Keycap position and state intelligent identification method

Abstract

The invention relates to the technical field of keycap management, and particularly discloses a keycap position and state intelligent identification method, which comprises the following steps of: dividing a keyboard into a plurality of areas according to a preset area, and arranging an electromagnetic sensor at the central point of each area on a keyboard circuit board, so as to obtain electromagnetic data of each keycap correspondingly monitored by each electromagnetic sensor; the wear degree of each key cap is judged; pressure sensors are arranged at the center points of all areas on a keyboard circuit board, the pressing force and frequency of a user corresponding to all key caps are monitored in real time, the current behavior mode of the user is judged accordingly, and then self-adjustment of all the key caps is achieved. The hardness and elasticity of the intelligent keycap can be self-adjusted according to the operation habit of a user, the adaptability greatly enhances the comfort of the keycap, the efficiency is improved, and the satisfaction degree of the user is also improved; fatigue and discomfort of parts such as fingers and wrists can be caused by long-time use of the keyboard, and the discomfort can be effectively relieved by adjusting hardness and elasticity of the intelligent keycaps.

Description

Technical Field

[0001] The invention belongs to the technical field of key cap management, and relates to a method for intelligently identifying the position and state of a key cap. Background Art

[0002] The hardness and elasticity of traditional keycaps are usually fixed, and this design defect is particularly obvious in actual use by users. Whether in gaming or office environments, users have completely different requirements for the feel of the keyboard. In games, players need to press keys quickly and frequently, requiring the keycaps to have high elasticity to enable quick response and reduce key fatigue.

[0003] However, fixed hardness and elasticity often cannot meet this demand, causing players to feel slow button response during intense gaming, affecting gaming performance. Relatively speaking, in office scenarios, users prefer a stable and accurate input experience. Fixed keycap hardness may lead to insufficient button feedback, increase the risk of mispressing, and affect work efficiency. Therefore, traditional keycaps cannot adapt to the usage requirements in different scenarios, limiting the user's input experience, causing many users to feel uncomfortable when using them for a long time, and may even cause hand fatigue and other health problems. This design limitation calls for more flexible and intelligent solutions to meet user needs in diverse usage scenarios. Summary of the invention

[0004] In view of the problems existing in the above prior art, the present invention has developed a keycap with intelligent material characteristics, which can self-adjust hardness and elasticity according to the pressing force and frequency. By embedding intelligent materials, the keycap can automatically adjust its hardness and elasticity according to the user's operating habits and needs when pressed with different forces, so as to improve the comfort and accuracy of input. For example, in game mode, the keycap can enhance elasticity to increase response speed, and in office mode, it can increase hardness to improve input stability. It is used to solve the above technical problems.

[0005] In order to achieve the above purpose and other purposes, the technical solution adopted by the present invention is as follows: The present invention provides a key cap position and state intelligent recognition method, the method comprising the following steps: Step 1: Divide the keyboard into multiple areas according to a preset area, and arrange electromagnetic sensors at the center points of each area on the keyboard circuit board, thereby obtaining electromagnetic data of each keycap monitored by each electromagnetic sensor, and then determining the degree of wear of each keycap; Step 2: embed smart materials in each keycap, and place pressure sensors at the center of each area on the keyboard circuit board to monitor the user's pressing force and frequency of each keycap in real time, thereby determining the user's current behavior pattern and achieving self-adjustment of each keycap.

[0006] Exemplarily, the electromagnetic data of each keycap monitored by each electromagnetic sensor includes changes in pressing intensity, pressing frequency, and waveform signal over time.

[0007] Exemplarily, the changes of the pressing intensity, pressing frequency and waveform signal of each keycap monitored by each electromagnetic sensor over time are obtained, and the specific acquisition process is: Obtain the total number of keycaps monitored by each electromagnetic sensor, and number each keycap monitored by each electromagnetic sensor in sequence; According to the positions of the electromagnetic sensors and the positions of the key caps in the keyboard, the distance between each electromagnetic sensor and the corresponding key caps to be monitored is obtained, which is recorded as , where i is the number of each electromagnetic sensor, i = 1,2, ... M, j is the number of each keycap corresponding to the monitoring; Calculate the weight of each electromagnetic sensor and the corresponding keycap monitored , where k is the distance attenuation index, which is used to describe the attenuation of signal strength with distance; The pressing strength of each key cap monitored by each electromagnetic sensor is calculated accordingly. ,in is the electromagnetic signal strength detected by the i-th electromagnetic sensor; Calculate the pressing frequency of each keycap monitored by each electromagnetic sensor ,in is the key frequency detected by the i-th electromagnetic sensor; Calculate the change of the waveform signal of each key cap monitored by each electromagnetic sensor over time ,in is the change of the waveform signal detected by the i-th electromagnetic sensor over time.

[0008] Exemplarily, the specific judgment logic for judging the degree of wear of each keycap is: Degree of wear of each keycap The definition formula is shown below: , where d is the number of all keycaps corresponding to each keycap; is the initial wear resistance of the d-th keycap, is the instantaneous wear rate of keycap d at time t; The cumulative usage time of the d-th keycap, in seconds.

[0009] Exemplarily, the calculation formula for the instantaneous wear rate of the keycap d at time t is as follows: ; In the above formula, α1, α2, α3 and α4 represent the set weight coefficients respectively. They represent the key triggering frequency and pressing force of key cap d at time t, is the waveform change of keycap d at time t, is the influence of thermodynamic effect on wear of keycap d at time t; in , is the waveform of keycap d at time t, is the waveform of key cap d at the initial time point; , e is a natural constant, and λ is the thermal attenuation coefficient.

[0010] Exemplarily, the user's current behavior mode is divided into a non-game mode and a game mode.

[0011] Exemplarily, the decision logic for determining the user's current behavior mode is: Through the set behavior judgment model δ=δ1*A1+δ2*A2+δ3*A3+δ4*A4, the user's current behavior score δ is obtained through comprehensive judgment, where δ1, δ2, δ3 and δ4 represent the corresponding weights of the set calculation features, and the sum of δ1, δ2, δ3 and δ4 is 1; A1 is the key usage frequency feature, which obtains the total number of key presses on the user's current keyboard and the number of presses of each game-related key, and accumulates and sums the number of presses of each game-related key to obtain the total number of presses of the game-related keys; The total number of times the keys on the keyboard are pressed is used as the denominator of the fraction, and the total number of times the keys related to the game are pressed is used as the numerator of the fraction. The fraction is solved to obtain the user's current usage frequency characteristics; Obtain the pressing pressure value of each key on the user's current keyboard, sum and average the pressing pressure values ​​of each key on the user's current keyboard, and obtain the user's current key pressure feature A2; Obtain the duration of each key pressed by the user on the current keyboard, sum and average the duration of each key pressed by the user on the current keyboard, and obtain the user's current key pressing duration feature A3; A4 is the current key interval time characteristic of the user. , h is the number of times each key is pressed, h=1,2,...N, N is the total number of times the key is pressed, The timestamps of the h+1th and hth key presses respectively; The user's current behavior score δ is compared with the score threshold corresponding to the preset game mode. If the user's current behavior score δ is greater than or equal to the score threshold corresponding to the preset game mode, the user's current behavior mode is determined to be a game mode; otherwise, the user's current behavior mode is determined to be a non-game mode.

[0012] Exemplarily, if it is identified that the user's current behavior mode is a non-gaming mode, the self-adjustment process of each keycap includes: Collect the average pressing force and usage frequency of each keycap of the user over the past period of time, and then calculate the influencing factor value of the user's historical pressing data corresponding to each keycap , are the average pressing force and usage frequency of the keycap corresponding to the d-th keycap by the user in the past period of time; Collect the current average key usage rate and current average key pressure of each key cap of the user in the non-gaming mode, and record them as , use the inverse proportional function to evaluate the current usage status characteristics of each keycap ; The estimated adjustment hardness value of each keycap is calculated from this , YD is the basic hardness value of the keycap, is the wear degree of the d-th keycap; The estimated adjustment hardness value of each keycap is fed back to the keyboard background terminal, and then the background terminal adjusts the corresponding hardness of each keycap in turn.

[0013] Exemplarily, if it is identified that the user's current behavior mode is a game mode, the self-adjustment process of each keycap includes: Calculate the expected adjustment elasticity value of each keycap , TX is the basic elasticity value of the keycap; , is the impact factor of the user's historical key data corresponding to the d-th keycap, is the historical average key duration of the user corresponding to the d-th keycap, is the set key-press time threshold, μ is the parameter that controls the steepness of the curve; , is the current dynamic response characteristic of the d-th keycap, is the current response change corresponding to the d-th keycap, and μ1 is the influence coefficient of the response change; , CS is the total number of times the game-related buttons are pressed; The estimated adjustment elasticity value of each key cap is fed back to the keyboard background terminal, and then the background terminal adjusts the corresponding elasticity value of each key cap in turn.

[0014] As described above, the keycap position and state intelligent recognition method provided by the present invention has at least the following beneficial effects: The keycap position and state intelligent identification method provided by the present invention is to divide the keyboard into multiple areas according to the preset area, arrange electromagnetic sensors at the center points of each area on the keyboard circuit board, thereby obtaining the electromagnetic data of each keycap monitored by each electromagnetic sensor, and then judging the degree of wear of each keycap; arrange pressure sensors at the center points of each area on the keyboard circuit board, monitor the pressing force and frequency of each keycap in real time, thereby judging the current behavior mode of the user, and then realizing the self-adjustment of each keycap; first, the intelligent keycap can self-adjust the hardness and elasticity according to the user's operating habits, and this adaptability greatly enhances the comfort of the keycap. For different users, there are significant differences in keystroke force and frequency. In game mode, users usually need to press keys quickly and frequently, and enhanced elasticity can provide better response speed and reduce keystroke fatigue; while in office mode, users prefer stable and accurate input, and increased hardness can improve the stability and accuracy of input. Such adaptive characteristics enable the keycap to be optimized according to actual needs and improve the overall user experience; secondly, the application of this intelligent material can reduce the user's learning cost and adaptation time. Traditional keycaps often require users to select and adjust them according to their own habits, while smart keycaps can automatically adapt to the user's input style, reducing the switching cost of users in different scenarios. For example, when users frequently switch between games and office work, smart keycaps can automatically switch to the most suitable hardness and elasticity settings without manual adjustment, which not only improves efficiency but also improves user satisfaction; in addition, long-term use of the keyboard may cause fatigue and discomfort in the fingers, wrists and other parts. Smart keycaps can effectively reduce this discomfort by adjusting hardness and elasticity, and reduce the risk of occupational diseases caused by improper use. Especially in the case of long-term office or game work, smart keycaps can provide a more humane design to help users maintain a more comfortable posture, thereby protecting the user's health. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0016] Figure 1 It is a schematic diagram of the connection of each step of the method of the present invention. DETAILED DESCRIPTION

[0017] The above contents in combination with the implementation of the present invention are merely examples and explanations of the concept of the present invention. The technical personnel in the relevant technical field may make various modifications or supplements to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention. Example

[0018] See also Figure 1 As shown, a key cap position and state intelligent recognition method comprises the following steps: Step 1: Divide the keyboard into multiple areas according to a preset area, and arrange electromagnetic sensors at the center points of each area on the keyboard circuit board, thereby obtaining electromagnetic data of each keycap monitored by each electromagnetic sensor, and then determining the degree of wear of each keycap; Step 2: embed smart materials in each keycap, and place pressure sensors at the center of each area on the keyboard circuit board to monitor the user's pressing force and frequency of each keycap in real time, thereby determining the user's current behavior pattern and achieving self-adjustment of each keycap.

[0019] It should be added that the development of a keycap with intelligent material characteristics that can self-adjust hardness and elasticity according to the pressing force and frequency has significant innovation and practical value. The core of this technology is to use the characteristics of intelligent materials to enable the keycap to respond to the user's operating habits and needs in real time, thereby providing a more personalized and comfortable input experience. In the market, some high-end gaming keyboards have adopted adjustable keycap feedback technology. In summary, the development of keycaps with intelligent material characteristics can not only enhance the user's input experience and meet the needs of different scenarios, but also reduce learning costs and reduce the risk of occupational diseases. It has significant market potential and application value, and promotes the development of input devices towards higher intelligence and personalization.

[0020] On the basis of the above-mentioned embodiment, the electromagnetic data of each keycap monitored by each electromagnetic sensor includes the change of the pressing intensity, pressing frequency and waveform signal over time.

[0021] On the basis of the above embodiment, the pressing intensity, pressing frequency and waveform signal changes of each key cap monitored by each electromagnetic sensor are obtained over time. The specific acquisition process is as follows: Obtain the total number of keycaps monitored by each electromagnetic sensor, and number the keycaps monitored by each electromagnetic sensor in sequence, numbering them 1, 2, ...j, ...M respectively; According to the positions of the electromagnetic sensors and the positions of the key caps in the keyboard, the distance between each electromagnetic sensor and the corresponding key caps to be monitored is obtained, which is recorded as , where i is the number of each electromagnetic sensor, i = 1,2, ... M, j is the number of each keycap corresponding to the monitoring; Calculate the weight of each electromagnetic sensor and the corresponding keycap monitored , where k is the distance attenuation index, which is used to describe the attenuation of signal strength with distance, and k is usually taken as 2; When k=2, the signal strength decays in accordance with the inverse square law. This is a typical attenuation law of point source signals in free space (such as electromagnetic waves or sound waves); when k>2: it means that the signal decays faster and may be affected by additional environmental factors (such as interference, damping or shielding); when k<2: it means that the signal decays slowly, which may be due to reflection, refraction and other phenomena in the signal propagation path; In the calculation formula of the weight of each electromagnetic sensor and the corresponding key cap monitored, The reciprocal of is used to reflect the influence of distance on signal contribution. The specific meaning is: The closer the distance ( The smaller the weight The larger the value, the more significant the contribution of sensor i to the signal of key cap j; the farther the distance ( The larger the weight The smaller it is, the smaller the contribution of sensor i to the signal of key cap j is; The pressing strength of each key cap monitored by each electromagnetic sensor is calculated accordingly. ,in is the electromagnetic signal strength detected by the i-th electromagnetic sensor; Calculate the pressing frequency of each keycap monitored by each electromagnetic sensor ,in is the key frequency detected by the i-th electromagnetic sensor; Calculate the change of the waveform signal of each key cap monitored by each electromagnetic sensor over time ,in is the change of the waveform signal detected by the i-th electromagnetic sensor over time.

[0022] Based on the above embodiment, the specific judgment logic for judging the degree of wear of each key cap is: Degree of wear of each keycap The definition formula is shown below: , where d is the number of all keycaps corresponding to each keycap; is the initial wear resistance of the d-th keycap, is the instantaneous wear rate of keycap d at time t; The cumulative usage time of the d-th keycap, in seconds.

[0023] Based on the above embodiment, the calculation formula of the instantaneous wear rate of the key cap d at time t is as follows: ; In the above formula, α1, α2, α3 and α4 represent the set weight coefficients respectively. They represent the key triggering frequency and pressing force of key cap d at time t, is the waveform change of keycap d at time t, is the influence of thermodynamic effect on wear of keycap d at time t; in , is the waveform of keycap d at time t, is the waveform of key cap d at the initial time point; Waveform of keycap d at time t It is a dynamic signal captured by the sensor, reflecting the electromagnetic or mechanical properties of the keycap during the pressing and releasing process. These waveform data contain the following information: speed, force and duration of keystrokes; The dynamic process of key triggering (such as the elastic response of the key); Changes in the signal between the keycap and the sensor (may be related to wear and aging); Since the wear of the keycap will cause its physical properties (such as shape, surface friction coefficient, reset elasticity, etc.) to change, this change will be directly or indirectly reflected in the characteristics of the waveform. Therefore, the current waveform It is an important dynamic parameter that reflects the instantaneous state of the keycap d; In the above calculation formula, Multiple characteristic parameters (such as amplitude, frequency, waveform duration, slope, etc.) can be extracted through signal processing technology, and these characteristics can be used as input parameters for wear calculation. For example: Maximum amplitude change: reflects the change of pressing force; The width of the waveform: reflects the response time of the key; Frequency components of the waveform: reflects the vibration characteristics of the key.

[0024] , e is a natural constant, and λ is the thermal attenuation coefficient.

[0025] The above formulas for the degree of wear of each keycap not only take into account the frequency of use and pressing force of the keycap, but also introduce dynamic factors such as waveform changes and thermodynamic effects. Pressing force and waveform changes can reflect the user's keystroke strength and operating habits, while thermodynamic effects capture the microscopic fatigue that may occur in the keycap material due to long-term use. This comprehensiveness enables the formula to capture the multi-faceted characteristics of keycap wear, rather than simply relying on a single variable; Since the formula introduces the initial wear resistance of the keycap material and the spatial weighted distribution of the sensor signal, it can perform personalized analysis for different keycap areas, material properties, and user behaviors. For example, some keycaps may be more susceptible to wear due to their softer materials, while some areas may be more susceptible to aging due to high-frequency use by users. By introducing these parameters, the formula can provide accurate wear assessment for different keycaps.

[0026] In modern keyboard design, users have higher and higher requirements for keyboard durability and consistency of feel. Traditional wear assessment methods (such as simply counting the number of key presses) can no longer meet this demand because they cannot capture the differences in keycap wear caused by different user behaviors and pressing forces. The above formula can more accurately assess the wear of keycaps through multi-dimensional modeling, providing more reliable data support for keyboard design and optimization.

[0027] Based on the above embodiment, the user's current behavior mode is divided into a non-game mode and a game mode.

[0028] Based on the above embodiment, the decision logic for determining the user's current behavior mode is: Through the set behavior judgment model δ=δ1*A1+δ2*A2+δ3*A3+δ4*A4, the user's current behavior score δ is obtained through comprehensive judgment, where δ1, δ2, δ3 and δ4 represent the corresponding weights of the set calculation features, and the sum of δ1, δ2, δ3 and δ4 is 1; A1 is the key usage frequency feature, which obtains the total number of key presses on the user's current keyboard and the number of presses of each game-related key, and accumulates and sums the number of presses of each game-related key to obtain the total number of presses of the game-related keys; It should be added that the game-related keys include but are not limited to the "A" key, the "S" key, the "D" key, the "W" key or the space bar; The total number of times the keys on the keyboard are pressed is used as the denominator of the fraction, and the total number of times the keys related to the game are pressed is used as the numerator of the fraction. The fraction is solved to obtain the user's current usage frequency characteristics; Obtain the pressing pressure value of each key on the user's current keyboard, sum and average the pressing pressure values ​​of each key on the user's current keyboard, and obtain the user's current key pressure feature A2; Obtain the duration of each key pressed by the user on the current keyboard, sum and average the duration of each key pressed by the user on the current keyboard, and obtain the user's current key pressing duration feature A3; A4 is the current key interval time characteristic of the user. , h is the number of times each key is pressed, h=1,2,...N, N is the total number of times the key is pressed, The timestamps of the h+1th and hth key presses respectively; The user's current behavior score δ is compared with the score threshold corresponding to the preset game mode. If the user's current behavior score δ is greater than or equal to the score threshold corresponding to the preset game mode, the user's current behavior mode is determined to be a game mode; otherwise, the user's current behavior mode is determined to be a non-game mode.

[0029] On the basis of the above embodiment, if it is identified that the user's current behavior mode is a non-gaming mode, the self-adjustment process of each keycap includes: Collect the average pressing force and usage frequency of each keycap of the user over the past period of time, and then calculate the influencing factor value of the user's historical pressing data corresponding to each keycap , are the average pressing force and usage frequency of the keycap corresponding to the d-th keycap by the user in the past period of time; Collect the current average key usage rate and current average key pressure of each key cap of the user in the non-gaming mode, and record them as , use the inverse proportional function to evaluate the current usage status characteristics of each keycap ; The estimated adjustment hardness value of each keycap is calculated from this , YD is the basic hardness value of the keycap, is the wear degree of the d-th keycap; The estimated adjustment hardness value of each keycap is fed back to the keyboard background terminal, and then the background terminal adjusts the corresponding hardness of each keycap in turn.

[0030] By comprehensively considering the user's historical behavior and current status, this formula makes the adjustment of keycap hardness more personalized. Different users have significant differences in usage habits, pressing force and frequency. Personalized hardness adjustment can improve user satisfaction and comfort. In non-gaming mode, increasing the hardness of the keycap can effectively reduce misoperation and unnecessary input fluctuations. This is especially important for office users because they usually need higher input accuracy and stability. By accurately adjusting the hardness, users can maintain a good feel and reduce fatigue during long-term input; at the same time, proper hardness adjustment can slow down the wear of the keycap. Keycaps that are too soft or too hard will accelerate wear and shorten their service life. By dynamically adjusting the hardness, the service life of the keycap can be extended while ensuring user experience, and the replacement frequency can be reduced, thereby saving costs.

[0031] On the basis of the above embodiment, if it is identified that the user's current behavior mode is a game mode, the self-adjustment process of each keycap includes: Calculate the expected adjustment elasticity value of each keycap , TX is the basic elasticity value of the keycap; , is the impact factor of the user's historical key data corresponding to the d-th keycap, is the historical average key duration of the user corresponding to the d-th keycap, is the set key-press time threshold, μ is the parameter that controls the steepness of the curve; , is the current dynamic response characteristic of the d-th keycap, is the current response change corresponding to the d-th keycap, and μ1 is the influence coefficient of the response change; , CS is the total number of times the game-related keys are pressed, and σ3 is the user's current key usage coefficient; The estimated adjustment elasticity value of each key cap is fed back to the keyboard background terminal, and then the background terminal adjusts the corresponding elasticity value of each key cap in turn.

[0032] The above elasticity calculation formula provides an innovative method for setting the keycap elasticity, combining the user's historical keystroke data, the dynamic response characteristics of the current keycap, and the user's current usage mode. The advantage of this method is that it can achieve more refined and personalized keycap elasticity adjustment, thereby improving the user's overall experience, especially in gaming mode, where the response speed requirements are more stringent; First, the formula processes the user's historical key data through fuzzy logic, so that the elastic adjustment can adapt to the usage habits of different users. This nonlinear processing method can better reflect the user's key behavior in different situations, so that the elastic setting is more in line with the actual usage. For example, some users may have a higher key frequency and a shorter key duration in the game, and this difference can be effectively captured by fuzzy logic; Secondly, the dynamic response characteristics of the current keycaps are calculated using an inverse proportional function, which can reflect the response changes of the keycaps in real time during use. This is especially important for gamers, because in an intense gaming environment, the response speed of the keycaps directly affects the gaming performance. By dynamically adjusting the elasticity, users can get faster feedback in fast-changing games, thereby improving the accuracy and smoothness of operations; Furthermore, the introduction of the user's current key usage coefficient allows the elastic setting to better adapt to the user's actual needs. By processing the logarithm of the number of times game-related keys are used, we can effectively evaluate the user's usage frequency and then adjust the elasticity to meet different usage scenarios; Finally, the necessity of adopting this comprehensive computing method is that it can improve user satisfaction and loyalty. Modern users have increasingly higher demands for personalized devices, and simple hardware settings can no longer meet their expectations. Through this flexible setting based on user behavior and historical data, manufacturers can provide more competitive products, attract more users, and gain an advantage in the market.

[0033] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0034] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0035] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0036] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A key cap position and state intelligent recognition method, characterized in that: include: Step 1: Divide the keyboard into multiple areas according to a preset area, and arrange electromagnetic sensors at the center points of each area on the keyboard circuit board, thereby obtaining electromagnetic data of each keycap monitored by each electromagnetic sensor, and then determining the degree of wear of each keycap; Step 2: embed smart materials in each keycap, and place pressure sensors at the center of each area on the keyboard circuit board to monitor the user's pressing force and frequency of each keycap in real time, thereby determining the user's current behavior pattern and achieving self-adjustment of each keycap.

2. The keycap position and state intelligent recognition method according to claim 1, characterized in that: The electromagnetic data of each keycap monitored by each electromagnetic sensor includes changes in pressing intensity, pressing frequency, and waveform signal over time.

3. The keycap position and state intelligent recognition method according to claim 1, characterized in that: The changes of the pressing intensity, pressing frequency and waveform signal of each key cap monitored by each electromagnetic sensor over time are obtained. The specific acquisition process is as follows: Obtain the total number of keycaps monitored by each electromagnetic sensor, and number each keycap monitored by each electromagnetic sensor in sequence; According to the positions of the electromagnetic sensors and the positions of the key caps in the keyboard, the distance between each electromagnetic sensor and the corresponding key caps to be monitored is obtained, which is recorded as , where i is the number of each electromagnetic sensor, i = 1,2, ... M, j is the number of each keycap corresponding to the monitoring; Calculate the weight of each electromagnetic sensor and the corresponding keycap monitored , where k is the distance attenuation index, which is used to describe the attenuation of signal strength with distance; The pressing strength of each key cap monitored by each electromagnetic sensor is calculated accordingly. ,in is the electromagnetic signal strength detected by the i-th electromagnetic sensor; Calculate the pressing frequency of each keycap monitored by each electromagnetic sensor ,in is the key frequency detected by the i-th electromagnetic sensor; Calculate the change of the waveform signal of each key cap monitored by each electromagnetic sensor over time ,in is the change of the waveform signal detected by the i-th electromagnetic sensor over time.

4. The keycap position and state intelligent recognition method according to claim 1, characterized in that: The specific judgment logic for judging the degree of wear of each keycap is: Degree of wear of each keycap The definition formula is shown below: , where d is the number of all keycaps corresponding to each keycap; is the initial wear resistance of the d-th keycap, is the instantaneous wear rate of keycap d at time t; The cumulative usage time of the d-th keycap, in seconds.

5. The keycap position and state intelligent identification method according to claim 1, characterized in that: The calculation formula for the instantaneous wear rate of keycap d at time t is as follows: ； In the above formula, α1, α2, α3 and α4 represent the set weight coefficients respectively. They represent the key triggering frequency and pressing force of key cap d at time t, is the waveform change of keycap d at time t, is the influence of thermodynamic effect on wear of keycap d at time t; in , is the waveform of keycap d at time t, is the waveform of key cap d at the initial time point; , e is a natural constant, and λ is the thermal attenuation coefficient.

6. The keycap position and state intelligent identification method according to claim 1, characterized in that: Users' current behavior modes are divided into non-gaming mode and gaming mode.

7. The keycap position and state intelligent identification method according to claim 6, characterized in that: The decision logic for determining the user's current behavior mode is: Through the set behavior judgment model δ=δ1*A1+δ2*A2+δ3*A3+δ4*A4, the user's current behavior score δ is obtained through comprehensive judgment, where δ1, δ2, δ3 and δ4 represent the corresponding weights of the set calculation features, and the sum of δ1, δ2, δ3 and δ4 is 1; A1 is the key usage frequency feature, which obtains the total number of key presses on the user's current keyboard and the number of presses of each game-related key, and accumulates and sums the number of presses of each game-related key to obtain the total number of presses of the game-related keys; The total number of times the keys on the keyboard are pressed is used as the denominator of the fraction, and the total number of times the keys related to the game are pressed is used as the numerator of the fraction. The fraction is solved to obtain the user's current usage frequency characteristics; Obtain the pressing pressure value of each key on the user's current keyboard, sum and average the pressing pressure values ​​of each key on the user's current keyboard, and obtain the user's current key pressure feature A2; Obtain the duration of each key pressed by the user on the current keyboard, sum and average the duration of each key pressed by the user on the current keyboard, and obtain the user's current key pressing duration feature A3; A4 is the current key interval time characteristic of the user. , h is the number of times each key is pressed, h=1,2,...N, N is the total number of times the key is pressed, The timestamps of the h+1th and hth key presses respectively; The user's current behavior score δ is compared with the score threshold corresponding to the preset game mode. If the user's current behavior score δ is greater than or equal to the score threshold corresponding to the preset game mode, the user's current behavior mode is determined to be a game mode; otherwise, the user's current behavior mode is determined to be a non-game mode.

8. The keycap position and state intelligent identification method according to claim 6, characterized in that: If the user's current behavior mode is identified as non-gaming mode, the self-adjustment process of each keycap includes: Collect the average pressing force and usage frequency of each keycap of the user over the past period of time, and then calculate the influencing factor value of the user's historical pressing data corresponding to each keycap , are the average pressing force and usage frequency of the keycap corresponding to the d-th keycap by the user in the past period of time; Collect the current average key usage rate and current average key pressure of each key cap of the user in the non-gaming mode, and record them as , use the inverse proportional function to evaluate the current usage status characteristics of each keycap ; The estimated adjustment hardness value of each keycap is calculated from this , YD is the basic hardness value of the keycap, is the wear degree of the d-th keycap; The estimated adjustment hardness value of each keycap is fed back to the keyboard background terminal, and then the background terminal adjusts the corresponding hardness of each keycap in turn.

9. The keycap position and state intelligent identification method according to claim 6, characterized in that: If the user's current behavior mode is identified as a gaming mode, the self-adjustment process of each keycap includes: Calculate the expected adjustment elasticity value of each keycap , TX is the basic elasticity value of the keycap; , is the impact factor of the user's historical key data corresponding to the d-th keycap, is the historical average key duration of the user corresponding to the d-th keycap, is the set key-press time threshold, μ is the parameter that controls the steepness of the curve; , is the current dynamic response characteristic of the d-th keycap, is the current response change corresponding to the d-th keycap, and μ1 is the influence coefficient of the response change; , CS is the total number of times the game-related keys are pressed, and σ3 is the user's current key usage coefficient; The estimated adjustment elasticity value of each key cap is fed back to the keyboard background terminal, and then the background terminal adjusts the corresponding elasticity value of each key cap in turn.

Images