greater than the first nursing fitness, the ratio of the second nursing fitness to the first nursing fitness is calculated, and combined with the environmental comfort impact ratio, the retention probability is calculated, and the first dialysis influencing parameter or the second dialysis influencing parameter is retained according to the retention probability.

[0063] Specifically, by refining the judgment and selection mechanism of the auxiliary care plan optimization process, it is ensured that the optimal auxiliary care plan can be effectively selected in different situations. First, when the system determines that the second care fitness is greater than the first care fitness, the second auxiliary care plan is directly retained. The nursing fitness (ANF) here is the key indicator for the system to measure the pros and cons of the nursing plan. A higher nursing fitness indicates that the plan has achieved a better balance between the dialysis effect and the user's comfort. Therefore, when the second nursing fitness exceeds the first nursing fitness, the system believes that the second auxiliary care plan is more advantageous and chooses to retain the plan for subsequent optimization.

[0064] However, if the discrimination result shows that the second nursing fitness is not greater than the first nursing fitness, that is, the improvement effects of the two schemes are similar or the second scheme does not show obvious advantages, a more detailed strategy is needed to decide which scheme to retain. At this time, the ratio of the second nursing fitness to the first nursing fitness is calculated, and this ratio reflects the relative advantages and disadvantages between the two schemes. Subsequently, combined with the environmental comfort impact ratio, this ratio is calculated in the previous step, which quantifies the degree of influence of environmental factors on patient comfort. By comprehensively considering these two factors, a retention probability is calculated. For example, the ratio is multiplied by the environmental comfort impact ratio to obtain the retention probability. For example, if the retention probability is 0.55, a random number within 0-1 can be randomly generated. When the random number is greater than 0.55, the second auxiliary nursing scheme is retained. When the random number is less than 0.55, the first auxiliary nursing scheme is retained. This probability takes into account both the fitness difference of the scheme itself and the importance of environmental comfort to the patient experience. It can improve the globality and accuracy of the optimization process and jump out of the local optimum.

[0065] In summary, the embodiments of the present application have at least the following technical effects:

[0066] The present application senses and collects an array of environmental characteristic information within a hemodialysis environment, analyzes and obtains dialysis influencing parameters, performs comfort impact analysis, obtains perceived comfort influencing parameters, collects a perceived image array for actual comfort analysis, and analyzes and obtains the environmental comfort impact ratio, and combines dialysis influencing parameters and perceived comfort influencing parameters to perform auxiliary care program optimization and auxiliary care.

[0067] The technical effect of assisting in the optimization of nursing plans through dynamic environmental perception and intelligent analysis technology, and improving the adaptability and comfort of nursing plans has been achieved.

[0068] Embodiment 2

[0069] Based on the same inventive concept as the intelligent hemodialysis auxiliary care method based on dynamic environment perception in the aforementioned embodiment, Figure 3 As shown, the present application provides an intelligent hemodialysis auxiliary care system based on dynamic environment perception, and the system and method embodiments in the present application are based on the same inventive concept. Among them, the system includes:

[0070] The environmental characteristic information acquisition module 11 is used to sense and collect the environmental characteristic information array in the hemodialysis environment through a sensing device, wherein the environmental characteristic information array includes a humidity information array and a temperature information array, and the sensing device includes a sensor array configured at multiple sensing points around the dialysis position.

[0071] The blood pressure impact analysis module 12 is used to perform blood pressure impact analysis on the dialysis user according to the humidity information array and the temperature information array, obtain blood pressure impact parameters, and classify and obtain the dialysis impact parameters.

[0072] The comfort impact analysis module 13 is used to perform comfort impact analysis on the dialysis user according to the humidity information array and the temperature information array to obtain a perceived comfort impact parameter.

[0073] The environmental comfort impact ratio analysis module 14 is used to collect the perception image array of the dialysis user at the multiple perception points, perform comfort analysis, obtain actual comfort impact parameters, and perform environmental comfort impact ratio analysis in combination with the perceived comfort impact parameters to obtain the environmental comfort impact ratio.

[0074] The auxiliary care program optimization module 15 is used to optimize the auxiliary care program based on the dialysis influencing parameters, the perceived comfort influencing parameters and the environmental comfort influencing ratio, obtain the optimal auxiliary care program, and perform auxiliary care, wherein the optimal auxiliary care program includes the optimal temperature adjustment program and the optimal humidity adjustment program in the dialysis environment.

[0075] Furthermore, the blood pressure impact analysis module 12 is further configured to perform the following steps:

[0076] According to the historical hemodialysis data, a sample humidity information array set and a sample temperature information array set are collected, and according to the parameters of the blood pressure change in the blood pressure test data, a sample blood pressure influence parameter set is annotated to obtain; the sample humidity information array set, the sample temperature information array set and the sample blood pressure influence parameter set are used to train the environmental blood pressure influence analysis channel; based on the environmental blood pressure influence analysis channel, the humidity information array and the temperature information array are subjected to blood pressure influence analysis to obtain blood pressure influence parameters; according to the historical hemodialysis data, a sample dialysis influence parameter set is collected; according to the sample blood pressure influence parameter set and the sample dialysis influence parameter set, a dialysis influence classification channel is constructed; the blood pressure influence parameters are input into the dialysis influence analysis channel, and the dialysis influence parameters are obtained by classification.

[0077] Furthermore, the comfort impact analysis module 13 is further configured to perform the following steps:

[0078] According to the data records of the user in the hemodialysis environment, a sample humidity information array set and a sample temperature information array set are collected, and according to the user's comfort query data, a sample perceived comfort influence parameter set is annotated to obtain; the sample humidity information array set, the sample temperature information array set and the sample perceived comfort influence parameter set are used to train a perceived comfort influence analysis channel; based on the perceived comfort influence analysis channel, the humidity information array and the temperature information array are subjected to a comfort influence analysis of the dialysis user to obtain perceived comfort influence parameters.

[0079] Furthermore, the environmental comfort impact ratio analysis module 14 is further configured to perform the following steps:

[0080] At the multiple perception points, the perception image array of the dialysis user is collected; according to the user's comfort analysis data, a sample perception image set is collected, and according to the user's comfort in each sample perception image, a sample actual comfort impact parameter set is annotated to obtain; using the sample perception image set and the sample actual comfort impact parameter set, based on a convolutional neural network, an actual comfort impact analysis channel is trained; using the actual comfort impact analysis channel, multiple perception images in the perception image array are identified to obtain multiple actual comfort impact analysis results, and actual comfort impact parameters are calculated. The ratio of the perceived comfort impact parameter to the actual comfort impact parameter is calculated to obtain the environmental comfort impact ratio.

[0081] Furthermore, the auxiliary nursing program optimization module 15 is also used to perform the following steps:

[0082] Based on the dialysis influencing parameters, the perceived comfort influencing parameters and the environmental comfort influencing ratio, an auxiliary care function is constructed as follows:

[0083] ;

[0084] Among them, ANF is nursing adaptability, and are dialysis weight and comfort weight respectively, and The sum of is 1, To obtain the dialysis impact parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, is the dialysis influencing parameter, is the impact ratio of environmental comfort, To calculate the perceived comfort influencing parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, The sensory comfort influencing parameter is obtained; the temperature adjustment range and humidity adjustment range of the hemodialysis environment are obtained to construct an auxiliary care plan space; a first auxiliary care plan is randomly generated in the auxiliary care plan space, and the blood pressure impact analysis and classification of the dialysis user are performed according to the first temperature adjustment plan and the first humidity adjustment plan in the first auxiliary care plan to obtain the first dialysis influencing parameter; according to the first temperature adjustment plan and the first humidity adjustment plan, a comfort impact analysis is performed to obtain the first perceived comfort influencing parameter, and in combination with the first dialysis influencing parameter, the first nursing fitness is calculated based on the auxiliary care function; the first temperature adjustment plan and the first humidity adjustment plan are adjusted to generate a second auxiliary care plan, and the second nursing fitness is obtained by analysis and calculation; according to the second nursing fitness and the first nursing fitness, the first dialysis influencing parameter or the second dialysis influencing parameter is retained to be judged; and the retained auxiliary care plan is continued to be adjusted and iteratively optimized according to the auxiliary care function in the auxiliary care plan space until convergence, and the optimal auxiliary care plan with the largest nursing fitness is output.

[0085] Furthermore, the auxiliary nursing program optimization module 15 is also used to perform the following steps:

[0086] When it is determined that the second nursing fitness is greater than the first nursing fitness, the second auxiliary nursing plan is retained; when it is determined that the second nursing fitness is not greater than the first nursing fitness, the ratio of the second nursing fitness to the first nursing fitness is calculated, and combined with the environmental comfort impact ratio, the retention probability is calculated and the first dialysis influencing parameter or the second dialysis influencing parameter is retained according to the retention probability.

[0087] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0088] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0089] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An environmental adjustment method for intelligent hemodialysis assisted care, characterized in that: The method comprises: The environmental characteristic information array in the hemodialysis environment is sensed and collected by a sensing device, wherein the environmental characteristic information array includes a humidity information array and a temperature information array, and the sensing device includes a sensor array configured at multiple sensing points around the dialysis position; According to the humidity information array and the temperature information array, the blood pressure impact analysis of the dialysis user is performed to obtain blood pressure impact parameters, and the dialysis impact parameters are obtained by classification; Performing a comfort impact analysis on the dialysis user according to the humidity information array and the temperature information array to obtain a perceived comfort impact parameter; At the plurality of perception points, the perception image array of the dialysis user is collected to perform comfort analysis to obtain actual comfort impact parameters, and the environmental comfort impact ratio analysis is performed in combination with the perceived comfort impact parameters to obtain the environmental comfort impact ratio; Based on the dialysis influencing parameters, the perceived comfort influencing parameters and the environmental comfort influencing ratio, the auxiliary nursing plan is optimized to obtain the optimal auxiliary nursing plan and perform auxiliary nursing, wherein the optimal auxiliary nursing plan includes the optimal temperature adjustment plan and the optimal humidity adjustment plan in the dialysis environment; According to the humidity information array and the temperature information array, the blood pressure impact analysis of the dialysis user is performed to obtain the blood pressure impact parameters, including: According to the historical hemodialysis data, a sample humidity information array set and a sample temperature information array set are collected, and according to the parameters of blood pressure changes in the blood pressure test data, a sample blood pressure influencing parameter set is obtained by marking; Using the sample humidity information array set, the sample temperature information array set and the sample blood pressure influence parameter set, training an environmental blood pressure influence analysis channel; Based on the environmental blood pressure impact analysis channel, performing blood pressure impact analysis on the humidity information array and the temperature information array to obtain blood pressure impact parameters; Based on historical hemodialysis data, a set of sample dialysis-affecting parameters is collected; Constructing a dialysis impact classification channel according to the sample blood pressure impact parameter set and the sample dialysis impact parameter set; Inputting the blood pressure influence parameters into the dialysis influence analysis channel, and obtaining the dialysis influence parameters by classification; According to the humidity information array and the temperature information array, the comfort impact analysis of the dialysis user is performed to obtain the perceived comfort impact parameters, including: According to the data records of the user in the hemodialysis environment, a sample humidity information array set and a sample temperature information array set are collected, and according to the user's comfort query data, a sample perceived comfort influencing parameter set is annotated to obtain; The sample humidity information array set, the sample temperature information array set and the sample perceived comfort impact parameter set are used to train a perceived comfort impact analysis channel; Based on the perceived comfort impact analysis channel, performing a comfort impact analysis on the dialysis user on the humidity information array and the temperature information array to obtain a perceived comfort impact parameter; Based on the dialysis influencing parameters, the perceived comfort influencing parameters and the environmental comfort influencing ratio, the auxiliary nursing plan is optimized to obtain the optimal auxiliary nursing plan, including: Based on the dialysis influencing parameters, the perceived comfort influencing parameters and the environmental comfort influencing ratio, an auxiliary care function is constructed as follows: ； Among them, ANF is nursing adaptability, and are dialysis weight and comfort weight respectively, and The sum of is 1, To obtain the dialysis impact parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, is the dialysis influencing parameter, is the impact ratio of environmental comfort, To calculate the perceived comfort influencing parameters of the environmental characteristic information array after assisted nursing according to the assisted nursing plan, is the perceived comfort influencing parameter; Obtain the temperature adjustment range and humidity adjustment range of the hemodialysis environment and build auxiliary care plan space; randomly generating a first auxiliary care plan in the auxiliary care plan space, and performing blood pressure impact analysis and classification on the dialysis user according to a first temperature adjustment plan and a first humidity adjustment plan in the first auxiliary care plan to obtain a first dialysis impact parameter; Performing a comfort impact analysis according to the first temperature adjustment scheme and the first humidity adjustment scheme to obtain a first perceived comfort impact parameter, and calculating and obtaining a first nursing adaptability based on the auxiliary nursing function in combination with the first dialysis impact parameter; Adjusting the first temperature adjustment scheme and the first humidity adjustment scheme to generate a second auxiliary nursing scheme, and analyzing and calculating to obtain a second nursing fitness; Making a judgment according to the second nursing adaptability and the first nursing adaptability, and retaining the first dialysis influencing parameter or the second dialysis influencing parameter; Continue to adjust and iteratively optimize the retained auxiliary care plans in the auxiliary care plan space according to the auxiliary care function until convergence, and output the optimal auxiliary care plan with the maximum care fitness.

2. The environmental adjustment method for intelligent hemodialysis auxiliary care according to claim 1, characterized in that: At the plurality of perception points, the perception image array of the dialysis user is collected, and comfort analysis is performed to obtain actual comfort influencing parameters, including: At the plurality of sensing points, collecting a sensing image array of the dialysis user; According to the user's comfort analysis data, a set of sample perception images is collected, and according to the user's comfort in each sample perception image, a set of parameters influencing the actual comfort of the sample is annotated to obtain; Using the sample perception image set and the sample actual comfort impact parameter set, based on a convolutional neural network, training an actual comfort impact analysis channel; The actual comfort impact analysis channel is used to identify multiple perception images in the perception image array, obtain multiple actual comfort impact analysis results, and calculate actual comfort impact parameters.

3. The environmental adjustment method for intelligent hemodialysis auxiliary care according to claim 1, characterized in that: The environmental comfort impact ratio analysis is performed in combination with the perceived comfort impact parameters to obtain the environmental comfort impact ratio, including: The ratio of the perceived comfort influence parameter to the actual comfort influence parameter is calculated to obtain the environmental comfort influence ratio.

4. The environmental adjustment method for intelligent hemodialysis auxiliary care according to claim 1, characterized in that: The method of determining according to the second nursing adaptability and the first nursing adaptability and retaining the first dialysis influencing parameter or the second dialysis influencing parameter comprises: When it is determined that the second nursing adaptability is greater than the first nursing adaptability, retaining the second auxiliary nursing plan; When it is determined that the second nursing fitness is not greater than the first nursing fitness, the ratio of the second nursing fitness to the first nursing fitness is calculated, and the retention probability is calculated in combination with the environmental comfort impact ratio, and the first dialysis influencing parameter or the second dialysis influencing parameter is retained according to the retention probability.

5. An environmental adjustment system for intelligent hemodialysis auxiliary care, characterized in that: The system is used to execute the method according to any one of claims 1 to 4, and the system comprises: An environmental characteristic information acquisition module, the environmental characteristic information acquisition module is used to sense and acquire an environmental characteristic information array in the hemodialysis environment through a sensing device, wherein the environmental characteristic information array includes a humidity information array and a temperature information array, and the sensing device includes a sensor array configured at multiple sensing points around the dialysis position; A blood pressure impact analysis module, the blood pressure impact analysis module is used to perform blood pressure impact analysis on the dialysis user according to the humidity information array and the temperature information array, obtain blood pressure impact parameters, and classify and obtain the dialysis impact parameters; A comfort impact analysis module, wherein the comfort impact analysis module is used to perform a comfort impact analysis on the dialysis user according to the humidity information array and the temperature information array to obtain a perceived comfort impact parameter; An environmental comfort impact ratio analysis module, the environmental comfort impact ratio analysis module is used to collect the perception image array of the dialysis user at the multiple perception points, perform comfort analysis, obtain actual comfort impact parameters, and perform environmental comfort impact ratio analysis in combination with the perceived comfort impact parameters to obtain an environmental comfort impact ratio; An auxiliary care program optimization module is used to optimize the auxiliary care program based on the dialysis influencing parameters, perceived comfort influencing parameters and environmental comfort influencing ratios, obtain the optimal auxiliary care program, and perform auxiliary care, wherein the optimal auxiliary care program includes an optimal temperature adjustment program and an optimal humidity adjustment program in the dialysis environment.

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