Display system based on motion sensing and digital twinborn ecology fusion

Abstract

The invention relates to the technical field of motion sensing and intelligent analysis, in particular to a display system based on motion sensing and digital twinborn ecology fusion. Comprising a server, a dynamic analysis module and an intelligent display module, the exercise physiological deviation value is obtained by performing deviation analysis on the exercise data and the physiological data of each user, and then real-time trend analysis is performed on the exercise physiological deviation value, so that the exercise health state of the user can be accurately evaluated, and the future exercise physiological state can be predicted and managed; by displaying the overlapping value between the exercise posture of the user and the standard posture in real time, the user can be helped to clearly understand whether the exercise posture of the user is correct or not, posture adjustment suggestions are provided in time, and exercise injuries are reduced; in combination with simulation of the virtual scene, the user can experience the virtual scene matched with the actual exercise posture of the user, the effectiveness of exercise training and the input feeling of the user are enhanced, and the practicability and individuation of exercise guidance are improved.

Description

Technical Field

[0001] The present invention relates to the field of motion sensing and intelligent analysis technology, and specifically to a display system based on the integration of motion sensing and digital twin ecology. Background Art

[0002] Sports health display is to capture human movements and then use digital twins to create a virtual ecosystem, so as to generate a digital twin ecosystem that is synchronized with the real environment in real time and display it. This sports mode can increase the user's sense of immersion during exercise, while stimulating the user's interest in sports and environmental awareness; Current sports health displays usually compare and display the monitored health data (such as heart rate, exercise duration, breathing rate, etc.) with the set health thresholds. This static processing of health data cannot predict and adjust the user's health trends or changes, and cannot dynamically adjust the virtual scene or provide corresponding virtual feedback according to the user's health changes, reducing the effectiveness of the interaction between the user's health data and the virtual environment. Summary of the invention

[0003] The purpose of the present invention is to provide a display system based on the integration of motion sensing and digital twin ecology to solve the problems mentioned in the above background technology.

[0004] The purpose of the present invention can be achieved by the following technical solutions: A display system based on the integration of motion sensing and digital twin ecology, comprising: a server, a dynamic analysis module and an intelligent display module; The server collects the user's health information in real time through wearable devices and other monitoring devices worn by the user, including sports data and physiological data, and saves them; the specific sports data is the user's sports posture and movements captured by human motion sensors to determine the user's sports type and the corresponding data showing the user's sports status in real time; The dynamic analysis module comprehensively analyzes the user's exercise and physiological data based on health data, identifies changes in health status to obtain the exercise physiological deviation value at each monitoring moment, and constructs a line graph of the exercise physiological deviation value based on this, performs trend analysis on the line graph of the exercise physiological deviation value to obtain the exercise health assessment value, and sends it to the intelligent display module; The intelligent display module performs real-time display based on the received sports health assessment value and its corresponding sports physiological deviation value line graph, and generates corresponding health guidance suggestions based on this, specifically: the sports health assessment value is compared and analyzed with the set health interval. When the sports health assessment value is greater than the maximum value in the set health interval, a sports health signal is generated; when the sports health assessment value is in the set health interval, a normal exercise signal is generated; when the sports health assessment value is less than the minimum value in the set health interval, a sports danger signal is generated; at the same time, the intelligent display module monitors the user's movement posture in real time, and performs digital twinning based on this to create a movement simulation that fits the user's actual movement; the correctness of the user's actual movement posture is judged based on the virtual movement simulation, and corresponding sports posture guidance suggestions are generated.

[0005] Preferably, the specific process of comprehensively analyzing the user's exercise and physiological data based on health data is as follows: 2-1: Retrieve the user's exercise data, analyze the user's real-time exercise intensity based on the exercise data, and obtain the exercise intensity value; the specific exercise data includes weight recorded as W, exercise type, exercise posture and exercise speed at each monitoring moment recorded as Vj, where j=1,2,3,...J, J is a positive integer, J represents the total number of monitoring moments, and j represents any one of the monitoring moments; 2-1: Match the corresponding standard physiological parameters according to the exercise intensity value, including the standard heart rate range, standard respiratory rate range, standard blood sample saturation range and standard body temperature range; compare and analyze the deviation between the user's physiological data and the standard physiological parameters at each monitoring moment to obtain the exercise deviation value; 2-3: Construct a two-dimensional rectangular coordinate system with time as the horizontal coordinate and the exercise physiological deviation value as the vertical coordinate. Input the exercise physiological deviation value into the coordinate system according to its corresponding monitoring time, and record the position of the exercise physiological deviation value in the coordinate system as a physiological point. Connect each physiological point in sequence with a line segment to obtain an exercise physiological value line graph.

[0006] Preferably, the specific process of analyzing the user's real-time exercise intensity based on exercise data is: Set each type of exercise to correspond to a running base value, extract the exercise type, and compare it with all the set exercise types to match the corresponding exercise base value, which is recorded as L; The exercise base value L, body weight W and exercise speed Vj are normalized and their values ​​are taken. The values ​​are analyzed and calculated to obtain the exercise intensity value LVj. The specific calculation formula is: Where a1 and a2 are the set weight constants respectively.

[0007] Preferably, the specific process of comparing and analyzing the deviation between the user's physiological data at each monitoring moment and the standard physiological parameters is as follows: The exercise intensity at this time is compared with several set intensity intervals to match the corresponding standard physiological parameters. The specific standard physiological parameters include standard heart rate interval, standard respiratory rate interval, standard blood oxygen saturation interval and standard body temperature interval, and they are respectively recorded as [AX1, AX2], [AP1, AP2], [AH1, AH2] and [AT1, AT2]; thereby, the standard physiological parameters corresponding to each monitoring moment can be obtained, and the physiological data at each monitoring moment are compared and analyzed with the corresponding standard physiological parameters to obtain the heart rate deviation value, respiratory deviation value, blood oxygen deviation value and body temperature deviation value at each monitoring moment, and they are respectively recorded as CXj, CPj, CHj and CTj; the specific comparison and analysis steps are as follows: Compare the heart rate Xj with the standard heart rate interval [AX1, AX2]. If the heart rate Xj is within the standard heart rate interval [AX1, AX2], the heart rate deviation value is assigned to zero; otherwise, the heart rate deviation value is calculated by CXj=min[AX1-Xj, Xj-AX2]. Thus, the corresponding heart rate deviation value CXj at each monitoring moment can be obtained; similarly, the breathing deviation value, blood oxygen deviation value and body temperature deviation value can be obtained. The heart rate deviation value CXj, breathing deviation value CPj, blood oxygen deviation value CHj and body temperature deviation value CTj at each monitoring moment are normalized and their values ​​are taken. The numerical values ​​are calculated and analyzed by formula to obtain the exercise physiological deviation value Ddj at each monitoring moment. The specific calculation formula is: Among them, d1, d2, d3, and d4 are the set weight constants respectively.

[0008] Preferably, the specific process of performing trend analysis on the sports physiological deviation value line graph is as follows: The slope of the line segment formed by two adjacent physiological points is calculated by data fitting and recorded as the physiological slope , summing up the physiological slopes greater than zero to obtain the deviation increase value recorded as G1, and summing up the physiological slopes less than zero and taking the absolute value to obtain the deviation decrease value recorded as G2; The physiological deviation value Ddj and physiological slope at each monitoring moment , the deviation increase value G1 and the deviation decrease value G2 are normalized and their values ​​are taken, and the values ​​are analyzed and calculated by formula to obtain the sports health assessment value DG. The specific calculation formula is: Among them, λ1, λ2, and λ3 are the set weight constants, is the mean of each physiological slope.

[0009] Preferably, the correctness of the user's actual exercise posture is judged, and corresponding exercise posture guidance suggestions are generated; the specific judgment process is: 6-1: Set each movement to correspond to a posture set, which stores various standard postures corresponding to the movement, extract the movement type, and compare it with all the set movement types to match the corresponding posture set; match the movement posture at each monitoring moment with each standard posture in the posture set to obtain the target posture; 6-2: Synchronize and number the special joints of the motion posture and the target posture one by one, analyze the difference between the special joints in the motion posture and the target posture, and obtain the Euclidean distance of the special joints, thereby obtaining the Euclidean distances of several special joints; 6-3: Connect two adjacent special joints in the motion posture and the target posture to form a joint vector, analyze the angle difference between the joint vectors composed of the same two special joints, and obtain the cosine value, thereby obtaining the cosine values ​​of several joint vectors; 6-4: The Euclidean distance D between the motion posture and the target posture k And the cosine value of each joint vector Normalization is performed and the numerical value is obtained. The numerical value is calculated and analyzed by formula to obtain the overlap value DQ between the motion posture and the standard posture. The specific calculation formula is: Where η1 and η2 are the set weight constants, respectively. From this, the overlap value between the motion posture and the target posture at each monitoring moment can be obtained and recorded as DQj.

[0010] Preferably, the difference between each special joint in the motion posture and the target posture is analyzed, and the specific process is as follows: The special joints of the motion posture and the target posture are synchronously numbered one by one and recorded as k, where k=1,2,3...K, K is a positive integer, K represents the total number of special joints, and k represents the number of any special joint; the motion posture and the target posture are simultaneously input into the three-dimensional coordinate system to obtain the three-dimensional coordinates of any special joint, and they are recorded as Qk(X Qk , Y Qk , Z Qk ) and Bk(X Bk , Y Bk , Z Bk ); select the special joint with the same number in the motion posture and the target posture, and use the Euclidean calculation formula to calculate the Euclidean distance of the same special joint in the motion posture and the target posture, which is recorded as D k ; The specific calculation formula is: This gives the Euclidean distance of any particular joint.

[0011] Preferably, the angle difference between the joint vectors composed of the same two special joints is analyzed, and the specific process is as follows: The two adjacent special joints in the motion posture and the target posture are connected to form joint vectors, which are recorded as and , use cosine similarity to measure the angle difference between two joint vectors to get the cosine value , the specific calculation formula is: The · in the formula represents the vector dot product, and Represents the modulus of the joint vector composed of two adjacent joints; from this, the cosine value of each joint vector can be obtained.

[0012] Preferably, the steps for generating the exercise posture guidance suggestion are: When the user's overlap value is less than the minimum value in the set overlap interval, a motion posture error is generated and a corresponding associated voice is issued; when the user's overlap value is within the set overlap interval, a motion posture general is generated and a corresponding associated voice is issued; when the user's overlap value is greater than the maximum value in the set overlap interval, a motion posture standard is generated and a corresponding associated voice is issued.

[0013] Preferably, the intelligent display module is also used to continuously track and analyze the user's motion posture according to the overlap value at each monitoring moment, specifically: A two-dimensional rectangular coordinate system is constructed with time as the horizontal coordinate and the overlap value of each monitoring time as the vertical coordinate. The overlap value is input into the coordinate system according to its corresponding monitoring time, and the position of the overlap value in the coordinate system is recorded as the overlap point. Each overlap point is connected in sequence by a line segment to obtain an overlap value line graph; The slope of the line segment composed of two adjacent overlapping points is calculated by data fitting and recorded as the overlapping slope , the overlap slopes greater than zero are summed up to obtain the overlap increase value, recorded as M1, and the overlap slopes less than zero are summed up and then the absolute value is taken to obtain the overlap reduction value, recorded as M2; The overlap value DQj and overlap slope at each monitoring time , overlap increase value M1 and overlap decrease value M2 are normalized and their values ​​are taken, and the values ​​are analyzed and calculated by formula to obtain the posture standard evaluation value MU. The specific calculation formula is: Among them, μ1, μ2, and μ3 are the set weight constants, is the mean of the overlapping slopes; The sports health assessment value and the posture standard assessment value are normalized and their numerical values ​​are taken, and the numerical values ​​are weighted to obtain the ranking value, and the online exercise users are sorted in descending order according to the ranking value.

[0014] Beneficial effects of the present invention: By customizing individual standard sports physiological parameters for each user based on their body shape, age, gender and physical fitness; performing deviation analysis on each user's sports data and physiological data to obtain sports physiological deviation values, and then performing real-time trend analysis on the sports physiological deviation values, the user's sports health status can be accurately assessed, the future sports physiological status can be predicted, and exercise recommendations can be adjusted in a timely manner, which helps to detect sports physiological health problems at an early stage, prevent potential health risks, and ensure the safety of users during exercise; By displaying the overlap value between the user's sports posture and the standard posture in real time, it can help users understand more clearly whether their sports posture is correct, and provide timely suggestions for posture adjustment to reduce sports injuries; combined with the simulation of virtual scenes, users can experience virtual scenes that match their actual sports postures, which enhances the effectiveness of sports training and the user's sense of involvement, and improves the practicality and personalization of sports guidance; By combining the sports health assessment value and the posture standard assessment value, the ranking value is calculated and the users are sorted, which not only motivates users to improve their health level and sports performance, but also increases the interaction between users; In summary, the present invention not only optimizes health management during exercise, but also improves exercise effects and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below in conjunction with the accompanying drawings.

[0016] Figure 1 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention is a display system based on the integration of motion sensing and digital twin ecology, including: a server, a dynamic analysis module and an intelligent display module; The server collects the user's health information in real time through wearable devices (such as smart bracelets, fitness bracelets, etc.) and other monitoring devices worn by the user, including motion data and physiological data, and saves them; the specific motion data is captured by human motion sensors (such as accelerometers, gyroscopes, depth cameras, etc.) to capture the user's motion posture and movements, so as to determine the user's motion type (such as walking, jogging, sprinting, cycling, etc.) and the corresponding data showing the user's motion status in real time; The dynamic analysis module performs trend analysis on the user's exercise and physiological data based on health data to identify changes in health status, specifically: The user's motion data and physiological data at each monitoring moment are retrieved. The specific motion data include weight, exercise type, exercise posture and exercise speed. The weight and exercise speed are recorded as W and Vj respectively, where j=1,2,3,...J, J is a positive integer, J represents the total number of monitoring moments, and j represents any one of the monitoring moments; the physiological data include heart rate, respiratory rate, blood oxygen saturation and body temperature, which are recorded as Xj, Pj, Hj and Tj respectively; it should be noted that the motion data and physiological data are collected synchronously; Set a running base value for each type of exercise. It should be noted that the base values ​​for different types of exercise should be based on the intensity, energy consumption, muscle involvement and physiological load of the exercise, so the corresponding exercise base values ​​are different. For example, even if the exercise distance is the same, the exercise base values ​​for walking and running are different, and the exercise base value for running is usually higher than that for walking; extract the exercise type, and compare it with all the set exercise types to match the corresponding exercise base value, and record it as L; The exercise base value L, body weight W and exercise speed Vj are normalized and their values ​​are taken. The values ​​are analyzed and calculated to obtain the exercise intensity value LVj. The specific calculation formula is: Where a1 and a2 are respectively set weight constants, and their values ​​are set by the personnel in this field according to actual needs. It can be seen from the formula that for the same amount of exercise, the heavier the person, the greater the exercise intensity. Therefore, when the user's weight is greater, the exercise intensity value is greater; when the exercise speed is greater, the exercise intensity value is greater; thus, the exercise intensity value corresponding to the user at each monitoring time can be obtained; There are several intensity intervals, each of which corresponds to a standard physiological parameter. The specific standard physiological parameters include a standard heart rate interval, a standard respiratory rate interval, a standard blood sample saturation interval, and a standard body temperature interval. It should be noted that the specific standard physiological parameters are obtained by performing exercise simulation in different exercise intensity intervals according to the user's body shape, age, gender, and physical fitness. This individualized simulation method can accurately customize exercise health guidance suitable for each user's body shape and physical fitness, avoid the health risks of excessive or light exercise, and improve exercise effect and safety. The exercise intensity at this time is compared with several set intensity intervals to match the corresponding standard physiological parameters. The specific standard physiological parameters include standard heart rate interval, standard respiratory rate interval, standard blood oxygen saturation interval and standard body temperature interval, and they are respectively recorded as [AX1, AX2], [AP1, AP2], [AH1, AH2] and [AT1, AT2]; thereby, the standard physiological parameters corresponding to each monitoring moment can be obtained, and the physiological data at each monitoring moment are compared and analyzed with the corresponding standard physiological parameters to obtain the heart rate deviation value, respiratory deviation value, blood oxygen deviation value and body temperature deviation value at each monitoring moment, and they are respectively recorded as CXj, CPj, CHj and CTj; the specific comparison and analysis steps are as follows: Compare the heart rate Xj with the standard heart rate interval [AX1, AX2]. If the heart rate Xj is within the standard heart rate interval [AX1, AX2], the heart rate deviation value is assigned to zero; otherwise, the heart rate deviation value is calculated by CXj=min[AX1-Xj, Xj-AX2]. Thus, the corresponding heart rate deviation value CXj at each monitoring time can be obtained; Similarly, the respiratory frequency Pj is compared with the standard respiratory frequency interval [AP1, AP2]. If the respiratory frequency Pj belongs to the standard respiratory frequency interval [AP1, AP2], the respiratory deviation value is assigned to zero; otherwise, the respiratory deviation value is calculated by CPj=min[AP1-Pj, Pj-AP2]. Thus, the corresponding respiratory deviation value CPj at each monitoring time can be obtained; Similarly, the blood oxygen saturation Hj is compared with the standard blood oxygen saturation interval [AH1, AH2]. If the exhaled blood oxygen saturation Hj belongs to the standard respiratory rate interval [AH1, AH2], the blood oxygen deviation value is assigned to zero; otherwise, the blood oxygen deviation value is calculated by CHj=min[AH1-Hj, Hj-AH2]. Thus, the corresponding blood oxygen deviation value CHj at each monitoring time can be obtained; Similarly, compare the body temperature Tj with the standard body temperature interval [AT1, AT2]. If the body temperature Tj belongs to the standard body temperature interval [AT1, AT2], the body temperature deviation value is assigned to zero; otherwise, the body temperature deviation value is calculated by CTj=min[AT1-Tj, Tj-AT2]. Thus, the corresponding body temperature deviation value CTj at each monitoring time can be obtained; The heart rate deviation value CXj, breathing deviation value CPj, blood oxygen deviation value CHj and body temperature deviation value CTj at each monitoring moment are normalized and their values ​​are taken. The numerical values ​​are calculated and analyzed by formula to obtain the exercise physiological deviation value Ddj at each monitoring moment. The specific calculation formula is: Wherein d1, d2, d3, and d4 are respectively set weight constants, and their specific values ​​are set by personnel in this field according to actual needs; A two-dimensional rectangular coordinate system was constructed with time as the horizontal coordinate and the sports physiological deviation value as the vertical coordinate. The sports physiological deviation value was input into the coordinate system according to its corresponding monitoring time, and the position of the sports physiological deviation value in the coordinate system was recorded as a physiological point. Each physiological point was connected in sequence with a line segment to obtain a sports physiological value line graph; the slope of the line segment formed by two adjacent physiological points was calculated by data fitting and recorded as the physiological slope. It should be noted that when the physiological slope is greater than zero, it indicates that the sports physiological deviation value shows an increasing trend, and the larger the physiological slope value is, the greater the increase in the physiological deviation value is; when the physiological slope is less than zero, it indicates that the sports physiological deviation value shows a decreasing trend, and the smaller the physiological slope value is, the greater the decrease in the physiological deviation value is; the deviation increase value obtained by summing up the physiological slopes greater than zero is recorded as G1, and the deviation decrease value obtained by summing up the physiological slopes less than zero and taking the absolute value is recorded as G2; The physiological deviation value Ddj and physiological slope at each monitoring moment , the deviation increase value G1 and the deviation decrease value G2 are normalized and their values ​​are taken, and the values ​​are analyzed and calculated by formula to obtain the sports health assessment value DG. The specific calculation formula is: Among them, λ1, λ2, and λ3 are the set weight constants, is the mean of each physiological slope; from the formula, it can be seen that when the increasing trend of the sports physiological deviation value is greater and the increasing amplitude is greater, the sports health assessment value is smaller; conversely, when the decreasing trend of the sports physiological deviation value is greater and the decreasing amplitude is greater, the sports health assessment value is greater; when the sports physiological deviation value is more volatile, the sports health assessment value is smaller; Send the sports health assessment value and its corresponding sports physiological deviation value line chart to the intelligent display module; By customizing personalized standard sports physiological parameters for each user based on the individual's body shape, age, gender and physical fitness; conducting deviation analysis on each user's sports data and physiological data to obtain the sports physiological deviation value, and then performing real-time trend analysis on the sports physiological deviation value, it is possible to accurately assess the user's sports health status, predict the future sports physiological status, and adjust exercise recommendations in a timely manner, which is helpful to detect sports physiological health problems at an early stage, prevent potential health risks, and ensure the safety of users during exercise.

[0019] The intelligent display module performs real-time display based on the received sports health assessment value and its corresponding sports physiological deviation value line graph, and generates corresponding health guidance suggestions accordingly; specifically: the sports health assessment value is compared and analyzed with the set health interval, and when the sports health assessment value is greater than the maximum value in the set health interval, a sports health signal is generated; when the sports health assessment value is within the set health interval, a sports normal signal is generated; when the sports health assessment value is less than the minimum value in the set health interval, a sports danger signal is generated to remind the user to stop exercising in time to prevent danger; At the same time, the intelligent display module monitors the user's movement posture in real time, and uses this to create a digital twin to create a movement simulation that fits the user's actual movement. It judges the correctness of the user's actual movement posture based on the virtual movement simulation, and generates corresponding movement posture guidance suggestions to achieve dynamic interaction between health data and virtual scenes. Specifically: Each sport is set to correspond to a posture set, which stores various standard postures corresponding to the sport. The specific standard posture is simulated and generated based on the user's weight and body shape; the sport type is extracted and compared with all the set sport types to match the corresponding posture set; the sport posture at each monitoring moment is matched with each standard posture in the posture set to obtain the target posture. The specific matching process is as follows: The standard postures in the posture set are simulated and connected using a kinematic model to obtain a standard trajectory (it should be noted that these standard trajectories represent the motion paths of each joint under an ideal motion state), and then the motion postures at each monitoring moment constitute a user motion trajectory. The user motion trajectory and the standard trajectory are compared using a time series matching method to obtain a standard posture corresponding to each motion posture, and the standard posture is used as the target posture of the motion posture, thereby obtaining the target posture of the motion posture at each monitoring moment (i.e., the ideal posture state); The special joints of the motion posture and the target posture (the special joints usually used for positioning are the head, shoulders and limb joints, etc., and the limb joints include elbows, knees, palms and soles) are synchronously numbered one by one and recorded as k, where k=1,2,3...K, K is a positive integer, K represents the total number of special joints, and k represents the number of any special joint; the motion posture and the target posture are simultaneously input into the three-dimensional coordinate system to obtain the three-dimensional coordinates of any special joint, and they are recorded as Qk(X Qk , Y Qk , Z Qk ) and Bk(X Bk , Y Bk , Z Bk ); select the special joint with the same number in the motion posture and the target posture, and use the Euclidean calculation formula to calculate the Euclidean distance of the same special joint in the motion posture and the target posture, which is recorded as D k ; The specific calculation formula is: Thus, the Euclidean distance of any special joint can be obtained. It should be noted that the larger the Euclidean distance corresponding to the special joint, the greater the difference between the motion posture and the target posture, which means that the user's motion posture is less standard; The two adjacent special joints in the motion posture and the target posture are connected to form joint vectors, which are recorded as and , use cosine similarity to measure the angle difference between two joint vectors to get the cosine value , the specific calculation formula is: The · in the formula represents the vector dot product, and Represents the modulus length of the joint vector composed of two adjacent joints; the cosine value of each joint vector can be obtained from this; it should be noted that the closer the two joint vectors are, the smaller the angle difference between the current user's motion posture and the target posture is, and the larger the cosine value is; when the two joint vectors are exactly the same, the cosine value is equal to 1, and the cosine value is the largest at this time; if the two joint vectors are orthogonal, the cosine value is 0, and the cosine value is the smallest at this time; theoretically, when the two vectors are in opposite directions, the cosine value is less than zero, but in this application scenario, the cosine value usually does not appear to be less than zero; therefore, in the present invention, the cosine value is greater than or equal to zero; The Euclidean distance D between the motion posture and the target posture k And the cosine value of each joint vector Normalization is performed and the numerical value is obtained. The numerical value is calculated and analyzed by formula to obtain the overlap value DQ between the motion posture and the standard posture. The specific calculation formula is: Among them, η1 and η2 are respectively the set weight constants. It can be seen from the formula that when the Euclidean distance between the motion posture and the target posture is larger, it means that the gap between the motion posture and the target posture is larger, and the overlap value is smaller; when the cosine value is closer to 1, it means that the angle difference between the motion posture and the target posture is smaller, and the overlap value is larger; thus, the overlap value between the motion posture and the target posture at each monitoring moment can be obtained, and it is recorded as DQj; Based on the motion posture captured by motion sensing technology, a virtual motion simulation that matches the user's actual motion is created. Based on digital twin technology (i.e., virtual reproduction of reality), a virtual scene that is consistent with the actual motion is constructed, so that the user can see a simulation that matches their own motion posture in the virtual environment, and the user's motion posture and the corresponding overlap value are displayed in real time. Based on this, it is determined whether the user's posture is standard, so as to issue the corresponding associated voice, specifically: When the user's overlap value is less than the minimum value in the set overlap interval, a motion posture error is generated and a corresponding associated voice is issued. The specific voice associated with the motion posture error is: "Posture error, please pay attention to adjust the motion posture"; when the user's overlap value is in the set overlap interval, a general motion posture is generated and a corresponding associated voice is issued. The specific voice associated with the general motion posture is: "Posture is general, please keep up the good work"; when the user's overlap value is greater than the maximum value in the set overlap interval, a standard motion posture is generated and a corresponding associated voice is issued. The specific voice associated with the standard motion posture is: "Standard posture, please continue to maintain it"; improve the interaction between the user and the virtual ecosystem, and enhance the user experience and the practicality of sports guidance; By displaying the overlap value between the user's exercise posture and the standard posture in real time, it can help the user understand more clearly whether their exercise posture is correct, and provide timely posture adjustment suggestions to reduce sports injuries; combined with the simulation of virtual scenes, users can experience virtual scenes that match their actual exercise postures, which enhances the effectiveness of sports training and the user's sense of involvement, and improves the practicality and personalization of sports guidance.

[0020] A two-dimensional rectangular coordinate system is constructed with time as the horizontal coordinate and the overlap value of each monitoring time as the vertical coordinate. The overlap value is input into the coordinate system according to its corresponding monitoring time, and the position of the overlap value in the coordinate system is recorded as the overlap point. The overlap points are connected in sequence using line segments to obtain an overlap value line graph; the slope of the line segment composed of two adjacent overlap points is calculated using data fitting and recorded as the overlap slope , the overlap slopes greater than zero are summed up to obtain the overlap increase value, recorded as M1, and the overlap slopes less than zero are summed up and then taken to obtain the overlap reduction value, recorded as M2; the overlap value DQj and overlap slope at each monitoring time are calculated. , overlap increase value M1 and overlap decrease value M2 are normalized and their values ​​are taken, and the values ​​are analyzed and calculated by formula to obtain the posture standard evaluation value MU. The specific calculation formula is: Among them, μ1, μ2, and μ3 are the set weight constants, is the mean of the overlap slopes; from the formula, it can be seen that when the overlap increase value is larger, it means that the overlap value increase trend is larger, the user's posture is more and more standard, and the posture standard evaluation value is larger; conversely, when the overlap decrease value is larger, it means that the overlap value decrease trend is larger, the user's posture is less and less standard, and the posture standard evaluation value is smaller; when the user's overlap slope is The more fluctuations there are, the more unstable the user's exercise posture standard is, and the smaller the posture standard evaluation value is; Normalize the sports health assessment value and the posture standard assessment value and take their values, perform weighted calculation on the values ​​to obtain ranking values, and sort the online exercise users in descending order according to the ranking values; By combining the sports health assessment value and the posture standard assessment value, the ranking value is calculated and the users are sorted, which not only motivates users to improve their health level and sports performance, but also increases the interaction between users.

[0021] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A display system based on the integration of motion sensing and digital twin ecosystem, characterized by: include: Dynamic analysis module and intelligent display module; The dynamic analysis module comprehensively analyzes the user's exercise and physiological data based on health data, identifies changes in health status to obtain the exercise physiological deviation value at each monitoring moment, and constructs a line graph of the exercise physiological deviation value based on this, performs trend analysis on the line graph of the exercise physiological deviation value to obtain the exercise health assessment value, and sends it to the intelligent display module; The intelligent display module performs real-time display based on the received sports health assessment value and its corresponding sports physiological deviation value line graph, and generates corresponding health guidance suggestions based on this, specifically: the sports health assessment value is compared and analyzed with the set health interval. When the sports health assessment value is greater than the maximum value in the set health interval, a sports health signal is generated; when the sports health assessment value is in the set health interval, a normal exercise signal is generated; when the sports health assessment value is less than the minimum value in the set health interval, a sports danger signal is generated; at the same time, the intelligent display module monitors the user's movement posture in real time, and performs digital twinning based on this to create a movement simulation that fits the user's actual movement; the correctness of the user's actual movement posture is judged based on the virtual movement simulation, and corresponding sports posture guidance suggestions are generated.

2. The display system based on the integration of motion sensing and digital twin ecosystem according to claim 1 is characterized in that: The specific process of comprehensive analysis of the user's exercise and physiological data based on health data is as follows: 2-1: Retrieve the user's exercise data, analyze the user's real-time exercise intensity based on the exercise data, and obtain the exercise intensity value; the specific exercise data includes weight, exercise type, exercise posture and exercise speed at each monitoring time; 2-1: Match the corresponding standard physiological parameters according to the exercise intensity value, including the standard heart rate range, standard respiratory rate range, standard blood sample saturation range and standard body temperature range; compare and analyze the deviation between the user's physiological data and the standard physiological parameters at each monitoring moment to obtain the exercise deviation value; 2-3: Construct a two-dimensional rectangular coordinate system with time as the horizontal coordinate and the exercise physiological deviation value as the vertical coordinate. Input the exercise physiological deviation value into the coordinate system according to its corresponding monitoring time, and record the position of the exercise physiological deviation value in the coordinate system as a physiological point. Connect each physiological point in sequence with a line segment to obtain an exercise physiological value line graph.

3. The display system based on the integration of motion sensing and digital twin ecology according to claim 2 is characterized in that: The specific process of analyzing the user's real-time exercise intensity based on exercise data is as follows: Set each type of exercise to correspond to a base exercise value, extract the exercise type, and compare it with all set exercise types to match the corresponding base exercise value; The exercise base value, body weight and exercise speed are normalized and their values ​​are taken. The values ​​are then formula-solved and analyzed to obtain the exercise intensity value, thereby obtaining the exercise intensity value corresponding to the user at each monitoring moment.

4. The display system based on the integration of motion sensing and digital twin ecology according to claim 3 is characterized in that: The specific process of comparing and analyzing the deviation between the user's physiological data and the standard physiological parameters at each monitoring moment is as follows: The exercise intensity at this time is compared with several set intensity intervals to match the corresponding standard physiological parameters, and the specific standard physiological parameters include standard heart rate interval, standard breathing rate interval, standard blood sugar saturation interval and standard body temperature interval; thereby, the standard physiological parameters corresponding to each monitoring moment can be obtained, and the physiological data at each monitoring moment is compared and analyzed with the corresponding standard physiological parameters to obtain the heart rate deviation value, breathing deviation value, blood oxygen deviation value and body temperature deviation value at each monitoring moment; the specific comparison and analysis steps are: Compare the heart rate with the standard heart rate range. If the heart rate is within the standard heart rate range, the heart rate deviation value is assigned to zero; otherwise, the difference between the heart rate and the upper and lower limits of the standard heart rate range is calculated, and the smallest difference is taken as the heart rate deviation value; similarly, the breathing deviation value, blood oxygen deviation value and body temperature deviation value can be obtained; The heart rate deviation value, breathing deviation value, blood oxygen deviation value and body temperature deviation value at each monitoring moment are normalized and their numerical values ​​are taken, and the numerical values ​​are calculated and analyzed by formula to obtain the exercise physiological deviation value at each monitoring moment.

5. The display system based on the integration of motion sensing and digital twin ecology according to claim 4 is characterized in that: The specific process of trend analysis of the sports physiological deviation value line chart is as follows: The slope of the line segment formed by two adjacent physiological points is calculated by data fitting and recorded as the physiological slope. The physiological slopes greater than zero are summed to obtain the deviation increase value, and the physiological slopes less than zero are summed and then the absolute value is taken to obtain the deviation reduction value. The physiological deviation value, physiological slope, deviation increase value and deviation decrease value at each monitoring moment are normalized and their numerical values ​​are taken, and the numerical values ​​are calculated and analyzed by formula to obtain the sports health assessment value.

6. The display system based on the integration of motion sensing and digital twin ecology according to claim 1 is characterized in that: The correctness of the user's actual exercise posture is judged, and corresponding exercise posture guidance suggestions are generated; the specific judgment process is as follows: 6-1: Set each movement to correspond to a posture set, which stores various standard postures corresponding to the movement, extract the movement type, and compare it with all the set movement types to match the corresponding posture set; Match the motion posture at each monitoring moment with each standard posture in the posture set to obtain a target posture; 6-2: Synchronize and number the special joints of the motion posture and the target posture one by one, analyze the difference between the special joints in the motion posture and the target posture, and obtain the Euclidean distance of the special joints, thereby obtaining the Euclidean distances of several special joints; 6-3: Connect two adjacent special joints in the motion posture and the target posture to form a joint vector, analyze the angle difference between the joint vectors composed of the same two special joints, and obtain the cosine value, thereby obtaining the cosine values ​​of several joint vectors; 6-4: Normalize the Euclidean distances between the motion posture and the target posture and the cosine values ​​of the joint vectors and take their numerical values, and perform formulaic calculation and analysis on the numerical values ​​to obtain the overlap value between the motion posture and the standard posture; thereby, the overlap value between the motion posture and the target posture at each monitoring moment can be obtained.

7. The display system based on the integration of motion sensing and digital twin ecology according to claim 6 is characterized in that: Analyze the difference between the specific joints in the exercise posture and the target posture. The specific process is as follows: The special joints of the motion posture and the target posture are synchronously numbered one by one and recorded as k, where k=1,2,3...K, K is a positive integer, K represents the total number of special joints, and k represents the number of any special joint; the motion posture and the target posture are simultaneously input into the three-dimensional coordinate system to obtain the three-dimensional coordinates of any special joint, and they are recorded as Qk(X Qk , Y Qk , Z Qk ) and Bk(X Bk , Y Bk , Z Bk );At Select the special joints with the same number in the motion posture and the target posture, and use the Euclidean calculation formula to calculate the Euclidean distance of the same special joint in the motion posture and the target posture, which is recorded as D k ; The specific calculation formula is: This gives the Euclidean distance of any particular joint.

8. The display system based on the integration of motion sensing and digital twin ecology according to claim 7 is characterized in that: Analyze the angle difference between the joint vectors composed of the same two special joints. The specific process is as follows: The two adjacent special joints in the motion posture and the target posture are connected to form joint vectors, which are recorded as and , use cosine similarity to measure the angle difference between two joint vectors to get the cosine value , the specific calculation formula is: The · in the formula represents the vector dot product, and Represents the modulus of the joint vector composed of two adjacent joints; from this, the cosine value of each joint vector can be obtained.

9. The display system based on the integration of motion sensing and digital twin ecology according to claim 8 is characterized in that: The steps for generating exercise posture guidance suggestions are: When the user's overlap value is less than the minimum value in the set overlap interval, a motion posture error is generated and a corresponding associated voice is issued; when the user's overlap value is within the set overlap interval, a motion posture general is generated and a corresponding associated voice is issued; when the user's overlap value is greater than the maximum value in the set overlap interval, a motion posture standard is generated and a corresponding associated voice is issued.

10. The display system based on the integration of motion sensing and digital twin ecosystem according to claim 9 is characterized in that: The intelligent display module is also used to continuously track and analyze the user's motion posture based on the overlap value at each monitoring moment, specifically: A two-dimensional rectangular coordinate system is constructed with time as the horizontal coordinate and the overlap value of each monitoring time as the vertical coordinate. The overlap value is input into the coordinate system according to its corresponding monitoring time, and the position of the overlap value in the coordinate system is recorded as the overlap point. Each overlap point is connected in sequence by a line segment to obtain an overlap value line graph; The slope of the line segment composed of two adjacent overlapping points is calculated by data fitting and recorded as the overlapping slope. The overlapping slopes greater than zero are summed to obtain the overlapping increase value, and the overlapping slopes less than zero are summed and then the absolute value is taken to obtain the overlapping reduction value. The overlap value, overlap slope, overlap increase value and overlap decrease value at each monitoring moment are normalized and taken as the numerical value, and the numerical value is analyzed by formula calculation to obtain the posture standard evaluation value; The sports health assessment value and the posture standard assessment value are normalized and their numerical values ​​are taken, and the numerical values ​​are weighted to obtain the ranking value, and the online exercise users are sorted in descending order according to the ranking value.

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