Aerobics landing buffer training platform integrating gait analysis

Abstract

This invention discloses an aerobics landing cushioning training platform integrating gait analysis, belonging to the field of sports equipment technology. It includes a fixed base plate, with an air compressor fixedly connected to one side of the inner wall of the fixed base plate. Multiple sets of discharge pipes are fixedly connected to the output end of the air compressor. This aerobics landing cushioning training platform integrating gait analysis independently delivers compressed gas to airbags within each protective sleeve via the air compressor in the fixed base plate through the discharge pipes and connecting pipes. Each airbag has an independently connected solenoid valve on the inner wall of its bottom air inlet pipe, allowing each airbag to be independently controlled for inflation and deflation via its corresponding solenoid valve. Combined with a cushioning pad connected to the top of each airbag, the independent deformation of each airbag is converted into differentiated support stiffness in different areas of the cushioning pad. This achieves independent cushioning adjustment capability for different landing areas of the athlete, avoiding the shortcomings of traditional integral cushioning pads where the deformation of each area is linked and cannot accurately respond to local impacts.

Description

Technical Field

[0001] This invention relates to the field of sports equipment technology, specifically to an aerobics landing cushioning training platform that integrates gait analysis. Background Technology

[0002] Landing movements in aerobic gymnastics are characterized by high impact loads, short peak load times, and highly variable landing positions. Landing cushioning training platforms, as core training equipment for reducing the risk of lower limb joint impact injuries in athletes, have evolved from passive elastic pads to active air pressure regulating devices. Passive elastic pads rely on the material's inherent physical properties to absorb impact energy, but their cushioning stiffness is constant and cannot adapt to the differentiated cushioning needs under varying training intensities. Active air pressure regulating devices, on the other hand, use air pumps to inflate sealed airbags to create an air cushion-like cushioning interface, achieving adjustable cushioning stiffness and improving the training platform's adaptability to different scenarios. They are now widely used in professional aerobic gymnastics training.

[0003] However, existing active pressure-regulated cushioning training platforms all connect multiple airbags to the same pressure pipeline via a connecting pipe, or although they use independent airbag structures, the control logic applies a uniform pressure regulation command to all airbags. This design causes the cushioning pad to undergo global, synchronized deformation when compressed. When an athlete's landing point deviates from a certain area of ​​the platform, the airbag in that area, after being compressed, squeezes the internal gas through the connecting pipe to other airbags. The cushioning stiffness of all areas of the platform changes synchronously with the same amplitude and rate. This fails to provide targeted reinforcement cushioning for the actual landing area and also causes unnecessary height changes in non-landing areas due to synchronized deformation. This makes it impossible for the training platform to achieve localized differential matching of cushioning stiffness based on the athlete's actual landing position when facing actual training scenarios such as random changes in landing position and uneven force on the left and right feet. As a result, the training platform always responds to the specific precise needs of the landing area with a coarse mode of uniform response across the entire platform. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of this invention is to provide an aerobics landing cushioning training platform that integrates gait analysis, so as to solve the problem in the prior art that the uniform response of the cushioning stiffness of the entire platform makes it impossible to achieve local differential matching of cushioning stiffness according to the actual landing position of the athlete.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an aerobics landing cushioning training platform integrating gait analysis, comprising a fixed base plate, an air compressor fixedly connected to one side of the inner wall of the fixed base plate, a plurality of discharge pipes fixedly connected to the output end of the air compressor, and a plurality of connecting pipes fixedly connected to one end of the discharge pipes.

[0006] The inner wall of the fixed base plate is fixedly connected to multiple sets of protective sleeves, and one end of the connecting pipe is inserted through and inserted into the surface of the protective sleeve. An airbag is fixedly connected to the inner bottom wall of the protective sleeve, and an air inlet pipe is fixedly connected to the bottom end of the airbag. A solenoid valve is fixedly connected to the inner wall of the air inlet pipe, and the bottom end of the air inlet pipe is fixedly connected to the surface of the connecting channel.

[0007] Furthermore, a buffer pad is fixedly connected to the top of the airbag, and multiple pressure sensors are fixedly connected to the inner wall of the buffer pad. A limit frame is fixedly connected to the surface of the buffer pad, and the limit frame is sleeved on the surface of the fixed base plate but does not contact the fixed base plate.

[0008] Furthermore, mounting plates are fixedly connected to all four sides of the fixed base plate, and a camera is fixedly connected to the top of the mounting plate.

[0009] Furthermore, a controller body is fixedly connected to one side of the fixed base plate.

[0010] Furthermore, the controller body is communicatively connected to the air compressor, solenoid valve, pressure sensor, and camera. The controller body receives the landing pressure signal collected by the pressure sensor and the gait image signal collected by the camera. Based on the landing pressure signal and the gait image signal, it generates a buffer control command and adjusts the opening degree of the solenoid valve and the output pressure of the air compressor. The controller body calculates the single landing impact characteristic index according to the following formula. and based on Generate the buffer control instructions:

[0011]

[0012] in, For the first Pressure sensor number 1 at time The instantaneous pressure value, For a moment Coordinates of the center of pressure on the foot. The preset reference pressure value for the system. For spatial attenuation scale parameters, The duration of a single landing.

[0013] Furthermore, the controller body has a built-in gait analysis module and a buffer adjustment module. The gait analysis module is used to extract the foot landing position and landing angle based on multiple consecutive frames of gait images captured by the camera, and to calculate a comprehensive gait stability evaluation index. The buffer adjustment module is used to determine the target air pressure value of each airbag based on the foot landing position and landing angle, and adjusts the actual air pressure of each airbag to the target air pressure value by controlling the opening and closing time of the corresponding solenoid valve. The gait analysis module calculates according to the following formula. :

[0014]

[0015] in, For the first Impact characteristics index of the second landing. For the first The trajectory vector of the pressure center of the second landing. For the first The average pressure distribution matrix of the second landing. The system's preset ideal reference pressure distribution template, Let be the cross-entropy divergence function. The weighting coefficients and , The system's preset standard pressure center movement speed;

[0016] Furthermore, the buffer adjustment module determines the target air pressure vector for each airbag according to the following formula. :

[0017]

[0018] in, This represents the current actual air pressure vector of the airbag. Let buffer performance be the objective function. The learning rate parameter, For the first Characteristic pressure scale parameters of each airbag.

[0019] Furthermore, a multi-point pressure monitoring loop is formed between the controller body and each pressure sensor; the controller body determines whether the current landing area deviates from the preset training area based on the real-time pressure distribution data fed back by each pressure sensor, and adjusts the support stiffness of the airbag at the corresponding position when a deviation is determined.

[0020] Furthermore, the controller body also acquires the peak pressure change rate of each pressure sensor per unit time and compares the peak pressure change rate with a preset safe change rate threshold; when the peak pressure change rate exceeds the safe change rate threshold, the controller body controls the air compressor to increase the output pressure.

[0021] Furthermore, the controller body stores air pressure configuration parameters corresponding to multiple training modes; in response to an externally input mode selection signal, the controller body calls the corresponding air pressure configuration parameters and controls each solenoid valve to independently adjust the inflation state of each airbag according to the air pressure configuration parameters.

[0022] Furthermore, the controller body also includes a data recording unit and an evaluation unit; the data recording unit records the pressure distribution data and gait data for each landing in a time series; the evaluation unit generates a gait stability evaluation index based on the pressure distribution data and gait data from multiple landings, compares the evaluation index with historical training data, and generates a training effect feedback signal; the evaluation unit calculates the long-term training effect trend prediction value according to the following formula. :

[0023]

[0024] in, For the total number of training sessions, For the first Gait stability evaluation index for each training session. To train the initial baseline values, This is the learning efficiency coefficient. For time decay rate parameter, The fatigue effect coefficient is... This is the timescale parameter for fatigue accumulation.

[0025] Compared with existing technologies, this invention provides an aerobics landing cushioning training platform that integrates gait analysis. An air compressor fixedly connected to the inner wall of a fixed base plate independently delivers compressed gas to airbags within each protective sleeve via discharge and connecting pipes. Each airbag has an independently fixed solenoid valve on the inner wall of its bottom air inlet pipe, allowing each airbag to be independently controlled for inflation and deflation via its corresponding solenoid valve. Combined with a cushioning pad connected to the top of each airbag, the independent deformation of each airbag is converted into differentiated support stiffness in different areas of the cushioning pad. This achieves independent cushioning adjustment capability for different landing areas of the athlete, avoiding the shortcomings of traditional integral cushioning pads where coordinated deformation in different areas prevents precise response to localized impacts. It effectively solves the problem of inconsistent cushioning needs at different landing points and significantly improves the training platform's adaptive adjustment capability to differentiated landing areas.

[0026] The controller body is communicatively connected to the air compressor, solenoid valve, pressure sensor, and camera. It receives landing pressure signals from the pressure sensor and gait image signals from the camera, and then calculates the single-landing impact characteristic index based on a fusion of Gaussian spatial weights and time integrals. And a comprehensive evaluation index of gait stability that integrates impact continuity, pressure center drift, and pressure distribution regularity. The gradient descent method is used to evaluate the buffer performance objective function, which consists of logarithmic terms and composite smoothing kernel integral terms. Iterative optimization is performed to solve for the target air pressure vector of each airbag. Furthermore, by controlling the opening and closing time of the corresponding solenoid valves and the output pressure of the air compressor, the support stiffness of each area of ​​the buffer pad is dynamically adjusted. This establishes a complete closed-loop control mechanism from multi-source sensor data acquisition to adaptive decision-making of buffer parameters. This enables the training platform to adjust the buffer response strategy in real time according to the actual impact characteristics and gait stability of the athlete's landing each time. Compared with existing buffer training devices that rely on fixed stiffness or manual adjustment, this achieves dynamic matching between buffer characteristics and the athlete's actual landing state, effectively improving the accuracy and adaptability of buffer intervention during training. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0028] Figure 1 This is a schematic diagram of the overall structure provided in an embodiment of the present invention;

[0029] Figure 2 This is a schematic diagram of the airbag structure provided in an embodiment of the present invention;

[0030] Figure 3 This is a schematic diagram of the pressure sensor structure provided in an embodiment of the present invention;

[0031] Figure 4 This is a schematic diagram of an air compressor structure provided in an embodiment of the present invention;

[0032] Figure 5 This is a schematic diagram of the solenoid valve structure provided in an embodiment of the present invention.

[0033] Explanation of reference numerals in the attached figures:

[0034] 1. Fixed base plate; 2. Air compressor; 3. Discharge pipe; 4. Connecting pipe; 5. Protective sleeve; 6. Airbag; 7. Inlet pipe; 8. Solenoid valve; 9. Buffer pad; 10. Pressure sensor; 11. Limiting sleeve; 12. Mounting plate; 13. Camera; 14. Controller body. Detailed Implementation

[0035] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0036] As attached Figure 1 To be continued Figure 5 As shown:

[0037] Example 1:

[0038] The present invention provides an aerobics landing cushioning training platform that integrates gait analysis, including a fixed base plate 1, an air compressor 2 fixedly connected to one side of the inner wall of the fixed base plate 1, a plurality of discharge pipes 3 fixedly connected to the output end of the air compressor 2, and a plurality of connecting pipes 4 fixedly connected to one end of the discharge pipes 3.

[0039] Multiple sets of protective sleeves 5 are fixedly connected to the inner wall of the fixed base plate 1, and one end of the connecting pipe 4 is inserted through and inserted into the surface of the protective sleeve 5. An airbag 6 is fixedly connected to the inner bottom wall of the protective sleeve 5, and an air inlet pipe 7 is fixedly connected to the bottom end of the airbag 6. A solenoid valve 8 is fixedly connected to the inner wall of the air inlet pipe 7, and the bottom end of the air inlet pipe 7 is fixedly connected to the surface of the connecting channel 4.

[0040] In use, the fixed base plate 1 serves as the supporting structure of the entire training platform, providing stable installation support and spatial positioning for the various internal functional components. An air compressor 2, fixedly connected to one side of its inner wall, acts as the core of the air source power. Upon receiving a buffer adjustment command from the controller body 14, it starts operating, compressing external air into high-pressure gas with a preset pressure value and continuously outputting it. Multiple sets of discharge pipes 3, fixedly connected to the output end of the air compressor 2, guide the compressed gas according to the designed flow path to the corresponding connecting pipes 4, ensuring that the airflow maintains stable pressure and no additional energy loss during the delivery path. The connecting pipes 4 serve as intermediate transition airflow channels, with one end connected to the discharge pipe 3 and the other end inserted through and inserted into the surface of multiple sets of protective sleeves 5 fixedly connected to the inner wall of the fixed base plate 1, thereby orderly introducing the compressed gas into the interior of each protective sleeve 5. The protective sleeves 5 act as the rigid protective shell of the airbag 6. The airbag 6, fixedly connected to its inner bottom wall, expands and unfolds along the axial direction of the protective sleeve 5 when inflated, and the inner wall of the protective sleeve 5 limits the radial expansion of the airbag 6, ensuring that the airbag 6 only expands vertically. The airbag 6 undergoes elastic deformation in the straight direction, providing stable and directionally controllable cushioning support for the cushioning pad 9. The air inlet pipe 7, fixedly connected to the bottom of the airbag 6, serves as a dedicated channel for gas to enter and exit the airbag 6. The solenoid valve 8, fixedly connected to its inner wall, performs opening or closing actions under the electrical signal control of the controller body 14. When the solenoid valve 8 is open, compressed gas from the connecting pipe 4 is filled into the airbag 6 through the air inlet pipe 7. When the solenoid valve 8 is closed, the gas inside the airbag 6 is sealed to maintain the current air pressure. At the same time, the bottom of the air inlet pipe 7 is fixedly connected to the surface of the connecting channel 4, forming an airtight connection between the air inlet pipe 7 and the connecting pipe 4, ensuring that the compressed gas does not leak during the process of being transported from the connecting pipe 4 to the air inlet pipe 7. Through the coordinated operation of the above structures, each airbag 6 can independently adjust its internal air pressure under the control of the controller body 14 according to the real-time collected impact force distribution and gait image data, thereby achieving differentiated cushioning response for different landing areas and different training intensities, effectively absorbing and dispersing the impact load generated when aerobics athletes land.

[0041] Example 2:

[0042] This embodiment is basically the same as the previous embodiment, except that a buffer pad 9 is fixedly connected to the top of the airbag 6, multiple pressure sensors 10 are fixedly connected to the inner wall of the buffer pad 9, a limiting sleeve 11 is fixedly connected to the surface of the buffer pad 9, and the limiting sleeve 11 is fitted onto the surface of the fixed base plate 1 without contacting the fixed base plate 1. Mounting plates 12 are fixedly connected to all four sides of the fixed base plate 1, a camera 13 is fixedly connected to the top of the mounting plate 12, and a controller body 14 is fixedly connected to one side of the fixed base plate 1.

[0043] The controller body 14 is communicatively connected to the air compressor 2, solenoid valve 8, pressure sensor 10, and camera 13. The controller body 14 receives the landing pressure signal collected by the pressure sensor 10 and the gait image signal collected by the camera 13. Based on the landing pressure signal and gait image signal, it generates a buffer control command and adjusts the opening degree of the solenoid valve 8 and the output pressure of the air compressor 2. The controller body 14 calculates the single landing impact characteristic index according to the following formula. and based on Generate buffer control instructions:

[0044] The impact force of a landing is not uniformly distributed; it is mainly concentrated in the contact area between the foot and the table surface, and the center of pressure (COP) shifts over time. It is necessary to extract the overall impact intensity of a single landing, while emphasizing the weight of the area near the COP, including the following steps:

[0045] Countertop division The first sensing unit, the first Unit time pressure value ;

[0046] Define reference pressure (Statistical mean), normalizing the pressure to a relative value. ;

[0047] The camera captures COP coordinates in real time. Calculate the Euclidean distance from each element to the COP. ;

[0048] Introducing the Gaussian kernel function As a spatial weight, the contribution of cells closer to COP is greater, while the contribution of cells farther away decreases exponentially, which is consistent with the actual impact concentration in biomechanics.

[0049] For each moment, the weighted impact intensity at that moment is obtained by multiplying the normalized pressure of all units by the spatial weight and summing the results.

[0050] The entire landing process By averaging over time, we obtain the single-landing impact characteristic index. :

[0051]

[0052] in, For the first Pressure sensor number 1 at time The instantaneous pressure value, For a moment Coordinates of the center of pressure on the foot. The preset reference pressure value for the system. For spatial attenuation scale parameters, The duration of a single landing.

[0053] The controller body 14 has a built-in gait analysis module and a buffer adjustment module. The gait analysis module is used to extract the foot landing position and landing angle based on the continuous multi-frame gait images captured by the camera 13, and to calculate the comprehensive gait stability evaluation index. The buffer adjustment module determines the target air pressure value of each airbag 6 based on the foot landing position and landing angle, and adjusts the actual air pressure of each airbag 6 to the target air pressure value by controlling the opening and closing time of the corresponding solenoid valve 8. The gait analysis module calculates the target air pressure value according to the following formula. :

[0054] Stability is determined not only by a single impact, but also by the volatility of multiple consecutive impacts, COP drift, and pressure distribution regularity. Therefore, three sub-dimensions are designed, and a weighted average is calculated, including the following steps:

[0055] Assume there is a total Each consecutive landing, calculated as follows: ;

[0056] Sub-dimension 1 (Shock Continuity): The smaller the difference between two adjacent shocks, the more stable the situation. Define the normalized difference. (To prevent overshoot in the denominator);

[0057] Sub-dimension 2 (COP drift): Total length of the COP movement path during landing. , divided by Normalization ( (for standard speed), to obtain The larger the value, the more severe the shaking.

[0058] Sub-dimension 3 (Pressure Distribution Normalization): This will include the first... Average pressure distribution matrix of the second impact (Time Average) and Ideal Template Comparison using cross-entropy divergence The smaller this value, the closer the distribution is to the ideal;

[0059] Weighting the three sub-dimensions Later The average is taken twice to obtain the comprehensive index. The range is (0,1);

[0060] Therefore, we can conclude that:

[0061]

[0062] in, For the first Impact characteristics index of the second landing. For the first The trajectory vector of the pressure center of the second landing. For the first The average pressure distribution matrix of the second landing. The system's preset ideal reference pressure distribution template, Let be the cross-entropy divergence function. The weighting coefficients and , The system's preset standard pressure center movement speed;

[0063] Furthermore, the buffer adjustment module determines the target air pressure vector for each airbag according to the following formula. :

[0064] To make Minimize (i.e., optimal stability) by adjusting Individual airbag pressure is achieved. Direct optimization. Difficulty, constructing a with Positively correlated objective function Then, the gradient descent method is used to iteratively update the air pressure.

[0065] make This is the current air pressure vector.

[0066] Define the objective function The first item follows Monotonically increasing, the second term is a smoothing penalty term, when When the value is too large, the integral approaches the saturation value, thus preventing the air pressure from increasing indefinitely; the combination of the Gaussian factor and the rational factor in the integrand makes it sensitive within a reasonable range and saturates in the extreme range.

[0067] Calculate the gradient of the objective function with respect to air pressure. Its weight It can be obtained by numerical or analytical methods.

[0068] Using the gradient descent method, from the current air pressure Starting from the negative gradient direction, adjust in one step by a certain amount. (Usually negative). For brevity, it is written as a positive gradient, but in actual control, it is inverted.

[0069] Obtain the target air pressure vector (The negative sign has been omitted here; in actual implementation, the negative sign is used.)

[0070] Therefore, we obtain (given the positive gradient form, with specific notation determined by the system):

[0071]

[0072] in, This represents the current actual air pressure vector of the airbag. Let buffer performance be the objective function. The learning rate parameter, For the first Characteristic pressure scale parameters of each airbag.

[0073] A multi-point pressure monitoring loop is formed between the controller body 14 and each pressure sensor 10. Based on the real-time pressure distribution data fed back by each pressure sensor 10, the controller body 14 determines whether the current landing area deviates from the preset training area, and adjusts the support stiffness of the airbag 6 at the corresponding position when a deviation is detected. The controller body 14 also acquires the peak pressure change rate of each pressure sensor 10 per unit time and compares the peak pressure change rate with a preset safe change rate threshold. When the peak pressure change rate exceeds the safe change rate threshold, the controller body 14 controls the air compressor 2 to increase the output pressure. The controller body 14 stores multiple training modes. The controller body 14 responds to the externally input mode selection signal, calls the corresponding air pressure configuration parameters, and controls each solenoid valve 8 to independently adjust the inflation state of each airbag 6 according to the air pressure configuration parameters. The controller body 14 also includes a data recording unit and an evaluation unit. The data recording unit records the pressure distribution data and gait data of each landing in a time series. The evaluation unit generates gait stability evaluation indicators based on the pressure distribution data and gait data of multiple landings, compares the evaluation indicators with historical training data, and generates training effect feedback signals. The evaluation unit calculates the long-term training effect trend prediction value according to the following formula. :

[0074] set up Each training session yields one... value.

[0075] Initial baseline These are the evaluation values ​​before the first training session.

[0076] Training Improvement Item: 1 The improvement contribution of this training session is ( The smaller the size, the greater the potential for improvement, but the distance from the current... The longer the time elapsed, the greater the decay of the contribution should be, hence the need to multiply by an exponential decay factor. Multiply by learning efficiency .

[0077] Fatigue accumulation: Increased training repetitions lead to fatigue, which is addressed using an integral method. The integral is in It grows faster when it is smaller. When the value is large, it tends to saturate, and the coefficient is used. Adjust the intensity of the influence.

[0078] The baseline, improvement contribution, and fatigue correction are added together to obtain the predicted value. , with a value range of [0,1].

[0079] Therefore, we can conclude that:

[0080]

[0081] in, For the total number of training sessions, For the first Gait stability evaluation index for each training session. To train the initial baseline values, This is the learning efficiency coefficient. For time decay rate parameter, The fatigue effect coefficient is... This is the timescale parameter for fatigue accumulation.

[0082] In use, the cushioning pad 9 serves as the support interface that directly contacts the athlete's body upon landing. It is laid on top of each airbag 6 and moves up and down synchronously with the expansion and contraction of the airbags 6, thus providing the athlete with a flat and cushioned landing area. Multiple pressure sensors 10, fixedly connected to the inner wall of the cushioning pad 9, collect pressure change signals at each sensing point in real time at the moment of landing, converting these analog signals into digital pressure distribution data to reflect the spatial distribution of the impact force on the plane of the cushioning pad 9. Limiters are fixedly connected to the surface of the cushioning pad 9. The sleeve 11 is fitted onto the surface of the fixed base plate 1 without contacting it. This limiting sleeve 11 rises and falls together with the buffer pad 9, and mechanically limits the maximum downward displacement of the buffer pad 9 during its downward compression to prevent the airbag 6 from exceeding its safe deformation range due to over-compression. Simultaneously, the non-contact gap between the limiting sleeve 11 and the fixed base plate 1 avoids interference from friction on the free movement of the buffer pad 9. The mounting plates 12, fixedly connected around the perimeter of the fixed base plate 1, provide a stable mounting base for the camera 13, ensuring that the camera 13 remains fixed during training. The variable field of view; the camera 13 fixedly connected to the top of the mounting plate 12 continuously collects gait image sequences of the athlete's landing area during training and transmits the image data to the controller body 14 as the raw data source for extracting the foot landing position and landing angle; the controller body 14 fixedly connected to one side of the fixed base plate 1 serves as the data processing and control decision core of the entire training platform. Its built-in signal acquisition module synchronously receives the pressure distribution signal output by the pressure sensor 10 and the gait image signal output by the camera 13. The algorithm program pre-set inside the controller body 14 calculates the impact characteristics and gait stability evaluation index of the current landing in real time based on the above multi-source sensor data, and generates independent air pressure adjustment commands for each airbag 6 accordingly. Then, by controlling the opening and closing action of the corresponding solenoid valve 8 and the output pressure of the air compressor 2, the dynamic adjustment of the support stiffness of each area of ​​the buffer pad 9 is realized. Through the coordinated cooperation of the above structures, the training platform can perceive the impact force distribution and foot landing position in real time during each landing of the athlete, and actively adjust the buffer characteristics of each airbag 6 based on the fused gait analysis results, thereby achieving precise absorption and dispersion of landing impact.

[0083] Application example:

[0084] Designed for aerobics training, this training program is aimed at professional aerobics athletes, aerobics students at sports colleges, and amateur aerobics enthusiasts. It is suitable for various scenarios, including daily landing cushioning training, stability enhancement training for jumping movements, and impact adaptation training during post-injury rehabilitation. In aerobics, athletes frequently perform various jumping, turning, and flexion landing movements. The impact force generated between the foot and the ground upon landing can be several times the athlete's body weight. Improper cushioning or an unbalanced landing posture can easily lead to lower limb sports injuries such as ankle sprains, knee ligament injuries, and plantar fasciitis. Existing conventional cushioning training platforms are mostly passive elastic pads or fixed-stiffness shock absorbers, providing only constant cushioning characteristics. They cannot dynamically adjust based on the impact force distribution characteristics and foot landing position of a single landing, nor can they quantitatively assess and provide feedback on gait stability and technical standardization after multiple consecutive landings. Coaches mainly rely on visual observation and experience to guide athletes in improving their landing techniques, which is highly subjective and lacks precise data support. The training platform of this invention integrates the landing impact force distribution monitoring of the pressure sensor array with the gait image acquisition of the camera, combined with the gait analysis module and buffer adjustment module built into the controller body 14, to perform real-time quantitative evaluation of the impact characteristics and gait stability of each landing, and independently adjust the air pressure of each airbag 6 in a closed loop according to the evaluation results, thereby achieving adaptive matching of buffer stiffness, effectively reducing the risk of landing impact injury and assisting athletes to optimize landing techniques. It is especially suitable for the technical refinement of repetitive landing movements in high-frequency, high-intensity aerobics training scenarios.

[0085] Before training begins, the coach selects the appropriate training mode based on the type and intensity requirements of the day's training plan through the human-computer interaction interface of the controller body 14. Responding to the externally input mode selection signal, the controller body 14 retrieves the air pressure configuration scheme matching the current training mode from a pre-stored set of air pressure configuration parameters corresponding to multiple training modes. Based on this scheme, it controls each solenoid valve 8 to independently adjust the initial inflation state of each airbag 6, ensuring that the cushioning pad 9 exhibits an initial support stiffness adapted to the training intensity. Simultaneously, the data recording unit built into the controller body 14 records the start time and mode parameters of this training session. After training begins, the athlete stands on the cushioning pad 9 and begins performing jump landing movements according to the predetermined training content. Cameras 13 on top of mounting plates 12, which are fixedly connected to the four sides of the base plate 1, continuously collect gait image sequences of the athlete's landing area at a preset frame rate and transmit the image signals to the gait analysis module of the controller body 14 in real time. At the same time, multiple sets of pressure sensors 10, which are fixedly connected to the inner wall of the buffer pad 9, collect the instantaneous pressure values ​​at each sensing point at the moment of each athlete's landing using a high-frequency sampling method and transmit the pressure signals to the controller body 14 in real time. The signal acquisition module built into the controller body 14 receives the above two sets of sensor data simultaneously, and the gait analysis module extracts the foot landing position and landing angle based on the continuous gait images of multiple frames. Combined with the landing pressure signals collected by the pressure sensors 10, the module calculates the single landing impact characteristic index using a formula. This index quantitatively characterizes the overall impact intensity of the landing. Subsequently, the gait analysis module will analyze the impact characteristic indices calculated from multiple consecutive landings. By substituting the pressure center trajectory vector and average pressure distribution matrix of each landing into the formula, the comprehensive gait stability evaluation index is calculated. This index comprehensively reflects the consistency of impact, the degree of foot wobble, and the standardization of pressure distribution during multiple consecutive landings of the athlete; the buffer adjustment module of the controller body 14 obtains the current gait stability comprehensive evaluation index. Then, the actual air pressure vector of each airbag 6 is... and Substitute the values ​​into the formula, first construct the AND... Positive correlation buffer performance objective function Then, the gradient vector of the objective function with respect to the air pressure of each airbag is calculated, and the target air pressure vector of each airbag is obtained by iteratively solving the gradient descent method. The controller body 14 generates independent air pressure adjustment commands for each airbag 6. At the air pressure adjustment execution level, the controller body 14 sends opening control signals to the solenoid valves 8 fixedly connected to the inner wall of the corresponding airbag 6's inlet pipe 7. When it is necessary to increase the air pressure of a certain airbag 6, the controller body 14 opens the corresponding solenoid valve 8, allowing compressed gas in the connecting pipe 4 to enter the airbag 6 through the inlet pipe 7. When it is necessary to decrease the air pressure of a certain airbag 6, the controller body 14 controls the solenoid valve 8 to intermittently release air. The air compressor 2 adjusts its output pressure according to the commands from the controller body 14. To maintain stable air pressure in the main air supply pipeline, the discharge pipe 3 diverts and guides the compressed gas output from the air compressor 2 to each connecting pipe 4. The connecting pipe 4 is inserted through the surface of the protective sleeve 5, orderly introducing gas into the interior of each protective sleeve 5. During inflation or deflation, the airbag 6 expands or contracts along the axial direction of the protective sleeve 5, and the inner wall of the protective sleeve 5 provides a limiting constraint on the radial expansion of the airbag 6, ensuring that the airbag 6 only undergoes elastic deformation in the vertical direction. The buffer pad 9 adjusts the height and support stiffness of each area according to the synchronous lifting and lowering movement of each airbag 6, thereby achieving the next... Differentiated impact buffering response; During the closed-loop adjustment process described above, the controller body 14 maintains continuous multi-point pressure monitoring loop connection with each pressure sensor 10. The controller body 14 monitors the real-time pressure distribution data fed back by each pressure sensor 10 in real time. When it is determined that the current landing area deviates from the preset training area, it actively adjusts the support stiffness of the airbag 6 at the corresponding position to guide the athlete's landing point back to the training target area. At the same time, the controller body 14 calculates the peak pressure change rate of each pressure sensor 10 in real time per unit time. When the peak pressure change rate exceeds the preset safe change rate threshold, the controller body 14 controls the air compressor 2 to increase the output pressure to quickly improve the buffering damping of the airbag 6 to cope with sudden high-intensity impacts. In a training session, the entire process of data acquisition, gait analysis, buffering decision and air pressure execution described above is executed cyclically during each landing. The data recording unit continuously records the pressure distribution data and gait data of each landing in time series. After each landing, the evaluation unit compares the current gait stability evaluation index with historical training data and calculates the long-term training effect trend prediction value according to the formula. ,when When the value shows a monotonically increasing trend and gradually approaches 1, it indicates that the training scheme is effective. When the gait becomes flat or declines, it indicates that the training may have entered a plateau or that excessive fatigue has occurred. After training, the evaluation unit generates a training effect feedback signal containing gait stability evaluation indicators and long-term trend prediction values ​​for each stage of the training. This signal is then presented to the coach and athlete through the display interface of the controller body 14 or an external terminal, allowing them to comprehensively evaluate the training effectiveness and formulate subsequent training plans. Throughout the training process, the limiting sleeve 11, which is fixedly connected to the surface of the buffer pad 9, rises and falls together with the buffer pad 9. During the downward pressing of the buffer pad 9, it forms a mechanical limit on the maximum downward displacement of the buffer pad 9 to prevent the airbag 6 from exceeding the safe deformation range due to over-compression. At the same time, the non-contact gap between the limiting sleeve 11 and the fixed base plate 1 ensures that the buffer pad 9 is not disturbed by friction during the rising and falling process. All structures work together to complete a complete closed-loop control process from sensing acquisition, data analysis, buffer decision-making to execution feedback.

[0086] Working principle: When an athlete lands on the cushioning pad 9, the cushioning pad 9, as the direct support interface, first receives the initial impact load of the foot landing and transmits the impact force to the airbags 6 at its bottom. Multiple pressure sensors 10, fixedly connected to the inner wall of the cushioning pad 9, collect the instantaneous pressure value at each sensing point at the moment of landing using a high-frequency sampling method and convert it into an electrical signal. At the same time, the camera 13 on the top of the mounting plate 12 fixedly connected around the base plate 1 synchronously collects continuous multi-frame gait images of the athlete during the landing process. The pressure signals collected by the pressure sensors 10 and the image signals collected by the camera 13 are transmitted in real time via a communication link to the controller body 14 fixedly connected to one side of the base plate 1. After the signal acquisition module built into the controller body 14 synchronously receives the above two channels of sensor data, the gait analysis module extracts the foot landing position and landing angle based on the continuous multi-frame gait images provided by the camera 13, and combines the landing pressure distribution data provided by the pressure sensors 10 into the formula to calculate the duration of the entire landing process. The single-impact characteristic index is calculated by integrating the normalized pressure values ​​of all internal sensing units with the Gaussian spatial weights over time and then summing the results twice. This index quantitatively characterizes the impact concentration and overall impact intensity of a single landing. Subsequently, the gait analysis module will analyze the impact characteristic indices calculated from multiple consecutive landings. By combining the total length of the pressure center movement path described by the pressure center trajectory vector during each landing and the average pressure distribution matrix of each landing, and substituting them into the formula, the deviation between the actual pressure distribution and the system's preset ideal reference pressure distribution template is quantified using the cross-entropy divergence function. The weighted summation of the impact continuity sub-dimension, pressure center drift sub-dimension, and pressure distribution normality sub-dimension is then averaged over the total number of consecutive landings to calculate the gait stability comprehensive evaluation index. This index comprehensively reflects the consistency of impact during multiple consecutive landings, the speed of body posture adjustment after landing, and the standardization of landing posture; the buffer adjustment module of the controller body 14 obtains the current gait stability comprehensive evaluation index. Then, the actual air pressure vector of each airbag 6 is... and Substitute the values ​​into the formula, first construct... The objective function of buffer performance is the sum of the logarithmic terms and the pressure smoothing penalty terms. Then, the gradient vector of the objective function with respect to the air pressure of each airbag is calculated, and the target air pressure vector of each airbag is obtained by iteratively solving along the gradient direction of the objective function using the gradient descent method. The controller body 14 generates independent air pressure adjustment commands for each airbag 6 accordingly. When performing air pressure adjustment, the controller body 14 sends corresponding opening degree or opening / closing duration control signals to the solenoid valves 8 fixedly connected to the inner wall of the air inlet pipe 7 at the bottom of each airbag 6. For airbags 6 that need increased air pressure, the controller body 14 opens the corresponding solenoid valve 8 to allow compressed gas from the connecting pipe 4 to be injected into the airbag 6 through the air inlet pipe 7. For airbags 6 that need decreased air pressure, the controller body 14 controls the corresponding solenoid valve 8 to open intermittently with a set duty cycle to allow gas inside the airbag 6 to be injected into the airbag 6 through the air inlet pipe 7 and the connecting pipe 4. External release: Air compressor 2 adjusts its output power according to the instructions of controller body 14 to maintain the air pressure of the main air supply pipeline within the required target range. Multiple sets of discharge pipes 3 fixedly connected to the output end of air compressor 2 guide the compressed gas to the corresponding connecting pipes 4 according to the designed flow path. One end of the connecting pipe 4 is inserted through and inserted into the surface of multiple sets of protective sleeves 5 fixedly connected to the inner wall of the fixed base plate 1, so that the compressed gas is orderly introduced into the interior of each protective sleeve 5. The high-pressure gas entering the interior of each protective sleeve 5 acts on the inner cavity of the air bag 6 through the air inlet pipe 7 at the bottom of the corresponding air bag 6, so that the air bag 6 moves along the air supply line during inflation or deflation. The protective sleeve 5 undergoes elastic deformation by expanding or contracting in the axial direction, and the inner wall of the protective sleeve 5 provides a limiting constraint on the radial expansion of the airbag 6, ensuring that the airbag 6 deforms only in the vertical direction. The expansion or contraction of the airbag 6 causes the corresponding area of ​​the buffer pad 9 fixedly connected to its top to move up and down, thereby adjusting the support stiffness and buffering characteristics of each area of ​​the buffer pad 9 to achieve differentiated absorption and dispersion of the impact of the next landing. Throughout the entire closed-loop adjustment process, the controller body 14 maintains a continuous connection with each pressure sensor 10 through a multi-point pressure monitoring loop. The controller body 14 monitors the pressure in real time according to the pressure of each sensor. The force sensor 10 feeds back real-time pressure distribution data to determine whether the current landing area deviates from the preset training area. When a deviation is determined, the support stiffness of the airbag 6 at the corresponding position is actively adjusted through the aforementioned air pressure regulation method to guide the athlete's landing point back to the target area. At the same time, the controller body 14 calculates the peak pressure change rate of each pressure sensor 10 in real time and compares the change rate with the preset safe change rate threshold. When the peak pressure change rate exceeds the safe change rate threshold, the controller body 14 controls the air compressor 2 to increase the output pressure to quickly improve the buffer damping of the airbag 6 to cope with sudden high-intensity impacts.Meanwhile, the limiting sleeve 11, which is fixedly connected to the surface of the buffer pad 9, rises and falls together with the buffer pad 9. When the buffer pad 9 is pressed down to its limit position due to over-inflation of the airbag 6 or under extreme impact load, the lower end face of the limiting sleeve 11 forms a mechanical abutment with the upper end face of the fixed base plate 1, rigidly limiting the maximum downward displacement of the buffer pad 9 to prevent the airbag 6 from being damaged due to exceeding the safe deformation range. The non-contact design of the limiting sleeve 11, which is sleeved on the surface of the fixed base plate 1 but does not contact the fixed base plate 1, ensures that the buffer pad 9 is not disturbed by friction within the normal lifting stroke range, thereby ensuring pressure sensing. The accuracy of the data collected by the device 10; in a complete training session, the entire process from signal acquisition, gait analysis and impact characteristic calculation, stability comprehensive evaluation, target air pressure optimization solution to air pressure execution adjustment and safety monitoring is executed cyclically in each landing process. The data recording unit built into the controller body 14 continuously stores the pressure distribution data and gait data of each landing in time series. The evaluation unit built into the controller body 14 compares the current gait stability evaluation index with the historical training data after each landing and substitutes it into the formula to calculate the gait stability evaluation index of each training session. Multiply each by a learning efficiency coefficient that decays exponentially over time, sum them, and then add them together with the total number of training sessions. The fatigue cumulative correction integral term for the upper limit of integration is used to calculate the predicted value of the long-term training effect trend. The predicted value is dynamically updated as the number of training sessions increases and serves as a criterion for the effectiveness of the training program. Thus, through the coordinated operation of all the above structures, the training platform has achieved a complete closed-loop control from landing impact perception, gait analysis and evaluation, adaptive adjustment of buffer stiffness to long-term training effect tracking.

[0087] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A gait analysis-integrated aerobics landing cushioning training platform, comprising a fixed base plate (1), characterized in that, An air compressor (2) is fixedly connected to one side of the inner wall of the fixed base plate (1). Multiple sets of discharge pipes (3) are fixedly connected to the output end of the air compressor (2). Multiple sets of connecting pipes (4) are fixedly connected to one end of the discharge pipes (3). The inner wall of the fixed base plate (1) is fixedly connected to multiple sets of protective sleeves (5), and one end of the connecting pipe (4) is inserted through the surface of the protective sleeve (5). The inner bottom wall of the protective sleeve (5) is fixedly connected to an airbag (6), the bottom end of the airbag (6) is fixedly connected to an air inlet pipe (7), the inner wall of the air inlet pipe (7) is fixedly connected to a solenoid valve (8), and the bottom end of the air inlet pipe (7) is fixedly connected to the surface of the connecting channel (4).

2. The aerobics landing cushioning training platform integrating gait analysis according to claim 1, characterized in that, The top of the airbag (6) is fixedly connected to a buffer pad (9), and the inner wall of the buffer pad (9) is fixedly connected to multiple pressure sensors (10). The surface of the buffer pad (9) is fixedly connected to a limiting sleeve (11), and the limiting sleeve (11) is sleeved on the surface of the fixed base plate (1) and does not contact the fixed base plate (1).

3. The aerobics landing cushioning training platform integrating gait analysis according to claim 1, characterized in that, Mounting plates (12) are fixedly connected to all four sides of the fixed base plate (1), and a camera (13) is fixedly connected to the top of the mounting plate (12).

4. The aerobics landing cushioning training platform integrating gait analysis according to claim 1, characterized in that, The controller body (14) is fixedly connected to one side of the fixed base plate (1).

5. The aerobics landing cushioning training platform integrating gait analysis according to claim 4, characterized in that, The controller body (14) is communicatively connected to the air compressor (2), solenoid valve (8), pressure sensor (10), and camera (13). The controller body (14) receives the landing pressure signal collected by the pressure sensor (10) and the gait image signal collected by the camera (13). Based on the landing pressure signal and the gait image signal, it generates a buffer control command and adjusts the opening degree of the solenoid valve (8) and the output pressure of the air compressor (2). The controller body (14) calculates the single landing impact characteristic index according to the following formula. and based on Generate the buffer control instructions: in, For the first Pressure sensor number 1 at time The instantaneous pressure value, For a moment Coordinates of the center of pressure on the foot. The preset reference pressure value for the system. For spatial attenuation scale parameters, The duration of a single landing.

6. The aerobics landing cushioning training platform integrating gait analysis according to claim 4, characterized in that, The controller body (14) has a built-in gait analysis module and a buffer adjustment module. The gait analysis module is used to extract the foot landing position and landing angle based on the continuous multi-frame gait images collected by the camera (13), and to calculate the comprehensive gait stability evaluation index. The buffer adjustment module is used to determine the target air pressure value of each airbag (6) based on the foot landing position and landing angle, and adjusts the actual air pressure of each airbag (6) to the target air pressure value by controlling the opening and closing time of the corresponding solenoid valve (8). The gait analysis module calculates the target air pressure value according to the following formula. : in, For the first Impact characteristics index of the second landing. For the first The trajectory vector of the pressure center of the second landing. For the first The average pressure distribution matrix of the second landing. The system's preset ideal reference pressure distribution template, Let be the cross-entropy divergence function. The weighting coefficients and , The system's preset standard pressure center movement speed; Furthermore, the buffer adjustment module determines the target air pressure vector for each airbag according to the following formula. : in, This represents the current actual air pressure vector of the airbag. Let buffer performance be the objective function. The learning rate parameter, For the first Characteristic pressure scale parameters of each airbag.

7. The aerobics landing cushioning training platform integrating gait analysis according to claim 4, characterized in that, The controller body (14) forms a multi-point pressure monitoring loop with each pressure sensor (10); the controller body (14) determines whether the current landing area deviates from the preset training area based on the real-time pressure distribution data fed back by each pressure sensor (10), and adjusts the support stiffness of the airbag (6) at the corresponding position when the deviation is determined.

8. The aerobics landing cushioning training platform integrating gait analysis according to claim 4, characterized in that, The controller body (14) also acquires the peak pressure change rate of each pressure sensor (10) within a unit time and compares the peak pressure change rate with a preset safe change rate threshold; when the peak pressure change rate exceeds the safe change rate threshold, the controller body (14) controls the air compressor (2) to increase the output pressure.

9. The aerobics landing cushioning training platform integrating gait analysis according to claim 4, characterized in that, The controller body (14) stores air pressure configuration parameters corresponding to multiple training modes; the controller body (14) responds to the external input mode selection signal, calls the corresponding air pressure configuration parameters, and controls each solenoid valve (8) to independently adjust the inflation state of each airbag (6) according to the air pressure configuration parameters.

10. The aerobics landing cushioning training platform integrating gait analysis according to claim 4, characterized in that, The controller body (14) also includes a data recording unit and an evaluation unit; the data recording unit records the pressure distribution data and gait data of each landing in a time series; the evaluation unit generates a gait stability evaluation index based on the pressure distribution data and gait data of multiple landings, compares the evaluation index with historical training data, and generates a training effect feedback signal; the evaluation unit calculates the long-term training effect trend prediction value according to the following formula. : in, For the total number of training sessions, For the first Gait stability evaluation index for each training session. To train the initial baseline values, This is the learning efficiency coefficient. For time decay rate parameter, The fatigue effect coefficient is... This is the timescale parameter for fatigue accumulation.

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