Competitive sports activity digital management method and device for colleges and universities and storage medium

Abstract

The invention relates to the technical field of data processing, in particular to a college competitive sports activity digital management method and device and a storage medium, and the method comprises the steps: collecting target motion data and physiological data; a target physical fitness index is determined according to the target blood oxygen saturation degree of the monitoring period, and the training intensity of the next monitoring period is determined; judging the target action normalization based on the target stride frequency and the target landing vertical impact force, and adjusting the determination process of the target training intensity according to the judgment result of the target action normalization in the monitoring period; collecting sEMG signal peak timestamps of target rectus abdominis and rectus femoris in a pedaling and stretching period to determine a target dynamic kinematic chain synchronization index of a current time window, and judging a target dynamic kinematic chain synchronization state; and sending a core-lower limb coordination training suggestion to the target. The training efficiency of college athletes is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, device and storage medium for digital management of competitive sports activities in universities. Background Technology

[0002] Existing competitive sports training management programs, both domestically and internationally, largely focus on single-dimensional data collection and analysis, such as monitoring physiological load based on heart rate variability or assessing movement amplitude using inertial sensors. While these methods can quantify local parameters, they generally suffer from three limitations: First, the dynamic fluctuations in blood oxygen saturation are not fully explored, making it difficult to accurately map changes in oxygen supply metabolism during high-intensity interval training; second, the synergistic analysis of asymmetric bipedal impact force and discrete stride frequency is lacking, making it difficult to identify key movement pattern defects in a timely manner; and third, the biomechanical relationship between neuromuscular activation timing and core stability has not yet been established, limiting the potential for improving kinetic chain coordination efficiency.

[0003] Furthermore, existing systems often employ separate monitoring modules and decision-making units, resulting in significant data silos and hindering the formation of closed-loop control capabilities. This embodiment innovatively solves these bottleneck problems through cross-layer data fusion and a threshold-driven adaptive algorithm. Summary of the Invention

[0004] The purpose of this invention is to provide a digital management method, device, and storage medium for competitive sports activities in universities, so as to solve at least one of the problems existing in the prior art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A digital management method for competitive sports activities in universities includes: The target physical fitness index is determined based on the target blood oxygen saturation during the monitoring period, and the training intensity for the next monitoring period is determined accordingly. The process of determining the standardization of target movements based on target step frequency and target vertical impact force upon landing, and adjusting the target training intensity based on the results of the standardization of target movements within the monitoring period; The peak timestamps of sEMG signals of the target rectus abdominis and rectus femoris muscles during the push-off cycle are collected to determine the target dynamic kinetic chain synchronization index in the current time window and to judge the target dynamic kinetic chain synchronization status. Based on the target's physical fitness index, the target's movement standardization, and the synchronization status of the target's dynamic kinetic chain in each time window during the monitoring period, core-lower limb coordination training suggestions are sent to the target.

[0006] Optionally, the maximum value of the target blood oxygen concentration in the current time window is extracted as a1, the minimum value of the target blood oxygen concentration in the current time window is extracted as a2, and the target state parameter is set as Z, with Z=1-(a1-a2) / △a; The average value of the target state parameters for each time window within the statistical monitoring period is Zp, and the standard deviation of the target state parameters for each time window within the statistical monitoring period is Zb. The average value and standard deviation of the target state parameters are fused to determine the target physical fitness index for the current monitoring period.

[0007] Optionally, the training intensity for the next monitoring period is determined based on the target physical fitness index of the current monitoring period. When T is less than or equal to the physical fitness threshold T0, the training intensity for the next monitoring period is set to Q1, where Q1 = Qb × [1 - α × (T0 - T)], α is the adjustment factor, and Qb is the baseline training volume.

[0008] Optionally, the peak value of the vertical impact force of the target's left foot landing in the current time window is extracted as F1, and the peak value of the vertical impact force of the target's right foot landing in the current time window is extracted as F2. An impact force symmetry index Fs is constructed based on F1 and F2, and Fs is set as 1-|F1-F2| / (F1+F2). The average value of the target step frequency in the current time window is Sp, the standard deviation of the target step frequency in the current time window is Sa, and a step frequency stability index B is constructed based on Sp and Sa, with B = 1 - Sa / Sp. When the impact force symmetry index Fs is less than the impact force symmetry threshold F0 or the step frequency stability index B is less than the stability threshold B0, the target action in the current time window is determined to be non-standard and a correction prompt is triggered. Conversely, the target action in the current time window is determined to be standard and no correction prompt is triggered.

[0009] Optionally, the number of time windows in which the target action is non-standard within the statistical monitoring period is M1, the number of time windows in the statistical monitoring period is M0, and the proportion of non-standard actions is set as YG, with YG=M1 / M0. The abnormality rate YG is compared with the abnormality rate threshold Y0. If YG is greater than or equal to Y0, the target action in the current monitoring period is determined to be non-standard, and the adjustment factor is adjusted to α1 to adjust the determination process of the target training intensity in the next monitoring period. Otherwise, the target action in the current monitoring period is determined to be standard, and the determination process of the target training intensity in the next monitoring period is not adjusted.

[0010] Optionally, the peak timestamp of the sEMG signal of the target rectus abdominis muscle during the push-up cycle is extracted as t1, and the peak timestamp of the sEMG signal of the target rectus femoris muscle during the push-up cycle is extracted as t2. The absolute value of the difference between t1 and t2 is used as the activation time difference of the target in the push-up cycle. The average value of the activation time difference of the target in each push-up cycle in the current time window is calculated as tj, and it is used as the synchronization index of the target dynamic kinetic chain in the current time window. When tj is less than or equal to the time difference threshold t0, the synchronization state of the target dynamic motion chain in the current time window is determined to be normal; otherwise, the synchronization state of the target dynamic motion chain in the current time window is determined to be abnormal.

[0011] Optionally, the number of time windows in which the target dynamic motion chain synchronization status is abnormal within the current monitoring period is counted as U1. When the ratio of U1 to M0 is less than or equal to the proportional coefficient k1, the target dynamic motion chain synchronization status within the current monitoring period is determined to be normal; otherwise, the target dynamic motion chain synchronization status within the current monitoring period is determined to be abnormal.

[0012] Optionally, if the target physical fitness index is greater than the physical fitness threshold T0, the target movement is standardized, and the target dynamic kinetic chain synchronization is abnormal during the current monitoring period, core-lower limb coordination training suggestions are sent to the user; otherwise, core-lower limb coordination training suggestions are not sent to the user.

[0013] According to another aspect of this application, a digital management device for competitive sports activities in universities is provided, comprising: The data acquisition unit is used to collect target motion data and physiological data; The physical fitness determination unit is used to determine the target physical fitness index based on the target blood oxygen saturation in the monitoring period, and to determine the training intensity for the next monitoring period. The standardization unit is used to determine the standardization of the target's movements based on the target's step frequency and the vertical impact force of the target's landing, and to adjust the target's training intensity based on the determination results of the standardization of the target's movements within the monitoring period. The synchronization determination unit is used to collect the peak timestamps of the sEMG signals of the target rectus abdominis and rectus femoris muscles during the push-off cycle, in order to determine the synchronization index of the target dynamic kinetic chain in the current time window and to judge the synchronization status of the target dynamic kinetic chain. The training suggestion unit is used to send core-lower limb coordination training suggestions to the target based on the target's physical fitness index, the target's movement standardization, and the synchronization status of the target's dynamic kinetic chain in each time window within the monitoring period.

[0014] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, wherein the computer program is used to control the electronic device on which the computer-readable storage medium is located to execute the digital management method for competitive sports activities in colleges and universities during runtime.

[0015] The beneficial effects of this invention are as follows: Through the efficient fusion and closed-loop control mechanism of multi-dimensional heterogeneous data, the accuracy and safety of competitive sports training are significantly improved. The dynamic correlation model between blood oxygen saturation and physical fitness index enables real-time physiological load monitoring and on-demand adaptation to anti-fatigue training, avoiding sports injuries caused by overtraining. The movement standardization analysis module, based on the quantitative assessment of bipedal impact force symmetry and gait frequency stability, instantly identifies deviations in technical movements and triggers corrective commands, accelerating movement pattern optimization. The dynamic kinetic chain synchronization index accurately captures the collaborative activation defects of core and lower limb muscles, providing targeted guidance for neuromuscular control training. Finally, personalized training suggestions are generated through the joint discrimination of physical fitness, movement technique, and electromyographic synergy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the digital management method for competitive sports activities in universities in this embodiment.

[0018] Figure 2 This is a flowchart illustrating the method for analyzing the standardization of target actions in this embodiment.

[0019] Figure 3 This is a flowchart illustrating the training suggestion analysis method in this embodiment.

[0020] Figure 4 This is a schematic diagram of the structure of the digital management device for competitive sports activities in colleges and universities in this embodiment. Detailed Implementation

[0021] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments and accompanying drawings, further explains the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0023] Specifically, this embodiment is applied to the management of daily training data of college sprinters. Through multi-source data fusion and closed-loop control algorithms, it upgrades traditional experience-driven training to an intelligent management mode of "state perception - quantitative diagnosis - precise control".

[0024] Please see Figure 1 As shown, it is a flowchart illustrating the digital management method for competitive sports activities in universities according to this embodiment, including: Step S101: Collect target motion data and physiological data. The target motion data includes target cadence and target vertical impact force upon landing. The target vertical impact force includes the target left foot landing vertical impact force and the target right foot landing vertical impact force. The physiological data is the target blood oxygen saturation. The target is a college athlete. The left foot landing vertical impact force is the instantaneous peak value of the vertical ground reaction force acting on the left foot from the moment the left heel touches the ground to the moment the toes leave the ground. The right foot landing vertical impact force is the instantaneous peak value of the vertical ground reaction force acting on the right foot from the moment the right heel touches the ground to the moment the toes leave the ground.

[0025] For example, in this embodiment, a pre-set electronic fence (such as a rectangular area from the starting line to the finish line) can be used in the training field. When the GPS coordinates enter the fence, data collection is initiated. A set of training for the target is a time window. For example, a 50-meter sprinter runs a set of 50-meter races as a training set. The target's stride frequency is collected through the foot pressure pad, the target's vertical impact force upon landing is collected through the triaxial force sensor integrated into the midsole of the running shoe, and the target's blood oxygen saturation is collected through the wrist-type photoelectric pulse oximeter. This embodiment does not specifically limit the data collection method. Those skilled in the art can freely set it according to their needs.

[0026] Please continue reading. Figure 1 As shown, the digital management method for competitive sports activities in universities also includes: Step S102: Determine the target physical fitness index based on the target blood oxygen saturation of the monitoring period, and determine the training intensity for the next monitoring period.

[0027] Specifically, extract the maximum value of the target blood oxygen concentration in the current time window as a1, extract the minimum value of the target blood oxygen concentration in the current time window as a2, and set the target state parameter as Z, setting Z=1-(a1-a2) / △a; The average value of the target state parameters for each time window within the statistical monitoring period is Zp, and the standard deviation of the target state parameters for each time window within the statistical monitoring period is Zb. The average value and standard deviation of the target state parameters are fused to determine the target physical fitness index for the current monitoring period. The expression for the target physical fitness index is: T=w1×Zp / Z0-w2×Zb / (Zp×b0); In the formula, △a is the blood oxygen fluctuation threshold, w1 is the first weighting factor, w2 is the second weighting factor, Z0 is the state parameter threshold, b0 is the fluctuation threshold, and w1+w2=1. The training intensity for the next monitoring period is determined based on the target physical fitness index of the current monitoring period. When T is less than or equal to the physical fitness threshold T0, the training intensity for the next monitoring period is set to Q1. Q1 is set as Qb×[1-α×(T0-T)], where α is the adjustment factor and Qb is the baseline training volume. When T is less than 0, the value of T is 0.

[0028] For example, in this embodiment, the first weighting factor can be set to 0.8, the second weighting factor can be set to 0.2, the state parameter threshold can be set to 1.2, the fluctuation threshold can be set to 0.3, the blood oxygen fluctuation threshold can be set to 0.15, the physical fitness threshold can be set to 0.7, and the adjustment factor can be set to 0.3. This embodiment does not specifically limit the above settings, and those skilled in the art can set them freely according to their needs.

[0029] Specifically, by dynamically assessing the fluctuation trend of blood oxygen concentration, the system reflects the athlete's real-time physiological load status, overcoming the lag of traditional physical fitness monitoring; by integrating a two-factor model of mean and standard deviation, it takes into account both physiological stability and sudden fluctuations, establishing a more accurate fatigue risk early warning mechanism; and by dynamically adjusting the training load according to the physical fitness index, it achieves an automatic balance between anti-fatigue training and supercompensation, avoiding sports injuries caused by overtraining.

[0030] Please continue reading. Figure 1 As shown, the digital management method for competitive sports activities in universities also includes: Step S103 is the process of determining the standardization of the target's movements based on the target's step frequency and the vertical impact force of the target's landing, and adjusting the target's training intensity based on the determination results of the standardization of the target's movements within the monitoring period.

[0031] Specifically, based on quantitative analysis of stride frequency stability and bipedal impact symmetry, athletes' gait imbalances or abnormal force patterns are objectively identified; the results of the movement standardization judgment are fed back into the training plan to intervene in time before technical defects become entrenched, thus shortening the movement learning cycle; the coupling mechanism between the proportion of abnormalities and the adjustment of training intensity takes into account both short-term correction prompts and long-term load adaptation.

[0032] Please see Figure 2 As shown, the method for analyzing the standardization of the target action includes: Step S201: Determine the standardization of the target's movement based on the target's step frequency and the vertical impact force of the target landing in the current time window.

[0033] Specifically, the peak value of the vertical impact force of the target's left foot landing in the current time window is extracted as F1, and the peak value of the vertical impact force of the target's right foot landing in the current time window is extracted as F2. Based on F1 and F2, an impact force symmetry index Fs is constructed, and Fs is set as 1-|F1-F2| / (F1+F2). The average value of the target step frequency in the current time window is Sp, the standard deviation of the target step frequency in the current time window is Sa, and a step frequency stability index B is constructed based on Sp and Sa, with B = 1 - Sa / Sp. When the impact force symmetry index Fs is less than the impact force symmetry threshold F0 or the step frequency stability index B is less than the stability threshold B0, the target action in the current time window is determined to be non-standard and a correction prompt is triggered. Conversely, the target action in the current time window is determined to be standard and no correction prompt is triggered.

[0034] Specifically, it captures the difference in force exertion between the two feet and the fluctuation in cadence within a single step cycle, and identifies potential risks of declining running economy in real time; it improves the agility of capturing erroneous movements by judging thresholds for key parameters; and it is decoupled from the training intensity adjustment process to ensure that high-risk movements can trigger immediate alerts without affecting the overall plan execution.

[0035] Please continue reading. Figure 2 As shown, the method for analyzing the standardization of target actions also includes: Step S202: The process of determining the training intensity of the target for the next monitoring period based on the judgment results of the standardization of the target actions in each time window within the monitoring period.

[0036] Specifically, the number of time windows in which the target action is non-standard within the statistical monitoring period is M1, the number of time windows in the statistical monitoring period is M0, and the proportion of non-standard actions is set as YG, with YG=M1 / M0. The abnormality rate YG is compared with the abnormality rate threshold Y0. When YG is greater than or equal to Y0, the target action in the current monitoring period is determined to be non-standard, and the adjustment factor is adjusted to α1. α1 is set as α-0.1×ln[6×(YG-Y0)+1] / ln7 to adjust the determination process of the target training intensity in the next monitoring period. Conversely, if YG is not greater than or equal to Y0, the target action in the current monitoring period is determined to be standard, and the determination process of the target training intensity in the next monitoring period is not adjusted.

[0037] For example, in this embodiment, the impact force symmetry threshold can be set to 0.9, the step frequency stability threshold can be set to 0.95, and the abnormal proportion threshold can be set to 0.2. This embodiment does not specifically limit the above settings, and those skilled in the art can set them freely according to their needs.

[0038] Specifically, a macro-analysis perspective based on the proportion of time windows is introduced to distinguish between occasional errors and systemic technical defects; the training load coefficient is adjusted by a logarithmic decay function to balance the demand for high-intensity training and the recovery period.

[0039] Please continue reading. Figure 1 As shown, the digital management method for competitive sports activities in universities also includes: Step S104: Collect the peak timestamps of the sEMG signals of the target rectus abdominis and rectus femoris muscles during the push-off cycle to determine the target dynamic kinetic chain synchronization index in the current time window and to judge the target dynamic kinetic chain synchronization status. The push-off cycle is the duration from the heel of one side of the target foot touching the ground to the toe of the other side leaving the ground. The peak value of the rectus abdominis sEMG signal is the moment corresponding to the maximum instantaneous amplitude of the full-wave rectified signal after the electromyographic signal on the surface of the rectus abdominis muscle is filtered by a 20-500Hz bandpass filter during the push-off cycle. The peak value of the rectus femoris sEMG signal is the moment corresponding to the maximum amplitude of the rectified electromyographic signal on the surface of the rectus femoris muscle after the same filtering process during the push-off cycle.

[0040] For example, in this embodiment, a dual-channel wireless sEMG sensor can be attached to the rectus femoris muscle belly of the left and right legs respectively to collect the peak timestamps of the sEMG signals of the target rectus abdominis and rectus femoris muscles during the push-off cycle. In this embodiment, no specific limitation is made on the data acquisition method, and those skilled in the art can set it freely according to their needs.

[0041] Specifically, the peak timestamp of the sEMG signal of the target rectus abdominis muscle during the push-up cycle is extracted as t1, and the peak timestamp of the sEMG signal of the target rectus femoris muscle during the push-up cycle is extracted as t2. The absolute value of the difference between t1 and t2 is used as the activation time difference of the target in the push-up cycle. The average value of the activation time difference of the target in each push-up cycle in the current time window is calculated as tj, and it is used as the synchronization index of the dynamic kinetic chain of the target in the current time window. When tj is less than or equal to the time difference threshold t0, the synchronization state of the target dynamic motion chain in the current time window is determined to be normal; otherwise, the synchronization state of the target dynamic motion chain in the current time window is determined to be abnormal.

[0042] For example, in this embodiment, the timing difference threshold can be set to 50ms. This embodiment does not specifically limit the above setting, and those skilled in the art can set it freely according to their needs.

[0043] Specifically, by detecting the activation sequence synchronization of core muscle groups and lower limb muscle groups, we can reveal the deep-seated problems of neuromuscular coordination in the kinetic chain; by using an evaluation strategy based on the average value of a time window rather than a single movement, we can improve the stability of results and reduce the risk of misjudgment due to occasional errors; and by integrating quantitative indicators of muscle synergy into the training system, we can provide data support for the coordinated development of core stability and explosive power.

[0044] Please continue reading. Figure 1 As shown, the digital management method for competitive sports activities in universities also includes: Step S105: Based on the target's physical fitness index, the target's movement standardization, and the synchronization status of the target's dynamic kinetic chain in each time window during the monitoring period, core-lower limb coordination training suggestions are sent to the target.

[0045] Specifically, by integrating three factors—physiological state, movement technique, and neuromuscular synergy—global optimization suggestions are generated, overcoming the limitations of traditional single-dimensional analysis; and by clearly defining the triggering logic to generate coordinated training instructions, ineffective suggestions are avoided from interfering with the training rhythm.

[0046] Please see Figure 3 As shown, the training suggestion analysis method includes: Step S301: Determine the target dynamic motion chain synchronization status within the current monitoring period based on the target dynamic motion chain synchronization status of each time window in the current monitoring period.

[0047] Specifically, the number of time windows in which the target's dynamic motion chain synchronization status is abnormal within the current monitoring period is counted as U1. When the ratio of U1 to M0 is less than or equal to the proportional coefficient k1, the target's dynamic motion chain synchronization status within the current monitoring period is determined to be normal; otherwise, it is determined to be abnormal.

[0048] For example, in this embodiment, the scaling factor can be set to 0.15. This embodiment does not specifically limit the above setting, and those skilled in the art can set it freely according to their needs.

[0049] Specifically, by combining the proportion of abnormal windows within the cycle, short-term fatigue fluctuations and long-term neural control defects can be distinguished; the threshold determination strategy adapts to the needs of different projects, links with physical fitness and movement data, and accurately locates the physiological or neural transmission root cause of technical problems.

[0050] Please continue reading. Figure 1 As shown, the training suggestion analysis method further includes: Step S302: Based on the target physical fitness index, target movement standardization, and target dynamic kinetic chain synchronization status of the current monitoring period, core-lower limb coordination training suggestions are sent to the user.

[0051] Specifically, if the target physical fitness index is greater than the physical fitness threshold T0, the target movement is standardized, and the target dynamic kinetic chain synchronization is abnormal during the current monitoring period, core-lower limb coordination training suggestions will be sent to the user; otherwise, core-lower limb coordination training suggestions will not be sent to the user.

[0052] For example, in this embodiment, the monitoring period can be set to 24 hours. This embodiment does not specifically limit the setting of the monitoring period, and those skilled in the art can set it freely according to their needs.

[0053] Specifically, based on the joint judgment criteria of three states (physical fitness, technique, and coordination), it ensures that the recommendations are only triggered when "intervention is needed and appropriate"; at the same time, it avoids overloading training recommendations and focuses on the targeted improvement of the higher-order ability of core-lower limb coordination; and promotes athletes to break through plateaus through specialized coordination training and achieve non-linear ability leaps.

[0054] Please see Figure 4 As shown, the digital management device for competitive sports activities in universities includes: The data acquisition unit is used to collect target motion data and physiological data; The physical fitness determination unit is used to determine the target physical fitness index based on the target blood oxygen saturation in the monitoring period, and to determine the training intensity for the next monitoring period. The standardization unit is used to determine the standardization of the target's movements based on the target's step frequency and the vertical impact force of the target's landing, and to adjust the target's training intensity based on the determination results of the standardization of the target's movements within the monitoring period. The synchronization determination unit is used to collect the peak timestamps of the sEMG signals of the target rectus abdominis and rectus femoris muscles during the push-off cycle, in order to determine the synchronization index of the target dynamic kinetic chain in the current time window and to judge the synchronization status of the target dynamic kinetic chain. The training suggestion unit is used to send core-lower limb coordination training suggestions to the target based on the target's physical fitness index, the target's movement standardization, and the synchronization status of the target's dynamic kinetic chain in each time window within the monitoring period.

[0055] The digital management device for competitive sports activities in colleges and universities provided in this application embodiment can execute the digital management method for competitive sports activities in colleges and universities provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the execution method.

[0056] This application also provides a computer-readable storage medium, which is a tangible physical storage medium that can store the aforementioned computer program and various types of data used in the program; the physical storage medium includes, but is not limited to, existing physical storage media or combinations thereof, such as random access memory, read-only memory, optical disk, and hard disk.

[0057] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable programs, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable programs, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0058] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description. It is impossible to exhaustively list all the implementation methods here. All obvious variations or modifications derived from the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. A digital management method for competitive sports activities in universities, characterized in that, include: The target physical fitness index is determined based on the target blood oxygen saturation during the monitoring period, and the training intensity for the next monitoring period is determined accordingly. The process of determining the standardization of target movements based on target step frequency and target vertical impact force upon landing, and adjusting the target training intensity based on the results of the standardization of target movements within the monitoring period; The peak timestamps of sEMG signals of the target rectus abdominis and rectus femoris muscles during the push-off cycle are collected to determine the target dynamic kinetic chain synchronization index in the current time window and to judge the target dynamic kinetic chain synchronization status. Based on the target's physical fitness index, the target's movement standardization, and the synchronization status of the target's dynamic kinetic chain in each time window during the monitoring period, core-lower limb coordination training suggestions are sent to the target.

2. The digital management method for competitive sports activities in universities according to claim 1, characterized in that, Extract the maximum value of the target blood oxygen concentration in the current time window as a1, extract the minimum value of the target blood oxygen concentration in the current time window as a2, and set the target state parameter as Z, setting Z=1-(a1-a2) / △a; The average value of the target state parameters for each time window within the statistical monitoring period is Zp, and the standard deviation of the target state parameters for each time window within the statistical monitoring period is Zb. The average value and standard deviation of the target state parameters are fused to determine the target physical fitness index for the current monitoring period.

3. The digital management method for competitive sports activities in universities according to claim 2, characterized in that, The training intensity for the next monitoring period is determined based on the target physical fitness index of the current monitoring period. When T is less than or equal to the physical fitness threshold T0, the training intensity for the next monitoring period is set to Q1, where Q1 = Qb × [1 - α × (T0 - T)], α is the adjustment factor, and Qb is the baseline training volume.

4. The digital management method for competitive sports activities in universities according to claim 3, characterized in that, Extract the peak vertical impact force of the target's left foot landing in the current time window as F1, and extract the peak vertical impact force of the target's right foot landing in the current time window as F2. Construct the impact force symmetry index Fs based on F1 and F2, and set Fs = 1 - |F1 - F2| / (F1 + F2); The average value of the target step frequency in the current time window is Sp, the standard deviation of the target step frequency in the current time window is Sa, and a step frequency stability index B is constructed based on Sp and Sa, with B = 1 - Sa / Sp. When the impact force symmetry index Fs is less than the impact force symmetry threshold F0 or the step frequency stability index B is less than the stability threshold B0, the target action in the current time window is determined to be non-standard and a correction prompt is triggered. Conversely, the target action in the current time window is determined to be standard and no correction prompt is triggered.

5. The digital management method for competitive sports activities in universities according to claim 4, characterized in that, The number of time windows in which the target action is non-standard within the statistical monitoring period is M1, the number of time windows in the statistical monitoring period is M0, and the proportion of non-standard actions is set as YG, with YG=M1 / M0. The abnormality rate YG is compared with the abnormality rate threshold Y0. If YG is greater than or equal to Y0, the target action in the current monitoring period is determined to be non-standard, and the adjustment factor is adjusted to α1 to adjust the determination process of the target training intensity in the next monitoring period. Otherwise, the target action in the current monitoring period is determined to be standard, and the determination process of the target training intensity in the next monitoring period is not adjusted.

6. The digital management method for competitive sports activities in universities according to claim 5, characterized in that, The peak timestamp of the sEMG signal of the target rectus abdominis muscle during the push-up cycle is extracted as t1, and the peak timestamp of the sEMG signal of the target rectus femoris muscle during the push-up cycle is extracted as t2. The absolute value of the difference between t1 and t2 is used as the activation time difference of the target in the push-up cycle. The average value of the activation time difference of the target in each push-up cycle in the current time window is calculated as tj, and it is used as the synchronization index of the dynamic kinetic chain of the target in the current time window. When tj is less than or equal to the time difference threshold t0, the synchronization state of the target dynamic motion chain in the current time window is determined to be normal; otherwise, the synchronization state of the target dynamic motion chain in the current time window is determined to be abnormal.

7. The digital management method for competitive sports activities in universities according to claim 6, characterized in that, The number of time windows in which the target's dynamic motion chain synchronization status is considered abnormal during the current monitoring period is defined as U1. When the ratio of U1 to M0 is less than or equal to the proportional coefficient k1, the target's dynamic motion chain synchronization status is determined to be normal during the current monitoring period; otherwise, it is determined to be abnormal.

8. The digital management method for competitive sports activities in universities according to claim 7, characterized in that, If, during the current monitoring period, the target's physical fitness index is greater than the physical fitness threshold T0, the target's movement standardization is normal, and the target's dynamic kinetic chain synchronization state is abnormal, core-lower limb coordination training suggestions will be sent to the user; otherwise, core-lower limb coordination training suggestions will not be sent to the user.

9. A digital management device for competitive sports activities in universities, applied to the digital management method for competitive sports activities in universities as described in any one of claims 1-8, characterized in that, include: The data acquisition unit is used to collect target motion data and physiological data; The physical fitness determination unit is used to determine the target physical fitness index based on the target blood oxygen saturation in the monitoring period, and to determine the training intensity for the next monitoring period. The standardization unit is used to determine the standardization of the target's movements based on the target's step frequency and the vertical impact force of the target's landing, and to adjust the target's training intensity based on the determination results of the standardization of the target's movements within the monitoring period. The synchronization determination unit is used to collect the peak timestamps of the sEMG signals of the target rectus abdominis and rectus femoris muscles during the push-off cycle, in order to determine the synchronization index of the target dynamic kinetic chain in the current time window and to judge the synchronization status of the target dynamic kinetic chain. The training suggestion unit is used to send core-lower limb coordination training suggestions to the target based on the target's physical fitness index, the target's movement standardization, and the synchronization status of the target's dynamic kinetic chain in each time window within the monitoring period.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is used to control the electronic device on which the computer-readable storage medium is located to execute the digital management method for competitive sports activities in colleges and universities as described in any one of claims 1-8 during runtime.

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