Pressure adjusting method and device for kneecap

Abstract

The invention provides a pressure adjusting method and device for a knee pad. The pressure adjusting method comprises the following steps that a database is established; the current pressure value Pn applied by the knee pad is obtained, the current motion state of the knee pad is recognized by the controller, and the maximum allowable pressure Pmax and the minimum allowable pressure Pmin of the current motion state are obtained from the database according to the current motion state; if Pngt; pmax, the controller controls a pressure reducing mechanism of the pressure adjusting device to release pressure; if Pnlt; and Pmin, the controller controls a pressurizing mechanism of the pressure adjusting device to pressurize. By monitoring the pressure data in the kneecap in real time, the working state of the pressure adjusting device is automatically adjusted based on the preset pressure range of each motion state, and dynamic and adjustable support and protection are provided, so that the use requirements in different scenes are met.

Description

Technical Field

[0001] The present invention relates to the technical field of knee pads, and in particular to a method for adjusting the pressure of a knee pad. The present invention also relates to a device for adjusting the pressure of a knee pad. Background Art

[0002] With the development of sports and rehabilitation medicine, knee pads, as an important equipment for protecting the knee joint, are widely used in athletes, the elderly, and people with knee problems. Traditional knee pads usually use elastic materials or fillers to provide fixed support and pressure. However, this method has the following disadvantages: the fixed pressure cannot be adjusted, it cannot be adjusted in real time according to the actual movement situation, and the dynamic adjustment performance is poor; the comfort is poor, and long-term wearing of knee pads with excessive pressure will affect blood circulation; it cannot provide effective support. Since the pressure of the knee pad cannot be adjusted, in some cases, the knee pad may slip due to insufficient pressure, resulting in a slippage problem, especially during strenuous exercise. Summary of the Invention

[0003] The present invention aims to provide a method for adjusting the pressure of a knee pad to overcome the deficiencies in the prior art.

[0004] To solve the above technical problems, the technical solution of the present invention is: a method for adjusting the pressure of a knee pad, wherein a controller and a pressure adjustment device are provided on the knee pad, and the controller controls the pressure adjustment device to realize the pressure adjustment of the knee pad. The pressure adjustment device is a pneumatic adjustment structure; the pressure adjustment method includes the following steps:

[0005] S1. Establish a database. By collecting data, establish a database and set the maximum allowable pressure Pmax and the minimum allowable pressure Pmin corresponding to each motion state.

[0006] S2. Obtain the current pressure value Pn exerted by the knee pad on the human knee through the pressure detection mechanism of the pressure adjustment device. The controller identifies the current motion state of the knee pad and obtains the maximum operating pressure and the minimum allowable pressure of the current motion state from the database according to the current motion state.

[0007] S3. If Pn > Pmax, it means that the pressure exerted by the knee pad on the human knee exceeds the safe range, and the controller controls the pressure relief mechanism of the pressure adjustment device to release pressure; if Pn < Pmin, it means that the pressure exerted by the knee pad on the human knee is lower than the required minimum safe pressure, and the controller controls the pressure increasing mechanism of the pressure adjustment device to increase pressure.

[0008] Furthermore, in the pressure adjustment method of the knee pad, the database also sets an expected pressure value Pe corresponding to each motion state, the difference between the current pressure value of the current motion state and the expected pressure value is the air pressure error Perr, the rate of change of the air pressure error is Perrd, and the calculation formulas of the air pressure error Perr and the air pressure change rate Perrd are as follows:

[0009] Perr=Pn–Pe

[0010] Perrd=1 / Perr

[0011] The controller adopts a compliant impedance control method to control the adjustment speed of the pressure regulating device based on the air pressure error Perr and the air pressure change rate Perrd.

[0012] Furthermore, in the pressure regulation method of the above-mentioned knee pad, when the air pressure error Perr is a positive value, that is, when the current air pressure Pn is greater than the expected pressure value Pe, the controller controls the boosting mechanism of the pressure regulating device to close, and adjusts the decompression speed by controlling the duty cycle of the decompression mechanism of the pressure regulating device.

[0013] Furthermore, in the above-mentioned pressure regulation method of the knee pad, when the air pressure error Perr is a negative value, that is, when the current air pressure Pn is less than the expected pressure value Pe, the controller controls the pressure reducing mechanism of the pressure regulating device to close, and adjusts the boosting speed by controlling the duty cycle of the boosting mechanism of the pressure regulating device.

[0014] Furthermore, in the pressure regulation method of the knee pad, the controller calculates the duty ratio of the pressure reducing mechanism and the pressure increasing mechanism based on the air pressure error Perr and the air pressure change rate Perrd, and the calculation formula is as follows:

[0015] OUTv=Kp×(Perr)2+Kd×Perrd

[0016] Among them, OUTv is the output value of the duty cycle, which is used to determine the duty cycle of the pressure reducing mechanism and the pressure increasing mechanism. Kp is the stiffness coefficient, which reflects the adjustment ability of the system response speed. Kd is the damping coefficient, which affects the flexibility of the system. The controller transmits the generated duty cycle signal to the pressure reducing mechanism control circuit and the pressure increasing mechanism control circuit through the output pin, and finally increases or decreases the air pressure of the pressure regulating device smoothly.

[0017] Furthermore, in the above-mentioned pressure adjustment method of the knee pad, the value range of Kp is 0.5-1, and the value range of Kd is 0-0.1.

[0018] Furthermore, in the above-mentioned method for adjusting the pressure of the knee pad, the controller identifies the current motion state of the knee pad by:

[0019] S21, the three-axis accelerometer on the knee pad acquires the motion data of the knee in real time at a frequency of 100 Hz, and the motion data is the three-axis acceleration {gx, gy, gz}; the acquired data is stored in the controller buffer area, and when the amount of data in the buffer area reaches a specified depth, a data set is obtained, triggering a model operation, and the model includes a database corresponding to each motion state, which is deployed in the controller;

[0020] S22, the controller extracts the characteristic values ​​of the three-axis acceleration in the data set, normalizes the characteristic values, and inputs them into the model in a standardized form. The model uses an integrated decision tree method to calculate the original probability of each motion state;

[0021] S23, the controller performs weighted processing on the calculated original probabilities of the motion states to obtain a final predicted probability, and the motion state with the highest probability is identified as the current motion state.

[0022] Furthermore, in the above-mentioned knee pad pressure adjustment method, the characteristic value of the three-axis acceleration includes the maximum value, minimum value, average value, and standard deviation of the three-axis acceleration; the characteristic value extraction method of the three-axis acceleration is:

[0023] For the X-axis direction, first extract the maximum and minimum values ​​in a column of data, record them as Xmax and Xmin respectively, then calculate the average value Xavg of a column of data and the standard deviation Xstd of the column of data. The calculation formula of the average value Xavg is as follows:

[0024]

[0025] The calculation formula of standard deviation Xstd is as follows:

[0026]

[0027] Where N is the depth of a column of data;

[0028] Then use the same method to extract Ymax, Ymin, Yavg, Ystd in the Y-axis direction and Zmax, Zmin, Zavg, Zstd in the Z-axis direction.

[0029] Furthermore, in the above-mentioned knee pad pressure adjustment method, the weighted processing method comprises the following steps:

[0030] A weighting coefficient table is set according to the probability relationship between the past motion state and the current motion state. The table contains three weighting factors representing the probability relationship between the past motion state and the current motion state. The three weighting factors are W1, W2, and W3, which are arranged from large to small.

[0031] According to the past motion state, the weighted coefficient table is checked to obtain the weighted factor of the current motion state, and then the weighted probability is calculated. The weighted probability calculation formula is as follows:

[0032] P{=P×W

[0033] Among them, i is the sport category, P i is the original probability of motion category i, W i is the weighting factor of motion category i, P i ′ is the weighted probability of motion category i;

[0034] Then the weighted probabilities of all items are normalized, and the normalized calculation formula is as follows:

[0035]

[0036] Among them, P i ” is the normalized final probability of motion category i, j is the category index number, P j ′ is the sum of the weighted probabilities of all motion categories, and k is the total number of categories. After normalization, the final probability of all items is obtained, among which the highest probability result is the current motion state.

[0037] The present invention also provides a pressure regulating device for a knee pad, comprising a protection mechanism, a pressure detection mechanism, a pressurizing mechanism, and a decompressing mechanism, wherein the protection mechanism is an airbag, which protects the knee and supports the knee pad; the pressure detection mechanism is a pressure sensor, which is used to detect the air pressure inside the airbag and feed back the measured value to a controller; the pressurizing mechanism is a miniature air pump, which is used to inflate the airbag; the decompressing mechanism is a solenoid valve, which is used to control the release of the air in the airbag; the controller receives data from the pressure sensor and analyzes the current motion state and the current air pressure state, thereby controlling the operation of the air pump and the solenoid valve to maintain a stable air pressure in the airbag.

[0038] Compared with the prior art, the beneficial effects of the present invention are: by real-time monitoring of the pressure data inside the kneepad, based on the preset pressure range of each motion state, the working state of the pressure regulating device is automatically adjusted to ensure that the kneepad can provide the most suitable pressure and support in any situation, which not only improves the comfort and safety of the kneepad, but also enhances its protective effect on the knee joint. In addition, the pressure can be adjusted according to different motion states, and the adjustment speed can be controlled by duty cycle, so that the air pressure of the pressure regulating device can be smoothly increased or decreased, realizing precise control of the air pressure of the pressure regulating device, ensuring that the air pressure can be intelligently adjusted according to demand, providing dynamic and adjustable support and protection to meet the use requirements in different scenarios, thereby providing users with a better sports experience and higher safety guarantee. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0040] Figure 1 It is a flowchart of the pressure adjustment method for the knee pad of the present invention;

[0041] Figure 2 It is a schematic diagram of the pressure adjustment device for the knee pad of the present invention;

[0042] Figure 3 It is a working flowchart of the pressure adjustment device for the knee pad of the present invention; Specific embodiments

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0044] Embodiment 1

[0045] As Figure 1 shown, a pressure adjustment method for a knee pad. A controller and a pressure adjustment device are provided on the knee pad. The controller controls the pressure adjustment device to achieve the pressure adjustment of the knee pad. The pressure adjustment device is a pneumatic adjustment structure; the pressure adjustment method includes the following steps:

[0046] S1. Establish a database. The database is established by collecting data, and the maximum allowable pressure Pmax, the minimum allowable pressure Pmin, and the expected pressure value Pe corresponding to each motion state are set;

[0047] S2. Obtain the current pressure value Pn exerted by the knee pad on the human knee through the pressure detection mechanism of the pressure adjustment device. The controller identifies the current motion state of the knee pad and obtains the maximum operating pressure and the minimum allowable pressure of the current motion state from the database;

[0048] S3. If Pn > Pmax, it means that the pressure exerted by the knee pad on the human knee exceeds the safety range, and the controller controls the pressure relief mechanism of the pressure adjustment device to relieve pressure; if Pn < Pmin, it means that the pressure exerted by the knee pad on the human knee is lower than the required minimum safety pressure, and the controller controls the pressure increasing mechanism of the pressure adjustment device to increase pressure.

[0049] The database includes the maximum operating pressure, the minimum allowable pressure and the expected pressure value Pe of each part of the motion state; the following table illustrates the maximum operating pressure, the minimum allowable pressure and the expected pressure value Pe of the part of the motion state;

[0050] Table 1:

[0051] grade Movement status Expected air pressure Pe Minimum air pressure Pmin Maximum air pressure Pmax 0 Zero pressure 2kPa 0kPa 5kPa 1 still 10kPa 5kPa 15kPa 2 walk 22kPa 15kPa 28kPa 3 running 32kPa 28kPa 36kPa 4 Climbing stairs 38kPa 36kPa 40kPa

[0052] The controller adopts a compliant impedance control method to control the adjustment speed of the pressure regulating device based on the air pressure error Perr and the air pressure change rate Perrd. The difference between the current pressure value and the expected pressure value in the current motion state is the air pressure error Perr, and the change rate of the air pressure error is Perrd. The calculation formulas of the air pressure error Perr and the air pressure change rate Perrd are as follows:

[0053] Perr=Pn–Pe

[0054] Perrd=1 / Perr

[0055] When the air pressure error Perr is positive, that is, when the current air pressure Pn is greater than the expected pressure value Pe, the controller controls the boost mechanism of the pressure regulating device to close, and adjusts the decompression speed by controlling the duty cycle of the decompression mechanism of the pressure regulating device to ensure rapid decompression while ensuring system stability.

[0056] When the air pressure error Perr is a negative value, that is, when the current air pressure Pn is less than the expected pressure value Pe, the controller controls the pressure reducing mechanism of the pressure regulating device to close, and adjusts the boosting speed by controlling the duty cycle of the boosting mechanism of the pressure regulating device to ensure that the air pressure is restored within a reasonable time, while avoiding excessive pressure caused by excessive air replenishment.

[0057] Among them, based on the air pressure error Perr and the air pressure change rate Perrd, the controller calculates the duty cycle (PMW) of the pressure reducing mechanism and the pressure increasing mechanism. The calculation formula is as follows:

[0058] OUTv=Kp×(Perr)2+Kd×Perrd

[0059] Among them, OUTv is the output value of the duty cycle, which is used to determine the duty cycle of the pressure reducing mechanism and the pressure increasing mechanism. Kp is the stiffness coefficient, which reflects the adjustment ability of the system response speed. The Kp value range is 0.5-1. A larger Kp value can correct the air pressure error faster, but if it is too large, it may cause system instability and oscillation. Kd is the damping coefficient, which affects the compliance of the system. The Kd value range is 0-0.1. A larger Kd value helps to reduce system oscillation and improve control stability.

[0060] The controller transmits the generated duty cycle signal to the pressure reducing mechanism control circuit and the pressure increasing mechanism control circuit through the output pin, which ultimately causes the air pressure of the pressure regulating device to increase or decrease smoothly, thereby achieving precise control of the air pressure of the pressure regulating device, ensuring that the air pressure can be automatically adjusted according to demand, and providing stable and effective support and protection.

[0061] Example 2

[0062] Based on Example 1, the method for the controller to identify the current motion state of the knee pad is:

[0063] S21, the three-axis accelerometer on the knee pad acquires the motion data of the knee in real time at a frequency of 100 Hz, and the motion data is the three-axis acceleration {gx, gy, gz}; the acquired data is stored in the controller buffer area, and when the amount of data in the buffer area reaches a specified depth, a data set is obtained, triggering a model operation, and the model includes a database corresponding to each motion state, which is deployed in the controller;

[0064] S22, the controller extracts the characteristic values ​​of the three-axis acceleration in the data set, normalizes the characteristic values, and inputs them into the model in a standardized form. The model uses an integrated decision tree method to calculate the original probability of each motion state;

[0065] S23, the controller performs weighted processing on the calculated original probabilities of the motion states to obtain a final predicted probability, and the motion state with the highest probability is identified as the current motion state.

[0066] In the above steps, the characteristic values ​​of the three-axis acceleration include the maximum value, minimum value, average value, and standard deviation of the three-axis acceleration; the characteristic value extraction method of the three-axis acceleration is:

[0067] For the X-axis direction, first extract the maximum and minimum values ​​in a column of data, record them as Xmax and Xmin respectively, then calculate the average value Xavg of a column of data and the standard deviation Xstd of the column of data. The calculation formula of the average value Xavg is as follows:

[0068]

[0069] The calculation formula of standard deviation Xstd is as follows:

[0070]

[0071] Where N is the depth of a column of data;

[0072] Then, the same method is used to extract Ymax, Ymin, Yavg, and Ystd in the Y-axis direction and Zmax, Zmin, Zavg, and Zstd in the Z-axis direction. In step S22, the maximum value, minimum value, average value, and standard deviation of the three directions of XYZ, a total of 12 eigenvalues, are normalized and input into the model in a standardized form.

[0073] The weighted processing method in the above steps includes the following steps:

[0074] The weighting coefficient table is set according to the probability relationship between the past motion state and the current motion state. The table contains three weighting factors representing the probability relationship between the past motion state and the current motion state. The three weighting factors are W1, W2, and W3, arranged from large to small. The three weighting factors W1, W2, and W3 are adjustable according to the actual effect. The value range of W1 is 1.5-2.0, the value range of W2 is 1.0-1.5, and the value range of W3 is 0.5-1.0. The specific probability relationship is shown in the weighting coefficient table below;

[0075] Table 2:

[0076]

[0077] According to the past motion state, the weighted coefficient table is checked to obtain the weighted factor of the current motion state, and then the weighted probability is calculated. The weighted probability calculation formula is as follows:

[0078] P=P×W

[0079] Among them, i is the sport category, P i is the original probability of motion category i, W i is the weighting factor of motion category i, P i ′ is the weighted probability of motion category i;

[0080] Then the weighted probabilities of all motion categories are normalized, and the normalization calculation formula is as follows:

[0081]

[0082] Among them, Pi” is the normalized final probability of motion category i, j is the category index number, P j ′ is the sum of the weighted probabilities of all motion categories, and k is the total number of categories. After normalization, the final probability of all motion categories is obtained, among which the highest probability result is the current motion state.

[0083] For example, if the current user changes from running to walking, the controller's recognition process is as follows:

[0084] First, the controller communicates with the three-axis accelerometer to obtain the three-axis original motion information. After reaching the specified depth, feature extraction is performed to obtain 12 feature data, which are imported into the model for calculation. After the model calculation is completed, the original probability P of 5 specified motion states is output. i ; Assumption: P i ={0.1, 0.4, 0.3, 0.1, 0.1}, which are the original probabilities of stationary, walking, running, climbing stairs and special sports respectively. Let W1 = 2.0, W2 = 1.0, W3 = 0.5, and calculate the weighted probability P i ′={0.2, 0.8, 0.6, 0.05, 0.05}, after normalization, P i "={0.12,0.47,0.35,0.03,0.03},wherein the final probability of walking motion state P"=0.8 / (0.2+0.8+0.6+0.05+0.05)=0.47,the probability of walking 0.47 is the largest,then the system outputs the walking project motion state as the current motion state.

[0085] Example 3

[0086] like Figure 2-3 As shown, the present invention also provides a pressure regulating device for a knee pad, comprising a protection mechanism, a pressure detection mechanism, a pressurizing mechanism, and a decompressing mechanism, wherein the protection mechanism is an airbag, which protects the knee and supports the kneepad; the pressure detection mechanism is a pressure sensor, which is used to detect the air pressure inside the airbag and feed back the measured value to a controller; the pressurizing mechanism is a micro air pump, which is used to inflate the airbag; the decompressing mechanism is a solenoid valve, which is used to control the release of the air in the airbag; the controller is a microcontroller MCU, which controls the operation of the air pump and the solenoid valve by receiving data from the pressure sensor and analyzing the current motion state and the current air pressure state, so as to maintain a stable air pressure in the airbag.

[0087] The working method of the pressure regulating device is as follows:

[0088] The current pressure value Pn applied by the knee brace to the human knee is obtained through the pressure sensor, and the controller identifies the current motion state of the knee brace, and obtains the maximum operating pressure Pmax, the minimum allowable pressure Pmin and the expected pressure value Pe of the current motion state from the database according to the current motion state;

[0089] If Pn > Pmax, it indicates that the pressure inside the airbag has exceeded the safe range, there is a risk of over-inflation, and the pressure exerted by the knee pad on the human knee exceeds the safe range. The controller controls the solenoid valve to release pressure to prevent the airbag from exerting excessive pressure on the user or damaging the airbag. If Pn < Pmin, it means that the pressure inside the airbag is lower than the required minimum safe pressure, and it may not provide sufficient support or protection for the user. The controller controls the micro air pump to increase the pressure to restore the air pressure to the preset safe range.

[0090] In addition, the controller adopts a compliant impedance control method to control the adjustment speed of the pressure regulating device based on the air pressure error Perr and the air pressure change rate Perrd. The difference between the current pressure value of the current motion state and the desired pressure value Pe is the air pressure error Perr, and the change rate of the air pressure error is Perrd.

[0091] When the air pressure error Perr is positive, that is, when the current air pressure Pn is greater than the desired pressure value Pe, the controller controls the micro air pump to close and releases some gas by adjusting the working state of the solenoid valve, thereby reducing the pressure inside the airbag. The duty cycle of the solenoid valve is controlled to adjust the pressure reduction speed to ensure rapid pressure reduction while ensuring the stability of the system.

[0092] When the air pressure error Perr is negative, that is, when the current air pressure Pn is less than the desired pressure value Pe, the controller controls the solenoid valve to close to prevent gas leakage, and inflates the airbag by increasing the working frequency or time of the air pump to increase the air pressure. The duty cycle of the micro air pump is controlled to adjust the pressure increase speed to ensure that the air pressure is restored within a reasonable time while avoiding excessive pressure caused by over-inflation.

[0093] In the closed-loop control of the air pressure system, the MCU calculates the duty cycles (PWM) of the solenoid valve and the micro air pump based on the air pressure error Perr and the air pressure change rate Perrd through the compliant impedance control method. The calculation formula is as follows:

[0094] OUTv = Kp×(Perr)2 + Kd×Perrd

[0095] Among them, OUTv is the output value of the duty cycle, which is used to determine the duty cycles of the pressure reduction mechanism and the pressure increase mechanism. Kp is the stiffness coefficient, which reflects the adjustment ability of the system response speed. The value range of Kp is 0.5 - 1. A larger Kp value can correct the air pressure error faster, but if it is too large, it may cause the system to be unstable and oscillate. Kd is the damping coefficient, which affects the compliance of the system. The value range of Kd is 0 - 0.1. A larger Kd value helps to reduce system oscillation and improve the stability of control.

[0096] The controller transmits the generated PWM signal to the air pump control circuit and the solenoid valve control circuit through the output pin. Ultimately, the air pressure in the airbag increases or decreases smoothly, achieving precise control of the air pressure and ensuring that the air pressure can be intelligently adjusted according to demand to provide stable and effective support and protection.

[0097] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0098] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for adjusting pressure of a knee pad, characterized in that: The knee guard is provided with a pressure regulating device which is a pneumatic regulating structure, and the pressure regulating method includes the following steps: S1. Establish a database. By collecting data, establish a database and set the maximum allowable pressure Pmax and the minimum allowable pressure Pmin corresponding to each motion state; S2. Obtain the current pressure value Pn exerted by the knee guard on the human knee through the pressure detection mechanism of the pressure regulating device. The controller identifies the current motion state of the knee guard and obtains the maximum operating pressure and the minimum allowable pressure of the current motion state from the database according to the current motion state; S3. If Pn > Pmax, it means that the pressure exerted by the knee guard on the human knee exceeds the safe range, and the controller controls the pressure relief mechanism of the pressure regulating device to release pressure; if Pn < Pmin, it means that the pressure exerted by the knee guard on the human knee is lower than the required minimum safe pressure, and the controller controls the pressure boosting mechanism of the pressure regulating device to boost pressure.

2. The pressure adjustment method of the kneepad according to claim 1, characterized in that: In the database, the expected pressure value Pe corresponding to each motion state is also set. The difference between the current pressure value and the expected pressure value in the current motion state is the pneumatic error Perr, and the change rate of the pneumatic error is Perrd. The calculation formulas of the pneumatic error Perr and the pneumatic change rate Perrd are as follows: Perr = Pn – Pe Perrd = 1 / Perr The controller adopts a compliant impedance control method to control the adjustment speed of the pressure regulating device based on the pneumatic error Perr and the pneumatic change rate Perrd.

3. The pressure adjustment method of the kneepad according to claim 2, characterized in that: When the pneumatic error Perr is positive, the controller controls the pressure boosting mechanism of the pressure regulating device to close and adjusts the pressure relief speed by controlling the duty cycle of the pressure relief mechanism of the pressure regulating device.

4. The pressure adjustment method of the kneepad according to claim 3, characterized in that: When the pneumatic error Perr is negative, the controller controls the pressure relief mechanism of the pressure regulating device to close and adjusts the pressure boosting speed by controlling the duty cycle of the pressure boosting mechanism of the pressure regulating device.

5. The method for adjusting the pressure of a knee pad according to claim 4, characterized in that: Based on the pneumatic error Perr and the pneumatic change rate Perrd, the controller calculates the duty cycles of the pressure relief mechanism and the pressure boosting mechanism. The calculation formula is as follows: OUTV=Kp×(Perr) 2 +Kd×Perrd Among them, OUTv is the output value of the duty cycle, which is used to determine the duty cycles of the pressure relief mechanism and the pressure boosting mechanism. Kp is the stiffness coefficient, which reflects the adjustment ability of the system response speed. Kd is the damping coefficient, which affects the compliance of the system. The controller transmits the generated duty cycle signal to the pressure relief mechanism control circuit and the pressure boosting mechanism control circuit through the output pin, and finally makes the air pressure of the pressure regulating device increase or decrease compliantly.

6. The method for adjusting the pressure of a kneepad according to claim 5, characterized in that: The value range of Kp is 0.5 - 1, and the value range of Kd is 0 - 0.

1.

7. The method for adjusting the pressure of a kneepad according to claim 1, characterized in that: The method for the controller to identify the current motion state of the knee guard is: S21. The triaxial accelerometer on the knee guard obtains the motion data of the knee in real time at a frequency of 100Hz. The motion data is the triaxial acceleration {gx, gy, gz}. The collected data is stored in the controller buffer area. When the data volume in the buffer area reaches the specified depth, a data set is obtained and a model operation is triggered. The model includes a database corresponding to each motion state and is deployed in the controller; S22, the controller extracts the characteristic values ​​of the three-axis acceleration in the data set, normalizes the characteristic values, and inputs them into the model in a standardized form. The model uses an integrated decision tree method to calculate the original probability of each motion state; S23, the controller performs weighted processing on the calculated original probabilities of the motion states to obtain a final predicted probability, and the motion state with the highest probability is identified as the current motion state.

8. The method for adjusting the pressure of a knee pad according to claim 7, characterized in that: The characteristic values ​​of the three-axis acceleration include the maximum value, minimum value, average value, and standard deviation of the three-axis acceleration; the characteristic value extraction method of the three-axis acceleration is: For the X-axis direction, first extract the maximum and minimum values ​​in a column of data, record them as Xmax and Xmin respectively, then calculate the average value Xavg of a column of data and the standard deviation Xstd of the column of data. The calculation formula of the average value Xavg is as follows: The calculation formula of standard deviation Xstd is as follows: Where N is the depth of a column of data; Then use the same method to extract Ymax, Ymin, Yavg, Ystd in the Y-axis direction and Zmax, Zmin, Zavg, Zstd in the Z-axis direction.

9. The method for adjusting the pressure of a kneepad according to claim 7, characterized in that: The weighted processing method comprises the following steps: A weighting coefficient table is set according to the probability relationship between the past motion state and the current motion state. The table contains three weighting factors representing the probability relationship between the past motion state and the current motion state. The three weighting factors are W1, W2, and W3, which are arranged from large to small. According to the past motion state, the weighted coefficient table is checked to obtain the weighted factor of the current motion state, and then the weighted probability is calculated. The weighted probability calculation formula is as follows: P′ i =P i ×W i Among them, i is the sport category, P i is the original probability of motion category i, W i is the weighting factor of motion category i, P i ′ is the weighted probability of motion category i; Then the weighted probabilities of all items are normalized, and the normalized calculation formula is as follows: Among them, P i ” is the normalized final probability of motion category i, j is the category index number, P j ′ is the sum of the weighted probabilities of all motion categories, and k is the total number of categories. After normalization, the final probability of all items is obtained, among which the highest probability result is the current motion state.

10. A pressure regulating device for a kneepad, characterized in that: The pressure regulating device is applied to the pressure regulating method of the knee pad described in any one of claims 1 to 9, comprising a protection mechanism, a pressure detection mechanism, a pressurization mechanism, and a decompression mechanism. The protection mechanism is an airbag, which protects the knee and supports the kneepad; the pressure detection mechanism is a pressure sensor, which is used to detect the air pressure inside the airbag and feed back the measured value to the controller; the pressurization mechanism is a micro air pump, which is used to inflate the airbag; the decompression mechanism is a solenoid valve, which is used to control the release of the air in the airbag; the controller receives data from the pressure sensor and analyzes the current motion state and the current air pressure state, thereby controlling the operation of the air pump and the solenoid valve to maintain a stable air pressure in the airbag.

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