Intelligent medical bracelet system

Abstract

The invention discloses an intelligent medical bracelet system, and relates to the technical field of intelligent health assessment. The intelligent medical bracelet system comprises a data acquisition module, a change analysis module, an evaluation analysis module and a judgment analysis module, the data acquisition module is used for continuously acquiring cardiovascular measurement data, respiration measurement data and skin measurement data of a patient in a plurality of time periods, and the change analysis module is used for comprehensively analyzing the cardiovascular measurement data, the respiration measurement data and the skin measurement data of the patient in the plurality of time periods. According to the method, multiple physiological data, such as cardiovascular, breathing and skin health indexes, of the patient can be monitored in real time, the change trend of the health condition can be recognized through continuous time period data collection and analysis, a dynamic health report is provided for the patient, and the patient can be monitored in real time. The real-time monitoring can help doctors and patients to find potential health problems or risks in time.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent health assessment, and in particular to an intelligent medical bracelet system. Background Art

[0002] With the advancement of science and technology, smart wearable devices have gradually become an indispensable part of modern life. In the field of health management, smart medical bracelets have been widely used as a convenient and efficient health monitoring tool. By integrating sensors, wireless communications, data processing and other technologies, smart medical bracelets can monitor users' physiological data in real time, providing strong support for personal health management and disease prevention.

[0003] With the improvement of people's health awareness and the arrival of an aging society, health management has become an important issue in social development. Traditional health monitoring methods often rely on regular check-ups in hospitals or clinics, which is not only limited by time and location, but may also delay the early diagnosis of diseases. Especially in the management of chronic diseases, health monitoring of the elderly, sports and fitness, the demand for real-time health monitoring and data analysis is becoming more urgent.

[0004] As a typical wearable device, smart bracelets have become a popular choice for daily health monitoring due to their lightness, comfort and portability. They are mainly used for basic functions such as recording steps and monitoring sleep quality.

[0005] Based on the above findings, the current smart medical bracelet systems rarely have systems that conduct comprehensive analysis through multi-dimensional physiological data in patient health monitoring, and often lack dynamic change analysis and personalized evaluation. The existing technology mainly relies on the monitoring and evaluation of a single physiological parameter during design, and lacks continuous tracking and analysis of changes in different physiological parameters in different time periods. This can easily lead to difficulty in timely capturing the dynamic changes in the patient's health status, limiting the comprehensive assessment of the patient's health, lacking multi-dimensional data joint analysis and evaluation of dynamic change trends, making it difficult to effectively identify potential health problems, especially in the early stages when timely warnings are not given, thus affecting the patient's health management and treatment effects. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a smart medical bracelet system, which solves the problems in the prior art of lacking comprehensive analysis of multi-dimensional physiological data, dynamic change tracking and personalized evaluation.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a smart medical bracelet system, comprising: a data acquisition module, a change analysis module, an evaluation analysis module, and a judgment analysis module; the data acquisition module is used to continuously acquire the patient's cardiovascular measurement data, respiratory measurement data, and skin measurement data of several time periods, and perform preprocessing; the change analysis module is used to perform comprehensive analysis on the patient's cardiovascular measurement data, respiratory measurement data, and skin measurement data of several time periods after preprocessing, respectively, to obtain the patient's cardiovascular change index set, respiratory change index set, and skin change index set; the evaluation analysis module is used to perform comprehensive analysis on the patient's cardiovascular change index set, respiratory change index set, and skin change index set, respectively, to obtain the patient's cardiovascular change health assessment index, respiratory change health assessment index, and skin change health assessment index; the judgment analysis module is used to judge whether the patient's cardiovascular change health assessment index, respiratory change health assessment index, and skin change health assessment index are respectively within the preset cardiovascular change health assessment interval, respiratory change health assessment interval, and skin change health assessment interval, and take corresponding measures according to the judgment and analysis results.

[0008] Further, the cardiovascular measurement data includes heart rate value, pulse wave velocity value, blood pressure value, and blood flow value of several blood flow measurement positions; the respiratory measurement data includes respiratory rate value, vital capacity value, skin oxygen partial pressure value of several skin measurement positions, and blood oxygen saturation value of several blood flow measurement positions; the skin measurement data includes skin temperature value, skin conductivity value, skin surface water content value, and skin surface pH value of each skin measurement position; the cardiovascular change index set includes heart rate change index, pulse wave velocity change index, blood pressure change index, and blood flow change index; the respiratory change index set includes respiratory rate change index, vital capacity change index, skin oxygen partial pressure change index, and blood oxygen saturation change index; the skin change index set includes skin temperature change index, skin conductivity change index, skin surface water content change index, and skin surface pH change index.

[0009] Furthermore, the specific steps for obtaining the patient's cardiovascular change index set are as follows: read the patient's heart rate value, pulse wave velocity value, blood pressure value, and blood flow value at each blood flow measurement position in each time period, and perform change analysis respectively to obtain the patient's heart rate change index, pulse wave velocity change index, blood pressure change index, and blood flow initial change index at each blood flow measurement position; perform a comprehensive analysis of the patient's initial blood flow change index at each blood flow measurement position to obtain the patient's blood flow change index.

[0010] Furthermore, the specific formulas for calculating the patient's heart rate change index, pulse wave velocity change index, blood pressure change index, blood flow initial change index at each blood flow measurement position, and blood flow change index are as follows: Among them, XpB is the patient's heart rate change index, XpP i is the heart rate value of the patient in the i-th period, XpP i-1 is the patient's heart rate value in the i-1th period, McB is the patient's pulse wave velocity change index, McS i is the pulse wave velocity value of the patient in the i-th period, McS i-1 is the pulse wave velocity value of the patient in the i-1th period, XyB is the patient's blood pressure change index, XyZ i is the patient's blood pressure value in the i-th period, XyZ i-1 is the patient's blood pressure value in the i-1th period, XcB j is the initial change index of blood flow at the jth blood flow measurement position of the patient, XLZ ij is the blood flow value of the jth blood flow measurement position in the i-th period of the patient, XLZ (i-1)j is the blood flow value of the jth blood flow measurement position in the i-1th period of the patient, XbH is the patient's blood flow change index, α j is the weighted coefficient of the initial change index of the blood flow at the jth blood flow measurement position stored in the database, i=2, 3, 4, ...i0, i0 is the number of time periods, j=1, 2, 3, ...j0, j0 is the number of blood flow measurement positions.

[0011] Furthermore, the specific formula for calculating the patient's cardiovascular change health assessment index is as follows: Among them, XxG is the patient's cardiovascular change health assessment index, e is a natural constant, XpB is the patient's heart rate change index, ω1 is the heart rate coefficient stored in the database, McB is the patient's pulse wave conduction velocity change index, ω2 is the pulse wave conduction velocity coefficient stored in the database, XyB is the patient's blood pressure change index, ω3 is the blood pressure coefficient stored in the database, XbH is the patient's blood flow change index, ω4 is the blood flow coefficient stored in the database, ω1+ω2+ω3+ω4=1.

[0012] Furthermore, the specific steps for obtaining the patient's respiratory change index set are as follows: reading the patient's respiratory rate value, vital capacity value, skin oxygen partial pressure value at each skin measurement position, and blood oxygen saturation value at each blood flow measurement position in each time period, and performing change analysis respectively to obtain the patient's respiratory rate change index, vital capacity change index, skin oxygen partial pressure initial change index at each skin measurement position, and blood oxygen saturation initial change index at each blood flow measurement position; performing a comprehensive analysis on the patient's skin oxygen partial pressure initial change index at each skin measurement position and the blood oxygen saturation initial change index at each blood flow measurement position to obtain the patient's skin oxygen partial pressure change index and blood oxygen saturation change index.

[0013] Furthermore, the specific formulas for calculating the patient's respiratory rate change index, vital capacity change index, skin oxygen partial pressure initial change index at each skin measurement position, skin oxygen partial pressure change index, blood oxygen saturation initial change index at each blood flow measurement position, and blood oxygen saturation change index are as follows: Among them, HxB is the patient's respiratory rate change index, HxP i is the respiratory rate value of the patient in the i-th period, HxP i-1 is the respiratory rate value of the patient in the i-1th period, FhB is the patient's vital capacity change index, and FhL i is the vital capacity value of the patient in the i-th period, FhL i-1 is the vital capacity value of the patient in the i-1th period, PcB t is the initial change index of skin oxygen partial pressure at the patient's tth skin measurement position, PyF it is the skin oxygen partial pressure value of the patient at the tth skin measurement position in the i-th period, PyF (i-1)t is the skin oxygen partial pressure value of the patient at the t-th skin measurement position in the i-1th period, PyB is the patient's skin oxygen partial pressure change index, β t1 PcB is the weighting coefficient of the initial change index of skin oxygen partial pressure at the tth skin measurement position of the patient, t+1 is the initial change index of skin oxygen partial pressure at the patient's t+1th skin measurement position, β t2 is the weighting coefficient of the initial change index of skin oxygen partial pressure at the patient's t+1th skin measurement position, β t1 +β t2 =1,XyB j is the initial change index of blood oxygen saturation at the jth blood flow measurement position of the patient, XyH ij is the blood oxygen saturation value of the jth blood flow measurement position in the i-th period of the patient, XyH (i-1)jis the blood oxygen saturation value of the Jth blood flow measurement position in the i-1th period of the patient, XbB is the patient's blood oxygen saturation change index, η j1 is the weighting coefficient of the initial change index of blood oxygen saturation at the jth blood flow measurement position of the patient, XyB j+1 is the initial change index of blood oxygen saturation at the j+1th blood flow measurement position of the patient, η j2 is the weighting coefficient of the initial change index of blood oxygen saturation at the j+1th blood flow measurement position of the patient, η j1 +η j2 =1, i=2, 3, 4, ... i0, i0 is the number of time periods, t=1, 2, 3, ... t0, t0 is the number of skin measurement positions, j=1, 2, 3, ... j0, j0 is the number of blood flow measurement positions.

[0014] Furthermore, the specific formula for calculating the patient's respiratory change health assessment index is as follows: Among them, HbP is the patient's respiratory change health assessment index, HxB is the patient's respiratory rate change index, ξ1 is the respiratory rate coefficient stored in the database, FhB is the patient's vital capacity change index, ξ2 is the vital capacity coefficient stored in the database, PyB is the patient's skin oxygen partial pressure change index, ξ3 is the skin oxygen partial pressure coefficient stored in the database, XbB is the patient's blood oxygen saturation change index, ξ4 is the blood oxygen saturation coefficient stored in the database, ξ1+ξ2+ξ3+ξ4=1, and e is a natural constant.

[0015] Furthermore, the specific steps for obtaining the patient's skin change index set are as follows: read the skin temperature value, skin conductivity value, skin surface moisture content value, and skin surface pH value of each skin measurement position of the patient in each time period, and perform change analysis respectively to obtain the skin temperature initial change index, skin conductivity initial change index, skin surface moisture content initial change index, and skin surface pH initial change index of each skin measurement position of the patient; perform comprehensive analysis on the skin temperature initial change index, skin conductivity initial change index, skin surface moisture content initial change index, and skin surface pH initial change index of each skin measurement position of the patient to obtain the patient's skin temperature change index, skin conductivity change index, skin surface moisture content change index, and skin surface pH change index; wherein, the specific formulas for calculating the skin temperature initial change index, skin conductivity initial change index, skin surface moisture content initial change index, skin surface pH initial change index, skin temperature change index, skin conductivity change index, skin surface moisture content change index, and skin surface pH change index of each skin measurement position of the patient are as follows: Among them, PwC t PwD is the initial change index of skin temperature at the tth skin measurement position of the patient.it is the skin temperature value of the tth skin measurement position of the patient in the i-th period, PwD (i-1)t is the skin temperature value of the t-th skin measurement position of the patient in the i-1-th period, PwB is the patient's skin temperature change index, δ t is the weighting coefficient of the initial skin temperature change index at the tth skin measurement position stored in the database, PdC t is the initial change index of skin conductivity at the patient's tth skin measurement location, PdD it is the skin conductivity value of the patient at the tth skin measurement position in the ith period, PdD (i-1)t is the skin conductivity value of the patient at the t-th skin measurement position in the i-1-th period, PdB is the patient's skin conductivity change index, φ t is the weighting coefficient of the initial change index of skin conductivity at the tth skin measurement position stored in the database, PsC t PhS is the initial change index of skin surface moisture content at the tth skin measurement position of the patient, it is the skin surface moisture value of the patient at the tth skin measurement position in the ith period, PhS (i-1)t is the skin surface moisture content value of the t-th skin measurement position of the patient in the i-1-th period, PsB is the patient's skin surface moisture content change index, χ t is the weighting coefficient of the initial change index of skin surface moisture content at the tth skin measurement position stored in the database, PhC t PhZ is the initial change index of skin surface pH at the patient's tth skin measurement position. it is the skin surface pH value of the patient at the tth skin measurement position in the ith period, PhZ (i-1)t is the skin surface pH value of the patient at the t-th skin measurement position in the i-1-th period, PhB is the patient's skin surface pH change index, is the weighting coefficient of the initial change index of skin surface PH at the t-th skin measurement position stored in the database, i=2, 3, 4, ...i0, i0 is the number of time periods, t=1, 2.3...t0, t0 is the number of skin measurement positions.

[0016] Furthermore, the specific formula for calculating the patient's skin change health assessment index is as follows: Among them, PfP is the patient's skin change health assessment index, PwB is the patient's skin temperature change index, ψ1 is the skin temperature coefficient stored in the database, PdB is the patient's skin conductivity change index, ψ2 is the skin conductivity coefficient stored in the database, PsB is the patient's skin surface water content change index, ψ3 is the skin surface water content coefficient stored in the database, PhB is the patient's skin surface PH change index, ψ4 is the skin surface PH coefficient stored in the database, ψ1+ψ2+ψ3+ψ4=1, and π is pi.

[0017] The present invention has the following beneficial effects:

[0018] (1) The smart medical bracelet system can monitor multiple physiological data of patients in real time, such as cardiovascular, respiratory and skin health indicators. Through continuous time period data collection and analysis, it can identify changing trends in health conditions and provide patients with dynamic health reports. This real-time monitoring can help doctors and patients promptly identify potential health problems or risks, such as cardiovascular abnormalities or respiratory problems, and thus achieve early warning and intervention to prevent the occurrence or deterioration of diseases.

[0019] (2) The smart medical bracelet system generates a personalized health assessment index based on the changes in different physiological indicators of the patient, and makes judgments based on the set health range. Since the health status of each patient is different, the system can provide personalized health data analysis to make the patient's health management more refined. For example, the system can not only evaluate cardiovascular health, but also respiratory and skin health at the same time, and make comprehensive judgments based on various changes, so as to tailor health intervention plans for patients and ensure more effective health maintenance.

[0020] (3) The smart medical bracelet system can greatly improve the efficiency and accuracy of medical decision-making through automated analysis and health assessment of patients' multi-dimensional physiological data. Doctors can quickly understand the health status of patients through the health assessment index and change analysis provided by the system without having to manually interpret a large amount of single data. This data integration and analysis method not only saves doctors' time, but also avoids errors in human judgment, further improving the scientificity and accuracy of patient health management, and helping to improve treatment outcomes and patients' quality of life.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a system block diagram of a smart medical bracelet according to the present invention.

[0023] Figure 2This is a flowchart of the specific steps for obtaining a patient's cardiovascular change index set in a smart medical bracelet system of the present invention.

[0024] Figure 3 This is a flowchart of the specific steps for obtaining a patient's skin change index set in a smart medical bracelet system of the present invention. DETAILED DESCRIPTION

[0025] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0026] First, the smart medical bracelet system continuously acquires the patient's cardiovascular, respiratory, skin and other physiological data through the data acquisition module. These data come from multiple measurement points in different time periods, and the acquired data include heart rate, pulse wave velocity, blood pressure, respiratory rate, vital capacity, skin oxygen partial pressure, etc. Then, all data will be preprocessed to ensure the accuracy and availability of the data. Next, the preprocessed data enters the change analysis module to conduct a detailed comprehensive analysis of each type of physiological data. The goal of this module is to calculate the cardiovascular change index set, respiratory change index set, and skin change index set. These index sets reflect the changing trends of various physiological parameters of the patient. Finally, the evaluation and analysis module conducts a comprehensive analysis of the cardiovascular, respiratory and skin change index sets to obtain various health assessment indexes. The judgment and analysis module compares these health assessment indexes with the preset health intervals to determine whether the patient's health status is normal, and takes appropriate measures based on the results, such as reminders, alarms or medical interventions.

[0027] See also Figure 1 The embodiment of the present invention provides a technical solution: a smart medical bracelet system, comprising: a data acquisition module, a change analysis module, an evaluation analysis module, and a judgment analysis module; the data acquisition module is used to continuously acquire the patient's cardiovascular measurement data, respiratory measurement data, and skin measurement data of several time periods, and perform preprocessing; the change analysis module is used to perform comprehensive analysis on the patient's cardiovascular measurement data, respiratory measurement data, and skin measurement data of several time periods after preprocessing, respectively, to obtain the patient's cardiovascular change index set, respiratory change index set, and skin change index set; the evaluation analysis module is used to perform comprehensive analysis on the patient's cardiovascular change index set, respiratory change index set, and skin change index set, respectively, to obtain the patient's cardiovascular change health assessment index, respiratory change health assessment index, and skin change health assessment index; the judgment analysis module is used to judge whether the patient's cardiovascular change health assessment index, respiratory change health assessment index, and skin change health assessment index are respectively within the preset cardiovascular change health assessment interval, respiratory change health assessment interval, and skin change health assessment interval, and take corresponding measures according to the judgment analysis results, which are specifically:

[0028] When the patient's cardiovascular change health assessment index is outside the preset cardiovascular change health assessment range, an abnormal cardiovascular change alert is sent to relevant staff.

[0029] When the patient's respiratory change health assessment index is outside the preset respiratory change health assessment range, an abnormal respiratory change alarm is sent to relevant staff.

[0030] When the patient's skin change health assessment index is outside the preset skin change health assessment range, an abnormal skin change alert is sent to relevant staff.

[0031] The cardiovascular measurement data include heart rate value, pulse wave velocity value, blood pressure value, and blood flow value of several blood flow measurement positions; the respiratory measurement data include respiratory rate value, vital capacity value, skin oxygen partial pressure value of several skin measurement positions, and blood oxygen saturation value of several blood flow measurement positions; the skin measurement data include skin temperature value, skin conductivity value, skin surface water content value, and skin surface pH value of each skin measurement position; the cardiovascular change index set includes heart rate change index, pulse wave velocity change index, blood pressure change index, and blood flow change index; the respiratory change index set includes respiratory rate change index, vital capacity change index, skin oxygen partial pressure change index, and blood oxygen saturation change index; the skin change index set includes skin temperature change index, skin conductivity change index, skin surface water content change index, and skin surface pH change index.

[0032] Among them, the heart rate value can be measured and obtained through a heart rate monitor (such as an electrocardiogram device) and transmitted to the smart medical bracelet in real time. It is used to reflect the working status of the patient's heart. The normal heart rate is between 60-100bpm.

[0033] The pulse wave velocity value can be measured and obtained through pulse wave velocity measuring equipment (such as ultrasonic pulse sensor, pressure sensor, etc.) and transmitted to the smart medical bracelet in real time. It is used to assess the patient's degree of arteriosclerosis. Vascular sclerosis usually means a high risk of cardiovascular events (such as stroke, heart disease, etc.).

[0034] Blood pressure values ​​can be measured and obtained using a sphygmomanometer (such as a manual sphygmomanometer, automatic blood pressure monitoring device) and transmitted in real time to a smart medical bracelet, which is used to assess the patient's heart and vascular health.

[0035] The blood flow value can be measured by a blood flow sensor or an ultrasonic Doppler and transmitted to a smart medical bracelet in real time. It is used to reflect the patient's heart's pumping ability, the patency of blood vessels, and the health of the body's blood circulation.

[0036] The respiratory rate value can be measured by a respiratory rate sensor and transmitted to the smart medical bracelet in real time. It is used to assess the patient's respiratory health. The normal respiratory rate is 12-20 times per minute.

[0037] The vital capacity value can be measured and obtained through a spirometer (such as a portable spirometer, pulmonary function testing equipment) and transmitted to a smart medical bracelet in real time, which is used to reflect the health status of the patient's lung function.

[0038] The skin oxygen partial pressure value can be measured and obtained through a skin oxygen partial pressure sensor or a portable oxygen partial pressure monitor, and transmitted to a smart medical bracelet in real time, which is used to reflect the patient's tissue oxygenation.

[0039] The blood oxygen saturation value can be measured by a pulse oximeter (such as a finger-clip oximeter) and transmitted to a smart medical bracelet in real time. It is used to reflect the health of the patient's respiratory and circulatory systems. Normal blood oxygen saturation is 95% and above.

[0040] Skin temperature can be measured by an infrared thermometer and transmitted to a smart medical bracelet in real time, which is used to evaluate the patient's blood circulation and inflammatory response.

[0041] Skin conductivity values ​​can be measured by a skin conductance meter or electrophysiological sensor and transmitted to a smart medical bracelet in real time, which is used to assess the patient's skin hydration and emotional health.

[0042] The skin surface moisture content can be measured by a skin moisture meter (capacitive moisture meter) and transmitted to a smart medical bracelet in real time, which is used to reflect the patient's skin health and hydration.

[0043] The pH value of the skin surface can be measured by a skin pH tester (portable pH meter) and transmitted to a smart medical bracelet in real time, which is used to reflect the patient's skin barrier health.

[0044] Specifically, Figure 2 As shown, the specific steps for obtaining the patient's cardiovascular change index set are as follows: read the patient's heart rate value, pulse wave velocity value, blood pressure value, and blood flow value at each blood flow measurement position in each time period, and perform change analysis respectively to obtain the patient's heart rate change index, pulse wave velocity change index, blood pressure change index, and blood flow initial change index at each blood flow measurement position; perform a comprehensive analysis on the patient's initial blood flow change index at each blood flow measurement position to obtain the patient's blood flow change index.

[0045] The specific formulas for calculating the patient's heart rate change index, pulse wave velocity change index, blood pressure change index, blood flow initial change index at each blood flow measurement position, and blood flow change index are as follows: Among them, XpB is the patient's heart rate change index, XpP i is the heart rate value of the patient in the i-th period, XpP i-1 is the patient's heart rate value in the i-1th period, McB is the patient's pulse wave velocity change index, McS i is the pulse wave velocity value of the patient in the i-th period, McS i-1 is the pulse wave velocity value of the patient in the i-1th period, XyB is the patient's blood pressure change index, XyZ i is the patient's blood pressure value in the i-th period, XyZ i-1 is the patient's blood pressure value in the i-1th period, XcB j is the initial change index of blood flow at the jth blood flow measurement position of the patient, XLZ ij is the blood flow value of the jth blood flow measurement position in the i-th period of the patient, XLZ (i-1)j is the blood flow value of the jth blood flow measurement position in the i-1th period of the patient, XbH is the patient's blood flow change index, α j is the weighted coefficient of the initial change index of the blood flow at the jth blood flow measurement position stored in the database, i=2, 3, 4, ...i0, i0 is the number of time periods, j=1, 2, 3, ...j0, j0 is the number of blood flow measurement positions.

[0046] In this implementation, by quantitatively analyzing the changes in multiple important physiological parameters (such as heart rate, pulse wave velocity, blood pressure, blood flow, etc.), the patient's cardiovascular health status can be accurately understood. This is more comprehensive than the traditional single indicator (such as a single blood pressure measurement) and can provide more detailed dynamic health data. Each patient's physiological response and cardiovascular changes may be different. Therefore, by monitoring the cardiovascular change index (such as the heart rate change index, the pulse wave velocity change index, etc.), the doctor can formulate a more personalized treatment plan based on the specific health change trend of each patient, which helps to detect abnormalities early, adjust the treatment plan, avoid excessive intervention or missed diagnosis, and continuously monitor the patient's cardiovascular changes in different time periods. It can help doctors identify long-term health trends instead of just one. It is not just the health status at a single point in time. This dynamic monitoring helps to detect potential health problems early, take preventive measures or interventions in time, and avoid further deterioration of cardiovascular diseases. Through comprehensive analysis of changes in various cardiovascular indicators, the ability to predict cardiovascular events (such as heart attack, blood vessel blockage, etc.) can be improved. For example, abnormal changes in blood flow variation index and pulse wave velocity variation index may indicate vascular sclerosis or other cardiovascular risks. Identifying these changes in advance will help to carry out more effective prevention and intervention. Through quantified change indexes, doctors can rely more on data to make decisions, which reduces the bias of subjective judgment and improves the accuracy of diagnosis. Especially in chronic disease management, data-driven decision-making can help doctors monitor long-term changes and make timely treatment adjustments.

[0047] Specifically, the specific formula for calculating the patient's cardiovascular change health assessment index is as follows: Among them, XxG is the patient's cardiovascular change health assessment index, e is a natural constant, which is taken as 2.718 in this embodiment, XpB is the patient's heart rate change index, ω1 is the heart rate coefficient stored in the database, McB is the patient's pulse wave conduction velocity change index, ω2 is the pulse wave conduction velocity coefficient stored in the database, XyB is the patient's blood pressure change index, ω3 is the blood pressure coefficient stored in the database, XbH is the patient's blood flow change index, ω4 is the blood flow coefficient stored in the database, ω1+ω2+ω3+ω4=1.

[0048] In this embodiment, by integrating the changes of multiple key cardiovascular parameters (such as heart rate, pulse wave velocity, blood pressure, blood flow, etc.) into a comprehensive index, the patient's cardiovascular health status can be evaluated from multiple dimensions, which is more comprehensive than the evaluation method of a single parameter and can avoid missing potential health risks. Since the index can detect abnormal changes earlier through comprehensive analysis of multiple physiological parameters, for example, even if a single change in heart rate or blood pressure is not obvious, when the changes in these indicators are combined, they may indicate certain potential cardiovascular problems. Such an early warning mechanism can help doctors intervene in advance and reduce the risk of sudden cardiovascular events. Cardiovascular health status is affected by many factors. Analyzing each physiological parameter separately may result in too much complex data. By summarizing these changes into a comprehensive index, doctors and patients can more intuitively understand the patient's overall cardiovascular health status, reducing the tedious data interpretation process.

[0049] Specifically, the specific steps for obtaining the patient's respiratory change index set are as follows: read the patient's respiratory rate value, vital capacity value, skin oxygen partial pressure value at each skin measurement position, and blood oxygen saturation value at each blood flow measurement position in each time period, and perform change analysis respectively to obtain the patient's respiratory rate change index, vital capacity change index, skin oxygen partial pressure initial change index at each skin measurement position, and blood oxygen saturation initial change index at each blood flow measurement position; perform comprehensive analysis on the patient's skin oxygen partial pressure initial change index at each skin measurement position and the blood oxygen saturation initial change index at each blood flow measurement position to obtain the patient's skin oxygen partial pressure change index and blood oxygen saturation change index.

[0050] The specific formulas for calculating the patient's respiratory rate change index, vital capacity change index, skin oxygen partial pressure initial change index at each skin measurement location, skin oxygen partial pressure change index, blood oxygen saturation initial change index at each blood flow measurement location, and blood oxygen saturation change index are as follows: Among them, HxB is the patient's respiratory rate change index, HxP i is the respiratory rate value of the patient in the i-th period, HxP i-1 is the respiratory rate value of the patient in the i-1th period, FhB is the patient's vital capacity change index, and FhL i is the vital capacity value of the patient in the i-th period, FhL i-1 is the vital capacity value of the patient in the i-1th period, PcB t is the initial change index of skin oxygen partial pressure at the patient's tth skin measurement position, PyF it is the skin oxygen partial pressure value of the patient at the tth skin measurement position in the i-th period, PyF (i-1)tis the skin oxygen partial pressure value of the patient at the t-th skin measurement position in the i-1th period, PyB is the patient's skin oxygen partial pressure change index, β t1 PcB is the weighting coefficient of the initial change index of skin oxygen partial pressure at the tth skin measurement position of the patient, t+1 is the initial change index of skin oxygen partial pressure at the patient's t+1th skin measurement position, β t2 is the weighting coefficient of the initial change index of skin oxygen partial pressure at the patient's t+1th skin measurement position, β t1 +β t2 =1,XyB j is the initial change index of blood oxygen saturation at the jth blood flow measurement position of the patient, XyH ij is the blood oxygen saturation value of the jth blood flow measurement position in the i-th period of the patient, XyH (i-1)j is the blood oxygen saturation value of the jth blood flow measurement position in the i-1th period of the patient, XbB is the patient's blood oxygen saturation change index, η j1 is the weighting coefficient of the initial change index of blood oxygen saturation at the jth blood flow measurement position of the patient, XyB j+1 is the initial change index of blood oxygen saturation at the j+1th blood flow measurement position of the patient, η j2 is the weighting coefficient of the initial change index of blood oxygen saturation at the j+1th blood flow measurement position of the patient, η j1 +η j2 =1, i=2, 3, 4, ... i0, i0 is the number of time periods, t=1, 2, 3, ... t0, t0 is the number of skin measurement positions, j=1, 2, 3, ... j0, j0 is the number of blood flow measurement positions.

[0051] It needs to be explained that β t1 , β t2 The specific calculation process is: summing and analyzing the initial change index of skin oxygen partial pressure at the patient's t and t+1 skin measurement positions, and then performing proportion analysis on the skin oxygen partial pressure values ​​at the patient's t and t+1 skin measurement positions and the sum analysis result, respectively, and the analysis result is the corresponding weighting coefficient.

[0052] η j1 , η j2 The specific calculation process is: summing up and analyzing the initial change indexes of blood oxygen saturation at the jth and j+1th blood flow measurement positions of the patient, and then performing proportion analysis on the initial change indexes of blood oxygen saturation at the jth and j+1th blood flow measurement positions of the patient and the sum analysis result respectively, and the analysis result is the corresponding weighting coefficient.

[0053] In this implementation plan, a comprehensive analysis of changes in multiple physiological parameters such as respiratory rate, vital capacity, skin oxygen partial pressure, and blood oxygen saturation can more comprehensively evaluate the patient's respiratory health. Through these indices, doctors can not only understand the changes in a single indicator of the patient, but also capture the interactive relationship between various indicators, and provide a more accurate judgment of health status. By continuously monitoring the changes in each period, it is possible to identify subtle changes in health status, especially some subtle but potential health problems. For example, fluctuations in respiratory rate and vital capacity, or a decrease in skin oxygen partial pressure, may indicate abnormalities in the respiratory system. Timely detection of these changes will help to diagnose respiratory diseases, cardiopulmonary function decline, and other problems at an early stage, and avoid As the disease progresses to a more serious stage, the respiratory function of different patients may vary due to factors such as the cause of the disease, age, and physical condition. By calculating a personalized respiratory change index, doctors can develop targeted treatment plans based on the patient's specific health data. For patients with some chronic diseases (such as chronic obstructive pulmonary disease, asthma, etc.), doctors can adjust drug dosages or treatment plans based on the dynamic data of the change index to provide more precise care. This method can monitor the patient's respiratory system changes over a long period of time, and is particularly suitable for diseases that require long-term management (such as COPD, asthma, etc.). The health data provided by patients at different time periods can help doctors understand the fluctuating trends of the patient's condition and make preparations in advance.

[0054] Specifically, the specific formula for calculating the patient's respiratory change health assessment index is as follows: Among them, HbP is the patient's respiratory change health assessment index, HxB is the patient's respiratory rate change index, ξ1 is the respiratory rate coefficient stored in the database, FhB is the patient's vital capacity change index, ξ2 is the vital capacity coefficient stored in the database, PyB is the patient's skin oxygen partial pressure change index, ξ3 is the skin oxygen partial pressure coefficient stored in the database, XbB is the patient's blood oxygen saturation change index, ξ4 is the blood oxygen saturation coefficient stored in the database, ξ1+ξ2+ξ3+ξ4=1, e is a natural constant, and the value in this embodiment is 2.718.

[0055] In this embodiment, a more comprehensive health assessment can be provided by comprehensively analyzing the changes in multiple key indicators of the patient, such as respiratory rate, vital capacity, skin oxygen partial pressure and blood oxygen saturation. These indicators can reflect different aspects of respiratory function, such as gas exchange efficiency, lung capacity and oxygen transport capacity. Therefore, the comprehensive index can more comprehensively reflect the patient's respiratory health status than a single indicator. The health assessment index can continuously monitor changes in the respiratory system over multiple time periods. For example, fluctuations in blood oxygen saturation, respiratory rate or vital capacity may indicate potential respiratory diseases (such as chronic obstructive pulmonary disease, asthma, etc.) or cardiopulmonary function problems. By dynamically monitoring these changes, doctors can identify abnormal trends in a timely manner and take intervention measures in advance to avoid the deterioration of health problems. The respiratory health status of each patient varies due to individual differences. By combining multiple physiological parameters with personalized coefficients in the database (such as respiratory rate coefficient, vital capacity coefficient, etc.), the calculated health assessment index can more accurately reflect the patient's specific situation. In this way, doctors can formulate personalized treatment plans and intervention measures based on the patient's unique data to avoid "one-size-fits-all" standard treatment methods.

[0056] Specifically, Figure 3 As shown, the specific steps of obtaining the patient's skin change index set are as follows: read the patient's skin temperature value, skin conductivity value, skin surface moisture value, and skin surface pH value at each skin measurement position of each time period, and perform change analysis respectively to obtain the patient's skin temperature initial change index, skin conductivity initial change index, skin surface moisture content initial change index, and skin surface pH initial change index at each skin measurement position; perform comprehensive analysis on the skin temperature initial change index, skin conductivity initial change index, skin surface moisture content initial change index, and skin surface pH initial change index at each skin measurement position of the patient to obtain the patient's skin temperature change index, skin conductivity change index, skin surface moisture content change index, and skin surface pH change index.

[0057] The specific formulas for calculating the initial change index of skin temperature, the initial change index of skin conductivity, the initial change index of skin surface water content, the initial change index of skin surface pH, the skin temperature change index, the skin conductivity change index, the skin surface water content change index, and the skin surface pH change index at each skin measurement position of the patient are as follows: Among them, PwC t PwD is the initial change index of skin temperature at the tth skin measurement position of the patient. it is the skin temperature value of the tth skin measurement position of the patient in the i-th period, PwD (i-1)t is the skin temperature value of the t-th skin measurement position of the patient in the i-1-th period, PwB is the patient's skin temperature change index, δt is the weighting coefficient of the initial skin temperature change index at the tth skin measurement position stored in the database, PdC t is the initial change index of skin conductivity at the patient's tth skin measurement location, PdD it is the skin conductivity value of the patient at the tth skin measurement position in the ith period, PdD (i-1)t is the skin conductivity value of the patient at the t-th skin measurement position in the i-1-th period, PdB is the patient's skin conductivity change index, φ t is the weighting coefficient of the initial change index of skin conductivity at the tth skin measurement position stored in the database, PsC t PhS is the initial change index of skin surface moisture content at the tth skin measurement position of the patient, it is the skin surface moisture value of the patient at the tth skin measurement position in the ith period, PhS (i-1)t is the skin surface moisture content value of the t-th skin measurement position of the patient in the i-1-th period, PsB is the patient's skin surface moisture content change index, χ t is the weighting coefficient of the initial change index of skin surface moisture content at the tth skin measurement position stored in the database, PhC t PhZ is the initial change index of skin surface pH at the patient's tth skin measurement position. it is the skin surface pH value of the patient at the tth skin measurement position in the ith period, PhZ (i-1)t is the skin surface pH value of the patient at the t-th skin measurement position in the i-1-th period, PhB is the patient's skin surface pH change index, is the weighting coefficient of the initial change index of skin surface PH at the t-th skin measurement position stored in the database, i=2, 3, 4, ...i0, i0 is the number of time periods, t=1, 2, 3, ...t0, t0 is the number of skin measurement positions.

[0058] In this embodiment, skin health is affected by many factors, including temperature, humidity, skin conductivity, etc. By calculating the change index of skin temperature, skin conductivity, skin surface water content, and skin surface pH value at each skin measurement location, the health status of the skin can be comprehensively evaluated. For example, skin conductivity reflects skin hydration and sweat gland activity, while skin surface pH value helps to monitor skin barrier function. By comprehensively analyzing these multiple data, a complete trend of skin health changes can be obtained. Changes in the physiological state of the skin are usually a reflection of some inherent health problems, such as dehydration, decreased skin barrier function, inflammation, etc. By dynamically monitoring changes in various skin parameters, abnormal changes in skin health can be detected early. For example, abnormal fluctuations in skin temperature may indicate blood circulation problems or inflammation, while changes in skin conductivity and pH value may be a precursor to dry skin or infection. Detecting these abnormalities in advance can help to adjust the treatment plan in time. Or improve skin care. Everyone's skin condition and health needs are different. By providing a specific change index for each skin measurement location, doctors and caregivers can provide personalized care and treatment plans based on specific skin health data. The skin in different areas may show different changes due to different environments or health conditions. This personalized analysis helps to achieve precise treatment. For example, the hydration needs of facial skin and hand skin may be different. Doctors can adjust the care plan according to the changes in different areas. This part of the method integrates multiple skin physiological parameters for comprehensive change analysis. A single skin parameter may not be able to fully reflect the health status of the skin, but by combining skin temperature, skin conductivity, skin surface water content and pH value, the overall health of the skin can be more accurately grasped. Multidimensional data analysis helps to reveal health problems hidden behind a single indicator, especially for the diagnosis and treatment of complex skin diseases (such as eczema, psoriasis, etc.).

[0059] Specifically, the specific formula for calculating the patient's skin change health assessment index is as follows: Among them, PfP is the patient's skin change health assessment index, PwB is the patient's skin temperature change index, ψ1 is the skin temperature coefficient stored in the database, PdB is the patient's skin conductivity change index, ψ2 is the skin conductivity coefficient stored in the database, PsB is the patient's skin surface water content change index, ψ3 is the skin surface water content coefficient stored in the database, PhB is the patient's skin surface PH change index, ψ4 is the skin surface PH coefficient stored in the database, ψ1+ψ2+ψ3+ψ4=1, π is pi, and the value of this embodiment is 3.14.

[0060] In this embodiment, skin health is affected by multiple factors, including skin temperature, conductivity, hydration and pH value, etc. These factors not only reflect the physical and chemical properties of the skin, but also reveal potential physiological problems. By comprehensively analyzing these parameters, doctors can fully understand the patient's skin health status, thereby avoiding dependence on a single indicator. For example, changes in skin temperature may reflect circulation problems, changes in skin conductivity can show insufficient hydration or skin barrier dysfunction, and pH value may indicate skin health or the presence of inflammation. Therefore, a comprehensive skin change health assessment can provide more accurate diagnostic information. Skin changes are usually external manifestations of the body's inherent health status. For example, changes in skin conductivity and hydration may indicate an imbalance in body water or a damaged skin barrier, while fluctuations in skin pH may suggest inflammation or skin infection. Dynamic monitoring of these changes can help detect skin problems and potential systemic diseases early. Disease, thereby providing doctors with early warning and taking timely intervention measures to prevent the disease from worsening. Skin health is a physiological characteristic with obvious individual differences. The skin type, health status and external environment of different patients will affect skin parameters. Therefore, by calculating the skin change health assessment index, doctors can design personalized care and treatment plans based on the specific skin changes of each patient. For example, some patients may need more moisturizing care, while others may need anti-inflammatory treatment for abnormal skin pH. Personalized health management helps to improve the accuracy and effectiveness of treatment. Skin health is not just an instantaneous state. It will change with time, environmental changes and fluctuations in internal health status. By continuously monitoring various skin indicators, doctors can track the patient's skin health change trends, which is especially important for patients with chronic diseases. They can adjust the treatment plan in time according to skin changes to achieve the goal of long-term health management.

[0061] In summary, this application has at least the following effects:

[0062] It can monitor multiple physiological data of patients in real time, such as cardiovascular, respiratory and skin health indicators. Through continuous time period data collection and analysis, it can identify changing trends in health conditions and provide patients with dynamic health reports. This real-time monitoring can help doctors and patients promptly detect potential health problems or risks, such as cardiovascular abnormalities or respiratory problems, and thereby achieve early warning and intervention to prevent the occurrence or deterioration of the disease.

[0063] By generating a personalized health assessment index based on changes in different physiological indicators of patients, and making judgments based on set health ranges, the system can provide personalized health data analysis to make patient health management more refined, as each patient's health status is different. For example, the system can not only assess cardiovascular health, but also respiratory and skin health at the same time, and make comprehensive judgments based on various changes, tailor-made health intervention plans for patients to ensure more effective health maintenance.

[0064] Through automated analysis and health assessment of patients' multi-dimensional physiological data, the efficiency and accuracy of medical decision-making can be greatly improved. Doctors can quickly understand the patient's health status through the health assessment index and change analysis provided by the system without having to manually interpret a large amount of single data. This data integration and analysis method not only saves doctors' time, but also avoids errors in human judgment, further improving the scientificity and accuracy of patient health management, and helping to improve treatment outcomes and patients' quality of life.

[0065] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0066] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A smart medical bracelet system, characterized in that: include: Data acquisition module, change analysis module, evaluation analysis module, judgment analysis module; The data acquisition module is used to continuously acquire the patient's cardiovascular measurement data, respiratory measurement data, and skin measurement data for several time periods, and perform preprocessing; The change analysis module is used to comprehensively analyze the pre-processed cardiovascular measurement data, respiratory measurement data, and skin measurement data of the patient at several time periods, respectively, to obtain the patient's cardiovascular change index set, respiratory change index set, and skin change index set; The evaluation and analysis module is used to perform comprehensive analysis on the patient's cardiovascular change index set, respiratory change index set, and skin change index set, respectively, to obtain the patient's cardiovascular change health evaluation index, respiratory change health evaluation index, and skin change health evaluation index; The judgment and analysis module is used to judge whether the patient's cardiovascular change health assessment index, respiratory change health assessment index, and skin change health assessment index are respectively within the preset cardiovascular change health assessment interval, respiratory change health assessment interval, and skin change health assessment interval, and take corresponding measures based on the judgment and analysis results.

2. The smart medical bracelet system according to claim 1, characterized in that: The cardiovascular measurement data include heart rate value, pulse wave velocity value, blood pressure value, and blood flow value of several blood flow measurement positions; the respiratory measurement data include respiratory rate value, vital capacity value, skin oxygen partial pressure value of several skin measurement positions, and blood oxygen saturation value of several blood flow measurement positions; the skin measurement data include skin temperature value, skin conductivity value, skin surface water content value, and skin surface pH value of each skin measurement position; the cardiovascular change index set includes heart rate change index, pulse wave velocity change index, blood pressure change index, and blood flow change index; the respiratory change index set includes respiratory rate change index, vital capacity change index, skin oxygen partial pressure change index, and blood oxygen saturation change index; the skin change index set includes skin temperature change index, skin conductivity change index, skin surface water content change index, and skin surface pH change index.

3. The smart medical bracelet system according to claim 2, characterized in that: The specific steps for obtaining the patient's cardiovascular change index set are as follows: Read the patient's heart rate value, pulse wave velocity value, blood pressure value, and blood flow value at each blood flow measurement position in each period, and perform change analysis respectively to obtain the patient's heart rate change index, pulse wave velocity change index, blood pressure change index, and blood flow initial change index at each blood flow measurement position; The initial change index of blood flow at each blood flow measurement position of the patient is comprehensively analyzed to obtain the blood flow change index of the patient.

4. The smart medical bracelet system according to claim 3, characterized in that: The specific formulas for calculating the patient's heart rate change index, pulse wave velocity change index, blood pressure change index, blood flow initial change index at each blood flow measurement position, and blood flow change index are as follows: Among them, XpB is the patient's heart rate change index, XpP i is the heart rate value of the patient in the i-th period, XpP i-1 is the patient's heart rate value in the i-1th period, McB is the patient's pulse wave velocity change index, McS i is the pulse wave velocity value of the patient in the i-th period, McS i-1 is the pulse wave velocity value of the patient in the i-1th period, XyB is the patient's blood pressure change index, XyZ i is the patient's blood pressure value in the i-th period, XyZ i-1 is the patient's blood pressure value in the i-1th period, XcB j is the initial change index of blood flow at the jth blood flow measurement position of the patient, XLZ ij is the blood flow value of the jth blood flow measurement position in the i-th period of the patient, XLZ (i-1)j is the blood flow value of the jth blood flow measurement position in the i-1th period of the patient, XbH is the patient's blood flow change index, α j is the weighted coefficient of the initial change index of the blood flow at the jth blood flow measurement position stored in the database, i=2, 3, 4, ...i0, i0 is the number of time periods, j=1, 2, 3, ...j0, j0 is the number of blood flow measurement positions.

5. The smart medical bracelet system according to claim 3, characterized in that: The specific formula for calculating the patient's cardiovascular change health assessment index is as follows: Among them, XxG is the patient's cardiovascular change health assessment index, e is a natural constant, XpB is the patient's heart rate change index, ω1 is the heart rate coefficient stored in the database, McB is the patient's pulse wave conduction velocity change index, ω2 is the pulse wave conduction velocity coefficient stored in the database, XyB is the patient's blood pressure change index, ω3 is the blood pressure coefficient stored in the database, XbH is the patient's blood flow change index, ω4 is the blood flow coefficient stored in the database, ω1+ω2+ω3+ω4=1.

6. The smart medical bracelet system according to claim 2, characterized in that: The specific steps for obtaining the patient's respiratory change index set are as follows: Read the patient's respiratory rate value, vital capacity value, skin oxygen partial pressure value at each skin measurement position, and blood oxygen saturation value at each blood flow measurement position at each time period, and perform change analysis respectively to obtain the patient's respiratory rate change index, vital capacity change index, skin oxygen partial pressure initial change index at each skin measurement position, and blood oxygen saturation initial change index at each blood flow measurement position; The initial change index of skin oxygen partial pressure at each skin measurement position of the patient and the initial change index of blood oxygen saturation at each blood flow measurement position of the patient are comprehensively analyzed to obtain the patient's skin oxygen partial pressure change index and blood oxygen saturation change index.

7. The smart medical bracelet system according to claim 6, characterized in that: The specific formulas for calculating the patient's respiratory rate change index, vital capacity change index, skin oxygen partial pressure initial change index at each skin measurement location, skin oxygen partial pressure change index, blood oxygen saturation initial change index at each blood flow measurement location, and blood oxygen saturation change index are as follows: Among them, HxB is the patient's respiratory rate change index, HxP i is the respiratory rate value of the patient in the i-th period, HxP i-1 is the respiratory rate value of the patient in the i-1th period, FhB is the patient's vital capacity change index, and FhL i is the vital capacity value of the patient in the i-th period, FhL i-1 is the vital capacity value of the patient in the i-1th period, PcB t is the initial change index of skin oxygen partial pressure at the tth skin measurement position of the patient, PyF it is the skin oxygen partial pressure value at the tth skin measurement position of the patient in the i-th period, PyE (i-1)t is the skin oxygen partial pressure value of the patient at the t-th skin measurement position in the i-1th period, PyB is the patient's skin oxygen partial pressure change index, β t1 is the weighting coefficient of the initial change index of skin oxygen partial pressure at the tth skin measurement position of the patient, PcB t+1 is the initial change index of skin oxygen partial pressure at the patient's t+1th skin measurement position, β t2 is the weighting coefficient of the initial change index of skin oxygen partial pressure at the patient's t+1th skin measurement position, β t1 +β t2 =1,XyB j is the initial change index of blood oxygen saturation at the jth blood flow measurement position of the patient, XyH ij is the blood oxygen saturation value of the jth blood flow measurement position in the i-th period of the patient, XyH (i-1)j is the blood oxygen saturation value of the jth blood flow measurement position in the i-1th period of the patient, XbB is the patient's blood oxygen saturation change index, η jl is the weighting coefficient of the initial change index of blood oxygen saturation at the jth blood flow measurement position of the patient, XyB j+1 is the initial change index of blood oxygen saturation at the j+1th blood flow measurement position of the patient, η j2 is the weighting coefficient of the initial change index of blood oxygen saturation at the j+1th blood flow measurement position of the patient, η j1 +η j2 =1, i=2, 3, 4, ... i0, i0 is the number of time periods, t=1, 2, 3, ... t0, t0 is the number of skin measurement positions, j=1, 2, 3, ... j0, j0 is the number of blood flow measurement positions.

8. The smart medical bracelet system according to claim 1, characterized in that: The specific formula for calculating the patient's respiratory change health assessment index is as follows: Among them, HbP is the patient's respiratory change health assessment index, HxB is the patient's respiratory rate change index, ξ1 is the respiratory rate coefficient stored in the database, FhB is the patient's vital capacity change index, ξ2 is the vital capacity coefficient stored in the database, PyB is the patient's skin oxygen partial pressure change index, ξ3 is the skin oxygen partial pressure coefficient stored in the database, XbB is the patient's blood oxygen saturation change index, ξ4 is the blood oxygen saturation coefficient stored in the database, ξ1+ξ2+ξ3+ξ4=1, and e is a natural constant.

9. The smart medical bracelet system according to claim 1, characterized in that: The specific steps for obtaining the patient's skin change index set are as follows: Read the skin temperature value, skin conductivity value, skin surface moisture content value, and skin surface pH value of each skin measurement position of the patient at each time period, and perform change analysis respectively to obtain the skin temperature initial change index, skin conductivity initial change index, skin surface moisture content initial change index, and skin surface pH initial change index of each skin measurement position of the patient; Comprehensively analyze the initial change index of skin temperature, the initial change index of skin conductivity, the initial change index of skin surface water content, and the initial change index of skin surface pH at each skin measurement position of the patient to obtain the patient's skin temperature change index, skin conductivity change index, skin surface water content change index, and skin surface pH change index; The specific formulas for calculating the initial change index of skin temperature, the initial change index of skin conductivity, the initial change index of skin surface water content, the initial change index of skin surface pH, the skin temperature change index, the skin conductivity change index, the skin surface water content change index, and the skin surface pH change index at each skin measurement position of the patient are as follows: Among them, PwC t is the initial change index of skin temperature at the tth skin measurement position of the patient, PwD it is the skin temperature value of the tth skin measurement position of the patient in the i-th period, PwD (i-1)t is the skin temperature value of the t-th skin measurement position of the patient in the i-1-th period, PwB is the patient's skin temperature change index, δ t is the weighting coefficient of the initial skin temperature change index at the tth skin measurement position stored in the database, PdC t is the initial change index of skin conductivity at the patient's tth skin measurement location, PdD it is the skin conductivity value of the patient at the tth skin measurement position in the ith period, PdD (i-1)t is the skin conductivity value of the patient at the t-th skin measurement position in the i-1-th period, PdB is the patient's skin conductivity change index, φ t is the weighting coefficient of the initial change index of skin conductivity at the tth skin measurement position stored in the database, PsC t PhS is the initial change index of skin surface moisture content at the tth skin measurement position of the patient, it is the skin surface moisture value of the patient at the tth skin measurement position in the ith period, PhS (i-1)t is the skin surface moisture content value of the t-th skin measurement position of the patient in the i-1-th period, PsB is the patient's skin surface moisture content change index, χ t is the weighting coefficient of the initial change index of skin surface moisture content at the tth skin measurement position stored in the database, PhC t PhZ is the initial change index of skin surface pH at the patient's tth skin measurement position. it is the skin surface pH value of the patient at the tth skin measurement position in the ith period, PhZ (i-1)t is the skin surface pH value of the patient at the t-th skin measurement position in the i-1-th period, PhB is the patient's skin surface pH change index, is the weighting coefficient of the initial change index of skin surface PH at the tth skin measurement position stored in the database, i=2, 2, 4, ...i0, i0 is the number of time periods, t=1, 2, 3, ...t0, t0 is the number of skin measurement positions.

10. The smart medical bracelet system according to claim 1, characterized in that: The specific formula for calculating the patient's skin change health assessment index is as follows: Among them, PfP is the patient's skin change health assessment index, PwB is the patient's skin temperature change index, ψ1 is the skin temperature coefficient stored in the database, PdB is the patient's skin conductivity change index, ψ2 is the skin conductivity coefficient stored in the database, PsB is the patient's skin surface water content change index, ψ3 is the skin surface water content coefficient stored in the database, PhB is the patient's skin surface PH change index, ψ4 is the skin surface PH coefficient stored in the database, ψ1+ψ2+ψ3+ψ4=, π is pi.

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