Real-time motion data integration monitoring system and method

Abstract

The invention discloses a real-time motion data integration monitoring system and method, and relates to the technical field of motion monitoring, the real-time motion data integration monitoring system comprises a data acquisition module and a motion data analysis module, and the motion data analysis module comprises a motion intensity evaluation unit, a monitoring period adjustment unit and a fatigue degree evaluation unit; the real-time position and motion data of the athlete are monitored, when the athlete completes one step, related motion data of the step are recorded, and the motion data are preprocessed and transmitted after the monitoring period is finished; in combination with the heart rate and speed data, the exercise intensity of the athlete is judged, and whether a corresponding instruction is sent or not is judged; a fatigue index is comprehensively calculated through the step length, the vertical amplitude and the single-foot grounding time, and whether a rest instruction is sent or not is judged after the fatigue index is compared with a preset threshold value; adjusting the length of the monitoring period according to the analysis result of the exercise intensity and the fatigue degree; the comprehensive system design is beneficial for scientifically guiding training and recovery of athletes, and the training effect is improved.

Description

Technical Field

[0001] The present invention relates to the field of motion monitoring technology, and in particular to a real-time motion data integration monitoring system and method. Background Art

[0002] The real-time sports data integrated monitoring system is an important tool in the field of modern sports training, sports health monitoring and sports safety. With the rapid development of science and technology, especially the advancement of Internet of Things technology, big data analysis and artificial intelligence technology, the collection, processing and application of real-time sports data have become increasingly important; the system aims to integrate a variety of sensors and data processing technologies to monitor and analyze athletes' physiological data, sports status and environmental information in real time, and provide scientific basis for coaches, athletes and medical staff to improve training effects, prevent sports injuries and ensure the safety of athletes; Although the real-time motion data integration monitoring system has made certain progress, there are still some defects; first, the existing real-time motion data integration monitoring system often adopts a fixed monitoring cycle, which will result in the inability to accurately and quickly identify the athlete's fatigue abnormality when suspected fatigue of the athlete is detected; second, the existing real-time motion data integration monitoring system often monitors all motion data of the athlete during the entire running process to determine whether the athlete has fatigue abnormalities, which will increase the workload of the system and reduce the efficiency of the entire system; finally, the existing real-time motion data integration monitoring system often only considers the athlete's heart rate and speed to determine whether fatigue abnormalities occur, which will reduce the accuracy of the athlete's fatigue identification results. Summary of the invention

[0003] 1. Technical issues to be resolved In response to the technical problems in the background technology, the present invention proposes a real-time motion data integration monitoring system and method, which adopts a dynamic adjustment method of the monitoring period, determines whether fatigue detection is needed based on the athlete's exercise intensity, and whether the monitoring period needs to be dynamically adjusted, and determines whether the athlete has fatigue abnormalities based on data such as step length, vertical amplitude, and foot contact time; thereby solving the technical problems recorded in the background technology.

[0004] (II) Technical solution To achieve the above objectives, the present invention is implemented through the following technical solutions: A real-time motion data integrated monitoring system, comprising: The data acquisition module monitors and analyzes the real-time position and motion data of the athlete based on the sensor group. Whenever the athlete takes a step, a set of motion data of the step is acquired and recorded in real time. At the end of the monitoring period, the multiple sets of motion data recorded in the monitoring period are pre-processed and transmitted to the motion data analysis module. The sports data analysis module includes a sports intensity evaluation unit, a monitoring cycle adjustment unit and a fatigue degree evaluation unit; it is used to analyze the sports intensity of athletes, adjust the monitoring cycle and detect the fatigue degree according to the analysis results of the sports intensity; Among them, the exercise intensity assessment unit obtains several groups of heart rate data and speed data in the current monitoring period, and combines all the heart rate data and all the speed data in the current monitoring period to obtain the comprehensive heart rate and comprehensive speed in the current monitoring period; determines the exercise intensity type under the comprehensive heart rate and comprehensive speed based on the exercise intensity judgment rule; and comprehensively judges whether to send corresponding signals to the fatigue degree assessment unit and the monitoring period adjustment unit based on the two exercise intensity types; The fatigue level evaluation unit obtains several groups of fatigue evaluation data in the current monitoring period, and combines all fatigue evaluation data obtained in the current monitoring period to obtain a fatigue index of the current monitoring period; based on the relationship between the fatigue index and the fatigue index threshold, it determines whether to send a rest instruction to the athlete; The monitoring period adjustment unit adjusts the monitoring period length accordingly based on the received signal type.

[0005] Specifically, RFID tags are added to athletes, and they are given sports bracelets on the sports field. The sports bracelets have built-in GPS positioning systems, light sensors, and acceleration sensors. Running dynamic sensors are installed on the left and right running shoes of athletes respectively. The photosensitive sensor is used to monitor the athlete's heart rate, the acceleration sensor is used to monitor the athlete's stride length and vertical amplitude when running, and the running dynamic sensor is used to monitor the time when the left and right feet touch the ground; combined with the time of alternation between the two feet in each step and the stride length of each step, the speed of each step is obtained.

[0006] Specifically, from the moment the athlete takes the first step, the number of times the athlete's left and right feet touch the ground is monitored in real time; every time any foot touches the ground, that is, every step, the athlete's motion data during this step is recorded, including the heart rate and speed data at the end of this step, the step length data of this step, and the vertical amplitude and contact time data during this step; When the number of times the left and right feet touch the ground is monitored to be five times each, that is, every ten steps, the ten sets of motion data recorded will be transmitted to the motion data analysis module; the monitoring cycle at this time is the time required for each ten steps, and the length of subsequent monitoring cycles is expressed according to the number of steps, and running ten steps is used as the standard monitoring cycle length.

[0007] Specifically, the heart rate data and speed data in several groups of exercise data in the current monitoring period are obtained and recorded as as well as , Indicates the first Group data; The current monitoring period The heart rate data and speed data in the group data are combined to obtain the comprehensive heart rate in the current monitoring period. And the overall speed , the expression is:

[0008] in, represents the weight of each group of data, .

[0009] Specifically, the exercise intensity judgment rules include: Based on the athlete's age , calculate each athlete's maximum heart rate , the expression is: ; Based on maximum heart rate and the athlete's heart rate data, calculate the first exercise intensity in each set of data , the expression is: ; When the first exercise intensity When the first exercise intensity is and When the first exercise intensity is When , it means the current athlete's exercise intensity is vigorous; Based on the VDOT system, the speed data in each set of data is matched to the corresponding level; the VDOT system divides the intensity of running into five levels, namely, E, M, T, I and R, with the intensity increasing from left to right; based on the five-level speed range, the speed data in each set of data is matched to the corresponding level; the speed is lower than the average of the speeds of E and M The exercise intensity is low intensity, making the speed higher than the average of level I and level R speed The exercise intensity that makes the speed between the above two average values ​​is vigorous intensity, and the exercise intensity that makes the speed between the above two average values ​​is moderate intensity.

[0010] Furthermore, if the comprehensive heart rate in the current monitoring period With comprehensive speed If the corresponding exercise intensities are all moderate, no fatigue detection signal is sent to the fatigue degree assessment unit; if the current monitoring cycle length is different from the standard monitoring cycle length, a first adjustment signal is sent to the monitoring cycle adjustment unit, otherwise no adjustment signal is sent to the monitoring cycle adjustment unit; If the comprehensive heart rate in the current monitoring period With comprehensive speed If the corresponding exercise intensities are all low or intense, a second adjustment signal is sent to the monitoring period adjustment unit, and a fatigue detection signal is sent to the fatigue level assessment unit; If the comprehensive heart rate in the current monitoring period With comprehensive speed If one of the corresponding exercise intensities is moderate and the other is low or vigorous, further analysis is required.

[0011] Specifically, the further analysis is as follows: Assume that the comprehensive heart rate data in the current monitoring period The corresponding exercise intensity is low intensity or vigorous intensity, and the comprehensive speed in the current monitoring period is , and the VDOT system normalizes the speeds corresponding to the five levels of running intensity to obtain the normalized comprehensive speed Average of E and M speeds in the system and the average of the I and R speeds ; If the heart rate data The corresponding exercise intensity is low intensity, then the comprehensive heart rate data Deviation from medium intensity for If the heart rate data is integrated The corresponding exercise intensity is vigorous intensity, then the comprehensive heart rate data Deviation from medium intensity for ; Normalized comprehensive speed data Compensation with medium intensity for , It means taking the minimum value between A and B; like , a second adjustment signal is sent to the monitoring period adjustment unit, and no fatigue detection signal is sent to the fatigue degree evaluation unit; like , a second adjustment signal is sent to the monitoring period adjustment unit, and a fatigue detection signal is sent to the fatigue degree evaluation unit.

[0012] Further, after receiving the fatigue detection signal, the fatigue assessment data in several groups of motion data in the current monitoring period is obtained, and the fatigue assessment data includes the step length data in each group of motion data. , vertical amplitude data And single foot contact time data ; The current monitoring period Step length data in group fatigue assessment data , vertical amplitude data Single foot contact time Combined, the fatigue index of the current monitoring period is obtained , the expression is: ; in, Represents step length data , vertical amplitude data Single foot contact time The weight coefficient of They represent the minimum step length, the minimum vertical amplitude, and the maximum single-foot contact time respectively; Setting the fatigue index threshold , the fatigue index of the current monitoring cycle Fatigue index threshold In comparison, if , a rest instruction is sent to the athlete's sports bracelet, and the rest instruction includes a voice reminder and a vibration reminder; like , the current monitoring period is marked as suspected fatigue. If two consecutive monitoring periods have been marked as suspected fatigue, a rest instruction is sent to the athlete's sports bracelet; like , no command is sent.

[0013] Further, when the first adjustment signal is received, the monitoring period length of the next period is adjusted to the standard period length; When the second adjustment signal is received, the monitoring period length of the next period is adjusted to half of the monitoring period length of the current period, specifically in the order of ten steps, five steps, and two steps; When the first and second adjustment signals are not received, the monitoring period length of the next period is assumed to be equal to the monitoring period length of the current period.

[0014] A real-time motion data integration monitoring method, comprising: Step 1: Based on the sensor group, the real-time position and motion data of the athlete are monitored and analyzed in real time. Whenever the athlete takes a step, a set of motion data of the step is obtained and recorded in real time; Step 2: Obtain several groups of heart rate data and speed data in the current monitoring period, and combine all the heart rate data and all the speed data in the current monitoring period to obtain the comprehensive heart rate and comprehensive speed in the current monitoring period; determine the exercise intensity type under the comprehensive heart rate and comprehensive speed based on the exercise intensity judgment rule; and comprehensively judge whether to send a fatigue detection signal and a monitoring period adjustment signal based on the two exercise intensity types; Step 3: when a fatigue detection signal is received, several groups of fatigue assessment data in the current monitoring period are obtained, and all fatigue assessment data obtained in the current monitoring period are combined to obtain a fatigue index of the current monitoring period; based on the relationship between the fatigue index and the fatigue index threshold, it is determined whether to send a rest instruction to the athlete; Step 4: When a monitoring period adjustment signal is received, the monitoring period length is adjusted accordingly based on the received signal type.

[0015] (III) Beneficial effects The present invention provides a real-time motion data integration monitoring system and method, which has the following beneficial effects: 1. Through the comprehensive use of RFID tags, GPS positioning systems, photosensitive sensors, acceleration sensors and running dynamic sensors, the athletes' location information is tracked in real time, and their heart rate, step length, vertical amplitude, ground contact time and speed and other key sports parameters are accurately recorded. The accuracy and integrity of the data are ensured through pre-processing operations. This not only improves the accuracy and efficiency of sports data collection, but also provides a reliable foundation for subsequent sports data analysis. 2. By comprehensively considering the athlete's heart rate data and speed data, and using scientific calculation methods and judgment rules, an accurate assessment of exercise intensity is achieved; based on multiple sets of heart rate data and speed data, by calculating the comprehensive heart rate and comprehensive speed, combined with the exercise intensity judgment rules, it is accurately judged whether the athlete's current exercise state is normal, abnormal or unstable; based on the evaluation results, the fatigue degree detection and monitoring cycle adjustment instructions are intelligently triggered, providing basic support for subsequent athlete fatigue monitoring and dynamic adjustment of the monitoring cycle; 3. A scientific fatigue assessment model is constructed by comprehensively analyzing key running parameters such as stride length, vertical amplitude and single-foot contact time. By monitoring the athlete's running data in real time, the fatigue index algorithm is used to accurately assess the athlete's fatigue state, and rest instructions are sent in time when fatigue is detected, effectively preventing sports injuries and overtraining. By setting suspected fatigue markers, the system can also warn of the athlete's fatigue trend, providing coaches and athletes with more accurate training feedback and adjustment suggestions; 4. By dynamically adjusting the length of the monitoring cycle, flexible monitoring of the athlete's exercise status is achieved; according to the received adjustment signal, the monitoring cycle is intelligently changed, which can not only maintain the standard monitoring cycle when the athlete's exercise status is stable, but also shorten the monitoring cycle in time when the exercise status is abnormal or unstable, so as to more frequently evaluate the athlete's fatigue level and exercise intensity. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A structural schematic diagram of a real-time motion data integration monitoring system provided by the present invention; Figure 2 A flowchart of the implementation of a sports intensity evaluation unit in a real-time sports data integration monitoring system provided by the present invention; Figure 3 A flowchart of the steps of a real-time motion data integration monitoring method provided by 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] refer to Figure 1 The present invention provides a real-time motion data integration monitoring system, comprising: The data acquisition module monitors and analyzes the real-time position and motion data of the athlete based on the sensor group. Whenever the athlete takes a step, a set of motion data of the step is acquired and recorded in real time. At the end of the monitoring period, the multiple sets of motion data recorded in the monitoring period are pre-processed and transmitted to the motion data analysis module. The data acquisition module includes the following steps: Step 101: adding an RFID tag to an athlete on the sports field, wherein the RFID tag contains an identifier for identifying the athlete; Athletes on the sports field are equipped with sports bracelets with built-in GPS positioning system, light sensor and acceleration sensor; running dynamic sensors are installed on the left and right running shoes of athletes respectively; Among them, the GPS positioning system is used to locate the real-time location information of the athletes, specifically based on the RFID tags of each athlete, and the real-time location information of each athlete is displayed in the digital twin model of the stadium; The photosensitive sensor relies on photoplethysmography to monitor the athlete's heart rate in real time. When the light source shines on the skin, the red blood cells in the blood absorb and reflect light of different intensities. During the heartbeat, the blood flow changes, causing the intensity of the reflected light to change. After the photosensitive sensor receives these signals, it can calculate the heart rate through algorithm analysis. The accelerometer is used to monitor the stride length and vertical amplitude of the athlete when running. The acceleration and deceleration of the athlete's wrist are monitored during running to identify the vibration of each step. When the sensor detects continuous and regular vibration, it will be counted as a step. Whenever the athlete is detected to have taken a step, the position change between the previous step and this step is taken as the step length of this step in combination with the athlete's position change. The vertical amplitude is calculated by monitoring the acceleration changes of the athlete's wrist in the vertical direction when running; when the athlete runs, the up and down movement of the body's center of gravity will produce a certain acceleration, and the sensor can capture this acceleration change, that is, the acceleration generated by the athlete in the up and down (Z-axis) direction; the acceleration data in the Z-axis direction is time-integrated to obtain the velocity data in the Z-axis direction; the velocity data is then time-integrated to obtain the displacement data in the vertical direction, and this displacement data is the vertical amplitude of the body's center of gravity; The running dynamic sensor is used to monitor the time when the left and right feet touch the ground. Its built-in accelerometer will collect the acceleration data of the athlete's two feet in the Z-axis direction in real time when the athlete's feet are running. When the athlete's feet just touch the ground, an obvious acceleration peak will be generated. This is caused by the sudden increase in the impact force between the feet and the ground: this impact force will cause the ground to produce an upward reaction force on the feet, thereby generating an upward acceleration peak on the acceleration sensor; when the athlete's feet just leave the ground, the acceleration signal will first reach a valley value, which is related to the deceleration process before the feet leave the ground: when the runner's feet are about to leave the ground, due to the contraction of the leg muscles and the inertia of the body, the feet will have an upward deceleration process, which will cause a downward acceleration on the acceleration sensor, namely the valley value; the time from the peak value to the valley value of each foot is recorded, which is the time when each foot touches the ground; Record the time of alternating between the two feet, that is, the duration of each step, combine the duration of each step with the length of each step, and calculate the speed of each step based on the speed formula; Step 102: starting from the first step taken by the athlete, the number of times the athlete's left and right feet touch the ground is monitored in real time, that is, the number of times the acceleration signal of each foot changes from a peak value to a valley value; whenever any foot is monitored to complete a touchdown action, that is, when the acceleration signal changes from a peak value to a valley value, that is, each step, the athlete's motion data during this step is recorded, including the heart rate and speed data at the end of this step, the step length data of this step, and the vertical amplitude and contact time data during this step; When the number of times the left and right feet touch the ground is detected to be five times, that is, when the acceleration signal is completed from the peak value to the valley value ten times, that is, every ten steps, the ten sets of motion data recorded are transmitted to the motion data analysis module; that is, the monitoring cycle is the time required for running ten steps; the length of the subsequent monitoring cycle is expressed according to the number of steps, and running ten steps is taken as the standard monitoring cycle length; Step 103: Before the ten sets of recorded motion data are transmitted to the motion data analysis module, the ten sets of motion data are preprocessed, including: outlier detection and missing value processing; wherein, outlier detection is used to check whether there are outliers that obviously deviate from the normal range in data such as heart rate, speed, vertical amplitude and ground contact time. For such outliers, deletion, replacement (such as replacement with the median, mean or the previous valid value) or interpolation can be adopted; due to equipment failure, signal interference or data transmission problems, some data may be missing. At this time, the missing value processing operation can be used to perform linear interpolation, polynomial interpolation or use machine learning model prediction filling according to the trend of the previous and next data; Step 104: Transmit the preprocessed ten sets of motion data to a motion data analysis module.

[0019] When using, combine the contents in steps 101 to 104: By comprehensively using RFID tags, GPS positioning systems, photosensitive sensors, accelerometers and running dynamic sensors, athletes' location information can be tracked in real time, and key sports parameters such as heart rate, stride length, vertical amplitude, ground contact time and speed can be accurately recorded. The accuracy and completeness of the data can be ensured through pre-processing operations. This not only improves the accuracy and efficiency of sports data collection, but also provides a reliable foundation for subsequent sports data analysis.

[0020] The sports data analysis module includes a sports intensity evaluation unit, a monitoring cycle adjustment unit and a fatigue degree evaluation unit; the sports data analysis module is used to analyze the sports intensity of the athletes, adjust the monitoring cycle and detect the fatigue degree according to the analysis results of the sports intensity; Among them, the exercise intensity assessment unit obtains several groups of heart rate data and speed data in the current monitoring period, and combines all the heart rate data and all the speed data in the current monitoring period to obtain the comprehensive heart rate and comprehensive speed in the current monitoring period; determines the exercise intensity type under the comprehensive heart rate and comprehensive speed based on the exercise intensity judgment rule; and comprehensively judges whether to send corresponding signals to the fatigue degree assessment unit and the monitoring period adjustment unit based on the two exercise intensity types; refer to Figure 2 , the exercise intensity assessment unit comprises the following steps: Step 201: Obtain heart rate data and speed data from several groups of exercise data in the current monitoring period, respectively recorded as as well as , Indicates the first group data; and , Indicates the total number of groups of motion data acquired in the current monitoring period; Step 202: Based on the athlete's age , calculate each athlete's maximum heart rate , the expression is: ; Based on maximum heart rate and the athlete's heart rate data, calculate the first exercise intensity in each set of data , the expression is: According to expert research, when the first exercise intensity When the first exercise intensity is and When the first exercise intensity is When , it means that the current exercise intensity of the athlete is vigorous; exercise at low intensity and vigorous intensity is abnormal exercise, and exercise at moderate intensity is normal exercise; Step 203: Based on the VDOT system, the speed data in each set of data is matched to the corresponding level; the VDOT system divides the running intensity into five levels based on the runner's speed, namely, E, M, T, I and R, wherein the R level intensity corresponds to the highest pace level among the five levels, i.e., the highest intensity; based on the speed range of the five levels, the speed data in each set of data is matched to the corresponding level; the speed is set to be lower than the average of the E and M speeds. The exercise intensity is low intensity, making the speed higher than the average of level I and level R speed The exercise intensity of is vigorous intensity, and the exercise intensity between the two averages is moderate intensity. Steps 202 to 203 are to establish exercise intensity judgment rules; Step 204: The heart rate data and speed data in the group data are combined to obtain the comprehensive heart rate in the current monitoring period. And the overall speed , the expression is: ;

[0021] in, represents the weight of each group of data, , because if Group data within the current monitoring period The later the position in the group data is, that is, the closer it is to the present, the more valuable the data is for the analysis of the athlete's sports state and fatigue state at the moment. Step 205: The comprehensive heart rate in the current monitoring period is And the overall speed Combined with the exercise intensity judgment rules in step 202 and step 203, the comprehensive heart rate in the current monitoring period is obtained. And the overall speed The corresponding exercise intensity; If the comprehensive heart rate in the current monitoring period With comprehensive speed If the corresponding exercise intensities are all moderate, it means that in the current monitoring period, the athlete's comprehensive exercise state is normal and there is no need to detect the fatigue level, that is, no fatigue detection signal is sent to the fatigue level assessment unit; if the current monitoring period length is different from the standard monitoring period length, it is necessary to adjust the length of the next monitoring period, and send a first adjustment signal to the monitoring period adjustment unit, otherwise no adjustment signal is sent to the monitoring period adjustment unit; If the comprehensive heart rate in the current monitoring period With comprehensive speed If the corresponding exercise intensities are all low or intense, it means that the athlete's comprehensive exercise state is abnormal during the current monitoring period, and fatigue detection is required. The duration of the next monitoring period also needs to be adjusted, that is, a second adjustment signal is sent to the monitoring period adjustment unit, and a fatigue detection signal is sent to the fatigue evaluation unit; If the comprehensive heart rate in the current monitoring period With comprehensive speed If one of the corresponding exercise intensities is moderate and the other is low or vigorous, it means that the athlete's comprehensive exercise state is unstable during the current monitoring period and further analysis is required, specifically: Assume that the comprehensive heart rate data in the current monitoring period The corresponding exercise intensity is low intensity or vigorous intensity, and the comprehensive speed in the current monitoring period is , and the VDOT system normalizes the speeds corresponding to the five levels of running intensity to obtain the normalized comprehensive speed , the average of E and M speeds in the VDOT system and the average of the I and R speeds ; If the heart rate data The corresponding exercise intensity is low intensity, then the comprehensive heart rate data Deviation from medium intensity for If the comprehensive heart rate data The corresponding exercise intensity is vigorous intensity, then the comprehensive heart rate data Deviation from medium intensity for ; Normalized comprehensive speed data Compensation with medium intensity for: , Indicates taking the minimum value between A and B; Deviation Indicates comprehensive heart rate data For the gap between medium intensity, the compensation Indicates comprehensive speed data For overflow values ​​between medium strength; like , then it means the comprehensive speed data For moderate intensity, the overflow value is enough to make up for the comprehensive heart rate data For the gap between the medium intensities, only the duration of the next monitoring cycle needs to be adjusted, and no fatigue level detection is required. Specifically, a second adjustment signal is sent to the monitoring cycle adjustment unit, and no fatigue detection signal is sent to the fatigue level assessment unit. like , then it means the comprehensive speed data For moderate intensity, the overflow value is not enough to make up for the comprehensive heart rate data For the gap between the medium intensities, it is necessary not only to adjust the duration of the next monitoring cycle, but also to detect the fatigue level, specifically, to send a second adjustment signal to the monitoring cycle adjustment unit, and to send a fatigue detection signal to the fatigue level assessment unit; When using, combine the contents in steps 201 to 205: By comprehensively considering the athlete's heart rate data and speed data, and applying scientific calculation methods and judgment rules, an accurate assessment of exercise intensity is achieved; based on multiple sets of heart rate data and speed data, by calculating the comprehensive heart rate and comprehensive speed, combined with exercise intensity judgment rules, it is accurately judged whether the athlete's current exercise state is normal, abnormal or unstable; based on the evaluation results, fatigue level detection and monitoring cycle adjustment instructions are intelligently triggered, providing basic support for subsequent athlete fatigue monitoring and dynamic adjustment of the monitoring cycle.

[0022] The fatigue level evaluation unit obtains several groups of fatigue evaluation data in the current monitoring period, and combines all fatigue evaluation data obtained in the current monitoring period to obtain a fatigue index of the current monitoring period; based on the relationship between the fatigue index and the fatigue index threshold, it determines whether to send a rest instruction to the athlete; The fatigue level assessment unit comprises the following steps: Step 301: After receiving the fatigue detection signal, obtain fatigue assessment data from several groups of motion data in the current monitoring period, the fatigue assessment data including the step length data in the motion data. , vertical amplitude data And single foot contact time data ; Among them, the shortening of stride length indicates a decrease in muscle strength or a change in movement pattern, which is usually a manifestation of fatigue; the reduction in vertical amplitude may be a weakening of muscle strength and elasticity, which is an important sign of fatigue; the increase in foot contact time indicates a decrease in running efficiency, muscle fatigue or a change in movement pattern, which are all related to fatigue; Step 302: Step length data in group fatigue assessment data , vertical amplitude data Single foot contact time Combined, the fatigue index of the current monitoring period is obtained , the expression is: ;in, Represents step length data , vertical amplitude data Single foot contact time The weight coefficient is determined by the number of abnormal step length, vertical amplitude, and single-foot ground contact time when the historical fatigue detection result is fatigue. , , The comprehensive expressions are: , ; They represent the minimum value of stride length, the minimum value of vertical amplitude and the maximum value of single-foot ground contact time respectively, wherein the minimum value of stride length, the minimum value of vertical amplitude and the maximum value of single-foot ground contact time are obtained according to the athlete's historical normal training running records. Specifically, the minimum value of stride length, the minimum value of vertical amplitude and the maximum value of single-foot ground contact time in each training record are combined and averaged to obtain the corresponding minimum value of stride length, the minimum value of vertical amplitude and the maximum value of single-foot ground contact time; Step 303: Setting fatigue index threshold , the fatigue index of the current monitoring cycle Fatigue index threshold In comparison, if , it means that the athlete is in a fatigue state at the end of the current monitoring period, and a rest instruction is sent to the athlete's sports bracelet. The rest instruction includes voice reminder and vibration reminder; like , it means that the athlete is suspected of fatigue at the end of the current monitoring cycle, and the current monitoring cycle is marked as suspected fatigue. If two consecutive monitoring cycles have been marked as suspected fatigue, a rest instruction is sent to the athlete's sports bracelet; like , it means that the athlete is not in a fatigue state at the end of the current monitoring and no instructions are sent.

[0023] When using, combine the contents in steps 301 to 303: A scientific fatigue assessment model is constructed by comprehensively analyzing key running parameters such as stride length, vertical amplitude and single-foot contact time. By real-time monitoring of athletes' running data, the fatigue index algorithm is used to accurately assess the athletes' fatigue status, and rest instructions are sent in time when fatigue is detected, effectively preventing sports injuries and overtraining. Through the setting of suspected fatigue marks, the system can also warn of athletes' fatigue trends, providing coaches and athletes with more accurate training feedback and adjustment suggestions.

[0024] A monitoring period adjustment unit, which adjusts the length of the monitoring period accordingly based on the received first adjustment signal or the second adjustment signal; When the first adjustment signal is received, the monitoring period length of the next period is adjusted to the standard period length, that is, the time for running ten steps; When the second adjustment signal is received, the monitoring period length of the next cycle is adjusted to half of the monitoring period length of the current cycle, specifically in the order of ten steps, five steps, and two steps. If the monitoring period length of the current cycle is the time for running two steps, then even if the second adjustment signal is received again, the monitoring period length of the next cycle is also adjusted to the time for running two steps. When the first and second adjustment signals are not received, the monitoring period length of the next period is assumed to be equal to the monitoring period length of the current period; The specific duration of the above monitoring cycle changes dynamically according to the athlete's exercise conditions. Specifically, the exercise intensity is monitored every time ten steps, five steps or two steps are detected.

[0025] By dynamically adjusting the length of the monitoring cycle, flexible monitoring of the athlete's exercise status is achieved; according to the received adjustment signal, the monitoring cycle is intelligently changed, which can not only maintain the standard monitoring cycle when the athlete's exercise status is stable, but also shorten the monitoring cycle in time when the exercise status is abnormal or unstable, so as to evaluate the athlete's fatigue level and exercise intensity more frequently.

[0026] refer to Figure 3 The present invention also provides a real-time motion data integration monitoring method, comprising: Step 1: Based on the sensor group, the real-time position and motion data of the athlete are monitored and analyzed in real time. Whenever the athlete takes a step, a set of motion data of the step is acquired and recorded in real time; Step 2: Obtain several groups of heart rate data and speed data in the current monitoring period, and combine all the heart rate data and all the speed data in the current monitoring period to obtain the comprehensive heart rate and comprehensive speed in the current monitoring period; determine the exercise intensity type under the comprehensive heart rate and comprehensive speed based on the exercise intensity judgment rule; and comprehensively judge whether to send a fatigue detection signal and a monitoring period adjustment signal based on the two exercise intensity types; Step 3: when a fatigue detection signal is received, several groups of fatigue assessment data in the current monitoring period are obtained, and all fatigue assessment data obtained in the current monitoring period are combined to obtain a fatigue index of the current monitoring period; based on the relationship between the fatigue index and the fatigue index threshold, it is determined whether to send a rest instruction to the athlete; Step 4: When a monitoring period adjustment signal is received, the monitoring period length is adjusted accordingly based on the received signal type.

[0027] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer storage medium or transmitted via a computer storage medium.

[0028] Computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer storage media can be any available media that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid state drives (SSDs)).

[0029] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A real-time motion data integration monitoring system, characterized in that: include: The data acquisition module monitors and analyzes the real-time position and motion data of the athlete based on the sensor group. Whenever the athlete takes a step, a set of motion data of the step is acquired and recorded in real time. At the end of the monitoring period, the multiple sets of motion data recorded in the monitoring period are pre-processed and transmitted to the motion data analysis module. Sports data analysis module, including sports intensity assessment unit, monitoring cycle adjustment unit and fatigue degree assessment unit; The sports data analysis module is used to analyze the sports intensity of athletes, adjust the monitoring cycle and detect the fatigue level according to the analysis results of the sports intensity; Among them, the exercise intensity assessment unit obtains several groups of heart rate data and speed data in the current monitoring period, and combines all the heart rate data and all the speed data in the current monitoring period to obtain the comprehensive heart rate and comprehensive speed in the current monitoring period; determines the exercise intensity type under the comprehensive heart rate and comprehensive speed based on the exercise intensity judgment rule; and comprehensively judges whether to send corresponding signals to the fatigue degree assessment unit and the monitoring period adjustment unit based on the two exercise intensity types; The fatigue level evaluation unit obtains several groups of fatigue evaluation data in the current monitoring period, and combines all fatigue evaluation data obtained in the current monitoring period to obtain a fatigue index of the current monitoring period; based on the relationship between the fatigue index and the fatigue index threshold, it determines whether to send a rest instruction to the athlete; The monitoring period adjustment unit adjusts the monitoring period length accordingly based on the received signal type.

2. A real-time motion data integration monitoring system as claimed in claim 1, characterized in that: Add RFID tags to athletes and have them wear sports bracelets on the sports field. The sports bracelets have built-in GPS positioning systems, photosensitive sensors, and acceleration sensors; and install running dynamic sensors on the left and right running shoes of athletes respectively. The photosensitive sensor is used to monitor the athlete's heart rate, the acceleration sensor is used to monitor the athlete's stride length and vertical amplitude when running, and the running dynamic sensor is used to monitor the time when the left and right feet touch the ground; combined with the time of alternation between the two feet in each step and the stride length of each step, the speed of each step is obtained.

3. A real-time motion data integration monitoring system as claimed in claim 2, characterized in that: From the moment the athlete takes the first step, the number of times the athlete's left and right feet touch the ground is monitored in real time; every time any foot touches the ground, that is, every step, the athlete's motion data during this step is recorded, including the heart rate and speed data at the end of this step, the step length data of this step, and the vertical amplitude and contact time data during this step; When the number of times the left and right feet touch the ground is monitored to be five times each, that is, every ten steps, the ten sets of motion data recorded will be transmitted to the motion data analysis module; the monitoring cycle at this time is the time required for each ten steps, and the length of subsequent monitoring cycles is expressed according to the number of steps, and running ten steps is used as the standard monitoring cycle length.

4. A real-time motion data integration monitoring system as claimed in claim 3, characterized in that: Get the heart rate data and speed data from several groups of exercise data in the current monitoring period, recorded as as well as , Indicates the first Group data; The current monitoring period The heart rate data and speed data in the group data are combined to obtain the comprehensive heart rate in the current monitoring period. And the overall speed , the expression is: ;in, represents the weight of each group of data, .

5. A real-time motion data integration monitoring system as claimed in claim 4, characterized in that: The exercise intensity judgment rules include: Based on the athlete's age , calculate each athlete's maximum heart rate , the expression is: ; Based on maximum heart rate and the athlete's heart rate data, calculate the first exercise intensity in each set of data , the expression is: ; When the first exercise intensity When the first exercise intensity is and When the first exercise intensity is When , it means the current athlete's exercise intensity is vigorous; Based on the VDOT system, the speed data in each set of data is matched to the corresponding level; the VDOT system divides the intensity of running into five levels, namely, E, M, T, I and R, with the intensity increasing from left to right; based on the five-level speed range, the speed data in each set of data is matched to the corresponding level; the speed is lower than the average of the speeds of E and M The exercise intensity is low intensity, making the speed higher than the average of level I and level R speed The exercise intensity that makes the speed between the above two average values ​​is vigorous intensity, and the exercise intensity that makes the speed between the above two average values ​​is moderate intensity.

6. A real-time motion data integration monitoring system as claimed in claim 5, characterized in that: If the comprehensive heart rate in the current monitoring period With comprehensive speed If the corresponding exercise intensities are all moderate, no fatigue detection signal is sent to the fatigue degree assessment unit; if the current monitoring cycle length is different from the standard monitoring cycle length, a first adjustment signal is sent to the monitoring cycle adjustment unit, otherwise no adjustment signal is sent to the monitoring cycle adjustment unit; If the comprehensive heart rate in the current monitoring period With comprehensive speed If the corresponding exercise intensities are all low or intense, a second adjustment signal is sent to the monitoring period adjustment unit, and a fatigue detection signal is sent to the fatigue level assessment unit; If the comprehensive heart rate in the current monitoring period With comprehensive speed If one of the corresponding exercise intensities is moderate and the other is low or vigorous, further analysis is required.

7. A real-time motion data integration monitoring system as claimed in claim 6, characterized in that: The further analysis is as follows: Assume that the comprehensive heart rate data in the current monitoring period The corresponding exercise intensity is low intensity or vigorous intensity, and the comprehensive speed in the current monitoring period is , and the VDOT system normalizes the speeds corresponding to the five levels of running intensity to obtain the normalized comprehensive speed , the average of E and M speeds in the VDOT system and the average of the I and R speeds ; If the heart rate data The corresponding exercise intensity is low intensity, then the comprehensive heart rate data Deviation from medium intensity for If the comprehensive heart rate data The corresponding exercise intensity is vigorous intensity, then the comprehensive heart rate data Deviation from medium intensity for ; Normalized comprehensive speed data Compensation with medium intensity for: , It means taking the minimum value between A and B; like , a second adjustment signal is sent to the monitoring period adjustment unit, and no fatigue detection signal is sent to the fatigue degree evaluation unit; like , a second adjustment signal is sent to the monitoring period adjustment unit, and a fatigue detection signal is sent to the fatigue degree evaluation unit.

8. A real-time motion data integration monitoring system as claimed in claim 7, characterized in that: When the fatigue detection signal is received, the fatigue assessment data in several groups of motion data in the current monitoring period is obtained, and the fatigue assessment data includes the step length data in each group of motion data , vertical amplitude data And single foot contact time data ; The current monitoring period Step length data in group fatigue assessment data , vertical amplitude data Single foot contact time Combined, the fatigue index of the current monitoring period is obtained. , the expression is: ;in, Represents step length data , vertical amplitude data Single foot contact time The weight coefficient of They represent the minimum step length, the minimum vertical amplitude, and the maximum single-foot contact time respectively; Setting the fatigue index threshold , the fatigue index of the current monitoring cycle Fatigue index threshold In comparison, if , a rest instruction is sent to the athlete's sports bracelet, and the rest instruction includes a voice reminder and a vibration reminder; like , the current monitoring period is marked as suspected fatigue. If two consecutive monitoring periods have been marked as suspected fatigue, a rest instruction is sent to the athlete's sports bracelet; like , no command is sent.

9. A real-time motion data integration monitoring system as claimed in claim 8, characterized in that: When the first adjustment signal is received, adjusting the monitoring period length of the next period to the standard period length; When the second adjustment signal is received, the monitoring period length of the next period is adjusted to half of the monitoring period length of the current period, specifically in the order of ten steps, five steps, and two steps; When the first and second adjustment signals are not received, the monitoring period length of the next period is assumed to be equal to the monitoring period length of the current period.

10. A real-time motion data integration monitoring method, characterized in that: include: Step 1: Based on the sensor group, the real-time position and motion data of the athlete are monitored and analyzed in real time. Whenever the athlete takes a step, a set of motion data of the step is obtained and recorded in real time; Step 2: Obtain several groups of heart rate data and speed data in the current monitoring period, and combine all the heart rate data and all the speed data in the current monitoring period to obtain the comprehensive heart rate and comprehensive speed in the current monitoring period; Determine the exercise intensity type under the comprehensive heart rate and comprehensive speed based on the exercise intensity judgment rules; Combining the two exercise intensity types, comprehensively judging whether to send a fatigue detection signal and a monitoring cycle adjustment signal; Step 3: when a fatigue detection signal is received, several groups of fatigue assessment data in the current monitoring period are obtained, and all fatigue assessment data obtained in the current monitoring period are combined to obtain a fatigue index of the current monitoring period; based on the relationship between the fatigue index and the fatigue index threshold, it is determined whether to send a rest instruction to the athlete; Step 4: When a monitoring period adjustment signal is received, the monitoring period length is adjusted accordingly based on the received signal type.

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