User health monitoring method and system based on intelligent medical bracelet

Abstract

The invention discloses a user health monitoring method and system based on an intelligent medical bracelet, and relates to the technical field of intelligent health monitoring. According to the user health monitoring method based on the intelligent medical bracelet, when a to-be-monitored postoperative rehabilitation user is in gait training, moving posture data and moving physiological data of the to-be-monitored postoperative rehabilitation user are obtained in real time, data analysis is carried out respectively, a body position imbalance risk index and a physiological health index are obtained, comprehensive analysis is carried out, and the health of the to-be-monitored postoperative rehabilitation user is obtained. According to the invention, the comprehensive health index of the to-be-monitored postoperative rehabilitation user and the preset comprehensive health index are judged and analyzed, and the corresponding training adjustment measures are taken based on the judgment and analysis result. Therefore, the health state of the postoperative rehabilitation user in the moving state is accurately and comprehensively evaluated, personalized safety training management measures are taken according to the health state of the postoperative rehabilitation user, and the rehabilitation efficiency of the postoperative rehabilitation user is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent health monitoring, and in particular to a user health monitoring method and system based on an intelligent medical bracelet. Background Art

[0002] Smart medical bracelets are widely used in chronic disease management, postoperative rehabilitation, elderly health monitoring and other fields. Smart medical bracelets are wearable devices that integrate multiple sensors. They can monitor multiple physiological parameters of users in real time, store and analyze the collected data through the cloud platform, and provide accurate safety training management services. Health monitoring refers to the real-time monitoring of human physiological parameters through a variety of technical means to detect potential health problems early, provide personalized prevention, treatment or rehabilitation suggestions, help users achieve safe training management, and guide users to conduct appropriate health interventions, which is especially important in chronic disease management and postoperative rehabilitation.

[0003] Prior art, such as a patent application with announcement number: CN118592907A, discloses a method and system for user health monitoring based on a smart ring, the steps of which are: obtaining user health tracking data collected by the smart ring, determining whether there is an emergency risk event based on the user health tracking data, and if so, sending a vibration command to the smart ring, and continuously identifying whether there is a confirmation command transmitted by the smart ring; if the confirmation command transmitted by the smart ring is not received within a preset time interval, obtaining the user's location information and the user's pre-stored emergency contact information, and transmitting the user's location information and the emergency risk event to the emergency contact. This solution can quickly detect potential health risks. Reminding users through vibration helps them take timely measures. Even if the user does not respond to the vibration command in time, further measures can be taken to ensure that when the user is unable to save himself, the emergency contact can intervene in time to provide multi-level protection for the user.

[0004] Based on the above solution, it is found that the limitations of the existing technology include at least the following problems. First, the existing technology is difficult to monitor and evaluate the health changes of users in exercise, rehabilitation and other states in real time and accurately, thereby missing the early warning opportunity of health risks. Second, the existing technology fails to effectively combine the user's movement posture data and physiological data for comprehensive analysis to determine whether there is a risk of body imbalance or other emergency health events, which makes it difficult for users to obtain timely health feedback during exercise or rehabilitation, increasing health risks. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a user health monitoring method and system based on a smart medical bracelet, which solves the problem that the prior art is difficult to monitor and evaluate health in a mobile state in real time and accurately.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a user health monitoring method based on a smart medical bracelet, comprising the following steps: when the postoperative rehabilitation user to be monitored is in gait training, obtaining the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored in real time; performing data analysis on the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored, respectively, to obtain the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored; and performing a comprehensive analysis on the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored, to obtain the comprehensive health index of the postoperative rehabilitation user to be monitored; performing judgment and analysis on the comprehensive health index of the postoperative rehabilitation user to be monitored and a preset comprehensive health index, and taking corresponding training adjustment measures based on the judgment and analysis results.

[0007] Furthermore, the movement posture data includes horizontal angular velocity value, vertical angular velocity value, standing direction angular velocity value, horizontal acceleration value, vertical acceleration value, standing direction acceleration value, muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stress value of each key joint; the movement physiological data includes pulse wave propagation velocity value, blood lactate concentration value, blood sugar level value, venous filling value, myoelectric intensity value, skin conductance value, and muscle oxygenation value.

[0008] Furthermore, the formula for calculating the comprehensive health index of the postoperative rehabilitation user to be monitored is as follows: Among them, ZjK is the comprehensive health index of the postoperative rehabilitation user to be monitored, TdF is the body imbalance risk index of the postoperative rehabilitation user to be monitored, α1 is the risk index stored in the database, SjK is the physiological health index of the postoperative rehabilitation user to be monitored, α2 is the physiological index stored in the database, and α1+α2=1.

[0009] Furthermore, the specific steps for obtaining the postural imbalance risk index of the postoperative rehabilitation user to be monitored are as follows: comprehensively analyze the horizontal angular velocity value, vertical angular velocity value, standing direction angular velocity value, horizontal acceleration value, vertical acceleration value, and standing direction acceleration value of the postoperative rehabilitation user to be monitored to obtain the postural inclination index of the postoperative rehabilitation user to be monitored; perform standard deviation analysis on the joint stress value of each key joint of the postoperative rehabilitation user to be monitored to obtain the joint stability index of the postoperative rehabilitation user to be monitored; obtain the muscle tension reference value of the postoperative rehabilitation user to be monitored, and normalize it in combination with the muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stability index; comprehensively analyze the muscle tension reference value, muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stability index of the postoperative rehabilitation user to be monitored after the normalization process to obtain the gait coordination index of the postoperative rehabilitation user to be monitored; and normalize the postural inclination index and gait coordination index of the postoperative rehabilitation user to be monitored; comprehensively analyze the postural inclination index and gait coordination index of the postoperative rehabilitation user to be monitored after the normalization process to obtain the postural imbalance risk index of the postoperative rehabilitation user to be monitored.

[0010] Furthermore, the formulas for calculating the gait coordination index and the body position imbalance risk index of the postoperative rehabilitation user to be monitored are as follows: Wherein, BtW is the gait coordination index of the postoperative rehabilitation user to be monitored, JzL′ is the muscle tension value of the postoperative rehabilitation user to be monitored after normalization, CkJ′ is the muscle tension reference value of the postoperative rehabilitation user to be monitored after normalization, β1 is the tension coefficient stored in the database, ZxP′ is the center of gravity deviation value of the postoperative rehabilitation user to be monitored after normalization, β2 is the deviation coefficient stored in the database, BaF′ is the step vibration amplitude value of the postoperative rehabilitation user to be monitored after normalization, β3 is the amplitude coefficient stored in the database, GjW′ is the joint stability index of the postoperative rehabilitation user to be monitored after normalization, β4 is the joint stability coefficient stored in the database, β1+β2+β3+β4=1, TdF is the postural imbalance risk index of the postoperative rehabilitation user to be monitored, TwQ′ is the postural inclination index of the postoperative rehabilitation user to be monitored after normalization, δ1 is the inclination coefficient stored in the database, BtW′ is the gait coordination index of the postoperative rehabilitation user to be monitored after normalization, δ2 is the coordination coefficient stored in the database, δ1+δ2=1, and e is a natural constant.

[0011] Furthermore, the specific steps for obtaining the body position inclination index of the postoperative rehabilitation user to be monitored are as follows: comprehensively analyze the horizontal angular velocity value, vertical angular velocity value, and standing direction angular velocity value of the postoperative rehabilitation user to be monitored, and obtain the gravity reference rotation angle value of the postoperative rehabilitation user to be monitored; comprehensively analyze the horizontal acceleration value, vertical acceleration value, and standing direction acceleration value of the postoperative rehabilitation user to be monitored, and obtain the gravity inclination angle value of the postoperative rehabilitation user to be monitored; comprehensively analyze the gravity reference rotation angle value and gravity inclination angle value of the postoperative rehabilitation user to be monitored, and obtain the body position inclination index of the postoperative rehabilitation user to be monitored.

[0012] Furthermore, the specific steps for obtaining the physiological health index of the postoperative rehabilitation user to be monitored are as follows: obtain the blood sugar level reference value and venous filling reference value of the postoperative rehabilitation user to be monitored, and standardize them in combination with the pulse wave propagation velocity value, blood lactate concentration value, blood sugar level value and venous filling value; conduct a comprehensive analysis on the blood sugar level reference value, venous filling reference value, pulse wave propagation velocity value, blood lactate concentration value, blood sugar level value and venous filling value of the postoperative rehabilitation user to be monitored after the standardization to obtain the cardiovascular vitality level index of the postoperative rehabilitation user to be monitored; obtain the electromyographic intensity reference value, skin conductance reference value and muscle oxygenation reference value of the postoperative rehabilitation user to be monitored, and conduct a comprehensive analysis in combination with the electromyographic intensity value, skin conductance value and muscle oxygenation value to obtain the muscle fatigue warning index of the postoperative rehabilitation user to be monitored; and conduct a comprehensive analysis on the cardiovascular vitality level index and muscle fatigue warning index of the postoperative rehabilitation user to be monitored to obtain the physiological health index of the postoperative rehabilitation user to be monitored.

[0013] Furthermore, the formulas for calculating the cardiovascular vitality level index, muscle fatigue warning index, and physiological health index of the postoperative rehabilitation user to be monitored are as follows: Among them, XgK is the cardiovascular vitality level index of the postoperative rehabilitation user to be monitored, CbM′ is the pulse wave propagation velocity value of the postoperative rehabilitation user to be monitored after standardization, η1 is the propagation coefficient stored in the database, RsN′ is the blood lactate concentration value of the postoperative rehabilitation user to be monitored after standardization, η2 is the lactate coefficient stored in the database, XtS′ is the blood glucose level value of the postoperative rehabilitation user to be monitored after standardization, CCtS′ is the blood glucose level reference value of the postoperative rehabilitation user to be monitored after standardization, η3 is the blood glucose coefficient stored in the database, JmC′ is the venous filling value of the postoperative rehabilitation user to be monitored after standardization, CmY′ is the venous filling reference value of the postoperative rehabilitation user to be monitored after standardization, η4 is the filling coefficient stored in the database, η1+η2+η3+η4=1, e is a natural constant, JrP is the muscle fatigue warning index of the postoperative rehabilitation user to be monitored, JdQ is the electromyographic strength value of the postoperative rehabilitation user to be monitored, CdQ is the electromyographic strength reference value of the postoperative rehabilitation user to be monitored, λ1 is the electromyographic coefficient stored in the database, PdF is the skin conductance value of the postoperative rehabilitation user to be monitored, CdF is the skin conductance reference value of the postoperative rehabilitation user to be monitored, λ2 is the skin conductance coefficient stored in the database, JyD is the muscle oxygenation value of the postoperative rehabilitation user to be monitored, CyD is the muscle oxygenation reference value of the postoperative rehabilitation user to be monitored, λ3 is the muscle oxygenation coefficient stored in the database, λ1+λ2+λ3=1, SjK is the physiological health index of the postoperative rehabilitation user to be monitored, μ1 is the cardiovascular coefficient stored in the database, μ2 is the muscle fatigue coefficient stored in the database, μ1+μ2=1.

[0014] Furthermore, the specific steps for taking corresponding safety training management measures based on the judgment and analysis results are as follows: if the comprehensive health index of the postoperative rehabilitation user to be monitored is lower than or equal to the preset comprehensive health index, then the abnormal index is identified, that is, the postural imbalance risk index and the physiological health index of the postoperative rehabilitation user to be monitored are compared and analyzed with the preset postural imbalance risk index threshold and the physiological health index threshold respectively; when the postoperative imbalance risk index of the postoperative rehabilitation user to be monitored is higher than the postural imbalance risk index threshold, the postural imbalance risk index is marked as an abnormal index, and the first emergency training adjustment measure is taken; when the physiological health index of the postoperative rehabilitation user to be monitored is lower than or equal to the physiological health index threshold, the physiological health index is marked as an abnormal index, and the second emergency training adjustment measure is taken; if the comprehensive health index of the postoperative rehabilitation user to be monitored is higher than the preset comprehensive health index, safety training adjustment measures are taken.

[0015] A user health monitoring system based on a smart medical bracelet comprises: a data acquisition module, a data analysis module, a comprehensive analysis module, and a safety training management module; the data acquisition module is used to acquire the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored in real time when the postoperative rehabilitation user to be monitored is in gait training; the data analysis module is used to perform data analysis on the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored, respectively, to obtain the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored; the comprehensive analysis module is used to perform comprehensive analysis on the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored, to obtain the comprehensive health index of the postoperative rehabilitation user to be monitored; the safety training management module is used to perform judgment analysis on the comprehensive health index of the postoperative rehabilitation user to be monitored and a preset comprehensive health index, and take corresponding safety training management measures based on the judgment analysis results.

[0016] The present invention has the following beneficial effects:

[0017] (1) The user health monitoring method based on the smart medical bracelet can collect the user's movement posture and physiological data in real time when the user is performing dynamic activities through real-time monitoring based on the smart medical bracelet, so as to provide instant feedback on the user's health status changes, especially for groups such as postoperative rehabilitation patients or the elderly, so as to capture potential health risks in time, and through the analysis of dynamic data, timely identify abnormal situations and provide early warnings, so as to ensure the safety and health of the user.

[0018] (2) The user health monitoring method based on the smart medical bracelet comprehensively analyzes the user's body imbalance risk index and physiological health index to comprehensively evaluate the user's health status, and can accurately reflect the user's health changes during rehabilitation training. Combined with the evaluation of the comprehensive health index, the user's health status can be monitored more accurately and personalized.

[0019] (3) The user health monitoring method based on the smart medical bracelet combines the comprehensive health index with the preset health standards for comparative analysis, so as to take personalized safety training management measures in a timely manner, and automatically adjust the safety training management measures according to the risk of body imbalance and changes in the health index, thereby enhancing the personalization and pertinence of safety training management, thereby effectively improving the rehabilitation efficiency of postoperative rehabilitation users.

[0020] (4) The user health monitoring system based on the smart medical bracelet, through modular design, intelligently integrates data acquisition, data analysis, comprehensive analysis and safety training management functions. No human intervention is required throughout the process. The safety training management strategy is automatically adjusted according to the user's health status, thereby realizing fully automated and intelligent health monitoring and management, thereby reducing the complexity and error rate of manual operations, thereby improving the accuracy of health monitoring and subsequently improving the reliability of safety training management.

[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 flow chart of a user health monitoring method based on a smart medical bracelet in the present invention.

[0023] Figure 2 This is a flow chart of the steps of obtaining the body posture imbalance risk index of a postoperative rehabilitation user to be monitored in a user health monitoring method based on a smart medical bracelet of the present invention.

[0024] Figure 3 This is a block diagram of a user health monitoring system based on a smart medical bracelet in the present invention. DETAILED DESCRIPTION

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

[0026] Firstly, when the postoperative rehabilitation user to be monitored is in gait training, the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored are obtained in real time, and the data are analyzed separately to obtain the postural imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored, and the postural imbalance risk index and the physiological health index are comprehensively analyzed to obtain the comprehensive health index of the postoperative rehabilitation user to be monitored. Finally, the comprehensive health index of the postoperative rehabilitation user to be monitored is judged and analyzed with the preset comprehensive health index, and corresponding training adjustment measures are taken based on the judgment and analysis results.

[0027] See also Figure 1The embodiment of the present invention provides a technical solution: a user health monitoring method based on a smart medical bracelet, comprising the following steps: when a postoperative rehabilitation user to be monitored is in gait training (such as walking on a gait trainer), obtaining the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored in real time; performing data analysis on the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored, respectively, to obtain the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored; and performing a comprehensive analysis on the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored, to obtain the comprehensive health index of the postoperative rehabilitation user to be monitored; performing judgment analysis on the comprehensive health index of the postoperative rehabilitation user to be monitored and a preset comprehensive health index, and taking corresponding training adjustment measures based on the judgment analysis results.

[0028] The mobile posture data include horizontal angular velocity value, vertical angular velocity value, standing direction angular velocity value, horizontal acceleration value, vertical acceleration value, standing direction acceleration value, muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stress value of each key joint (such as knee joint, ankle joint, hip joint, etc.). The mobile physiological data include pulse wave propagation velocity value, blood lactate concentration value, blood sugar level value, venous filling value, myoelectric intensity value, skin conductance value, and muscle oxygenation value.

[0029] Among them, the horizontal angular velocity value is the horizontal angular velocity of the postoperative rehabilitation user to be monitored, and the horizontal angular velocity value can be obtained by a gyroscope in the smart medical bracelet.

[0030] The vertical angular velocity value is the vertical angular velocity of the postoperative rehabilitation user to be monitored, and the vertical angular velocity value can be obtained by a gyroscope in the smart medical bracelet.

[0031] The standing direction angular velocity value is the angular velocity of the postoperative rehabilitation user to be monitored in the standing direction, and the standing direction angular velocity value can be obtained by a gyroscope in the smart medical bracelet.

[0032] The horizontal acceleration value is the horizontal acceleration of the postoperative rehabilitation user to be monitored, and the horizontal acceleration value can be obtained through the acceleration sensor in the smart medical bracelet.

[0033] The vertical acceleration value is the vertical acceleration of the postoperative rehabilitation user to be monitored, and the vertical acceleration value can be obtained by the acceleration sensor in the smart medical bracelet.

[0034] The standing direction acceleration value is the acceleration in the standing direction of the postoperative rehabilitation user to be monitored, and the standing direction acceleration value can be obtained through the acceleration sensor in the smart medical bracelet.

[0035] The muscle tension value is the tension generated by the muscles when the monitored postoperative rehabilitation user moves. If the muscle tension is too high (such as muscle stiffness), the gait will be unsmooth and the steps will be unstable. If the muscle tension is too low, the muscles will find it difficult to effectively support the body, resulting in weak steps and unstable balance. The muscle tension value can be obtained through the electromyography (EMG) sensor in the smart medical bracelet.

[0036] The center of gravity deviation value is used to monitor the degree of deviation of the user's center of gravity during movement, that is, the displacement from the ideal center of gravity position of the body (i.e., between the two feet) to the actual center of gravity position. If the center of gravity deviation value is too large, it means that the user's body balance is no longer concentrated during walking, and the user may lose balance or swing excessively, thereby increasing the risk of falling. The center of gravity deviation value can be obtained through the inertial measurement unit in the smart medical bracelet.

[0037] The step vibration amplitude value is the vibration amplitude generated by the contact between the footsteps and the trainer when moving. A larger step vibration amplitude means that the steps are too large or uneven, and the gait is unstable. The step vibration amplitude value can obtain the angular velocity signal through the acceleration sensor in the smart medical bracelet, and then perform peak analysis on the acceleration signal, that is, measure the difference between the maximum and minimum values ​​of the acceleration signal, and the difference is the step vibration amplitude value.

[0038] Joint stress value refers to the degree of load borne by key joints during walking. When the stress of the joints is too large, it means that the load borne by the joints exceeds their tolerance range, causing joint injury, pain or discomfort, thus affecting the smoothness and stability of gait. Conversely, too low stress means insufficient joint movement, lack of normal support and force output, which may also lead to unstable gait. The joint stress value can be obtained through the strain sensor in the smart medical bracelet.

[0039] The pulse wave propagation velocity value is the propagation speed of the pulse wave in the artery. A lower pulse wave propagation velocity value means that the blood vessels are healthier, and the pulse wave propagation velocity value can be obtained through the blood pressure sensor in the smart medical bracelet.

[0040] The blood lactate concentration value is the concentration of lactate in the blood, which is a byproduct produced when muscles break down glycogen under hypoxic conditions, and the blood lactate concentration value can be obtained by a transdermal lactate sensor.

[0041] The blood sugar level value is the concentration of glucose in the blood, and the blood sugar level value may be acquired by a non-invasive sensor.

[0042] The venous filling value refers to the filling state of blood in the veins, that is, the efficiency of venous blood flow. A higher venous filling value usually means that venous return is obstructed and blood is accumulated in the lower limbs and other parts, which is not good for health. Conversely, insufficient heart pumping or insufficient blood volume affects cardiovascular health. The venous filling value is obtained by an optical sensor.

[0043] The EMG value is the intensity of electrical activity generated when the muscle contracts, that is, the electrophysiological state of the muscle during activity. In the early stages of muscle fatigue, the EMG value will increase because the nervous system will recruit more muscle fibers to maintain the muscle's contraction force. The EMG value can be obtained through the surface electromyography sensor in the smart medical bracelet.

[0044] Skin conductance refers to the skin's ability to conduct electric current. In the early stages of muscle fatigue, sympathetic nerve activity increases and skin conductance rises. In addition, fatigue during exercise and emotional fluctuations can also increase skin conductance. Skin conductance can be obtained through the galvanic skin response sensor in the smart medical bracelet.

[0045] The muscle oxygenation value is the saturation of oxygen in the muscle. In the early stage of muscle fatigue, the muscle oxygen consumption is greater than the supply, resulting in a decrease in oxygenation. The muscle oxygenation value can be obtained through the near-infrared spectroscopy sensor in the smart medical bracelet.

[0046] Specifically, the formula for calculating the comprehensive health index of the postoperative rehabilitation user to be monitored is as follows: Among them, ZjK is the comprehensive health index of the postoperative rehabilitation user to be monitored, TdF is the body imbalance risk index of the postoperative rehabilitation user to be monitored, α1 is the risk index stored in the database, SjK is the physiological health index of the postoperative rehabilitation user to be monitored, α2 is the physiological index stored in the database, and α1+α2=1.

[0047] It needs to be explained that the specific acquisition process of α1 and α1 is: read the postural imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored (it should be noted here that the postural imbalance risk index and the physiological health index are dimensionless values, so they can be directly calculated), perform sum analysis to obtain the comprehensive health value, and perform proportion analysis on the postoperative imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored and the comprehensive health value, and use the proportion analysis results as the corresponding coefficients.

[0048] In this implementation scheme, the postural imbalance risk index and the physiological health index are integrated to obtain a comprehensive health value, thereby providing a multi-dimensional perspective for the overall assessment of the health status, taking into account not only the user's physiological health, but also whether the postoperative rehabilitation user's posture is stable during gait training, thereby reflecting a more comprehensive health analysis. Secondly, through proportion analysis, the relative impact of each indicator on the overall health status can be revealed, thereby providing doctors or caregivers with a clearer health management direction, so that rehabilitation training can be more accurately adjusted according to actual needs. Finally, by real-time monitoring of changes in the postural imbalance risk index and the physiological health index, the proportion analysis can provide real-time feedback and timely alarm when the health indicator approaches the critical value, thereby preventing potential health crises and dynamically adjusting safety training management measures based on its value.

[0049] Specifically, Figure 2 As shown in FIG, the specific steps for obtaining the body imbalance risk index of the postoperative rehabilitation user to be monitored are as follows: a comprehensive analysis is performed on the horizontal angular velocity value, vertical angular velocity value, standing direction angular velocity value, horizontal acceleration value, vertical acceleration value, and standing direction acceleration value of the postoperative rehabilitation user to be monitored to obtain the body tilt index of the postoperative rehabilitation user to be monitored; a standard deviation analysis is performed on the joint stress value of each key joint of the postoperative rehabilitation user to be monitored to obtain the joint stability index of the postoperative rehabilitation user to be monitored; the muscle tension reference value of the postoperative rehabilitation user to be monitored is obtained, and combined with the muscle tension value, center of gravity deviation value, and pace The vibration amplitude value and the joint stability index are normalized (i.e., the unit is removed); the muscle tension reference value, muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stability index of the postoperative rehabilitation user to be monitored after the normalization are comprehensively analyzed to obtain the gait coordination index of the postoperative rehabilitation user to be monitored; and the postural inclination index and gait coordination index of the postoperative rehabilitation user to be monitored are normalized (i.e., the unit is removed); based on the postural inclination index and gait coordination index of the postoperative rehabilitation user to be monitored after the normalization, a comprehensive analysis is performed to obtain the postural imbalance risk index of the postoperative rehabilitation user to be monitored.

[0050] Among them, muscle tension reference values ​​can be obtained through medical books such as "Principles and Practice of Rehabilitation Medicine" stored in the database.

[0051] The formula for calculating the gait coordination index and body imbalance risk index of the postoperative rehabilitation user to be monitored is as follows: Among them, BtW is the gait coordination index of the postoperative rehabilitation user to be monitored, JzL′ is the muscle tension value of the postoperative rehabilitation user to be monitored after normalization, CkJ′ is the muscle tension reference value of the postoperative rehabilitation user to be monitored after normalization, β1 is the tension coefficient stored in the database, ZxP′ is the center of gravity deviation value of the postoperative rehabilitation user to be monitored after normalization, β2 is the deviation coefficient stored in the database, BaF′ is the step vibration amplitude value of the postoperative rehabilitation user to be monitored after normalization, β3 is the amplitude coefficient stored in the database, GjW′ is the normalized value. The joint stability index of the postoperative rehabilitation user to be monitored after normalization, β4 is the joint stability coefficient stored in the database, β1+β2+β3+β4=1, TdF is the postural imbalance risk index of the postoperative rehabilitation user to be monitored, TwQ′ is the postural inclination index of the postoperative rehabilitation user to be monitored after normalization, δ1 is the inclination coefficient stored in the database, BtW′ is the gait coordination index of the postoperative rehabilitation user to be monitored after normalization, δ2 is the coordination coefficient stored in the database, δ1+δ2=1, e is a natural constant, and in this implementation example, the value is 2.71.

[0052] It needs to be explained that the specific acquisition process of β1, β2, β3, and β4 is: read the normalized muscle tension value, center of gravity deviation value, gait vibration amplitude value, and joint stability index of the postoperative rehabilitation user to be monitored, perform sum analysis, and obtain the gait stability sum value, and perform proportion analysis on the normalized muscle tension value, center of gravity deviation value, gait vibration amplitude value, and joint stability index of the postoperative rehabilitation user to be monitored and the gait stability sum value, and use the proportion analysis results as the corresponding coefficients.

[0053] The specific acquisition process of δ1 and δ2 is: read the normalized body tilt index and gait coordination index of the postoperative rehabilitation user to be monitored, perform sum analysis to obtain the risk sum value, and perform proportion analysis on the normalized body tilt index and gait coordination index of the postoperative rehabilitation user to be monitored and the risk sum value, respectively, and use the proportion analysis results as the corresponding coefficients.

[0054] In this implementation scheme, by comprehensively analyzing various indicators of the user (such as muscle tension, center of gravity deviation, gait vibration amplitude, joint stability, etc.), the user's rehabilitation progress and risk situation are comprehensively evaluated, so as to avoid the one-sidedness that may be caused by a single indicator, making the evaluation results more accurate and reliable. Secondly, normalizing different indicators can eliminate the influence of different units and dimensions on the analysis results, so that various indicators can be compared under the same standard, which helps to improve the accuracy and fairness of the analysis and avoid calculation deviations caused by large or small dimensions of a certain indicator. In addition, the process of proportion analysis helps to reveal the relative importance of different health indicators to the overall health status, thereby helping doctors or health management systems to identify the most critical risk factors in the rehabilitation process, so as to achieve precise intervention, and then ensure that the rehabilitation plan can be optimized and adjusted according to the actual needs of the user, and the postural imbalance risk index calculated by combining the normalized indicators can monitor the physical state of postoperative rehabilitation users during gait training in real time, so as to be able to warn the user's risk of falling in advance, thereby providing a basis for timely rehabilitation intervention and medical measures.

[0055] Specifically, the specific steps for obtaining the body position tilt index of the postoperative rehabilitation user to be monitored are as follows: comprehensively analyze the horizontal angular velocity value, vertical angular velocity value, and standing direction angular velocity value of the postoperative rehabilitation user to be monitored to obtain the gravity reference rotation angle value of the postoperative rehabilitation user to be monitored (that is, the rotation angle of the postoperative rehabilitation user relative to the gravity direction); comprehensively analyze the horizontal acceleration value, vertical acceleration value, and standing direction acceleration value of the postoperative rehabilitation user to be monitored to obtain the gravity tilt angle value of the postoperative rehabilitation user to be monitored (that is, the tilt angle of the postoperative rehabilitation user relative to the gravity direction); comprehensively analyze the gravity reference rotation angle value and gravity tilt angle value of the postoperative rehabilitation user to be monitored to obtain the body position tilt index of the postoperative rehabilitation user to be monitored; wherein, the formula for calculating the gravity reference rotation angle value, gravity tilt angle value, and body position tilt index of the postoperative rehabilitation user to be monitored is as follows: Among them, XzJ is the gravity reference rotation angle value of the postoperative rehabilitation user to be monitored, XjS is the horizontal angular velocity value of the postoperative rehabilitation user to be monitored, YjS is the vertical angular velocity value of the postoperative rehabilitation user to be monitored, ZjS is the standing direction angular velocity value of the postoperative rehabilitation user to be monitored, x is the conversion coefficient stored in the database, and in this implementation example, the value is 180, π is pi, and in this implementation example, the value is 3.14, ZqX is the gravity inclination angle value of the postoperative rehabilitation user to be monitored, ZjD is the standing direction acceleration value of the postoperative rehabilitation user to be monitored, XjD is the horizontal acceleration value of the postoperative rehabilitation user to be monitored, YjD is the vertical acceleration value of the postoperative rehabilitation user to be monitored, TwQ is the body position inclination index of the postoperative rehabilitation user to be monitored, φ1 is the gravity rotation coefficient stored in the database, φ2 is the gravity inclination coefficient stored in the database, φ1+φ2=1.

[0056] It needs to be explained that the specific acquisition process of φ1 and φ2 is: read the gravity reference rotation angle value and gravity tilt angle value of the postoperative rehabilitation user to be monitored (it should be noted here that the units of the gravity reference rotation angle value and the gravity tilt angle value are consistent and can be directly calculated), perform sum analysis to obtain the body position tilt sum value, and perform proportion analysis on the gravity reference rotation angle value and gravity tilt angle value of the postoperative rehabilitation user to be monitored and the body position tilt sum value, and use the proportion analysis results as the corresponding coefficients.

[0057] And arccos(x) is the inverse cosine function, with a domain of [-1,1] and a range of [0,π].

[0058] In this implementation, by comprehensively analyzing the angular velocity and acceleration in the horizontal, vertical and standing directions, the gravity reference rotation angle value and the gravity tilt angle value are obtained, so as to understand the posture and body position stability of the postoperative rehabilitation user. The gravity reference rotation angle reflects the rotation of the user relative to the gravity direction, and can reveal whether the user's body has excessive rotation or unbalanced movement, while the gravity tilt angle reveals whether the user's body position is tilted. The body position tilt index is calculated based on the gravity reference rotation angle value and the gravity tilt angle value. The index obtained through the comprehensive analysis of the two can accurately quantify the patient's body position imbalance risk, and can also provide reliable data support for subsequent rehabilitation training adjustments. At the same time, the process of calculating the angle using the inverse cosine function can convert the angular velocity and acceleration information into intuitive angle values, thereby providing accurate quantitative data for further body position stability analysis.

[0059] Specifically, the specific steps for obtaining the physiological health index of the postoperative rehabilitation user to be monitored are as follows: obtain the blood sugar level reference value and venous filling reference value of the postoperative rehabilitation user to be monitored, and perform standardization processing (i.e., de-unit processing) in combination with the pulse wave propagation velocity value, blood lactate concentration value, blood sugar level value, and venous filling value; conduct a comprehensive analysis on the blood sugar level reference value, venous filling reference value, pulse wave propagation velocity value, blood lactate concentration value, blood sugar level value, and venous filling value of the postoperative rehabilitation user to be monitored after the standardization processing to obtain the cardiovascular vitality level index (i.e., cardiovascular health) of the postoperative rehabilitation user to be monitored; obtain the electromyographic intensity reference value, skin conductance reference value, and muscle oxygenation reference value of the postoperative rehabilitation user to be monitored, and perform a comprehensive analysis in combination with the electromyographic intensity value, skin conductance value, and muscle oxygenation value to obtain the muscle fatigue warning index of the postoperative rehabilitation user to be monitored; and conduct a comprehensive analysis on the cardiovascular vitality level index and muscle fatigue warning index of the postoperative rehabilitation user to be monitored to obtain the physiological health index of the postoperative rehabilitation user to be monitored.

[0060] Among them, reference values ​​for blood glucose level, venous filling, myoelectric strength, skin conductance, and muscle oxygenation can all be obtained through medical literature stored in the database (such as postoperative rehabilitation, sports medicine, etc.).

[0061] The formulas for calculating the cardiovascular vitality level index, muscle fatigue warning index, and physiological health index of the postoperative rehabilitation user to be monitored are as follows: Wherein, XgK is the cardiovascular activity level index of the postoperative rehabilitation user to be monitored, CbM′ is the pulse wave propagation velocity value of the postoperative rehabilitation user to be monitored after standardization, η1 is the propagation coefficient stored in the database, RsN′ is the blood lactate concentration value of the postoperative rehabilitation user to be monitored after standardization, η2 is the lactate coefficient stored in the database, XtS′ is the blood glucose level value of the postoperative rehabilitation user to be monitored after standardization, CtS′ is the blood glucose level reference value of the postoperative rehabilitation user to be monitored after standardization, η3 is the blood glucose coefficient stored in the database, JmC′ is the venous filling value of the postoperative rehabilitation user to be monitored after standardization, CmY′ is the venous filling reference value of the postoperative rehabilitation user to be monitored after standardization, η4 is the filling coefficient stored in the database, η1+η2+η3+η4=1, e is a natural constant, and in In this implementation example, the value is taken as 2.71, JrP is the muscle fatigue warning index of the postoperative rehabilitation user to be monitored, JdQ is the electromyographic strength value of the postoperative rehabilitation user to be monitored, CdQ is the electromyographic strength reference value of the postoperative rehabilitation user to be monitored, λ1 is the electromyographic coefficient stored in the database, PdF is the skin conductance value of the postoperative rehabilitation user to be monitored, CdF is the skin conductance reference value of the postoperative rehabilitation user to be monitored, λ2 is the skin conductance coefficient stored in the database, JyD is the muscle oxygenation value of the postoperative rehabilitation user to be monitored, CyD is the muscle oxygenation reference value of the postoperative rehabilitation user to be monitored, λ3 is the muscle oxygenation coefficient stored in the database, λ1+λ2+λ3=1, SjK is the physiological health index of the postoperative rehabilitation user to be monitored, μ1 is the cardiovascular coefficient stored in the database, μ2 is the muscle fatigue coefficient stored in the database, μ1+μ2=1.

[0062] It needs to be explained that the specific acquisition process of η1, η2, η3, and η4 is: read the pulse wave propagation velocity values, blood lactate concentration values, blood sugar level values, and venous filling values ​​of the postoperative rehabilitation users to be monitored after standardization, perform sum analysis, and obtain the cardiovascular warning sum value, and perform proportion analysis on the pulse wave propagation velocity values, blood lactate concentration values, blood sugar level values, and venous filling values ​​of the postoperative rehabilitation users to be monitored after standardization, respectively, and the proportion analysis results are used as the corresponding coefficients.

[0063] The specific acquisition process of λ1, λ2, and λ3 is as follows: read the reference value of the electromyographic intensity, skin conductance, and muscle oxygenation of the postoperative rehabilitation user to be monitored, and perform standardization processing, perform sum analysis based on the results after standardization processing to obtain the muscle fatigue sum value, and perform proportion analysis on the standardized results and the muscle fatigue sum value, and use the proportion analysis results as the corresponding coefficients.

[0064] The specific acquisition process of μ1 and μ2 is: read the cardiovascular vitality level index and muscle fatigue warning index of the postoperative rehabilitation user to be monitored (it should be noted here that the cardiovascular vitality level index and the muscle fatigue warning index are dimensionless values, so they can be directly calculated), perform sum analysis to obtain the warning sum value, and perform proportion analysis on the cardiovascular vitality level index and muscle fatigue warning index of the postoperative rehabilitation user to be monitored and the warning sum value, respectively, and use the proportion analysis results as the corresponding coefficients.

[0065] A specific implementation example of calculating the physiological health index of a postoperative rehabilitation user to be monitored is as follows, and the following data is available;

[0066] The pulse wave propagation velocity value of the postoperative rehabilitation user to be monitored is (unit: m / s): 13.20. The blood lactate concentration value of the postoperative rehabilitation user to be monitored is (unit: mmol / L): 3.80. The blood glucose level value of the postoperative rehabilitation user to be monitored is (unit: mmol / L): 6.90.

[0067] The venous filling value of the postoperative rehabilitation user to be monitored is: 1.02.

[0068] The electromyographic intensity value of the postoperative rehabilitation user to be monitored is (unit: μV): 25.00.

[0069] The skin conductance value of the postoperative rehabilitation user to be monitored is (unit: μS): 5.60.

[0070] The muscle oxygenation value of the postoperative rehabilitation user to be monitored is: 0.75.

[0071] The reference value of blood glucose level for postoperative rehabilitation users to be monitored is (unit: mmol / L): 6.50.

[0072] The reference value of venous filling for postoperative rehabilitation users to be monitored is: 1.10.

[0073] The reference value of the electromyographic intensity of the postoperative rehabilitation user to be monitored is (unit: μV): 20.00.

[0074] The reference value of skin conductance of the postoperative rehabilitation user to be monitored is (unit: μS): 4.50.

[0075] The reference value of muscle oxygenation for postoperative rehabilitation users to be monitored is: 0.8.

[0076] After standardized processing, the pulse wave propagation velocity value of the postoperative rehabilitation user to be monitored is: 0.62.

[0077] After standardized treatment, the blood lactate concentration value of the postoperative rehabilitation users to be monitored is: 0.54.

[0078] The blood glucose level of the postoperative recovery users to be monitored after standardized treatment is: 0.46.

[0079] After standardized treatment, the venous filling value of the postoperative rehabilitation users to be monitored is: 0.31.

[0080] The reference value of blood glucose level for postoperative rehabilitation users to be monitored after standardized treatment is: 0.44.

[0081] The reference value of venous filling for postoperative rehabilitation users to be monitored after standardized treatment is: 0.33.

[0082] The propagation coefficient stored in the database is approximately: 0.32.

[0083] The lactate coefficient stored in the database is approximately: 0.28.

[0084] The glycemic coefficient stored in the database is approximately: 0.24.

[0085] The filling coefficient stored in the database is approximately: 0.16.

[0086] The electromyographic coefficient stored in the database is approximately: 0.41.

[0087] The skin conductance coefficient stored in the database is approximately: 0.23.

[0088] The muscle oxygenation coefficient stored in the database is approximately: 0.36.

[0089] The cardiovascular coefficient stored in the database is approximately: 0.56.

[0090] The muscle fatigue coefficient stored in the database is approximately: 0.44.

[0091] Substituting the above data into the formula of cardiovascular vitality level index, muscle fatigue warning index and physiological health index of the postoperative rehabilitation user to be monitored, we get:

[0092] The cardiovascular activity index of the postoperative rehabilitation user to be monitored = 2.71 0.32 *(1 / (0.62+1))+0.28*(1 / (0.54+1))+0.24*|1-(0.46 / 0.44)|+0.16*|1-(0.31 / 0.33)| ≈1.49.

[0093] The muscle fatigue warning index of the postoperative rehabilitation user to be monitored = 0.41*(25.00 / 20.00)+0.23*(5.60 / 4.50)+0.36*(0.75 / 0.80)≈1.17.

[0094] The physiological health index of the postoperative rehabilitation user to be monitored = ln(1+(0.56*1.49+0.44*(1 / 1.17)))≈0.79.

[0095] In this implementation scheme, by combining multiple physiological data (such as pulse wave propagation velocity, blood sugar level, myoelectric strength, etc.), the user's physiological health status is comprehensively monitored and evaluated, that is, through a comprehensive analysis of the cardiovascular vitality level index and the muscle fatigue warning index, the user's overall physiological health status is evaluated, potential health risks are discovered in time, and corresponding preventive measures are taken. Secondly, when multiple physiological data (such as blood sugar level, venous filling, pulse wave propagation velocity, etc.) are involved, standardization processing can remove the influence of different dimensions and units, thereby ensuring the comparability of various indicators and the accuracy of data integration, thereby making the data more unified and ensuring that the model operation is more accurate, thereby eliminating the differences between different physiological data. In addition, by analyzing indicators such as pulse wave propagation velocity, lactate concentration, blood sugar level, venous filling, etc., it is possible to monitor the cardiovascular response and potential problems of postoperative patients in real time, and by comprehensively analyzing data such as electromyographic intensity, skin conductance, and muscle oxygenation, a muscle fatigue warning index is obtained, which helps to detect the user's muscle fatigue level and avoid damage caused by excessive fatigue. Finally, through a comprehensive analysis of both cardiovascular and muscle health, a more comprehensive physiological health index is obtained, which more accurately reflects the patient's overall health level, especially during the rehabilitation process, to help determine whether there is excessive physical exertion, cardiovascular problems or other health risks.

[0096] Specifically, the specific steps for taking corresponding safety training management measures based on the judgment and analysis results are as follows: if the comprehensive health index of the postoperative rehabilitation user to be monitored is lower than or equal to the preset comprehensive health index, then the abnormal index is identified, that is, the postural imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored are compared and analyzed with the preset postural imbalance risk index threshold and physiological health index threshold respectively; when the postoperative imbalance risk index of the postoperative rehabilitation user to be monitored is higher than the postural imbalance risk index threshold, the postural imbalance risk index is marked as an abnormal index, and the first emergency training adjustment measure is taken (reducing the training intensity, that is, reducing the patient's exercise intensity in gait training, such as slowly reducing the speed of the trainer; real-time voice reminder, that is, providing a voice reminder to the user to inform that the current postural imbalance risk is too high). When the physiological health index of the postoperative rehabilitation user to be monitored is lower than or equal to the physiological health index threshold, the physiological health index will be marked as an abnormal index, and the second emergency training adjustment measure will be taken (a warning notice will be issued to the doctor or nursing staff for further diagnosis and treatment; an instruction to stop training will be issued to the user, and the gait trainer will be automatically turned off to avoid excessive burden on the heart or muscles); if the comprehensive health index of the postoperative rehabilitation user to be monitored is higher than the preset comprehensive health index, safety training adjustment measures will be taken (maintaining the level of rehabilitation training, that is, maintaining the amount of rehabilitation training, further restoring physical fitness and athletic ability, increasing training intensity or training time, but ensuring that it is carried out within a safe range; setting further rehabilitation goals, that is, setting long-term health recovery goals, such as: strengthening cardiovascular health, improving endurance, etc.).

[0097] In this implementation scheme, by comparing and analyzing the postural imbalance risk index and physiological health index of the monitored postoperative rehabilitation user with the corresponding thresholds, potential abnormal conditions can be discovered in time, which helps to identify the user's physiological health problems or postural imbalance risks at an early stage, and then take corresponding safety training adjustment measures to reduce the risk of injury. When the postural imbalance risk index or physiological health index is monitored to be abnormal, the first and second emergency training adjustment measures are automatically identified and taken, so as to ensure the patient's physical safety during rehabilitation training and avoid injuries caused by excessive training intensity, postural imbalance or excessive physiological load. By dynamically adjusting the training intensity, it is ensured that the patient's body is always within the safe load range, thereby effectively avoiding the negative effects of overtraining.

[0098] See also Figure 3The embodiment of the present invention provides a technical solution: a user health monitoring system based on a smart medical bracelet, comprising a data acquisition module, a data analysis module, a comprehensive analysis module, and a safety training management module; the data acquisition module is used to acquire the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored in real time when the postoperative rehabilitation user to be monitored is in gait training; the data analysis module is used to perform data analysis on the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored, respectively, to obtain the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored; the comprehensive analysis module is used to perform comprehensive analysis on the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored, to obtain the comprehensive health index of the postoperative rehabilitation user to be monitored; the safety training management module is used to judge and analyze the comprehensive health index of the postoperative rehabilitation user to be monitored with a preset comprehensive health index, and take corresponding safety training management measures based on the judgment and analysis results.

[0099] In summary, this application has at least the following effects:

[0100] Through real-time monitoring based on smart medical bracelets, the user's movement posture and physiological data can be collected in real time when the user is performing dynamic activities, so that instant feedback on changes in the user's health status can be provided. Especially for groups such as postoperative rehabilitation patients or the elderly, potential health risks can be captured in time, and through analysis of dynamic data, abnormal situations can be identified in time and early warnings can be provided to ensure the safety and health of users.

[0101] By comprehensively analyzing the user's postural imbalance risk index and physiological health index, the user's health status can be comprehensively assessed, which can accurately reflect the user's health changes during the rehabilitation training process. Combined with the assessment of the comprehensive health index, the user's health status can be monitored more accurately and personalized.

[0102] By comparing and analyzing the comprehensive health index with the preset health standards, personalized safety training management measures can be taken in a timely manner, and the safety training management measures can be automatically adjusted according to the risk of body imbalance and changes in the health index. This enhances the personalization and targeting of safety training management, thereby effectively improving the rehabilitation efficiency of postoperative rehabilitation users.

[0103] Through modular design, data acquisition, data analysis, comprehensive analysis and safety training management functions are intelligently integrated without the need for human intervention throughout the process. The safety training management strategy is automatically adjusted according to the user's health status, thereby realizing fully automated and intelligent health monitoring and management, thereby reducing the complexity and error rate of manual operations, thereby improving the accuracy of health monitoring and subsequently improving the reliability of safety training management.

[0104] 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.

[0105] 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 user health monitoring method based on a smart medical bracelet, characterized in that: The following steps are involved: When the postoperative rehabilitation user to be monitored is in gait training, the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored are obtained in real time; The movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored are analyzed respectively to obtain the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored; A comprehensive analysis is also conducted on the risk index of body position imbalance and physiological health index of the postoperative rehabilitation users to be monitored, so as to obtain a comprehensive health index of the postoperative rehabilitation users to be monitored; The comprehensive health index of the postoperative rehabilitation user to be monitored is compared with the preset comprehensive health index, and corresponding training adjustment measures are taken based on the judgment and analysis results.

2. The user health monitoring method based on the smart medical bracelet according to claim 1 is characterized in that: The movement posture data includes horizontal angular velocity value, vertical angular velocity value, standing direction angular velocity value, horizontal acceleration value, vertical acceleration value, standing direction acceleration value, muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stress value of each key joint; the movement physiological data includes pulse wave propagation velocity value, blood lactate concentration value, blood sugar level value, venous filling value, myoelectric intensity value, skin conductance value, and muscle oxygenation value.

3. The user health monitoring method based on the smart medical bracelet according to claim 1 is characterized in that: The formula for calculating the comprehensive health index of the postoperative rehabilitation user to be monitored is as follows: Among them, ZjK is the comprehensive health index of the postoperative rehabilitation user to be monitored, TdF is the body imbalance risk index of the postoperative rehabilitation user to be monitored, α1 is the risk index stored in the database, SjK is the physiological health index of the postoperative rehabilitation user to be monitored, α2 is the physiological index stored in the database, and α1+α2=1.

4. The user health monitoring method based on the smart medical bracelet according to claim 2 is characterized in that: The specific steps for obtaining the body position imbalance risk index of the postoperative rehabilitation user to be monitored are as follows: Comprehensively analyze the horizontal angular velocity value, vertical angular velocity value, standing direction angular velocity value, horizontal acceleration value, vertical acceleration value, and standing direction acceleration value of the postoperative rehabilitation user to be monitored, and obtain the body position tilt index of the postoperative rehabilitation user to be monitored; Perform standard deviation analysis on the joint stress value of each key joint of the postoperative rehabilitation user to be monitored, and obtain the joint stability index of the postoperative rehabilitation user to be monitored; Obtain the muscle tension reference value of the postoperative rehabilitation user to be monitored, and perform normalization processing based on the muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stability index; Comprehensively analyze the normalized muscle tension reference value, muscle tension value, center of gravity deviation value, step vibration amplitude value, and joint stability index of the postoperative rehabilitation user to be monitored to obtain the gait coordination index of the postoperative rehabilitation user to be monitored; The body position tilt index and gait coordination index of the postoperative rehabilitation user to be monitored are normalized; Based on the normalized body tilt index and gait coordination index of the postoperative rehabilitation users to be monitored, a comprehensive analysis is performed to obtain the body imbalance risk index of the postoperative rehabilitation users to be monitored.

5. The user health monitoring method based on the smart medical bracelet according to claim 4 is characterized in that: The formula for calculating the gait coordination index and body imbalance risk index of the postoperative rehabilitation user to be monitored is as follows: Wherein, BtW is the gait coordination index of the postoperative rehabilitation user to be monitored, JzL′ is the muscle tension value of the postoperative rehabilitation user to be monitored after normalization, CkJ′ is the muscle tension reference value of the postoperative rehabilitation user to be monitored after normalization, β1 is the tension coefficient stored in the database, ZxP′ is the center of gravity deviation value of the postoperative rehabilitation user to be monitored after normalization, β2 is the deviation coefficient stored in the database, BaF′ is the step vibration amplitude value of the postoperative rehabilitation user to be monitored after normalization, β3 is the amplitude coefficient stored in the database, GjW′ is the joint stability index of the postoperative rehabilitation user to be monitored after normalization, β4 is the joint stability coefficient stored in the database, β1+β2+β3+β4=1, TdF is the postural imbalance risk index of the postoperative rehabilitation user to be monitored, TwQ′ is the postural inclination index of the postoperative rehabilitation user to be monitored after normalization, δ1 is the inclination coefficient stored in the database, BtW′ is the gait coordination index of the postoperative rehabilitation user to be monitored after normalization, δ2 is the coordination coefficient stored in the database, δ1+δ2=1, and e is a natural constant.

6. The user health monitoring method based on the smart medical bracelet according to claim 4 is characterized in that: The specific steps for obtaining the body position tilt index of the postoperative rehabilitation user to be monitored are as follows: Comprehensively analyze the horizontal angular velocity value, vertical angular velocity value, and standing angular velocity value of the postoperative rehabilitation user to be monitored, and obtain the gravity reference rotation angle value of the postoperative rehabilitation user to be monitored; Comprehensively analyze the horizontal acceleration value, vertical acceleration value, and standing acceleration value of the postoperative rehabilitation user to be monitored, and obtain the gravity tilt angle value of the postoperative rehabilitation user to be monitored; A comprehensive analysis is performed on the gravity reference rotation angle value and the gravity tilt angle value of the postoperative rehabilitation user to be monitored to obtain the body position tilt index of the postoperative rehabilitation user to be monitored.

7. The user health monitoring method based on the smart medical bracelet according to claim 2 is characterized in that: The specific steps for obtaining the physiological health index of the postoperative rehabilitation user to be monitored are as follows: Obtain reference values ​​of blood sugar levels and venous filling of the postoperative rehabilitation user to be monitored, and perform standardization processing based on pulse wave velocity values, blood lactate concentration values, blood sugar level values, and venous filling values; Comprehensively analyze the blood sugar level reference value, venous filling reference value, pulse wave velocity value, blood lactate concentration value, blood sugar level value, and venous filling value of the postoperative rehabilitation user to be monitored after standardization, and obtain the cardiovascular vitality level index of the postoperative rehabilitation user to be monitored; Obtain the reference value of myoelectric strength, skin conductance, and muscle oxygenation of the postoperative rehabilitation user to be monitored, and conduct a comprehensive analysis based on the myoelectric strength value, skin conductance value, and muscle oxygenation value to obtain the muscle fatigue warning index of the postoperative rehabilitation user to be monitored; A comprehensive analysis is also conducted on the cardiovascular vitality level index and muscle fatigue warning index of the postoperative rehabilitation users to be monitored, so as to obtain the physiological health index of the postoperative rehabilitation users to be monitored.

8. The user health monitoring method based on the smart medical bracelet according to claim 7 is characterized in that: The formulas for calculating the cardiovascular vitality level index, muscle fatigue warning index, and physiological health index of the postoperative rehabilitation user to be monitored are as follows: Wherein, XgK is the cardiovascular activity level index of the postoperative rehabilitation user to be monitored, CbM′ is the pulse wave propagation velocity value of the postoperative rehabilitation user to be monitored after standardization, η1 is the propagation coefficient stored in the database, RsN′ is the blood lactate concentration value of the postoperative rehabilitation user to be monitored after standardization, η2 is the lactate coefficient stored in the database, XtS′ is the blood glucose level value of the postoperative rehabilitation user to be monitored after standardization, XtS′ is the blood glucose level reference value of the postoperative rehabilitation user to be monitored after standardization, η3 is the blood glucose coefficient stored in the database, JmC′ is the venous filling value of the postoperative rehabilitation user to be monitored after standardization, CmY′ is the venous filling reference value of the postoperative rehabilitation user to be monitored after standardization, η4 is the filling coefficient stored in the database, η1+η2+η3+η4=1, e is a natural constant, JrP is the muscle fatigue warning index of the postoperative rehabilitation user to be monitored, JdQ is the electromyographic strength value of the postoperative rehabilitation user to be monitored, CdQ is the electromyographic strength reference value of the postoperative rehabilitation user to be monitored, λ1 is the electromyographic coefficient stored in the database, PdF is the skin conductance value of the postoperative rehabilitation user to be monitored, CdF is the skin conductance reference value of the postoperative rehabilitation user to be monitored, λ2 is the skin conductance coefficient stored in the database, JyD is the muscle oxygenation value of the postoperative rehabilitation user to be monitored, CyD is the muscle oxygenation reference value of the postoperative rehabilitation user to be monitored, λ3 is the muscle oxygenation coefficient stored in the database, λ1+λ2+λ3=1, SjK is the physiological health index of the postoperative rehabilitation user to be monitored, μ1 is the cardiovascular coefficient stored in the database, μ2 is the muscle fatigue coefficient stored in the database, μ1+μ2=1.

9. The user health monitoring method based on the smart medical bracelet according to claim 1 is characterized in that: The specific steps for taking corresponding safety training management measures based on the judgment and analysis results are as follows: If the comprehensive health index of the postoperative rehabilitation user to be monitored is lower than or equal to the preset comprehensive health index, the abnormal index is identified, that is, the posture imbalance risk index and the physiological health index of the postoperative rehabilitation user to be monitored are compared and analyzed with the preset posture imbalance risk index threshold and the physiological health index threshold respectively. When the posture imbalance risk index of the postoperative rehabilitation user to be monitored is higher than the posture imbalance risk index threshold, the posture imbalance risk index is marked as an abnormal index, and the first emergency training adjustment measure is taken. When the physiological health index of the postoperative rehabilitation user to be monitored is lower than or equal to the physiological health index threshold, the physiological health index is marked as an abnormal index, and the second emergency training adjustment measure is taken; If the comprehensive health index of the postoperative rehabilitation user to be monitored is higher than the preset comprehensive health index, safety training adjustment measures will be taken.

10. A user health monitoring system based on a smart medical bracelet, applying the user health monitoring method based on a smart medical bracelet according to any one of claims 1 to 9, characterized in that: include: Data acquisition module, data analysis module, comprehensive analysis module, safety training management module; The data acquisition module is used to acquire the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored in real time when the postoperative rehabilitation user to be monitored is in gait training; The data analysis module is used to analyze the movement posture data and movement physiological data of the postoperative rehabilitation user to be monitored, and obtain the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored; The comprehensive analysis module is used to comprehensively analyze the body position imbalance risk index and physiological health index of the postoperative rehabilitation user to be monitored, so as to obtain the comprehensive health index of the postoperative rehabilitation user to be monitored; The safety training management module is used to judge and analyze the comprehensive health index of the postoperative rehabilitation user to be monitored and the preset comprehensive health index, and take corresponding safety training management measures based on the judgment and analysis results.

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