Children's intelligent asthma management monitoring device

Abstract

The invention provides an intelligent child asthma management and monitoring device. The device comprises a physiological parameter monitoring module, an environment monitoring module, a medicine management module and a data management module, the physiological parameter monitoring module is used for monitoring related physiological parameters of children asthma; the environment monitoring module is used for monitoring environment parameters; the medicine management module is used for recording and reminding the use condition of the asthma medicine; the data management module is used for collecting, analyzing and displaying physiological parameters, environmental parameters and medication information of children and supporting asthma condition assessment and disease trend early warning; through multi-dimensional parameter comprehensive monitoring, intelligent analysis and real-time early warning, comprehensiveness, accuracy and high efficiency of child asthma management are achieved, and scientific support is provided for child patient health.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and particularly to a children's intelligent asthma management and monitoring device. Background Art

[0002] Childhood asthma is a common chronic respiratory disease, and its onset is closely related to various physiological and environmental factors; due to the relatively fragile health status of children, the frequent onset of asthma not only seriously affects their quality of life, but also may bring long-term health risks; traditional asthma management methods often rely on subjective observation by parents and regular follow-up by doctors, making it difficult to capture the early signals of asthma attacks in a timely manner and unable to dynamically monitor the changing trend of the child's condition; with the development of sensing technology, data analysis and intelligent management tools, a more accurate and real-time solution is provided for the monitoring and management of childhood asthma, which can effectively improve the diagnosis and treatment efficiency and intervention effect of asthma.

[0003] Referring to relevant publicly disclosed technical solutions, the technology with the publication number CN113241143A proposes a method and system for digital monitoring and management of childhood asthma, including the following steps: S1: Taking PEF as the supervision index, following clinical evidence-based basis, constructing a graded medication plan model for asthmatic children, comparing the PEF index of the child's daily pulmonary function test with the individual prediction, and setting the medication plan according to different intervals of the ratio. The medication plan includes a first-class medication plan, a second-class medication plan, and a third-class medication plan; S2: Creating a control assessment scale according to the child's age and asthma management medical standards, and obtaining guiding opinions through the scores of the control assessment scale; S3: Dividing the children into four age groups: 0-4 years old, 5-6 years old, 6-11 years old, and over 12 years old, and creating a 1-year periodic follow-up plan for the four age groups. S4: Following the principles of precision, instantaneity, and non-intrusiveness, building a task message reaching engine to achieve automated and personalized message reaching for task events, key events, and abnormal events at both the doctor and patient ends; however, this solution takes PEF as the only supervision index. Although it has evidence-based medical basis, it does not involve the dynamic monitoring of multi-dimensional physiological parameters, and the monitoring dimension is relatively single; in addition, its asthma management focuses on medication plans and follow-up plans, and insufficient consideration is given to the analysis of real-time environmental factors and early warning of asthma attack trends. Summary of the Invention

[0004] The purpose of the present invention is to propose a children's intelligent asthma management and monitoring device for the current deficiencies.

[0005] The present invention adopts the following technical solutions:

[0006] A children's intelligent asthma management monitoring device, the device includes a physiological parameter monitoring module, an environmental monitoring module, a drug management module and a data management module; the physiological parameter monitoring module is used to monitor children's asthma-related physiological parameters; the environmental monitoring module is used to monitor environmental parameters; the drug management module is used to record and remind the use of asthma drugs; the data management module is used to collect, analyze and display children's physiological parameters, environmental parameters and medication information, and support asthma condition assessment and onset trend warning.

[0007] The physiological parameter monitoring module includes a respiratory rate monitoring unit, a blood oxygen monitoring unit and a heart rate monitoring unit; the respiratory rate monitoring unit includes a pressure sensor, which is used to monitor children's respiratory rate information by detecting the pressure change when the child's chest expands and contracts; the blood oxygen monitoring unit includes an optical sensor, which is used to monitor children's blood oxygen information; the heart rate monitoring unit includes an optical sensor, which is used to monitor children's heart rate information; the sensor used by the respiratory rate monitoring unit is integrated on a wearable device outside the chest, and the sensors used by the blood oxygen monitoring unit and the heart rate monitoring unit are integrated on a wearable device at the wrist.

[0008] Further, the environmental monitoring module includes an air quality monitoring unit and a humidity monitoring unit; the air quality monitoring unit is used to monitor the external air quality information; the temperature and humidity monitoring unit is used to monitor the external temperature and humidity information.

[0009] Further, the drug management module includes a medication reminder unit and a medication record unit; the medication reminder unit is used to remind children to take medicine on time according to the preset medication time; the medication record unit is used to record children's medication information.

[0010] Further, the data management module includes a data storage unit, a health status analysis unit, an asthma trend warning unit and an information display unit; the data storage unit is used to collect and store physiological parameters, environmental parameters and medication information; the health status analysis unit is used to monitor the child's health recovery when the child is in an asthma state; the asthma trend warning unit is used to analyze and predict the child's asthma attack trend and provide a warning reminder when the child is not in an asthma state; the information display unit is used to intuitively present physiological parameters, environmental parameters, medication records and analysis and prediction results, and provide accurate health management support for parents and doctors.

[0011] Further, the specific working process of the health status analysis unit is as follows:

[0012] S11: Set a continuous time acquisition period, and obtain the physiological parameters of the child within each time acquisition period; the physiological parameters include respiratory rate information, blood oxygen information and heart rate information;

[0013] S12: Calculate the asthma severity coefficient of the child within each time collection period in combination with the parameter data obtained in the previous step;

[0014]

[0015] Among them, A is the asthma severity coefficient within a certain time collection period, used to indicate the severity of the child's asthma within this time collection period; f r is the average respiratory rate of the child within this time collection period, is the reference respiratory rate of a preset normal child; SpO 2 is the average blood oxygen saturation of the child within this time collection period, is the reference blood oxygen saturation of a preset normal child; HR is the average heart rate of the child within this time collection period, HR e is the reference heart rate of a preset normal child; ω 1 and ω 2 and ω 3 are the influence weights of the respiratory rate, blood oxygen saturation, and heart rate on the asthma severity respectively;

[0016] S13: Obtain the asthma severity indices within consecutive n time collection periods including the current time collection period, and calculate the asthma fluctuation index based on the asthma severity indices within consecutive n time collection periods. The asthma fluctuation index is used to represent the overall fluctuation of the child's recent asthma severity;

[0017] S14: Calculate the health recovery coefficient in combination with the asthma severity coefficient and the asthma fluctuation index within the current time collection period to monitor the child's health recovery situation; The specific calculation method of the health recovery coefficient is as follows:

[0018]

[0019] Among them, R is the health recovery coefficient. The smaller the health recovery coefficient, the better the child's health recovery situation; A n is the asthma severity coefficient within the current time collection period, and α is an adjustment parameter used to control the exponential influence of the asthma fluctuation index on the health recovery coefficient, which is set through prior experiments, is the asthma fluctuation index.

[0020] Furthermore, the specific working process of the asthma trend warning unit is as follows:

[0021] S21: Set the warning monitoring period; and obtain the abnormal information of the physiological parameters and environmental parameters within the warning monitoring period; The specific acquisition method of the abnormal information of the physiological parameters and environmental parameters is as follows:

[0022] Abnormal physiological parameters: When a certain physiological parameter exceeds the preset normal range of this type of physiological parameter and the duration exceeds the preset time threshold, it is determined that this type of physiological parameter is abnormal at this time; the abnormal information of this type of physiological parameter recorded at this time includes the duration of the abnormality of this type of physiological parameter and the specific physiological parameter value when the abnormality exists; the physiological parameters include respiratory rate information, blood oxygen information, and heart rate information;

[0023] Abnormal environmental parameters: When a certain environmental parameter exceeds the preset normal range of this type of environmental parameter and the duration exceeds the preset time threshold, it is determined that this type of environmental parameter is abnormal at this time; the abnormal information of this type of environmental parameter recorded at this time includes the duration of the abnormality of this type of environmental parameter and the specific environmental parameter value when the abnormality exists; the environmental parameters include air quality information, temperature information, and humidity information;

[0024] S22: Calculate the asthma attack trend coefficient based on the information obtained in the previous step to predict the asthma attack trend of children;

[0025] S23: Set the asthma trend warning threshold, and when there is an asthma attack trend coefficient greater than the asthma trend warning threshold, a warning reminder about the asthma attack trend of children is issued at this time.

[0026] Advantages achieved by the present invention:

[0027] This solution completes the comprehensive monitoring and analysis related to children's asthma management through the comprehensive monitoring of physiological parameters and environmental parameters; when children are in the state of suffering from asthma, the health recovery of children is monitored in real time by combining dynamic physiological parameter analysis; when children are not in the state of suffering from asthma, the potential risk of asthma attack is predicted by combining the abnormal information and trend analysis of physiological parameters and environmental parameters, thereby realizing the all-round management and warning of children's asthma health status and attack trend, and providing scientific health management support. Description of the Drawings

[0028] The present invention can be further understood from the following description in conjunction with the drawings. The components in the drawings are not necessarily drawn to scale, but the emphasis is placed on showing the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0029] Figure 1 It is a schematic diagram of the overall module of the present invention.

[0030] Figure 2 It is a schematic diagram of the working process of the health status analysis unit of the present invention.

[0031] Figure 3 It is a schematic diagram of the working process of the asthma trend warning unit of the present invention. Detailed Embodiments

[0032] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below in conjunction with its embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention; for those skilled in the art, after referring to the following detailed description, other systems, methods and / or features of this embodiment will become obvious; it is intended that all such additional systems, methods, features and advantages are included in this specification; included within the scope of the present invention and protected by the appended claims; additional features of the disclosed embodiments are described in the following detailed description and will be obvious in accordance with the following detailed description.

[0033] In the drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", etc. indicating the orientation or positional relationship, they are based on the orientation or positional relationship shown in the drawings. This is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or component referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the drawings are only for illustrative purposes and cannot be construed as a limitation of this patent. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0034] Embodiment 1:

[0035] As Figure 1 shown, this embodiment provides a children's intelligent asthma management and monitoring device, which includes a physiological parameter monitoring module, an environmental monitoring module, a drug management module and a data management module; the physiological parameter monitoring module is used to monitor children's asthma-related physiological parameters; the environmental monitoring module is used to monitor environmental parameters; the drug management module is used to record and remind the use of asthma drugs; the data management module is used to collect, analyze and display children's physiological parameters, environmental parameters and medication information, and support asthma condition assessment and onset trend warning;

[0036] The physiological parameter monitoring module includes a respiratory rate monitoring unit, a blood oxygen monitoring unit and a heart rate monitoring unit; the respiratory rate monitoring unit includes a pressure sensor, which is used to monitor children's respiratory rate information by detecting the pressure changes when children's chest expands and contracts; the blood oxygen monitoring unit includes an optical sensor, which is used to monitor children's blood oxygen information; the heart rate monitoring unit includes an optical sensor, which is used to monitor children's heart rate information; the sensor used by the respiratory rate monitoring unit is integrated on a wearable device outside the chest, and the sensors used by the blood oxygen monitoring unit and the heart rate monitoring unit are integrated on a wearable device at the wrist;

[0037] Specifically, the pressure sensor in the respiratory rate monitoring unit obtains respiratory rate information by monitoring the pressure changes during the expansion and contraction of the child's chest; the optical sensor in the blood oxygen monitoring unit obtains blood oxygen information by monitoring the absorption changes of red light and infrared light by arterial blood under the skin; the optical sensor in the respiratory rate monitoring unit obtains heart rate information by capturing the periodic fluctuations of the light absorption changes caused by blood flow.

[0038] Furthermore, the environmental monitoring module includes an air quality monitoring unit and a humidity monitoring unit; the air quality monitoring unit is used to monitor the external air quality information; the temperature and humidity monitoring unit is used to monitor the external temperature and humidity information.

[0039] Furthermore, the drug management module includes a medication reminder unit and a medication record unit; the medication reminder unit is used to remind the child to take medicine on time according to the preset medication time; the medication record unit is used to record the child's medication information.

[0040] Furthermore, the data management module includes a data storage unit, a health status analysis unit, an asthma trend warning unit, and an information display unit; the data storage unit is used to collect and store physiological parameters, environmental parameters, and medication information; the health status analysis unit is used to monitor the child's health recovery when the child is in an asthma disease state; the asthma trend warning unit is used to analyze and predict the child's asthma attack trend and provide a warning reminder when the child is not in an asthma disease state; the information display unit is used to intuitively present physiological parameters, environmental parameters, medication records, and analysis and prediction results, providing accurate health management support for parents and doctors.

[0041] Specifically, the data management module is integrated in the cloud server, and uses cloud computing and storage technologies to complete the centralized management of physiological parameters, environmental parameters, and medication information.

[0042] Furthermore, as Figure 2 shown, the specific working process of the health status analysis unit is as follows:

[0043] S11: Set a continuous time acquisition period, and obtain the child's physiological parameters within each time acquisition period; the physiological parameters include respiratory rate information, blood oxygen information, and heart rate information.

[0044] S12: Calculate the asthma severity coefficient of the child within each time acquisition period by combining the parameter data obtained in the previous step.

[0045]

[0046] Among them, A is the asthma severity coefficient within a certain time collection period, used to indicate the severity of asthma in children during this time collection period; f r is the average respiratory rate of children during this time collection period, is the reference respiratory rate of pre-set normal children; SpO 2 is the average blood oxygen saturation of children during this time collection period, is the reference blood oxygen saturation of pre-set normal children; HR is the average heart rate of children during this time collection period, HR e is the reference heart rate of pre-set normal children; ω 1 、ω 2 and ω 3 are the influence weights of respiratory rate, blood oxygen saturation and heart rate on asthma severity respectively;

[0047] S13: Obtain the asthma severity index within consecutive n time collection periods including the current time collection period, and calculate the asthma fluctuation index based on the asthma severity index within consecutive n time collection periods. The asthma fluctuation index is used to represent the overall fluctuation of the recent asthma severity of children; among them, the quantity of n is set by the administrator according to the actual detection requirements and the length of the evaluation time period; the specific calculation method of the asthma fluctuation index is as follows:

[0048]

[0049] Among them, is the asthma fluctuation index, representing the overall fluctuation of the recent asthma severity of children; ΔA i is the asthma fluctuation change amount in the i-th time collection period; the larger i is, the closer the time collection period is to the current time collection period, and it satisfies:

[0050] ΔA i =A i -A i-1 ;

[0051] Among them, A i is the asthma severity coefficient in the i-th time collection period, A i-1 is the asthma severity coefficient in the (i - 1)-th time collection period;

[0052] S14: Combine the asthma severity coefficient and the asthma fluctuation index in the current time collection period to calculate the health recovery coefficient to monitor the health recovery situation of children; the specific calculation method of the health recovery coefficient is as follows:

[0053]

[0054] Among them, R is the health recovery coefficient. The smaller the health recovery coefficient, the better the child's health recovery; A n is the asthma severity coefficient within the current time collection period, and α is the adjustment parameter used to control the exponential impact of the asthma fluctuation index on the health recovery coefficient, which is set through pre-experiments;

[0055] Furthermore, the code for implementing part of the functions of the health status analysis unit is as follows:

[0056]

[0057]

[0058]

[0059]

[0060] This solution comprehensively quantifies the severity and fluctuation of childhood asthma by combining multi-dimensional physiological parameters such as respiratory rate, blood oxygen saturation, and heart rate; by analyzing the asthma severity coefficient and fluctuation index within the time collection period, it dynamically monitors the trend of disease changes; and it clearly evaluates the asthma recovery status through the health recovery coefficient, thereby helping parents and doctors quickly determine whether intervention is needed.

[0061] Example 2:

[0062] This example should be understood as including at least all the features of any one of the foregoing examples and further improving on this basis;

[0063] This example provides a children's intelligent asthma management and monitoring device, which includes a physiological parameter monitoring module, an environmental monitoring module, a drug management module, and a data management module; the physiological parameter monitoring module is used to monitor physiological parameters related to childhood asthma; the environmental monitoring module is used to monitor environmental parameters; the drug management module is used to record and remind the use of asthma drugs; the data management module is used to collect, analyze, and display the physiological parameters, environmental parameters, and medication information of children, and support asthma condition assessment and early warning of the onset trend;

[0064] Further, the data management module includes a data storage unit, a health status analysis unit, an asthma trend warning unit, and an information display unit; the data storage unit is used to collect and store physiological parameters, environmental parameters, and medication information; the health status analysis unit is used to monitor the health recovery of a child when the child is in an asthma-affected state; the asthma trend warning unit is used to analyze and predict the asthma attack trend of a child when the child is not in an asthma-affected state and provide a warning reminder; the information display unit is used to visually present physiological parameters, environmental parameters, medication records, and analysis and prediction results, providing accurate health management support for parents and doctors;

[0065] Further, as Figure 3 shown, the specific working process of the asthma trend warning unit is as follows:

[0066] S21: Set a warning monitoring period; and obtain abnormal information of physiological parameters and environmental parameters within the warning monitoring period; the specific obtaining methods for the abnormal information of physiological parameters and environmental parameters are as follows:

[0067] Abnormal physiological parameters: When a certain physiological parameter exceeds the normal range of the preset physiological parameter and the duration exceeds the preset time threshold, it is determined that the physiological parameter is abnormal at this time; the abnormal information of the physiological parameter recorded at this time includes the duration of the abnormal physiological parameter and the specific physiological parameter value when the abnormality exists; the physiological parameters include respiratory rate information, blood oxygen information, and heart rate information;

[0068] Abnormal environmental parameters: When a certain environmental parameter exceeds the normal range of the preset environmental parameter and the duration exceeds the preset time threshold, it is determined that the environmental parameter is abnormal at this time; the abnormal information of the environmental parameter recorded at this time includes the duration of the abnormal environmental parameter and the specific environmental parameter value when the abnormality exists; the environmental parameters include air quality information, temperature information, and humidity information;

[0069] S22: Calculate the asthma attack trend coefficient based on the information obtained in the previous step to predict the asthma attack trend of the child:

[0070]

[0071] Among them, Q is the asthma attack trend coefficient, which is used to quantitatively indicate the asthma attack trend of the child; w i is the influence weight of the i-th physiological parameter, reflecting the influence degree of this physiological parameter on the asthma attack trend; t i is the duration of the abnormality of the i-th physiological parameter within the warning monitoring period; max|x i | is the maximum difference value between the i-th physiological parameter and the boundary of its corresponding normal range within the warning monitoring period; is the normalized metric value of the preset i-th physiological parameter; F is the environmental inducing factor, satisfying:

[0072]

[0073] wherein, v j is the influence weight of the j-th environmental parameter, indicating the influence degree of this environmental parameter on the environmental inducing factor; T j is the duration of abnormality of the j-th environmental parameter during the warning monitoring period; max|y j | is the maximum difference value between the j-th environmental parameter and the corresponding normal range boundary during the warning monitoring period; is the normalized metric value of the preset j-th environmental parameter;

[0074] S23: Set the asthma trend warning threshold, and when there is an asthma attack trend coefficient greater than the asthma trend warning threshold, issue a warning reminder about the asthma attack trend of children at this time;

[0075] This solution realizes the quantitative assessment of the asthma attack trend by comprehensively analyzing the abnormal information of multi-dimensional physiological parameters and environmental parameters; accurately evaluates the potential risk of children's asthma attacks by combining the duration and degree of abnormality of each dimension parameter during the warning monitoring period, so as to achieve early warning, and then helps parents and doctors take intervention measures in time, effectively reducing the harm of acute asthma attacks;

[0076] Further, the information display unit provides services to users through a mobile application or a smart terminal; the main functions of the information display unit include:

[0077] Data visualization: Intuitively present the physiological parameters, environmental parameters and medication records of children in the form of icons and trend curves to help users quickly understand the current health status of children;

[0078] Generate a health status report: Generate a dynamic report on the health status of children, and the report content includes the health recovery coefficient, asthma attack trend coefficient and warning reminder information of the asthma attack trend, providing a scientific reference basis for parents and doctors;

[0079] Medication situation setting: Set the usage cycle of asthma drugs according to the asthma treatment plan of children and the doctor's advice; and through the control of the medication reminder unit, issue a medication reminder at the preset time point to ensure that children take medicine on time to achieve the best treatment effect;

[0080] Analysis mode switching: Dynamically switch the analysis mode according to the health status of children to meet the monitoring needs at different stages:

[0081] Asthma disease state: When a child is in the asthma disease state, the information display unit controls the health status analysis unit to run, monitors the health recovery situation by analyzing the health recovery coefficient and the changes in physiological parameters in real time, and provides a reference for subsequent treatment adjustment;

[0082] Non-asthma disease state: When a child is not in the asthma disease state, the information display unit controls the asthma trend warning unit to run, so as to provide a timely warning when the child has a potential risk of suffering from asthma.

[0083] The content disclosed above is only the preferred feasible embodiment of the present invention, and does not limit the protection scope of the present invention. Therefore, all equivalent technical changes made by using the content of the specification and drawings of the present invention are included in the protection scope of the present invention. In addition, with the development of technology, the elements therein can be updated.

Claims

1. A children's intelligent asthma management and monitoring device, characterized in that: The device includes a physiological parameter monitoring module, an environmental monitoring module, a drug management module and a data management module; the physiological parameter monitoring module is used to monitor physiological parameters related to children's asthma; the environmental monitoring module is used to monitor environmental parameters; the drug management module is used to record and remind the use of asthma drugs; the data management module is used to collect, analyze and display children's physiological parameters, environmental parameters and medication information, and support asthma condition assessment and early warning of disease trend; The physiological parameter monitoring module includes a respiratory rate monitoring unit, a blood oxygen monitoring unit and a heart rate monitoring unit; the respiratory rate monitoring unit includes a pressure sensor, and the pressure sensor monitors the child's respiratory rate information by detecting the pressure change when the child's chest cavity expands and contracts; the blood oxygen monitoring unit includes an optical sensor for monitoring the child's blood oxygen information; the heart rate monitoring unit includes an optical sensor for monitoring the child's heart rate information; The sensor used by the respiratory rate monitoring unit is integrated on a wearable device outside the chest cavity, and the sensors used by the blood oxygen monitoring unit and the heart rate monitoring unit are integrated on a wearable device at the wrist.

2. The intelligent asthma management and monitoring device for children according to claim 1, characterized in that: The environmental monitoring module includes an air quality monitoring unit and a humidity monitoring unit; the air quality monitoring unit is used to monitor external air quality information; the temperature and humidity monitoring unit is used to monitor external temperature and humidity information.

3. The intelligent asthma management and monitoring device for children according to claim 1, characterized in that: The medication management module includes a medication reminder unit and a medication recording unit; the medication reminder unit is used to remind children to take medication on time according to a preset medication time; the medication recording unit is used to record children's medication information.

4. The intelligent asthma management and monitoring device for children according to claim 1, characterized in that: The data management module includes a data storage unit, a health status analysis unit, an asthma trend warning unit and an information display unit; the data storage unit is used to collect and store physiological parameters, environmental parameters and medication information; the health status analysis unit is used to monitor the health recovery of children when they are in an asthma state; the asthma trend warning unit is used to analyze and predict the trend of asthma attacks in children when they are not in an asthma state, and provide warning reminders; The information display unit is used to intuitively present physiological parameters, environmental parameters, medication records and analysis and prediction results, providing accurate health management support for parents and doctors.

5. The intelligent asthma management and monitoring device for children according to claim 4, characterized in that: The specific working process of the health status analysis unit is as follows: S11: setting a continuous time collection period, and obtaining physiological parameters of the child in each time collection period; the physiological parameters include respiratory rate information, blood oxygen information and heart rate information; S12: Calculate the asthma severity coefficient of the child in each time collection period by combining the parameter data obtained in the previous step; Where A is the asthma severity coefficient within a certain time collection period, which is used to indicate the severity of asthma in children within the time collection period; f r is the average respiratory rate of the child during the collection period. is the preset normal reference respiratory rate for children; SpO2 is the average blood oxygen saturation of children during the collection period. is the preset normal children's reference blood oxygen saturation; HR is the average heart rate of the child during the collection period, HR e is the preset reference heart rate of normal children; ω1, ω2 and ω3 are the weights of the influence of respiratory rate, blood oxygen saturation and heart rate on the severity of asthma respectively; S13: obtaining asthma severity indexes within n consecutive time collection periods including the current time collection period, and calculating an asthma fluctuation index according to the asthma severity indexes within the n consecutive time collection periods, wherein the asthma fluctuation index is used to represent the overall fluctuation of the severity of the child's asthma in the recent period; S14: Calculate the health recovery coefficient by combining the asthma severity coefficient and the asthma fluctuation index in the current time collection period to monitor the health recovery of the child; the specific calculation method of the health recovery coefficient is as follows: Wherein, R is the health recovery coefficient, and the smaller the health recovery coefficient is, the better the child's health recovery is; A n is the asthma severity coefficient in the current time collection period, and α is the adjustment parameter used to control the exponential impact of the asthma fluctuation index on the health recovery coefficient. It is set by pre-experimental settings. Asthma volatility index.

6. The intelligent asthma management and monitoring device for children according to claim 4, characterized in that: The specific working process of the asthma trend early warning unit is as follows: S21: Setting an early warning monitoring period; and obtaining abnormal information of physiological parameters and environmental parameters within the early warning monitoring period; the specific method for obtaining the abnormal information of physiological parameters and environmental parameters is as follows: Physiological parameter abnormality: When a physiological parameter exceeds the preset normal range of the physiological parameter and the duration exceeds the preset time threshold, the physiological parameter is judged to be abnormal; The abnormal physiological parameter information recorded at this time includes the duration of the abnormal physiological parameter and the specific physiological parameter value when the abnormality exists; The physiological parameters include respiratory rate information, blood oxygen information and heart rate information; Abnormal environmental parameters: When a certain environmental parameter exceeds the preset normal range of the environmental parameter and the duration exceeds the preset time threshold, the environmental parameter is determined to be abnormal; the abnormal information of the environmental parameter recorded at this time includes the duration of the abnormal environmental parameter and the specific environmental parameter value when the abnormality exists; the environmental parameters include air quality information, temperature information and humidity information; S22: Calculate the asthma attack trend coefficient based on the information obtained in the previous step to predict the asthma attack trend of children; S23: Setting an asthma trend warning threshold, and when there is an asthma attack trend coefficient greater than the asthma trend warning threshold, issuing a warning reminder about the child's asthma attack trend.

Images