Human health management method based on smart watches

Abstract

The present invention relates to the technical field of human health management, and specifically discloses a human health management method based on a smart watch. By having each participating athlete in a target marathon wear a smart sports watch, physical parameters of each participating athlete in the target marathon and physical status information corresponding to each current monitoring time point are synchronously obtained. Thus, the motion status of each participating athlete in the target marathon corresponding to each current monitoring time point is analyzed, and dangerous athletes in the target marathon are screened out. The method can reflect the athletes' motion status and physical health status in real time, supervise the participating athletes in an intelligent manner, provide more comprehensive data analysis and management for competition organizers, effectively avoid the drawbacks of strong randomness and subjectivity in the current manual supervision mode, and improve the quality and safety of the competition.

Description

Technical Field

[0001] The present invention relates to the technical field of human health management, and in particular to a human health management method based on a smart watch. Background Art

[0002] The rapid development of the world economy has led to a continuous improvement in people's living standards, and physical exercise has become an indispensable part of people's daily lives. However, in large-scale, multi-person, long-term exercise scenarios such as marathon running, on the one hand, due to the long time taken by marathon races, athletes cannot pay attention to their sports health status at all times. On the other hand, in order to ensure the health and safety of athletes, the role of monitoring should not be borne by the athletes themselves, but by the organizers of the competition or other third parties. This highlights the importance of human health management based on smart watches.

[0003] The existing athlete health management and analysis based on smart watches still needs to be optimized in some areas, specifically in the following aspects:

[0004] 1. Currently, it is impossible to conduct a comprehensive analysis of the fatigue coefficient of participating athletes based on their gait parameters, and it is impossible to reflect the athletes' exercise status and physical health status in real time. This will lead to the occurrence of sports risks, further causing physical damage to athletes and causing immeasurable losses.

[0005] 2. Currently, the health management of marathon runners is mainly carried out by supervisors responsible for athlete safety. However, relying solely on manual management cannot obtain athletes' sports health data in real time, nor can it provide more comprehensive data analysis and management for competition organizers. It cannot effectively circumvent the drawbacks of strong randomness and subjectivity in the current manual supervision model, which reduces the quality and safety of the competition. It cannot effectively guarantee the comprehensiveness of athlete health management analysis, cannot effectively guarantee the scientificity and reliability of the analysis results, and cannot provide accurate data for subsequent use, and cannot improve the accuracy of judging dangerous athletes. Summary of the Invention

[0006] In view of the deficiencies in the prior art, the present invention provides a human health management method based on a smart watch.

[0007] The present invention solves the above technical problems through the following technical means:

[0008] A human health management method based on a smart watch, the method comprising the following steps:

[0009] Step 1: Athlete wearing equipment: Number each participant in the target marathon according to a preset order, and have each participant in the target marathon wear a smart sports watch, thereby synchronously obtaining the physical parameters of each participant in the target marathon;

[0010] Step 2: Athlete status monitoring: Using the smart sports watches worn by each athlete in the target marathon, the physical status information of each athlete in the target marathon corresponding to each current monitoring time point is obtained;

[0011] Step 3: Athlete status analysis: Based on the physical status information of each athlete in the target marathon at each current monitoring time point, the athletic status of each athlete in the target marathon at each current monitoring time point is analyzed;

[0012] Step 4: Athlete supply analysis: Screen the corresponding extreme exercise time points of each participating athlete in the target marathon, mark the participating athletes with extreme exercise time points as dangerous athletes, and further conduct energy supply analysis on each dangerous athlete in the target marathon;

[0013] Step 5: Result feedback processing: Feedback the energy supply analysis results of each dangerous athlete in the target marathon to the marathon sports management platform, so as to stop and replenish the dangerous athletes in the target marathon.

[0014] According to a preferred embodiment, the physical parameters of each athlete in the target marathon race specifically include name, age, height and weight.

[0015] According to a preferred embodiment, the physical status information of each athlete in the target marathon race corresponding to each current monitoring time point includes a respiratory decibel value and a respiratory frequency.

[0016] According to a preferred embodiment, the motion state analysis of each athlete in the target marathon corresponding to each current monitoring time point is performed, and the analysis process is as follows:

[0017] Based on high-definition cameras deployed along the route of the target marathon, the unit motion gait diagram of each athlete in the target marathon corresponding to each current monitoring time point is obtained, thereby obtaining the gait parameters of each athlete in the target marathon corresponding to each unit gait cycle, wherein the gait parameters include stride length, stride length, stride width, and foot angle. Each unit gait cycle is numbered and the unit gait cycle with the highest number is selected as the reference gait cycle. The stride length, stride length, stride width, and foot angle of each athlete in the target marathon corresponding to each reference gait cycle are obtained, and the sum and average of the sums are calculated to obtain the reference stride length, reference stride length, reference stride width, and reference foot angle of each athlete in the target marathon;

[0018] The stride length, stride length, stride width and foot angle of each athlete in the target marathon corresponding to each unit gait cycle are marked as and , r represents the number of each athlete, r=1,2,...d, f represents the number of each unit gait cycle, f=1,2,...i;

[0019] According to the physical parameters of each athlete in the target marathon, the height of each athlete in the target marathon is obtained, and the height is compared with the reference stride length floating difference corresponding to each height interval stored in the intelligent database, thereby obtaining the reference stride length floating difference of each athlete in the target marathon. , the reference stride length floating difference is obtained by the same analysis method based on the reference stride length floating difference of each participating athlete in the target marathon. Floating difference from reference step width ;

[0020] According to the physical parameters of each athlete in the target marathon, the weight of each athlete in the target marathon is obtained, and the weight is compared with the reference foot angle floating difference corresponding to each weight interval stored in the intelligent database, thereby obtaining the reference foot angle floating difference of each athlete in the target marathon. ;

[0021] pass , calculate the gait fatigue assessment coefficient of each athlete corresponding to each unit gait cycle in the target marathon ,in, , represents the reference stride length corresponding to the rth athlete in the target marathon, , represents the reference stride length corresponding to the rth athlete in the target marathon, , represents the reference stride width corresponding to the rth athlete in the target marathon, , represents the reference foot angle corresponding to the rth athlete in the target marathon, e represents a natural constant, Respectively represent the weight factors of step length, stride length, step width and foot angle corresponding to gait fatigue assessment.

[0022] According to a preferred embodiment, the motion state analysis of each athlete in the target marathon corresponding to each current monitoring time point is performed, and the analysis process further includes the following steps:

[0023] Based on the unit motion gait graphs of each athlete in the target marathon corresponding to each current monitoring time point, the motion videos of each athlete in the target marathon corresponding to all current monitoring time points are collected and spliced, and the change angles of each joint in each motion posture in each unit gait cycle of each athlete in the target marathon are further obtained, and the change angles of each joint in each motion posture are constructed into a set of change angles of each joint in each motion posture. , where g represents the joint change angle, g=1,2,...s, j represents the number corresponding to each movement posture, j=j1, j2, j3 and j4, j1, j2, j3 and j4 represent the first landing state, stance phase state, toe-off state and step phase state respectively, g=g1, g2 and g3, g1, g2 and g3 represent the hip joint, knee joint and ankle joint respectively, represents the change angle of the gth joint in the jth movement posture of the rth athlete in the target marathon race corresponding to the fth unit gait cycle;

[0024] A summary table of the floating coefficients of each joint under the reference motion state corresponding to each age level in each weight interval is extracted from the intelligent database, and compared with the age and weight corresponding to each athlete in the target marathon, thereby obtaining the floating coefficients of each joint under the reference motion state corresponding to each athlete in the target marathon. Simultaneously, a summary table of the reference change angles of each joint under the reference motion state corresponding to each age level in each weight interval is extracted from the intelligent database, and compared with the age and weight corresponding to each athlete in the target marathon, thereby obtaining the reference change angles of each joint under the reference motion state corresponding to each athlete in the target marathon, and multiplied by the floating coefficients of each joint under the reference motion state corresponding to each athlete in the target marathon, thereby obtaining the maximum calculated change angles of each joint under the reference motion state corresponding to each athlete in the target marathon. and the minimum calculated change angle ;

[0025] pass Calculate the joint fatigue assessment index of each athlete corresponding to each unit gait cycle in the target marathon , where j4 represents the total number of motion postures, g3 represents the total number of joints, Indicates the allowed difference in the change angle corresponding to the g-th joint in the unit motion posture in the intelligent database.

[0026] According to a preferred embodiment, the analysis of the movement status of each athlete in the target marathon corresponding to each current monitoring time point further includes:

[0027] Based on the physical condition information of each athlete in the target marathon at each current monitoring time point, the respiratory decibel value and respiratory rate of each athlete in the target marathon at each current monitoring time point are obtained, and the respiratory fatigue assessment coefficient of each athlete in the target marathon at each current monitoring time point is further calculated. , u represents the number of each current monitoring time point, u=1,2,...p;

[0028] Based on the gait fatigue assessment coefficient and joint fatigue assessment index of each participating athlete in the target marathon corresponding to each unit gait cycle, the gait fatigue assessment coefficient of each participating athlete in the target marathon corresponding to each current monitoring time point in each unit gait cycle is obtained. and Joint Fatigue Assessment Index ;

[0029] According to the analysis formula , analyze and obtain the comprehensive fatigue calculation coefficient of each athlete in the target marathon corresponding to each current monitoring time point ,in, Represent the calculated correction factors corresponding to the predefined breathing, gait and joint change angles respectively.

[0030] According to a preferred embodiment, the screening process for the extreme exercise time points corresponding to the athletes in the target marathon competition is as follows:

[0031] The comprehensive fatigue calculation coefficient of each participating athlete in the target marathon race corresponding to each current monitoring time point is compared with the set standard fatigue state coefficient. If the comprehensive fatigue calculation coefficient of a participating athlete in the target marathon race corresponding to a current monitoring time point is greater than or equal to the standard fatigue state coefficient, then the current monitoring time point is marked as the extreme exercise time point, thereby screening out the extreme exercise time points corresponding to each participating athlete in the target marathon race.

[0032] According to a preferred embodiment, the energy supply analysis of each dangerous athlete in the target marathon is performed, and the specific analysis process is as follows:

[0033] Obtaining the time of each dangerous athlete's corresponding extreme exercise time point in the target marathon, and extracting the standard start time of the target marathon from an intelligent database, calculating the difference between the time of each dangerous athlete's corresponding extreme exercise time point in the target marathon and the standard start time of the target marathon to obtain the time difference between the corresponding start time and the extreme exercise time point in the target marathon, comparing the time difference with predefined time difference levels to obtain the time difference level of each dangerous athlete in the target marathon, and comparing the time difference with the preset supplementary beverage types corresponding to the time difference levels to obtain the supplementary beverage type corresponding to the extreme exercise time point in the target marathon for each dangerous athlete;

[0034] According to the analysis formula , the minimum amount of supplementary drinks for each dangerous athlete in the target marathon is obtained by analysis, where w represents the number of each dangerous athlete, w=1,2,...n, Indicates the reference amount of supplementary beverage corresponding to the preset unit exercise duration. It represents the time difference between the start time and the extreme exercise time point of the w-th dangerous athlete in the target marathon. Indicates a predefined beverage size correction factor.

[0035] Beneficial effects of the present invention:

[0036] (1) The human health management method based on smart watches provided by the present invention, by having each participating athlete in the target marathon race wear a smart sports watch, synchronously obtains the physical parameters of each participating athlete in the target marathon race and the physical status information corresponding to each current monitoring time point, thereby performing a motion state analysis of each participating athlete in the target marathon race corresponding to each current monitoring time point, and then screening out dangerous athletes in the target marathon race, and further performing an energy replenishment analysis on each dangerous athlete in the target marathon race, solving the problem of insufficient intelligence existing in the current technology, and being able to reflect the athlete's motion state and physical health status in real time, avoiding the occurrence of motion risks, and reducing the possibility of physical damage to athletes.

[0037] (2) The embodiments of the present invention supervise the participating athletes in an intelligent manner, providing more comprehensive data analysis and management for the competition organizers, effectively avoiding the drawbacks of strong randomness and subjectivity in the current manual supervision mode, improving the quality and safety of the competition, and effectively ensuring the comprehensiveness of the athlete health management analysis, ensuring the scientificity and reliability of the analysis results, thereby improving the accuracy of the judgment of dangerous athletes. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the connection structure of the method steps of the present invention.

[0039] Figure 2 Schematic diagram of gait calculation parameters involved in the present invention.

[0040] Figure 3 It is a simulated diagram of the three-dimensional rectangular coordinate system corresponding to the participating athletes involved in the present invention.

[0041] Figure 4 This is an enlarged view of the skeuomorphic smart sports watch corresponding to the three-dimensional rectangular coordinate system of the participating athletes involved in the present invention.

[0042] Figure 5 This is a summary representation of the floating coefficients of each joint under the reference motion state for each weight interval corresponding to each age level involved in the present invention.

[0043] Figure 6 This is a schematic diagram of the summary of the reference change angles of each joint under the reference motion state for each weight interval corresponding to each age level involved in the present invention.

[0044] Reference numerals: represents the step length, Indicates stride length, represents the step width, Indicates the foot angle. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0046] See also Figure 1 As shown, a human health management method based on a smart watch includes the following steps:

[0047] Step 1: Athlete wearing equipment: Number each participant in the target marathon according to a preset order, and have each participant in the target marathon wear a smart sports watch, thereby synchronously obtaining the physical parameters of each participant in the target marathon;

[0048] It should be added that the smart sports watches worn by each participating athlete in the target marathon are connected to the marathon sports management platform.

[0049] Preferably, based on the above solution, the physical parameters of each athlete in the target marathon race specifically include name, age, height and weight.

[0050] Step 2: Athlete status monitoring: Using the smart sports watches worn by each athlete in the target marathon, the physical status information of each athlete in the target marathon corresponding to each current monitoring time point is obtained;

[0051] Preferably, based on the above solution, the physical status information of each athlete in the target marathon corresponding to each current monitoring time point includes a breathing decibel value and a breathing frequency.

[0052] It should be added that, based on the decibel sensor deployed in the smart sports watch, the physical condition information of each participating athlete in the target marathon race corresponding to each current monitoring time point is collected.

[0053] Step 3: Athlete status analysis: Based on the physical status information of each athlete in the target marathon at each current monitoring time point, the athletic status of each athlete in the target marathon at each current monitoring time point is analyzed;

[0054] Preferably, based on the above solution, the motion status of each athlete in the target marathon is analyzed at each current monitoring time point, and the analysis process is as follows:

[0055] See also Figure 2 As shown, based on the high-definition cameras deployed along the route of the target marathon, the unit motion gait diagram of each athlete in the target marathon corresponding to each current monitoring time point is obtained, thereby obtaining the gait parameters of each athlete in the target marathon corresponding to each unit gait cycle, wherein the gait parameters include stride length, stride length, stride width and foot angle degree, each unit gait cycle is numbered and the unit gait cycle with the highest number is selected as the reference gait cycle, and the stride length, stride length, stride width and foot angle degree of each athlete in the target marathon corresponding to each reference gait cycle are obtained, and the sum and average of the sums are calculated to obtain the reference stride length, reference stride length, reference stride width and reference foot angle degree corresponding to each athlete in the target marathon;

[0056] It should be added that the unit motion gait graph of each athlete in the target marathon corresponding to each current monitoring time point is obtained in the following specific process:

[0057] See also Figure 3 and Figure 4As shown, a complete route map of the target marathon race is obtained from the intelligent database and imported into the road model map corresponding to the target marathon race to obtain the route model map of the target marathon race, and the route model map of the target marathon race is brought into the three-dimensional rectangular coordinate system, and at the same time, based on the locator arranged in the smart sports watch worn by each participating athlete, the coordinate position of each participating athlete in the three-dimensional rectangular coordinate system is obtained, and the coordinate position of each participating athlete in the two-dimensional rectangular coordinate system is extracted based on the coordinate position of each participating athlete in the three-dimensional rectangular coordinate system, and it is simultaneously imported into the route model map of the target marathon race together with the positions of each high-definition camera arranged along the route of the target marathon race, thereby obtaining the number of the high-definition camera closest to each participating athlete, and starting the high-definition camera closest to each participating athlete to instantly capture each participating athlete, thereby obtaining the unit motion gait map of each participating athlete corresponding to each current monitoring time point in the target marathon race.

[0058] It should be added that the unit motion gait diagram of each participating athlete in the target marathon race corresponding to each current monitoring time point is materialized and imported into the road model diagram corresponding to the target marathon race. Based on the unit motion gait diagram of each participating athlete in the target marathon race corresponding to each current monitoring time point, the step length, stride, step width and foot angle of each participating athlete in the target marathon race corresponding to each unit gait cycle are monitored.

[0059] It should be added that three steps constitute a unit gait cycle.

[0060] It should be noted that since marathon is a long and energy-consuming race, runners will basically choose to move forward at a steady pace at the beginning of the race, so it is of certain reference value to select the unit gait cycles that are ranked at the top as the reference gait cycles.

[0061] It should be added that the unit gait cycles with higher numbers are selected as reference gait cycles. Here, the unit gait cycles with the highest numbers can be selected as reference gait cycles.

[0062] The stride length, stride length, stride width and foot angle of each athlete in the target marathon corresponding to each unit gait cycle are marked as and , r represents the number of each athlete, r=1,2,...d, f represents the number of each unit gait cycle, f=1,2,...i;

[0063] According to the physical parameters of each athlete in the target marathon, the height of each athlete in the target marathon is obtained, and the height is compared with the reference stride length floating difference corresponding to each height interval stored in the intelligent database, thereby obtaining the reference stride length floating difference of each athlete in the target marathon. , the reference stride length floating difference is obtained by the same analysis method based on the reference stride length floating difference of each participating athlete in the target marathon. Floating difference from reference step width ;

[0064] According to the physical parameters of each athlete in the target marathon, the weight of each athlete in the target marathon is obtained, and the weight is compared with the reference foot angle floating difference corresponding to each weight interval stored in the intelligent database, thereby obtaining the reference foot angle floating difference of each athlete in the target marathon. ;

[0065] pass , calculate the gait fatigue assessment coefficient of each athlete corresponding to each unit gait cycle in the target marathon ,in, , represents the reference stride length corresponding to the rth athlete in the target marathon, , represents the reference stride length corresponding to the rth athlete in the target marathon, , represents the reference stride width corresponding to the rth athlete in the target marathon, , represents the reference foot angle corresponding to the rth athlete in the target marathon, e represents a natural constant, Respectively represent the weight factors of step length, stride length, step width and foot angle corresponding to gait fatigue assessment.

[0066] It's important to note that stride length is the distance between the two points where your left and right heels or toes touch the ground. A step forward with your left foot is called the left stride length, and a step forward with your right foot is called the right stride length. Stride length is significantly correlated with height: shorter people have shorter strides.

[0067] It should be noted that stride length refers to the longitudinal straight-line distance between two consecutive heel landing points on the same side, equivalent to the sum of the left and right step lengths. Stride width refers to the lateral distance between the left and right feet, usually measured at the midpoint of the heel. Stride width reflects gait stability; the narrower the stride width, the less stable the gait. The foot angle is the angle formed by the centerline running through the sole of one foot (the long axis of the foot, connecting the midpoint of the heel to the second toe) and the direction of travel.

[0068] Preferably, based on the above solution, the motion status analysis of each athlete in the target marathon corresponding to each current monitoring time point is performed, and the analysis process further includes the following steps:

[0069] Based on the unit motion gait graphs of each athlete in the target marathon corresponding to each current monitoring time point, the motion videos of each athlete in the target marathon corresponding to all current monitoring time points are collected and spliced, and the change angles of each joint in each motion posture in each unit gait cycle of each athlete in the target marathon are further obtained, and the change angles of each joint in each motion posture are constructed into a set of change angles of each joint in each motion posture. , where g represents the joint change angle, g=1,2,...s, j represents the number corresponding to each movement posture, j=j1, j2, j3 and j4, j1, j2, j3 and j4 represent the first landing state, stance phase state, toe-off state and step phase state respectively, g=g1, g2 and g3, g1, g2 and g3 represent the hip joint, knee joint and ankle joint respectively, represents the change angle of the gth joint in the jth movement posture of the rth athlete in the target marathon race corresponding to the fth unit gait cycle;

[0070] It should be added that the specific process of obtaining the change angle of each joint in each movement posture corresponding to each unit gait cycle of each participating athlete in the target marathon is as follows:

[0071] The motion videos of each athlete in the target marathon race corresponding to all current monitoring time points are anthropomorphized, thereby obtaining the anthropomorphized motion videos of each athlete in the target marathon race corresponding to each motion posture in each unit gait cycle, and focusing on each joint, thereby obtaining the change angle of each joint in each motion posture in each unit gait cycle of each athlete in the target marathon race.

[0072] Please refer to Figure 5 and Figure 6As shown, a summary table of floating coefficients of each joint under the reference motion state corresponding to each age level for each weight interval is extracted from the intelligent database, and compared with the age and weight corresponding to each athlete in the target marathon, thereby obtaining the floating coefficients of each joint under the reference motion state corresponding to each athlete in the target marathon, and simultaneously a summary table of reference change angles of each joint under the reference motion state corresponding to each age level for each weight interval is extracted from the intelligent database, and compared with the age and weight corresponding to each athlete in the target marathon, thereby obtaining the reference change angles of each joint under the reference motion state corresponding to each athlete in the target marathon, and multiplied by the floating coefficients of each joint under the reference motion state corresponding to each athlete in the target marathon, thereby obtaining the maximum calculated change angles of each joint under the reference motion state corresponding to each athlete in the target marathon. and the minimum calculated change angle ;

[0073] In a specific embodiment, the weight in the first interval is smaller than the weight in the second interval, which is smaller than the weight in the third interval; the age in the first level is smaller than the age in the second level, which is smaller than the age in the third level, which is smaller than the age in the fourth level.

[0074] pass Calculate the joint fatigue assessment index of each athlete corresponding to each unit gait cycle in the target marathon , where j4 represents the total number of motion postures, g3 represents the total number of joints, Indicates the allowed difference in the change angle corresponding to the g-th joint in the unit motion posture in the intelligent database.

[0075] Preferably, based on the above solution, the motion status analysis of each athlete in the target marathon corresponding to each current monitoring time point is performed, and the analysis process further includes:

[0076] Based on the physical condition information of each athlete in the target marathon at each current monitoring time point, the respiratory decibel value and respiratory rate of each athlete in the target marathon at each current monitoring time point are obtained, and the respiratory fatigue assessment coefficient of each athlete in the target marathon at each current monitoring time point is further calculated. , u represents the number of each current monitoring time point, u=1,2,...p;

[0077] It should be noted that the respiratory fatigue assessment coefficient of each participating athlete in the target marathon corresponding to each current monitoring time point is calculated as follows:

[0078] Obtaining the weight of each athlete participating in the target marathon, extracting from the intelligent database an example table of reference breathing decibel values ​​corresponding to each weight interval and each exercise duration, thereby obtaining reference breathing decibel values ​​corresponding to each exercise duration for each athlete participating in the target marathon;

[0079] Obtain the weight of each athlete participating in the target marathon, extract an example table of reference respiratory rates corresponding to each weight interval and each exercise duration from the intelligent database, and thereby obtain the reference respiratory rates corresponding to each exercise duration for each athlete participating in the target marathon;

[0080] Obtain the time value of each current monitoring time point, calculate the difference between it and the standard start time of the target marathon, and obtain the cut-off exercise duration of each participating athlete in the target marathon. Compare it with the reference breathing decibel value corresponding to the reference exercise duration of each participating athlete in the target marathon, and further obtain the reference breathing decibel value corresponding to each current monitoring time point of each participating athlete in the target marathon. Based on the analysis method of the reference breathing decibel value of each athlete in the target marathon corresponding to each current monitoring time point, the reference breathing frequency of each athlete in the target marathon corresponding to each current monitoring time point is obtained by similar analysis. ;

[0081] Based on the breathing decibel values ​​of each athlete in the target marathon corresponding to each current monitoring time point and respiratory rate ,pass Calculate the respiratory fatigue assessment coefficient of each athlete in the target marathon corresponding to each current monitoring time point , where h1 and h2 represent the coefficient factors corresponding to the set breathing decibel value and breathing frequency respectively. They respectively represent the permitted breathing decibel difference and permitted breathing frequency difference stored in the intelligent database.

[0082] Based on the gait fatigue assessment coefficient and joint fatigue assessment index of each participating athlete in the target marathon corresponding to each unit gait cycle, the gait fatigue assessment coefficient of each participating athlete in the target marathon corresponding to each current monitoring time point in each unit gait cycle is obtained. and Joint Fatigue Assessment Index ;

[0083] According to the analysis formula , analyze and obtain the comprehensive fatigue calculation coefficient of each athlete in the target marathon corresponding to each current monitoring time point ,in, Represent the calculated correction factors corresponding to the predefined breathing, gait and joint change angles respectively.

[0084] The embodiments of the present invention supervise participating athletes in an intelligent manner, providing more comprehensive data analysis and management for competition organizers, effectively avoiding the drawbacks of strong randomness and subjectivity in the current manual supervision mode, improving the quality and safety of the competition, and effectively ensuring the comprehensiveness of athlete health management analysis, ensuring the scientificity and reliability of the analysis results, thereby improving the accuracy of judging dangerous athletes.

[0085] Step 4: Athlete supply analysis: Screen the corresponding extreme exercise time points of each participating athlete in the target marathon, mark the participating athletes with extreme exercise time points as dangerous athletes, and further conduct energy supply analysis on each dangerous athlete in the target marathon;

[0086] Based on the above solution, the screening process for the corresponding extreme exercise time points of each athlete in the target marathon is as follows:

[0087] The comprehensive fatigue calculation coefficient of each participating athlete in the target marathon race corresponding to each current monitoring time point is compared with the set standard fatigue state coefficient. If the comprehensive fatigue calculation coefficient of a participating athlete in the target marathon race corresponding to a current monitoring time point is greater than or equal to the standard fatigue state coefficient, then the current monitoring time point is marked as the extreme exercise time point, thereby screening out the extreme exercise time points corresponding to each participating athlete in the target marathon race.

[0088] Preferably, based on the above scheme, the energy supply analysis of each dangerous athlete in the target marathon is performed, and the specific analysis process is as follows:

[0089] Obtaining the time of each dangerous athlete's corresponding extreme exercise time point in the target marathon, and extracting the standard start time of the target marathon from an intelligent database, calculating the difference between the time of each dangerous athlete's corresponding extreme exercise time point in the target marathon and the standard start time of the target marathon to obtain the time difference between the corresponding start time and the extreme exercise time point in the target marathon, comparing the time difference with predefined time difference levels to obtain the time difference level of each dangerous athlete in the target marathon, and comparing the time difference with the preset supplementary beverage types corresponding to the time difference levels to obtain the supplementary beverage type corresponding to the extreme exercise time point in the target marathon for each dangerous athlete;

[0090] According to the analysis formula , the minimum amount of supplementary drinks for each dangerous athlete in the target marathon is obtained by analysis, where w represents the number of each dangerous athlete, w=1,2,...n, Indicates the reference amount of supplementary beverage corresponding to the preset unit exercise duration. It represents the time difference between the start time and the extreme exercise time point of the w-th dangerous athlete in the target marathon. Indicates a predefined beverage size correction factor.

[0091] It should be added that when an athlete's physical state reaches its limit, the importance of energy replenishment cannot be ignored. During high-intensity exercise, the body requires a large amount of energy to maintain muscle contraction, cardiopulmonary function, and the normal functioning of the nervous system. The importance of energy replenishment is reflected in the following aspects:

[0092] 1. Energy mainly comes from glycogen and fat in the body. By replenishing carbohydrates and fat in time, you can provide sufficient energy for the muscles and delay the occurrence of fatigue;

[0093] 2. High-intensity exercise consumes a lot of blood sugar. If the blood sugar level is too low, it will lead to problems such as decreased physical strength, lack of concentration, fatigue and fainting;

[0094] 3. High-intensity exercise can cause a large amount of water and electrolyte loss, including sodium, potassium, magnesium, etc. By replenishing energy in time, you can maintain the body's water and electrolyte balance and avoid muscle cramps and physical decline;

[0095] Therefore, it is very important for athletes to replenish energy in a timely and scientific manner during high-intensity exercise, which can provide long-lasting energy support, delay the onset of fatigue, and promote the body's repair and recovery.

[0096] Step 5: Result feedback processing: Feedback the energy supply analysis results of each dangerous athlete in the target marathon to the marathon sports management platform, so as to stop and replenish the dangerous athletes in the target marathon.

[0097] The human health management method based on smart watches provided by the present invention, by having each participating athlete in a target marathon race wear a smart sports watch, synchronously obtains the physical parameters of each participating athlete in the target marathon race and the physical status information corresponding to each current monitoring time point, thereby performing a motion status analysis of each participating athlete in the target marathon race corresponding to each current monitoring time point, and then screening out dangerous athletes in the target marathon race, and further performing an energy replenishment analysis on each dangerous athlete in the target marathon race, solving the problem of insufficient intelligence existing in current technologies, and being able to reflect the athlete's motion status and physical health status in real time, avoiding the occurrence of sports risks, and reducing the possibility of physical damage to athletes.

[0098] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments 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 scope of protection of the present invention.

[0099] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0100] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A human health management method based on a smart watch, characterized in that: The following steps are involved: Step 1: Athletes wearing equipment: Number each athlete in the target marathon according to a preset order, and have them wear smart sports watches to obtain their physical parameters; Step 2: Athlete status monitoring: Using a smart sports watch, the athlete's physical status information corresponding to each current monitoring time point is obtained, wherein the physical status information includes respiratory decibel value and respiratory rate; Step 3: Athlete status analysis: Based on the physical status information, the athlete's motion status is analyzed at each current monitoring time point. The process is as follows: Based on the high-definition cameras deployed along the competition route, the unit motion gait diagram of each athlete corresponding to each current monitoring time point is obtained, and the gait parameters of each athlete corresponding to each unit gait cycle are obtained. The gait parameters include step length, stride, step width and foot angle, and then the gait fatigue assessment coefficient of each unit gait cycle is obtained by analysis and calculation. ; The unit motion gait graphs are aggregated and spliced ​​to obtain the motion videos of each athlete corresponding to all current monitoring time points, and the change angles of each joint in each motion posture of each athlete corresponding to each unit gait cycle are obtained. The joint fatigue assessment index of each unit gait cycle is calculated based on the change angle analysis. ; According to the respiratory decibel value and respiratory frequency, the respiratory fatigue assessment coefficient is calculated , u represents the number of each current monitoring time point, u=1,2,...p; According to the gait fatigue assessment coefficient and joint fatigue assessment index, the gait fatigue assessment coefficient at each current monitoring time point in each unit gait cycle is obtained. and Joint Fatigue Assessment Index ; According to the analysis formula , analyze and obtain the comprehensive fatigue calculation coefficient of each current monitoring time point ,in, Represent the calculated correction factors corresponding to the predefined breathing, gait and joint change angles respectively; Step 4: Athlete Replenishment Analysis: Screen the extreme exercise time points of each athlete, mark the athletes with extreme exercise time points as dangerous athletes, and perform energy replenishment analysis on each dangerous athlete; the extreme exercise time point screening process is as follows: Compare the comprehensive fatigue calculation coefficient of each athlete at each current monitoring time point with the set standard fatigue state coefficient. If the former is greater than or equal to the latter, mark the current monitoring time point as the extreme exercise time point; Step 5: Result feedback processing: Feedback the energy supply analysis results of each dangerous athlete to the marathon sports management platform, so that each dangerous athlete can be stopped and supplied with the corresponding supply operation.

2. The human health management method based on a smart watch according to claim 1, characterized in that: The physical parameters specifically include name, age, height and weight.

3. The human health management method based on a smart watch according to claim 1, characterized in that: The athlete's motion status is analyzed at each current monitoring time point. The process is as follows: Based on the high-definition cameras deployed along the way during the competition, the unit motion gait diagram of each athlete corresponding to each current monitoring time point is obtained, and the gait parameters of each athlete corresponding to each unit gait cycle are obtained. The gait parameters include step length, stride, step width and foot angle, which are marked as and , r represents the number of each athlete, r=1,2,...d, f represents the number of each unit gait cycle, f=1,2,...i; The unit gait cycle with the highest number is used as the reference gait cycle, and the gait parameters of each athlete corresponding to each reference gait cycle are obtained to obtain the reference stride length, reference stride length, reference stride width and reference foot angle corresponding to each athlete in the target marathon competition; Compare the height of each athlete with the reference stride length floating difference corresponding to each height interval stored in the intelligent database to obtain the reference stride length floating difference of each athlete in the target marathon , the reference stride floating difference is obtained by similar analysis Floating difference from reference step width ; Compare the weight of each athlete with the reference foot angle fluctuation difference corresponding to each weight range stored in the intelligent database, and thus obtain the reference foot angle fluctuation difference of each athlete in the target marathon ; pass , calculate the gait fatigue assessment coefficient of each unit gait cycle ,in , , , , 、 、 as well as They represent the reference step length, reference stride length, reference step width and reference foot angle of the rth athlete respectively, e is a natural constant, Respectively represent the weight factors of step length, stride length, step width and foot angle corresponding to gait fatigue assessment.

4. The human health management method based on a smart watch according to claim 3, characterized in that: The athlete's motion status is analyzed at each current monitoring time point. The analysis process also includes the following steps: The unit motion gait graphs are aggregated and spliced ​​to obtain the motion videos of each athlete corresponding to all current monitoring time points, and the change angles of each joint in each motion posture of each athlete corresponding to each unit gait cycle are obtained, and the change angles of each joint in each motion posture are constructed into a set of change angles of each joint in each motion posture. , where g represents the joint change angle, g=1,2,...s, j represents the number corresponding to each movement posture, j=j1, j2, j3 and j4, j1, j2, j3 and j4 represent the first landing state, stance phase state, toe-off state and step phase state respectively, g=g1, g2 and g3, g1, g2 and g3 represent the hip joint, knee joint and ankle joint respectively, represents the change angle of the gth joint in the jth movement posture of the rth athlete corresponding to the fth unit gait cycle; Extract the summary table of floating coefficients of each joint and the summary table of reference change angles of each joint under the reference motion state of each weight range and each age level from the intelligent database, compare them with the age and weight of each athlete, and obtain the floating coefficient and reference change angle of each joint under the reference motion state of each athlete respectively. Multiply the two and obtain the maximum calculated change angle of each joint under the reference motion state. and the minimum calculated change angle ; pass , calculate the joint fatigue assessment index of each unit gait cycle , where j4 represents the total number of motion postures, g3 represents the total number of joints, Indicates the allowed difference in the change angle corresponding to the g-th joint in the unit motion posture in the intelligent database.

5. The human health management method based on a smart watch according to claim 1, characterized in that: The logic of energy replenishment analysis for each dangerous athlete is as follows: Obtaining the time corresponding to the extreme exercise time point of each dangerous athlete, and extracting the standard start time of the target marathon from the intelligent database, subtracting the time difference between the two to obtain a time difference value, comparing the time difference value with predefined time difference levels to obtain the time difference level of each dangerous athlete, and comparing the time difference value with the preset supplementary beverage types corresponding to each time difference level to obtain the supplementary beverage type corresponding to the extreme exercise time point of each dangerous athlete; According to the analysis formula , get the minimum amount of supplementary drinks, where w represents the number of each dangerous athlete, w=1,2,...n, Indicates the reference amount of supplementary beverage corresponding to the preset unit exercise duration. represents the time difference of the w-th dangerous athlete, Indicates a predefined beverage size correction factor.

Images