Method and system for intelligent control of touch pen based on full-bridge strain gauge

Abstract

The application relates to the field of electronic device interaction, and discloses an intelligent control method for a touch pen based on a full-bridge strain gauge, which comprises the following steps: acquiring touch pen use scene information, determining an adaptive full-bridge strain gauge and performing initialization calibration, collecting strain data to calculate a pressure value, combining a touch position to generate an operation instruction, then analyzing the operation instruction to determine a function module to execute an operation, detecting a pen tip action and a transmission signal to generate interaction response data, then analyzing feedback parameters of the interaction response data, identifying abnormal operation characteristics and calculating a misoperation probability, optimizing full-bridge strain gauge data based on the misoperation probability, analyzing touch operation habits corresponding to the optimized data, and further formulating a touch pen control scheme. The application can improve the control fluency of the touch pen in electronic device interaction.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of electronic device interaction, and in particular to a smart control method and system for a touch pen based on a full-bridge strain gauge. BACKGROUND

[0002] In today's electronic device interaction field, with the rapid development of technology and the continuous improvement of user operation experience requirements, as an important input tool, the optimization of the function and performance of the touch pen becomes crucial. The touch pen is widely used in electronic devices such as tablet computers and smartphones, providing users with a more precise and convenient operation method, especially in drawing, writing, and annotation scenarios.

[0003] Currently, the traditional touch pen control method is relatively simple, mainly through basic pressure sensing or capacitive sensing to realize basic writing and operation functions. However, this approach has many limitations. On the one hand, the traditional method is not accurate and comprehensive in recognizing the actions and postures of the touch pen, making it difficult to meet the needs of users in complex operation scenarios. For example, when performing fine drawing or rapid writing, it is difficult to accurately capture the subtle changes in user actions, affecting the smoothness and accuracy of the operation. On the other hand, the traditional control method lacks intelligent interaction mechanisms and cannot adapt to user habits and specific scenarios, reducing the smoothness of user experience. Therefore, a smart control method for a touch pen based on a full-bridge strain gauge is needed to improve the control smoothness of the touch pen in electronic device interaction. SUMMARY

[0004] The present application provides a smart control method and system for a touch pen based on a full-bridge strain gauge, which aims to improve the control smoothness of the touch pen in electronic device interaction.

[0005] To achieve the above purpose, the smart control method for a touch pen based on a full-bridge strain gauge provided by the present application includes:

[0006] Obtain the usage scenario information of the touch pen, analyze the touch operation requirements in the usage scenario information, determine the full-bridge strain gauge suitable for the touch pen based on the touch operation requirements, install the full-bridge strain gauge at the specified position of the touch pen, and then initialize and calibrate the full-bridge strain gauge to obtain calibration parameters;

[0007] Based on the calibration parameters, real-time collect strain data of the full-bridge strain gauge during touch operation, calculate the pressure value corresponding to the touch pen according to the strain data, and generate operation instructions corresponding to the touch pen based on the pressure value and touch position information corresponding to the touch pen;

[0008] Based on the operation instruction, analyze the function module corresponding to the touch pen, determine the execution operation corresponding to the function module, detect the pen tip action and transmission signal corresponding to the touch pen according to the execution operation, and generate interaction response data corresponding to the touch pen based on the pen tip action and the transmission signal;

[0009] Analyze the feedback parameters corresponding to the interaction response data, identify the abnormal operation characteristics in the feedback parameters, calculate the misoperation probability corresponding to the touch pen based on the abnormal operation characteristics;

[0010] Based on the misoperation probability, the data of the full-bridge strain gauge in the touch operation process is optimized to obtain optimized data, the touch operation habit corresponding to the optimized data is analyzed, and the control scheme corresponding to the touch pen is formulated based on the touch operation habit.

[0011] Optionally, the initialization calibration of the full-bridge strain gauge is performed to obtain the calibration parameter, comprising:

[0012] Query the initial resistance value corresponding to the full-bridge strain gauge;

[0013] According to the initial resistance value, analyze the basic electrical characteristics corresponding to the full-bridge strain gauge;

[0014] Based on the basic electrical characteristics, the full-bridge strain gauge is tested by using a preset standard pressure test device to obtain test data;

[0015] Analyze the deviation value between the test data and the preset standard;

[0016] Based on the deviation value, the full-bridge strain gauge is initialized and calibrated to obtain the calibration parameter.

[0017] Optionally, the real-time acquisition of the strain data of the full-bridge strain gauge in the touch operation process based on the calibration parameter comprises:

[0018] Query the parameter frequency corresponding to the calibration parameter;

[0019] Based on the parameter frequency, the full-bridge strain gauge is electrically detected to obtain the original electric signal;

[0020] The original electric signal is preprocessed to obtain preprocessed signal data;

[0021] Analyze the signal strain sequence corresponding to the preprocessed signal data;

[0022] Based on the signal strain sequence, the strain data of the full-bridge strain gauge in the touch operation process is real-time collected.

[0023] Optionally, the calculating the pressure value corresponding to the stylus according to the strain data comprises:

[0024] The pressure value corresponding to the stylus is calculated by the following formula:

[0025]

[0026] wherein P represents the pressure value corresponding to the stylus, k represents the stiffness coefficient corresponding to the full-bridge strain gauge, n represents the total number of measurement points corresponding to the stylus, i represents the quantity index corresponding to the measurement point, Δ∈ i represents the strain change at the i-th measurement point, ∈0 represents the initial strain value of the full-bridge strain gauge, t represents the time variable, represents the strain rate of the stylus over time, and C represents a constant compensation term.

[0027] Optionally, the detecting the stylus tip action and the transmission signal corresponding to the stylus according to the execution operation comprises:

[0028] analyzing the use scenario corresponding to the execution operation;

[0029] collecting original action and signal data of the stylus in the use process based on the use scenario;

[0030] screening key data segments in the original action and signal data;

[0031] extracting stylus tip action features and signal transmission features in the key data segments;

[0032] detecting the stylus tip action and the transmission signal corresponding to the stylus based on the stylus tip action features and the signal transmission features.

[0033] Optionally, the generating the interaction response data corresponding to the stylus based on the stylus tip action and the transmission signal comprises:

[0034] analyzing the operation intention corresponding to the stylus tip action and the transmission signal;

[0035] determining the interaction response type corresponding to the operation intention;

[0036] collecting interaction response materials corresponding to the interaction response type;

[0037] screening material segments in the interaction response materials;

[0038] extracting key interaction elements in the material segments;

[0039] generating the interaction response data corresponding to the stylus based on the key interaction elements.

[0040] Optionally, the analysis of the feedback parameter corresponding to the interaction response data comprises:

[0041] Inquiring a response target corresponding to the interaction response data;

[0042] Target refining the response target to obtain a refined sub-target;

[0043] Inquiring a target reference value corresponding to the refined sub-target;

[0044] Based on the target reference value, determining an analysis rule corresponding to the interaction response data;

[0045] Based on the analysis rule, analyzing the feedback parameter corresponding to the interaction response data.

[0046] Optionally, the calculation of the misoperation probability corresponding to the touch pen based on the abnormal operation feature comprises:

[0047] The misoperation probability corresponding to the touch pen is calculated by using the following formula:

[0048]

[0049] Wherein, WG represents the misoperation probability corresponding to the touch pen, n' represents the total number of touch pen operations, i' represents the number index of the touch pen operation, m represents the number of abnormal operation features, j represents the number index of the abnormal operation feature, w i′j represents the weight coefficient of the jth abnormal operation feature of the ith operation, h() represents the feature threshold function, B i′j (t i′ ) represents the abnormal operation feature value after time processing, t i′ represents the time point of the ith operation.

[0050] Optionally, the optimization processing of the full-bridge strain gauge data in the touch operation process based on the misoperation probability comprises:

[0051] Based on the misoperation probability, determining an optimization target corresponding to the full-bridge strain gauge data in the touch operation process;

[0052] According to the optimization target, screening the to-be-optimized points of the full-bridge strain gauge data in the touch operation process;

[0053] Inquiring the original data segment corresponding to the to-be-optimized point;

[0054] Analyzing the optimizable direction corresponding to the original data segment;

[0055] Based on the optimizable direction, an optimization strategy corresponding to the full-bridge strain gauge is constructed;

[0056] Based on the optimization strategy, data of the full-bridge strain gauge during the touch operation is optimized to obtain optimized data.

[0057] Optionally, to solve the above problems, the present application provides an intelligent control system of a touch pen based on a full-bridge strain gauge, which comprises:

[0058] An initial calibration module is configured to acquire usage scene information of the touch pen, analyze touch operation requirements in the usage scene information, determine a full-bridge strain gauge suitable for the touch pen based on the touch operation requirements, install the full-bridge strain gauge at a designated position of the touch pen, and calibrate the full-bridge strain gauge to obtain calibration parameters.

[0059] An instruction generation module is configured to acquire strain data of the full-bridge strain gauge during the touch operation based on the calibration parameters, calculate a pressure value corresponding to the touch pen according to the strain data, generate an operation instruction corresponding to the touch pen based on the pressure value and touch position information corresponding to the touch pen, and generate an operation instruction corresponding to the touch pen.

[0060] A data generation module is configured to analyze a function module corresponding to the touch pen based on the operation instruction, determine an execution operation corresponding to the function module, detect a pen tip action and a transmission signal corresponding to the touch pen according to the execution operation, and generate interactive response data corresponding to the touch pen based on the pen tip action and the transmission signal.

[0061] An error operation probability calculation module is configured to analyze feedback parameters corresponding to the interactive response data, identify abnormal operation features in the feedback parameters, and calculate an error operation probability corresponding to the touch pen based on the abnormal operation features.

[0062] A scheme development module is configured to optimize data of the full-bridge strain gauge during the touch operation based on the error operation probability to obtain optimized data, analyze touch operation habits corresponding to the optimized data, and develop a control scheme corresponding to the touch pen based on the touch operation habits.

[0063] Firstly, the application can make the control of the touch pen more accurate and fit the actual use by obtaining the use scene information of the touch pen and analyzing the touch operation demand in the use scene information, for example, in the drawing scene, by understanding the scene information, the specific operation demand of the user for line thickness, color selection, pen touch pressure change and the like can be analyzed, so that the touch pen can more accurately respond to these demands in the drawing process, at the same time, based on the calibration parameter, the strain data of the full-bridge strain gauge in the touch operation process is collected in real time, and the data deviation caused by the individual difference of the equipment, installation error and environmental factors and the like is eliminated, so that the collected strain data can reflect various forces and deformation conditions of the touch pen in the actual use process, based on the operation instruction, the function module corresponding to the touch pen is analyzed, and the execution operation corresponding to the function module is determined, so that the touch pen can flexibly switch and execute different tasks in various application scenes, and through the analysis of the function module and the determination of the execution operation, the personalized setting of the touch pen can be provided, so that the touch pen can better adapt to the needs of different users, by analyzing the feedback parameter corresponding to the interaction response data, which can include response time, accuracy, stability and the like, the quality of the interaction between the touch pen and the system is directly reflected, for example, short response time means that the user operation can be quickly responded, the smoothness and immediacy of the interaction are improved, so that the user will not feel lag or delay when drawing, writing or performing other operations, further, based on the misoperation probability, the data of the full-bridge strain gauge in the touch operation process is optimized to obtain optimized data, the data mode or abnormal condition that can cause misoperation can be identified, and the data of the full-bridge strain gauge is optimized accordingly, which helps to reduce the misoperation caused by inaccurate or abnormal data, ensures that the touch operation can accurately reflect the intention of the user, and improves the user experience and operation efficiency. Therefore, the intelligent control method and system of the touch pen based on the full-bridge strain gauge can improve the control smoothness of the touch pen in the interaction of the electronic device. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 The flowchart of the intelligent control method of the touch pen based on the full-bridge strain gauge provided by an embodiment of the application is shown.

[0065] Figure 2 The module diagram of the intelligent control system of the touch pen based on the full-bridge strain gauge provided by an embodiment of the application is shown.

[0066] The purpose implementation, functional characteristics and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0067] It is to be understood that the specific embodiments described herein are merely illustrative of the present application and should not be used to limit the scope of the present application.

[0068] The embodiment of the present application provides a smart control method for a touch pen based on a full-bridge strain gauge. An execution subject of the smart control method for the touch pen based on the full-bridge strain gauge includes but is not limited to at least one of electronic devices such as a server and a terminal which can be configured to execute the method provided by the embodiment of the present application. In other words, the smart control method for the touch pen based on the full-bridge strain gauge can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to a single server, a server cluster, a cloud server or a cloud server cluster.

[0069] Embodiment 1

[0070] Referring to Figure 1 FIG. 1 is a flowchart of a smart control method for a touch pen based on a full-bridge strain gauge provided by an embodiment of the present application. In the embodiment, the smart control method for the touch pen based on the full-bridge strain gauge includes the following steps.

[0071] S1, obtaining usage scenario information of a touch pen, analyzing touch operation requirements in the usage scenario information, determining a full-bridge strain gauge suitable for the touch pen based on the touch operation requirements, installing the full-bridge strain gauge at a specified position of the touch pen, and performing initialization calibration on the full-bridge strain gauge to obtain calibration parameters.

[0072] The present application can make the control of the touch pen more accurate and fit the actual use by obtaining the usage scenario information of the touch pen and analyzing the touch operation requirements in the usage scenario information. For example, in a drawing scenario, by understanding the scenario information, specific operation requirements of a user for line thickness, color selection, pen pressure change and the like can be analyzed, so that the touch pen can more accurately respond to these requirements in the drawing process.

[0073] The touch pen refers to an input tool for touch operation on an electronic device, which realizes various functions such as writing, drawing, annotation and the like by contacting the screen of the electronic device; the use scenario information refers to information related to the specific environment and situation of the touch pen in the use process, which includes but is not limited to the device type (such as tablet computer, smart phone and the like) using the touch pen, the application type (such as drawing software, office software, note application and the like), the specific scene (such as classroom note recording, artistic creation, business meeting annotation and the like) and other related factors; the touch operation requirement refers to the specific requirements of the user on the touch pen operation function and performance in a specific use scenario, for example, in the drawing scenario, the requirements on line precision, color switching convenience, different pen touch effect, in the writing scenario, the requirements on writing fluency, font recognition accuracy, writing speed adaptability and the like, in the annotation scenario, the requirements on the diversity of annotation tools, the clarity of marks and the interactivity with document content and the like, optionally, the use scenario information of the touch pen can be obtained through built-in sensors such as acceleration sensor, gyroscope and the like; the analysis of the touch operation requirement in the use scenario information can be realized through an association rule mining algorithm, for example, in the electronic reading application scenario, the association rule mining algorithm is used to mine the associated touch operation requirement of the user in this scenario after the text selection operation of the touch pen is followed by the annotation operation.

[0074] Based on the touch operation requirement, the full-bridge strain gauge matched with the touch pen is determined, so that the touch pen can realize the best performance in different use scenarios, for example, in the drawing scenario, the operation requirement of accurately depicting details and reflecting different pen touch pressure changes is reduced due to the mismatch, and the maintenance and replacement cost is reduced.

[0075] The full-bridge strain gauge refers to a sensor element for measuring the strain generated when an object is deformed by force, which is usually composed of four resistance strain gauges connected in the form of a Wheatstone bridge, when the object is deformed by external force, the resistance value of the full-bridge strain gauge will change accordingly, optionally, the determination of the full-bridge strain gauge matched with the touch pen can be realized through a computer screening method, such as quickly screening the full-bridge strain gauge more suitable for the touch operation requirement in theory through computer simulation.

[0076] The application can ensure that the full-bridge strain gauge accurately senses and measures various physical changes of the touch pen during use by installing the full-bridge strain gauge at a specified position of the touch pen, initializing and calibrating the full-bridge strain gauge, and obtaining calibration parameters, and the different installation positions may have an impact on the measurement results of the full-bridge strain gauge, and the calibration process can eliminate errors caused by installation differences, so that the strain gauge can truly reflect the pressure and deformation information of the touch pen, and provide reliable basic data for subsequent accurate data analysis and control.

[0077] The specified position refers to a position on the touch pen that is carefully designed and selected to maximize the performance of the full-bridge strain gauge and accurately reflect various physical changes during use of the touch pen; the calibration parameters refer to a series of parameters obtained by analyzing and processing the deviation value between the test data and the preset standard during the initialization and calibration of the full-bridge strain gauge, which are used to adjust and correct the measurement results of the full-bridge strain gauge.

[0078] As an embodiment of the application, the initialization and calibration of the full-bridge strain gauge to obtain calibration parameters comprises: querying the initial resistance value corresponding to the full-bridge strain gauge; analyzing the basic electrical characteristics corresponding to the full-bridge strain gauge according to the initial resistance value; based on the basic electrical characteristics, using a preset standard pressure test device to test the pressure of the full-bridge strain gauge to obtain test data; analyzing the deviation value between the test data and the preset standard; based on the deviation value, initializing and calibrating the full-bridge strain gauge to obtain calibration parameters.

[0079] The initial resistance value refers to the resistance value of the full-bridge strain gauge when it is not subjected to any external force and is in the initial state. The basic electrical characteristics refer to a series of electrical properties exhibited by the full-bridge strain gauge based on its initial resistance value and under different electrical conditions, including the resistance change characteristic with temperature (resistance temperature coefficient), the relationship between resistance and voltage and current, etc. The preset standard pressure testing equipment refers to a device specially used for pressure testing of the full-bridge strain gauge or a device containing the full-bridge strain gauge (such as a touch pen). The device can accurately apply a known size and direction of pressure and has a high-precision pressure measurement function, usually including a pressure generator (such as a hydraulic device, a pneumatic device or a mechanical loading device, etc.), a pressure sensor (for accurately measuring the applied pressure value) and an interface connected with the full-bridge strain gauge and data acquisition. The test data refers to the relevant data of the full-bridge strain gauge collected during the pressure testing of the full-bridge strain gauge by using the preset standard pressure testing equipment, mainly including the resistance change value and voltage output change value of the full-bridge strain gauge under different pressure actions. The preset standard refers to a series of data or indicators preset as a reference benchmark during the calibration of the full-bridge strain gauge, for example, the ideal resistance change value range of the full-bridge strain gauge under different pressures, the linearity requirement (i.e. the degree of linear relationship between resistance change and pressure change) etc. belong to the category of the preset standard. The deviation value refers to the difference value found between the test data obtained by testing the full-bridge strain gauge by the standard pressure testing equipment and the preset standard after comparison.

[0080] Further, the initial resistance value corresponding to the full-bridge strain gauge can be measured by a multimeter, such as connecting the pins of the full-bridge strain gauge with the test probes of the multimeter correctly, ensuring good connection without short circuit or open circuit, and then reading the resistance value displayed on the multimeter, which is the initial resistance value of the full-bridge strain gauge. The analysis of the basic electrical characteristics corresponding to the full-bridge strain gauge can be realized by a spectrum analyzer, such as applying an alternating current signal of a certain frequency to the full-bridge strain gauge, and observing the frequency spectrum change of the signal after passing through the strain gauge by the spectrum analyzer, which can reflect the frequency response characteristic of the full-bridge strain gauge. The pressure testing of the full-bridge strain gauge by using the preset standard pressure testing equipment can be realized by a pneumatic loading device, such as using the pneumatic loading device to generate compressed air as a pressure source, and accurately adjusting the air pressure by a pressure control system to apply pressure to the full-bridge strain gauge. The analysis of the deviation value between the test data and the preset standard can be realized by a visualization tool, such as MATLAB, Python, etc. The initialization calibration of the full-bridge strain gauge can be realized by a calibration algorithm, such as a least squares method calibration algorithm, a polynomial fitting calibration algorithm, etc.

[0081] S2, based on the calibration parameter, collecting strain data of the full-bridge strain gauge in a touch operation process in real time, calculating a pressure value corresponding to the touch pen according to the strain data, and generating an operation instruction corresponding to the touch pen based on the pressure value and touch position information corresponding to the touch pen.

[0082] The application collects strain data of the full-bridge strain gauge in a touch operation process in real time based on the calibration parameter, and eliminates data deviation caused by individual differences of devices, installation errors, environmental factors and the like, so that the collected strain data can reflect various forces and deformation conditions of the touch pen in actual use.

[0083] The strain data refers to accurate strain information of the full-bridge strain gauge in a touch operation process finally collected in real time, which is obtained after a series of processes including determining a parameter frequency based on the calibration parameter, detecting an original electric signal, preprocessing and analyzing a signal strain sequence, and is data that can accurately reflect mechanical influence of the touch operation on the strain gauge.

[0084] As an embodiment of the application, the collecting of the strain data of the full-bridge strain gauge in the touch operation process in real time based on the calibration parameter includes: querying a parameter frequency corresponding to the calibration parameter; detecting an electric signal of the full-bridge strain gauge based on the parameter frequency to obtain an original electric signal; preprocessing the original electric signal to obtain preprocessed signal data; analyzing a signal strain sequence corresponding to the preprocessed signal data; and collecting strain data of the full-bridge strain gauge in the touch operation process in real time based on the signal strain sequence.

[0085] The parameter frequency refers to a specific working frequency or data collection frequency related to the full-bridge strain gauge when operating based on the calibration parameter; the original electric signal refers to an initial electric signal output of the full-bridge strain gauge in the touch operation process without any processing or processing, which contains various original information about the touch operation, such as the size of the pressure, the direction, the duration of the action, etc.; the preprocessed signal data refers to data obtained after a series of preliminary processing of the original electric signal, and the preprocessing process usually includes noise removal, filtering, amplification and the like; the signal strain sequence refers to an ordered sequence reflecting strain change of the full-bridge strain gauge in the touch operation process obtained by analyzing and calculating the preprocessed signal data, which converts the preprocessed electric signal data into strain-related information, and each data point in the sequence corresponds to a strain value at a specific time.

[0086] Further, the query of the parameter frequency corresponding to the calibration parameter can be realized by querying a database, such as a MySQL, Oracle, or the like; the electrical signal detection on the full-bridge strain gauge can be realized by a strain gauge, such as a resistance strain gauge, an optical fiber strain gauge, or the like; the preprocessing of the original electrical signal can be realized by a digital filtering algorithm, such as a mean filtering algorithm, a median filtering algorithm, a Kalman filtering algorithm, or the like; the analysis of the signal strain sequence corresponding to the preprocessed signal data can be realized by a deep learning framework, such as TensorFlow, PyTorch, or the like; and the real-time collection of the strain data of the full-bridge strain gauge in the touch operation process can be realized by a real-time operating system, such as FreeRTOS, RT-Thread, or the like.

[0087] The present application can provide more accurate mechanical feedback for the operation of the touch pen by calculating the pressure value corresponding to the touch pen according to the strain data, and can be personalized to adapt and adjust, so that the touch pen can play the best performance in the hands of various users, and further expand the application range and practicability of the touch pen in various fields.

[0088] The pressure value refers to a quantitative value of the pressure generated by the touch pen in the use process due to the contact with the touch surface and the action of various forces.

[0089] As an embodiment of the present application, the calculation of the pressure value corresponding to the touch pen according to the strain data comprises:

[0090] The pressure value corresponding to the touch pen is calculated by using the following formula:

[0091]

[0092] Wherein, P represents the pressure value corresponding to the touch pen, k represents the stiffness coefficient corresponding to the full-bridge strain gauge, n represents the total number of measurement points corresponding to the touch pen, i represents the quantity index corresponding to the measurement point, ΔEi i represents the strain change at the i-th measurement point, ε0 represents the initial strain value of the full-bridge strain gauge, t represents the time variable, represents the strain rate of the touch pen with time, and C represents a constant compensation term.

[0093] In detail, the stiffness coefficient refers to a physical parameter corresponding to the full-bridge strain gauge, which reflects the rigidity degree of the material and structure of the full-bridge strain gauge, and the greater the stiffness coefficient, the smaller the strain of the strain gauge under the same external force, that is, the strain gauge is relatively hard and is not easy to deform; on the contrary, the smaller the stiffness coefficient, the easier the strain gauge to produce larger strain under the same external force, indicating that the strain gauge is relatively soft; the measurement point refers to a specific position or time point set on the stylus or its related system for measuring strain data; the strain change amount refers to the change of the strain of the full-bridge strain gauge from the initial state to the current state at the i-th measurement point, and the strain is the relative change of the shape or size of the object under the action of external force; the initial strain value refers to the strain state value of the full-bridge strain gauge without any external force; the time variable refers to the time course from the start of the touch operation to the current time; the strain rate refers to the rate of change of strain with time during the use of the stylus, that is, the amount of change of strain per unit time; the constant compensation term refers to a constant used to adjust and compensate the calculation results in the pressure value calculation formula, which has some factors that cannot be directly calculated by strain data, such as system error, environmental factors, etc.

[0094] Based on the pressure value and the touch position information corresponding to the stylus, the operation instruction corresponding to the stylus is generated, which can greatly enrich the operation function and interactivity of the stylus, and can realize more delicate and diversified operation instructions, for example, in electronic signature, by analyzing the dynamic changes of pressure value and touch position, the authenticity and uniqueness of the signature can be verified, and forgery can be prevented, in short, this way can fully exert the potential of the stylus, and improve the interaction experience and work efficiency of users in various application scenarios.

[0095] The touch position information refers to the specific position coordinates of the stylus on the surface of the touch device (such as a tablet computer, a touch screen mobile phone, etc.) when interacting with the touch device, which is usually represented in the form of two-dimensional plane coordinates, for example, on a touch screen with a resolution of 1920x1080, the touch position can be determined by the horizontal and vertical coordinates, such as (500, 300), which represents the position 500 pixel units away from the left edge of the screen in the horizontal direction and 300 pixel units away from the top edge of the screen in the vertical direction; the operation instruction refers to the command generated based on the pressure value and touch position information of the stylus for controlling the touch device to perform a specific operation, and the operation instruction can have various forms, for example, in drawing software, the operation instruction can include drawing lines, filling colors, selecting tools, etc.; in word processing software, the operation instruction can be inputting text, deleting characters, setting font formats, etc.

[0096] S3, based on the operation instruction, analyzing the function module corresponding to the touch pen, determining the execution operation corresponding to the function module, detecting the pen tip action and transmission signal corresponding to the touch pen according to the execution operation, and generating the interaction response data corresponding to the touch pen based on the pen tip action and the transmission signal.

[0097] The application analyzes the function module corresponding to the touch pen based on the operation instruction, determines the execution operation corresponding to the function module, can make the touch pen flexibly switch and execute different tasks in various application scenarios, and can also provide a basis for the personalized setting of the touch pen by analyzing the function module and determining the execution operation, so that the touch pen better adapts to the needs of different users.

[0098] The function module refers to an independent unit with a specific function in the software system inside or associated with the touch pen, can be a specific function part realized by a hardware component, or can be a code module responsible for a specific task in a software program, for example, in the function system of the touch pen, there is a pressure sensing module responsible for detecting the pressure value of the touch pen and converting it into an electrical signal; there is also a communication module for data transmission with the touch device; the drawing function module can draw different shapes and lines on the touch device according to the input instruction; the execution operation refers to the specific action or task performed by the function module according to the received operation instruction, for example, for the drawing function module, the execution operation can include drawing a straight line at a specific touch position, filling an area or adjusting the color, etc.; for the communication module, the execution operation can be to send the current pressure value and touch position information to the touch device; for the pressure sensing module, the execution operation can be to update and provide the current pressure data in real time, optionally, the analysis of the function module corresponding to the touch pen can be realized by expert system development tools, such as CLIPS, JESS, etc.; the determination of the execution operation corresponding to the function module can be realized by rule engine tools, such as Drools, OpenRules, etc.

[0099] Further, according to the execution operation, the pen tip action and transmission signal corresponding to the touch pen are detected, which can realize accurate monitoring and feedback of the touch pen operation, can accurately understand the specific behaviors of the user when using the touch pen, such as writing, drawing, etc., for example, the moving track of the pen tip, the pressure change, the dwell time, etc., can ensure the stable and accurate communication between the touch pen and the device, and timely convey the operation intention of the user to the device.

[0100] The pen tip action refers to specific physical movements and operations of the pen tip of the touch pen on the touch surface, including various action forms such as movement, clicking, hovering, pressure change, etc. The transmission signal refers to an electronic signal for communication between the touch pen and the device, which carries state information and user operation information of the touch pen, so that the device can accurately respond to the operation of the touch pen and perform corresponding processing and display.

[0101] As an embodiment of the present application, the detecting the pen tip action and the transmission signal corresponding to the touch pen according to the execution operation comprises: analyzing a use scenario corresponding to the execution operation; collecting original action and signal data of the touch pen in a use process based on the use scenario; screening key data segments in the original action and signal data; extracting pen tip action features and signal transmission features in the key data segments; and detecting the pen tip action and the transmission signal corresponding to the touch pen based on the pen tip action features and the signal transmission features.

[0102] The use scenario refers to a situation and environment of the touch pen in a specific application, for example, fine drawing in a drawing software, annotation in a document, operation in a game, etc. The original action refers to physical action performance of the touch pen in a use process without processing, including movement, clicking, pressure change, etc. of the pen tip on the touch surface directly generated by user operation. The signal data refers to electronic signal data for communication and transmission between the touch pen and the device, including position information, pressure value, button state, etc. sent by the touch pen to the device, and feedback signals sent by the device to the touch pen, etc. The key data segment refers to a data part with important significance and representation selected from the original action and signal data, for example, a data segment of a time period in which the pen tip moves quickly and generates large pressure change in a drawing process can be considered as a key data segment. The pen tip action feature refers to an attribute describing characteristics of the pen tip action extracted from the key data segment, for example, speed, acceleration, trajectory shape, pressure change curve, etc. of the pen tip movement belong to the pen tip action feature. The signal transmission feature refers to an attribute describing signal transmission conditions extracted from the key data segment, for example, strength, stability, delay time, transmission frequency, etc. of the signal belong to the signal transmission feature.

[0103] Further, the analysis of the use scene corresponding to the execution operation can be realized by a classification algorithm, such as a support vector machine (SVM) or a random forest, the data is trained to establish a classification model, when a new execution operation is input into the model, the model automatically predicts the corresponding use scene; the collection of the original action and signal data of the stylus in the use process can be realized by a sensor tool, such as an acceleration sensor, a pressure sensor, a gyroscope and the like; the screening of the key data segment in the original action and signal data can be realized by a data analysis library, such as a NumPy, a Pandas and the like; the extraction of the stylus tip action feature and signal transmission feature in the key data segment can be realized by a deep learning framework, such as a TensorFlow, a PyTorch and the like; the detection of the stylus tip action and transmission signal corresponding to the stylus can be realized by an anomaly detection method, such as a self-encoder, an isolated forest and the like.

[0104] Based on the stylus tip action and the transmission signal, the application generates the interaction response data corresponding to the stylus, which can accurately respond to the user's operation in real time, whether it is the delicate stroke change during drawing, the light and heavy of writing, or the click, slide and the like in various application scenes, which can get timely and appropriate feedback, so that the user feels as natural as writing or drawing on real paper, greatly improving the user's use comfort and immersion.

[0105] Among them, the interaction response data refers to the specific data generated according to the key interaction elements for feedback to the user or the system, in the drawing software, the interaction response data can be a specific color and shape line displayed on the screen; in the game, the interaction response data can be a specific sound effect played, an animation effect displayed and the like.

[0106] As an embodiment of the application, the generation of the interaction response data corresponding to the stylus based on the stylus tip action and the transmission signal comprises: analyzing the operation intention corresponding to the stylus tip action and the transmission signal; determining the interaction response type corresponding to the operation intention; collecting the interaction response material corresponding to the interaction response type; screening the material segment in the interaction response material; extracting the key interaction elements in the material segment; and generating the interaction response data corresponding to the stylus based on the key interaction elements.

[0107] The operation intention refers to the specific purpose or desired operation result expressed by the user through the pen tip action and transmission signal of the stylus, for example, fast movement of the pen tip with large pressure may indicate that the user wants to draw thick lines or make emphasis marks; light tapping of the pen tip with specific transmission signals may indicate that the user wants to select an object, etc.; the interaction response type refers to different kinds of interaction feedback modes determined according to the operation intention, for example, for a drawing scene, the interaction response type may include line drawing, color filling, erasing, etc.; for a document editing scene, the interaction response type may include text input, deletion, format adjustment, etc.; the interaction response material refers to various resources that may be used to generate interaction response data, which may include graphic elements, color libraries, font libraries, sound effects, etc., for example, in drawing software, the interaction response material may include different shaped brushes, various color palettes, etc.; in games, the interaction response material may include sound effect files, animation effects, etc.; the material segment refers to part of the content with specific use filtered from the interaction response material, for example, in drawing software, a material segment of a specific color range is filtered from the color library according to the operation intention of the user; in games, a sound material segment related to a specific action is selected from a sound effect file; the key interaction element refers to an element extracted from the material segment that plays a key role in generating interaction response data, for example, in drawing, specific color values are extracted from the color material segment, brush stroke shapes and sizes are extracted from the brush material segment, etc.; in games, specific audio features are extracted from the sound effect material segment, etc.

[0108] Further, the analysis of the operation intention corresponding to the pen tip action and the transmission signal can be realized by a classification algorithm, such as a support vector machine (SVM) or a random forest, which is trained on these data to establish a classification model. When there is a new pen tip action and transmission signal, its features are input into the model, and the model automatically predicts the corresponding operation intention; the determination of the interaction response type corresponding to the operation intention can be realized by a decision tree algorithm, such as taking the features of the operation intention as the input nodes of the decision tree and the interaction response type as the leaf nodes of the decision tree; the collection of the interaction response material corresponding to the interaction response type can be realized by a network request library, such as the requests library of Python and other tools; the filtering of the material segment in the interaction response material can be realized by a script programming tool, such as Python, C++, etc.; the extraction of the key interaction element in the material segment can be realized by an element extraction tool, such as OpenCV, PIL, etc.; the generation of the interaction response data corresponding to the stylus can be realized by a programming language and related libraries, such as the Jinja2 template engine of Python.

[0109] S4, analyze the feedback parameters corresponding to the interaction response data, identify the abnormal operation characteristics in the feedback parameters, and calculate the misoperation probability corresponding to the touch pen based on the abnormal operation characteristics.

[0110] By analyzing the feedback parameters corresponding to the interaction response data, which can include response time, accuracy, stability, etc., the quality of the interaction between the touch pen and the system is directly reflected, for example, a short response time means that the user's operation can be quickly responded to, improving the smoothness and immediacy of the interaction, so that the user does not feel lag or delay when drawing, writing or performing other operations.

[0111] The feedback parameters refer to specific indicators for evaluating the quality and effect of interaction response data, such as response time, accuracy, stability, resource occupancy, etc.

[0112] As an embodiment of the present application, the analysis of the feedback parameters corresponding to the interaction response data includes: querying the response target corresponding to the interaction response data; refining the response target to obtain a refined sub-target; querying the target reference value corresponding to the refined sub-target; determining the analysis rule corresponding to the interaction response data based on the target reference value; and analyzing the feedback parameters corresponding to the interaction response data based on the analysis rule.

[0113] The response target refers to the overall effect or purpose that the interaction response data is expected to achieve, for example, in a drawing software, the response target may be to quickly and accurately present the user's drawing operation, provide rich color and brush selection, etc.; in a game application, the response target may be to respond to the player's operation instruction in a timely manner, provide a smooth game experience, etc.; the refined sub-target refers to a specific, measurable small target that is further decomposed from the response target, for example, if the response target is to quickly and accurately present the user's drawing operation, the refined sub-target can include the smoothness of the drawing line, the accuracy of the color, the response time, etc.; the target reference value refers to a standard value or range used to measure whether the refined sub-target meets the expectation, for example, for the refined sub-target of the smoothness of the drawing line, the target reference value can be the length of the line drawn per second, the degree of line jitter within a certain range, etc.; for the refined sub-target of the response time, the target reference value can be a time range of milliseconds; the analysis rule refers to a specific method and standard for analyzing the feedback parameters of the interaction response data according to the target reference value, for example, if the target reference value specifies that the response time should be within 50 milliseconds, the analysis rule can be to count the response time of each operation in the interaction response data and determine whether it exceeds 50 milliseconds; the feedback parameters refer to specific indicators for evaluating the quality and effect of interaction response data, such as response time, accuracy, stability, resource occupancy, etc.

[0114] Further, the query of the response target corresponding to the interaction response data can be implemented by a scenario simulation tool, such as: various actual application scenarios can be simulated by using the scenario simulation tool, and the response target is combed and determined in combination with a demand analysis tool; the target refinement of the response target can be implemented by a mind mapping tool, such as: XMind, MindManager and the like; the query of the target reference value corresponding to the refined sub-target can be implemented by an industry standard reference method, such as: an industry standard document, a technical specification database and the like; the determination of the analysis rule corresponding to the interaction response data can be implemented by data analysis, such as: Excel, SPSS and the like; and the analysis of the feedback parameter corresponding to the interaction response data can be implemented by a simulation test tool, such as: various use scenarios and user operations are simulated by using the simulation test tool, and the feedback parameter of the interaction response data is collected.

[0115] By identifying the abnormal operation characteristics in the feedback parameter, the present application can discover and solve potential system problems in time, can quickly locate the abnormal situation appearing in the interaction process, such as sudden response delay, sharp decrease of operation accuracy and the like, is helpful for the technical personnel to investigate problems in time, so that corresponding measures are taken for repair, and stable operation of the touch pen is ensured.

[0116] Among them, the abnormal operation characteristics refer to specific attributes or performances deviating from normal mode or expected range presented by the feedback parameter in the interaction process of the touch pen and the system. These characteristics can be embodied in multiple aspects, such as operation response time obviously longer than normal average value (such as normal response time of 50 milliseconds, abnormal time of 200 milliseconds or more); sharp fluctuation of operation accuracy, such as drawing accuracy of originally drawn lines above 95%, suddenly reduced to below 70%; or in the pressure sensing aspect, abnormal pressure value change is recorded, such as high pressure value is recorded without obvious pressure, and the like. Optionally, the identification of the abnormal operation characteristics in the feedback parameter can be implemented by an anomaly detection algorithm, such as: Isolation Forest, One-Class SVM and the like.

[0117] Further, by calculating the misoperation probability of the touch pen based on the abnormal operation characteristics, the present application can intuitively use the operation accuracy in the touch pen process. When the misoperation probability is high, operation can be more cautious or it is checked whether the operation mode is correct, so as to reduce unnecessary troubles and error results caused by misoperation, such as avoiding content error or loss caused by misoperation in important document editing or drawing creation.

[0118] The misoperation probability refers to an index for measuring the possibility of misoperation of the touch pen during use. For example, if the misoperation probability is 0.3, it means that the touch pen has a 30% possibility of misoperation under given operation times and conditions.

[0119] As an embodiment of the present application, the misoperation probability of the touch pen is calculated based on the abnormal operation features, including:

[0120] The misoperation probability of the touch pen is calculated by the following formula:

[0121]

[0122] WG represents the misoperation probability of the touch pen, n' represents the total number of operations of the touch pen, i' represents the index of the number of operations of the touch pen, m represents the number of abnormal operation features, j represents the index of the number of abnormal operation features, w i′j represents the weight coefficient of the jth abnormal operation feature of the ith operation, h() represents a feature threshold function, B i′j (t i′ ) represents the abnormal operation feature value after time processing, t i′ represents the time point of the ith operation.

[0123] In detail, the weight coefficient refers to the relative importance of the jth abnormal operation feature of the ith operation in judging misoperation. For example, the abnormality of the pen tip pressure has a greater impact on misoperation than the abnormality of the pen tip moving speed, so the weight coefficient of the abnormality of the pen tip pressure is greater than that of the abnormality of the pen tip moving speed. The feature threshold function refers to a function for judging whether the abnormal operation feature value after time processing exceeds the normal range. If it exceeds the normal range, it means that the feature is in an abnormal state, and the function returns a specific value (for example, 1). Otherwise, the function returns another value (for example, 0). The abnormal operation feature value refers to the numerical value of the jth abnormal operation feature of the ith operation after time processing. For example, if the abnormal operation feature is the pen tip pressure fluctuation value, the abnormal operation feature value can be the average value, integral value or other statistical quantity of the pressure fluctuation value in a specific time interval.

[0124] S5, based on the misoperation probability, the data of the full-bridge strain gauge during touch operation is optimized to obtain optimized data, the touch operation habit corresponding to the optimized data is analyzed, and the control scheme corresponding to the touch pen is formulated based on the touch operation habit.

[0125] The application is based on the misoperation probability, optimizes the data of the full-bridge strain gauge during touch operation, obtains optimized data, can identify data patterns or abnormal conditions that may cause misoperation, and then optimizes the data of the full-bridge strain gauge, which helps to reduce misoperation caused by inaccurate or abnormal data, ensures that touch operation can accurately reflect the user's intention, and improves user experience and operation efficiency.

[0126] The optimized data refers to the data of the full-bridge strain gauge during touch operation after optimization strategy processing.

[0127] As an embodiment of the application, the optimization of the data of the full-bridge strain gauge during touch operation based on the misoperation probability includes: determining the optimization target of the data of the full-bridge strain gauge during touch operation based on the misoperation probability; screening the optimization points of the data of the full-bridge strain gauge during touch operation according to the optimization target; querying the original data segment corresponding to the optimization points; analyzing the optimizable direction corresponding to the original data segment; constructing the optimization strategy corresponding to the full-bridge strain gauge based on the optimizable direction; and optimizing the data of the full-bridge strain gauge during touch operation based on the optimization strategy to obtain optimized data.

[0128] The optimization target refers to the specific purpose of optimizing the data of the full-bridge strain gauge during touch operation, such as reducing the noise level of the data, improving the accuracy of the data, and enhancing the stability of the data; the optimization points refer to specific positions or data points in the data of the full-bridge strain gauge during touch operation that are determined to need optimization; the original data segment refers to a segment of original data containing optimization points; the optimizable direction refers to the direction that can be improved after analyzing the original data segment of the optimization points, such as reducing the fluctuation amplitude of the data, adjusting the mean value of the data, and removing outliers; and the optimization strategy refers to a specific optimization method and steps formulated according to the optimizable direction, such as using a filtering algorithm to remove noise, using an interpolation method to fill missing values, and performing data standardization.

[0129] Further, the determination of the optimization target corresponding to the data of the full-bridge strain gauge during the touch operation process can be achieved by data analysis tools such as Excel, SPSS, etc.; the screening of the to-be-optimized points of the data of the full-bridge strain gauge during the touch operation process can be achieved by an outlier detection algorithm, such as a statistical method (e.g., Z-score method) or a machine learning-based method (e.g., Isolation Forest algorithm) for detecting outliers in the data of the full-bridge strain gauge; the querying of the original data segment corresponding to the to-be-optimized points can be achieved by a time window method, such as determining a time window range according to the timestamp of the to-be-optimized points, and then extracting the data segment within the time window from the original data of the full-bridge strain gauge; the analysis of the optimizable direction corresponding to the original data segment can be achieved by a principal component analysis method, such as using the principal component analysis method to perform dimensionality reduction processing on the original data segment, analyzing the main components and change trend of the data, and determining the optimizable direction of the data according to the eigenvalues and eigenvectors of the principal components; the construction of the optimization strategy corresponding to the full-bridge strain gauge can be achieved by a data interpolation method, such as using the data interpolation method to construct the optimization strategy; and the optimization processing of the data of the full-bridge strain gauge during the touch operation process can be achieved by an embedded system development tool, such as Arduino, Raspberry Pi, etc.

[0130] The present application helps to further optimize the performance and user experience of the touch device by analyzing the touch operation habits corresponding to the optimized data, and by deeply understanding the touch operation habits of the user, such as the force, frequency, duration, etc., the sensitivity and response mode of the full-bridge strain gauge can be adjusted accordingly, so that the touch operation is more accurate and smooth, and the occurrence of misoperation is reduced.

[0131] The touch operation habits refer to the touch behavior patterns of the user when using the touch device (such as a touch device with a full-bridge strain gauge) that have certain regularity and repeatability, which include but are not limited to the size distribution of the user's touch force, the frequency of touch (such as the number of touches per unit time), the duration of touch, the trajectory characteristics of touch (such as straight line sliding, curve sliding, etc.), the position preference of touch (e.g., frequent touch in a specific area of the screen), etc. Optionally, the analysis of the touch operation habits corresponding to the optimized data can be achieved by a neural network model, such as using a convolutional neural network (CNN) to analyze the image data of the touch operation, or using a recurrent neural network (RNN) to process the time series data, to predict the type of user's touch operation habits.

[0132] Further, based on the touch operation habit, the control scheme corresponding to the touch pen is formulated, the sensitivity of the touch pen can be adjusted, so that it can respond to such light and fast operation more quickly, thereby making the user feel more smooth and natural during use.

[0133] The control scheme refers to a series of adjustment and optimization measures for the operation and performance of the touch pen according to the touch operation habit of the user, which includes but is not limited to specific provisions such as sensitivity setting, pressure sensing range adjustment, response speed optimization, function triggering mode customization, etc. For example, if the touch operation habit of the user is light touch and fast movement, the control scheme may increase the sensitivity of the touch pen, reduce the pressure threshold required to trigger the function, and speed up the response speed to adapt to the fast movement operation. Optionally, the formulation of the control scheme corresponding to the touch pen can be realized through a machine learning framework, such as TensorFlow, Scikit-learn, etc.

[0134] Firstly, the application can make the control of the touch pen more accurate and fit the actual use by obtaining the use scene information of the touch pen and analyzing the touch operation demand in the use scene information, for example, in the drawing scene, by understanding the scene information, the specific operation demand of the user for line thickness, color selection, pen touch pressure change and the like can be analyzed, so that the touch pen can more accurately respond to these demands in the drawing process, at the same time, based on the calibration parameter, the strain data of the full-bridge strain gauge in the touch operation process is collected in real time, and the data deviation caused by device individual difference, installation error and environmental factors and the like is eliminated, so that the collected strain data can reflect various forces and deformation conditions of the touch pen in the actual use process, based on the operation instruction, the function module corresponding to the touch pen is analyzed, and the execution operation corresponding to the function module is determined, so that the touch pen can flexibly switch and execute different tasks in various application scenes, and the analysis of the function module and the determination of the execution operation can also provide a basis for the personalized setting of the touch pen, so that the touch pen can better adapt to the needs of different users, by analyzing the feedback parameter corresponding to the interaction response data, which can include response time, accuracy, stability and the like, the quality of the interaction between the touch pen and the system is directly reflected, for example, short response time means that the user operation can be quickly responded, the smoothness and immediacy of the interaction are improved, so that the user will not feel lag or delay when drawing, writing or performing other operations, further, based on the misoperation probability, the data of the full-bridge strain gauge in the touch operation process is optimized to obtain optimized data, the data mode or abnormal condition that may cause misoperation can be identified, and then the data of the full-bridge strain gauge is optimized in a targeted manner, which is helpful to reduce the misoperation caused by inaccurate or abnormal data, and ensure that the touch operation can accurately reflect the intention of the user, improve the user experience and operation efficiency. Therefore, the intelligent control method and system of the touch pen based on the full-bridge strain gauge can improve the control smoothness of the touch pen in the interaction of the electronic device.

[0135] Embodiment 2:

[0136] As Figure 2 shown is a module schematic diagram of the intelligent control system of the touch pen based on the full-bridge strain gauge provided by an embodiment of the application.

[0137] The intelligent control system 200 of the touch pen based on the full-bridge strain gauge can be installed in an electronic device. According to the functions implemented, the intelligent control system 200 of the touch pen based on the full-bridge strain gauge can include an initial calibration module 201, an instruction generation module 202, a data generation module 203, a misoperation probability calculation module 204, and a scheme formulation module 205. The modules of the present application can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete a fixed function, which are stored in the memory of the electronic device.

[0138] In the present embodiment, the functions of each module / unit are as follows:

[0139] The initial calibration module 201 is configured to obtain usage scenario information of the touch pen, analyze touch operation requirements in the usage scenario information, determine a full-bridge strain gauge suitable for the touch pen based on the touch operation requirements, and perform initial calibration on the full-bridge strain gauge after installing the full-bridge strain gauge at a designated position of the touch pen to obtain calibration parameters.

[0140] The instruction generation module 202 is configured to collect strain data of the full-bridge strain gauge in a touch operation process in real time based on the calibration parameters, calculate a pressure value corresponding to the touch pen according to the strain data, and generate an operation instruction corresponding to the touch pen based on the pressure value and touch position information corresponding to the touch pen.

[0141] The data generation module 203 is configured to analyze a function module corresponding to the touch pen based on the operation instruction, determine an execution operation corresponding to the function module, detect a pen tip action and a transmission signal corresponding to the touch pen according to the execution operation, and generate interactive response data corresponding to the touch pen based on the pen tip action and the transmission signal.

[0142] The misoperation probability calculation module 204 is configured to analyze feedback parameters corresponding to the interactive response data, identify abnormal operation features in the feedback parameters, and calculate a misoperation probability corresponding to the touch pen based on the abnormal operation features.

[0143] The scheme formulation module 205 is configured to perform optimization processing on data of the full-bridge strain gauge in a touch operation process based on the misoperation probability to obtain optimized data, analyze touch operation habits corresponding to the optimized data, and formulate a control scheme corresponding to the touch pen based on the touch operation habits.

[0144] In detail, each module in the intelligent control system 200 of the touch pen based on the full-bridge strain gauge in the embodiments of the present application adopts the same technical means as the intelligent control method of the touch pen based on the full-bridge strain gauge in the accompanying drawings when in use, and can produce the same technical effects, which will not be described here again.

[0145] The above description is merely that of the specific embodiments of the present application, which enables those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Accordingly, the present application is not to be limited to these embodiments shown herein but is to be accorded the broadest scope possible as defined by the principles and novel features shown herein.

Claims

1. A method for intelligent control of a touch pen based on a full-bridge strain gauge, characterized in that, The method comprises: Obtain the use scene information of the touch pen, analyze the touch operation demand in the use scene information, determine the full-bridge strain gauge suitable for the touch pen based on the touch operation demand, install the full-bridge strain gauge at the specified position of the touch pen, and then initialize and calibrate the full-bridge strain gauge to obtain calibration parameters; Based on the calibration parameters, real-time collection of strain data of the full-bridge strain gauge in the touch operation process is performed, calculation of the pressure value corresponding to the touch pen according to the strain data, generation of the operation instruction corresponding to the touch pen based on the pressure value and the touch position information corresponding to the touch pen; Based on the operation instruction, the function module corresponding to the touch pen is analyzed, the execution operation corresponding to the function module is determined, the pen tip action and the transmission signal corresponding to the touch pen are detected according to the execution operation, and the interaction response data corresponding to the touch pen is generated based on the pen tip action and the transmission signal, wherein the generation of the interaction response data corresponding to the touch pen based on the pen tip action and the transmission signal comprises: Analyzing the operation intention corresponding to the pen tip action and the transmission signal; Determining the interaction response type corresponding to the operation intention; Collecting the interaction response material corresponding to the interaction response type; Screening the material segment in the interaction response material; Extracting the key interaction element in the material segment; Generating the interaction response data corresponding to the touch pen based on the key interaction element; Analyzing the feedback parameter corresponding to the interaction response data, identifying the abnormal operation feature in the feedback parameter, and calculating the misoperation probability corresponding to the touch pen based on the abnormal operation feature; Based on the misoperation probability, the data of the full-bridge strain gauge in the touch operation process is optimized to obtain optimized data, the touch operation habit corresponding to the optimized data is analyzed, and the control scheme corresponding to the touch pen is developed based on the touch operation habit. 2.The smart control method for realizing a touch pen based on a full-bridge strain gauge according to claim 1, wherein, The initialization calibration of the full-bridge strain gauge to obtain the calibration parameters comprises: Querying the initial resistance value corresponding to the full-bridge strain gauge; Analyzing the basic electrical characteristics corresponding to the full-bridge strain gauge according to the initial resistance value; Based on the basic electrical characteristics, the full-bridge strain gauge is tested by using a preset standard pressure test device to obtain test data; Analyzing the deviation value between the test data and the preset standard; Based on the deviation value, the full-bridge strain gauge is initialized and calibrated to obtain the calibration parameters. 3.The smart control method for realizing a touch pen based on a full-bridge strain gauge according to claim 1, wherein, The real-time collection of strain data of the full-bridge strain gauge in the touch operation process based on the calibration parameters comprises: Querying the parameter frequency corresponding to the calibration parameters; Based on the parameter frequency, the full-bridge strain gauge is electrically signal detected to obtain original electric signals; The original electric signals are preprocessed to obtain preprocessed signal data; Analyzing the signal strain sequence corresponding to the preprocessed signal data; Based on the signal strain sequence, the strain data of the full-bridge strain gauge in the touch operation process is real-time collected. 4.The smart control method for realizing a touch pen based on a full-bridge strain gauge according to claim 1, wherein, The calculation of the pressure value corresponding to the touch pen according to the strain data comprises: The pressure value corresponding to the touch pen is calculated by using the following formula: ； wherein, represents a pressure value corresponding to the touch pen, represents a stiffness coefficient corresponding to the full-bridge strain gauge, represents a total number of measurement points corresponding to the touch pen, represents a quantity index corresponding to the measurement point, represents a strain change amount at the th measurement point, represents an initial strain value of the full-bridge strain gauge, represents a time variable, represents a strain rate of the touch pen over time, represents a constant compensation term. 5.The smart control method for realizing a touch pen based on a full-bridge strain gauge according to claim 1, wherein, The pen tip action and transmission signal corresponding to the touch pen are detected according to the execution operation, and the detection includes: Analyzing the use scene corresponding to the execution operation; Based on the use scene, the original action and signal data of the touch pen during use are collected; Screening key data segments in the original action and signal data; Extracting the pen tip action features and signal transmission features in the key data segments; Based on the pen tip action features and the signal transmission features, the pen tip action and transmission signal corresponding to the touch pen are detected. 6.The smart control method for realizing a touch pen based on a full-bridge strain gauge according to claim 1, wherein, The feedback parameter corresponding to the interaction response data is analyzed, and the analysis includes: Querying the response target corresponding to the interaction response data; Target refinement is performed on the response target to obtain a refined sub-target; Querying the target reference value corresponding to the refined sub-target; Based on the target reference value, an analysis rule corresponding to the interaction response data is determined; Based on the analysis rule, the feedback parameter corresponding to the interaction response data is analyzed. 7.The smart control method for a touch pen based on a full-bridge strain gauge according to claim 1, wherein, The misoperation probability corresponding to the touch pen is calculated based on the abnormal operation features, and the calculation includes: The misoperation probability corresponding to the touch pen is calculated by using the following formula: ； wherein, represents the probability of misoperation corresponding to the touch pen, represents the total number of times of the touch pen operation, represents the number index of the touch pen operation, represents the number of abnormal operation features, represents the number index of the abnormal operation features, represents the weight coefficient of the th abnormal operation feature of the th operation, represents the feature threshold function, represents the abnormal operation feature value after time processing, represents the time point of the th operation. 8.The smart control method for realizing a touch pen based on a full-bridge strain gauge according to claim 1, wherein, Based on the misoperation probability, the data of the full-bridge strain gauge during the touch operation process is optimized to obtain optimized data, and the optimization includes: Based on the misoperation probability, an optimization target corresponding to the data of the full-bridge strain gauge during the touch operation process is determined; According to the optimization target, the to-be-optimized points of the data of the full-bridge strain gauge during the touch operation process are screened; Querying the original data segment corresponding to the to-be-optimized point; Analyzing the optimizable direction corresponding to the original data segment; Based on the optimizable direction, an optimization strategy corresponding to the full-bridge strain gauge is constructed; Based on the optimization strategy, the data of the full-bridge strain gauge during the touch operation process is optimized to obtain optimized data.

9. The intelligent control system of the touch pen based on the full-bridge strain gauge, characterized in that, A system for executing the intelligent control method of the touch pen based on the full-bridge strain gauge as claimed in any one of claims 1-8, the system comprising: An initial calibration module for obtaining use scene information of the touch pen, analyzing touch operation requirements in the use scene information, determining a full-bridge strain gauge suitable for the touch pen based on the touch operation requirements, and performing initial calibration on the full-bridge strain gauge after installing the full-bridge strain gauge at a specified position of the touch pen to obtain calibration parameters; An instruction generation module for real-time collection of strain data of the full-bridge strain gauge during a touch operation process based on the calibration parameters, calculation of a pressure value corresponding to the touch pen according to the strain data, generation of operation instructions corresponding to the touch pen based on the pressure value and touch position information corresponding to the touch pen, and generation of operation instructions corresponding to the touch pen. The data generation module is configured to analyze a function module corresponding to the touch pen based on the operation instruction, determine an execution operation corresponding to the function module, detect a pen tip action and a transmission signal corresponding to the touch pen according to the execution operation, and generate interaction response data corresponding to the touch pen based on the pen tip action and the transmission signal. The generation of the interaction response data corresponding to the touch pen based on the pen tip action and the transmission signal includes the following steps. analyzing an operation intention corresponding to the pen tip action and the transmission signal; determining an interaction response type corresponding to the operation intention; collecting interaction response materials corresponding to the interaction response type; screening material segments in the interaction response materials; extracting key interaction elements in the material segments; generating the interaction response data corresponding to the touch pen based on the key interaction elements; The misoperation probability calculation module is configured to analyze feedback parameters corresponding to the interaction response data, identify abnormal operation characteristics in the feedback parameters, and calculate a misoperation probability corresponding to the touch pen based on the abnormal operation characteristics. The scheme development module is configured to perform optimization processing on data of the full-bridge strain gauge during a touch operation based on the misoperation probability, obtain optimized data, analyze a touch operation habit corresponding to the optimized data, and develop a control scheme corresponding to the touch pen based on the touch operation habit.

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