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

Abstract

The invention relates to the field of electronic equipment interaction, and provides a method for realizing intelligent control of a touch pen based on a full-bridge strain gauge, which comprises the following steps of: acquiring use scene information of the touch pen, determining the adaptive full-bridge strain gauge, carrying out initialization calibration, acquiring strain data, calculating a pressure value, generating an operation instruction in combination with a touch position, and then, carrying out intelligent control on the touch pen based on the full-bridge strain gauge. Analyzing the operation instruction to determine that the function module executes operation, detects pen point action and transmits signals to generate interaction response data, then analyzing feedback parameters of the interaction response data, identifies abnormal operation characteristics, calculates a misoperation probability, optimizes full-bridge strain gauge data based on the misoperation probability, analyzes a touch operation habit corresponding to the optimized data, and displays the optimized touch operation habit. And a touch pen control scheme is formulated. The control fluency of the touch pen in interaction of the electronic equipment can be improved.

Description

Technical Field

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

[0002] In today's electronic device interaction field, with the rapid development of technology and the continuous improvement of users' requirements for operating experience, the optimization of the functions and performance of touch pens as an important input tool has become crucial. Touch pens are widely used in electronic devices such as tablets and smart phones, providing users with more accurate and convenient operation methods, especially playing an irreplaceable role in scenes such as drawing, writing, and annotating.

[0003] At present, the traditional touch pen control method is relatively simple, mainly through basic pressure sensing or capacitive sensing to achieve basic writing and operation functions, but this method has many limitations. On the one hand, the traditional method is not accurate and comprehensive enough in recognizing the movements and postures of the touch pen, and it is difficult to meet the needs of users in complex operation scenarios. For example, when performing fine drawing or fast writing, it is impossible to accurately capture the user's subtle movement changes, resulting in the smoothness and accuracy of the operation being affected; on the other hand, the traditional control method lacks an intelligent interaction mechanism and cannot be adaptively adjusted according to the user's usage habits and specific scenarios, which reduces the operational fluency of the user experience. Therefore, a touch pen intelligent control method based on a full-bridge strain gauge is needed to improve the control fluency of the touch pen in the interaction of electronic devices. Summary of the invention

[0004] The present invention provides an intelligent control method and system for a touch pen based on a full-bridge strain gauge, the main purpose of which is to improve the control fluency of the touch pen in the interaction of electronic devices.

[0005] To achieve the above object, the present invention provides an intelligent control method for a touch pen based on a full-bridge strain gauge, comprising:

[0006] Acquire usage scenario information of the touch pen, analyze touch operation requirements in the usage scenario information, determine a full-bridge strain gauge adapted 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 initialize and calibrate the full-bridge strain gauge to obtain calibration parameters;

[0007] Based on the calibration parameters, strain data of the full-bridge strain gauge during the touch operation is collected in real time, a pressure value corresponding to the touch pen is calculated according to the strain data, and an operation instruction corresponding to the touch pen is generated based on the pressure value and touch position information corresponding to the touch pen;

[0008] Based on the operation instruction, analyzing the functional module corresponding to the touch pen, determining the execution operation corresponding to the functional module, detecting the pen tip movement and the 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 movement and the transmission signal;

[0009] analyzing feedback parameters corresponding to the interactive response data, identifying abnormal operation features in the feedback parameters, and calculating a probability of misoperation corresponding to the touch pen based on the abnormal operation features;

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

[0011] Optionally, the initializing and calibrating the full-bridge strain gauge to obtain calibration parameters includes:

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

[0013] Analyzing basic electrical characteristics corresponding to the full-bridge strain gauge according to the initial resistance value;

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

[0015] Analyzing the deviation 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 calibration parameters.

[0017] Optionally, the collecting strain data of the full-bridge strain gauge during the touch operation in real time based on the calibration parameters includes:

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

[0019] Based on the parameter frequency, performing electrical signal detection on the full-bridge strain gauge to obtain an original electrical signal;

[0020] Preprocessing the original electrical signal to obtain preprocessed signal data;

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

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

[0023] Optionally, calculating the pressure value corresponding to the touch pen according to the strain data includes:

[0024] The pressure value corresponding to the touch pen is calculated using the following formula:

[0025]

[0026] 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 number 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 touch pen over time, and C represents a constant compensation term.

[0027] Optionally, the detecting, according to the execution operation, a pen tip movement and a transmission signal corresponding to the touch pen includes:

[0028] Analyze the usage scenario corresponding to the execution operation;

[0029] Based on the usage scenario, collecting original motion and signal data of the touch pen during use;

[0030] Filtering key data segments from the original action and signal data;

[0031] Extracting pen tip motion features and signal transmission features in the key data segment;

[0032] Based on the pen tip motion characteristics and the signal transmission characteristics, the pen tip motion and transmission signal corresponding to the touch pen are detected.

[0033] Optionally, the generating interactive response data corresponding to the touch pen based on the pen tip action and the transmission signal includes:

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

[0035] Determining an interactive response type corresponding to the operation intention;

[0036] Collecting interactive response materials corresponding to the interactive response type;

[0037] Filtering material clips in the interactive response material;

[0038] extracting key interactive elements from the material clips;

[0039] Based on the key interactive element, interactive response data corresponding to the touch pen is generated.

[0040] Optionally, analyzing the feedback parameters corresponding to the interactive response data includes:

[0041] Querying a response target corresponding to the interactive response data;

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

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

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

[0045] Based on the analysis rule, feedback parameters corresponding to the interactive response data are analyzed.

[0046] Optionally, the calculating, based on the abnormal operation feature, a probability of misoperation corresponding to the touch pen includes:

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

[0048]

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

[0050] Optionally, the optimizing processing of the data of the full-bridge strain gauge during the touch operation based on the probability of misoperation to obtain optimized data includes:

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

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

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

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

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

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

[0057] Optionally, in order to solve the above problem, the present invention provides an intelligent control system for a touch pen based on a full-bridge strain gauge, the system comprising:

[0058] An initial calibration module is used to obtain usage scenario information of the touch pen, analyze touch operation requirements in the usage scenario information, determine a full-bridge strain gauge adapted for the touch pen based on the touch operation requirements, and after installing the full-bridge strain gauge at a designated position of the touch pen, initialize and calibrate the full-bridge strain gauge to obtain calibration parameters;

[0059] an instruction generation module, 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;

[0060] a data generating module, configured to analyze the function module corresponding to the touch pen based on the operation instruction, determine the execution operation corresponding to the function module, detect the pen tip action and the transmission signal corresponding to the touch pen according to the execution operation, and generate the interaction response data corresponding to the touch pen based on the pen tip action and the transmission signal;

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

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

[0063] Firstly, the present invention can make the control of the touch pen more accurately fit the actual usage by acquiring the usage scenario information of the touch pen and analyzing the touch operation requirements in the usage scenario information. For example, in the drawing scenario, by understanding the scenario information, the user's specific operation requirements for line thickness, color selection, pen pressure change, etc. can be analyzed, so that the touch pen can respond to these requirements more accurately during the drawing process. At the same time, based on the calibration parameters, the present invention collects the strain data of the full-bridge strain gauge during the touch operation in real time, and eliminates the data deviation caused by individual differences in equipment, installation errors and environmental factors, so that the collected strain data can reflect the various forces and deformations to which the touch pen is subjected during actual use. Based on the operation instructions, the present invention analyzes the functional modules corresponding to the touch pen and determines the execution operations corresponding to the functional modules, so that the touch pen can flexibly switch and execute different tasks in various application scenarios, and And by analyzing the functional modules and determining the execution operation, it 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. The present invention can include response time, accuracy, stability, etc. by analyzing the feedback parameters corresponding to the interactive response data, which directly reflects the quality of the interaction between the touch pen and the system. For example, a short response time means that the user operation can be responded to quickly, which improves the fluency and immediacy of the interaction, so that the user will not feel stuck or delayed when drawing, writing or performing other operations. Further, based on the probability of misoperation, the present invention optimizes the data of the full-bridge strain gauge during the touch operation to obtain optimized data, which can identify data patterns or abnormal situations that may cause misoperation, and then optimize the data of the full-bridge strain gauge in a targeted manner, which helps to reduce false triggers caused by inaccurate or abnormal data, ensure that the touch operation can accurately reflect the user's intention, and improve user experience and operation efficiency. Therefore, the intelligent control method and system for realizing a touch pen based on a full-bridge strain gauge proposed in the present invention can improve the control fluency of the touch pen in the interaction of electronic devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic flow chart of a method for realizing intelligent control of a touch pen based on a full-bridge strain gauge provided in one embodiment of the present invention;

[0065] Figure 2 A schematic diagram of a module for realizing an intelligent control system of a touch pen based on a full-bridge strain gauge provided in an embodiment of the present invention.

[0066] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0067] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0068] The embodiment of the present application provides an intelligent control method for a touch pen based on a full-bridge strain gauge. The execution subject of the intelligent control method for a touch pen based on a full-bridge strain gauge includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the intelligent control method for a touch pen based on a 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, etc.

[0069] Embodiment 1:

[0070] Reference Figure 1 FIG. 1 is a flow chart of a method for realizing intelligent control of a touch pen based on a full-bridge strain gauge according to an embodiment of the present invention. In this embodiment, the method for realizing intelligent control of a touch pen based on a full-bridge strain gauge includes:

[0071] S1. Obtain usage scenario information of the touch pen, analyze touch operation requirements in the usage scenario information, determine a full-bridge strain gauge compatible with the touch pen based on the touch operation requirements, install the full-bridge strain gauge at a specified position of the touch pen, and then initialize and calibrate the full-bridge strain gauge to obtain calibration parameters.

[0072] The present invention can make the control of the touch pen more accurately fit the actual usage situation by acquiring 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, the user's specific operation requirements for line thickness, color selection, pen pressure changes, etc. can be analyzed, so that the touch pen can respond to these requirements more accurately during the drawing process.

[0073] Among them, the touch pen refers to an input tool for performing touch operations on an electronic device, which realizes various functions such as writing, drawing, and annotation by contacting the screen of the electronic device; the usage scenario information refers to information related to the specific environment and situation in which the touch pen is used during use, which includes but is not limited to the type of device using the touch pen (such as a tablet computer, a smart phone, etc.), the type of application (such as painting software, office software, note-taking application, etc.), the specific scenario of use (such as classroom note-taking, artistic creation, business meeting annotation, etc.) and other related factors involved; the touch operation requirement refers to the user's specific requirements for the operation functions and performance of the touch pen in a specific usage scenario, for example, in a drawing scenario, including requirements for line precision. In the writing scenario, it involves the requirements of writing fluency, font recognition accuracy, and writing speed adaptability; in the annotation scenario, it focuses on the diversity of annotation tools, clarity of markings, and interactivity with document content. Optionally, the acquisition of the usage scenario information of the touch pen can be achieved through built-in sensors, such as acceleration sensors, gyroscopes and other sensors; the analysis of touch operation requirements in the usage scenario information can be achieved through an association rule mining algorithm, such as using an association rule mining algorithm in an electronic reading application scenario, using a touch pen to perform a text selection operation followed by an annotation operation, so that the user's associated touch operation requirements in this scenario can be mined.

[0074] The present invention determines the full-bridge strain gauge adapted for the touch pen based on the touch operation requirements, thereby ensuring that the touch pen can achieve optimal performance in different usage scenarios. For example, in a drawing scenario, for operation requirements that require precise depiction of details and reflection of different pen stroke pressure changes, excessive loss or failure caused by mismatch can be reduced, thereby reducing maintenance and replacement costs.

[0075] Among them, the full-bridge strain gauge refers to a sensor element used to measure the strain generated when an object is deformed by force. It 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 on the full-bridge strain gauge will change accordingly. Optionally, the determination of the full-bridge strain gauge suitable for the touch pen can be achieved through a computer screening method, such as: quickly screening out full-bridge strain gauges that are theoretically more suitable for touch operation requirements through computer simulation.

[0076] The present invention installs the full-bridge strain gauge at a specified position of the touch pen and then initializes and calibrates the full-bridge strain gauge to obtain calibration parameters, thereby ensuring that the full-bridge strain gauge accurately senses and measures changes in various physical quantities of the touch pen during use. Different installation positions may affect the measurement results of the full-bridge strain gauge. The calibration process can eliminate errors caused by installation differences, so that the strain gauge can truly reflect information such as pressure and deformation exerted on the touch pen, thereby providing reliable basic data for subsequent accurate data analysis and control.

[0077] Among them, the designated 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 the use of the touch pen; the calibration parameter refers to a series of parameters used to adjust and correct the measurement results of the full-bridge strain gauge obtained by analyzing and processing the deviation value between the test data and the preset standard during the initialization calibration of the full-bridge strain gauge.

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

[0079] Among them, 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 variation characteristics with temperature (resistance temperature coefficient), the relationship between resistance and voltage and current, etc.; the preset standard pressure test equipment refers to a device specially used for pressure testing of a full-bridge strain gauge or a device containing a full-bridge strain gauge (such as a touch pen), which can accurately apply pressure of known magnitude and direction and has a high-precision pressure measurement function, and usually includes a pressure generator (such as a hydraulic device, a pneumatic device or a mechanical loading device, etc.), a pressure sensor (used to accurately measure the applied pressure value) and a pressure sensor connected to the full-bridge strain gauge. and data acquisition interface; the test data refers to the relevant data of the full-bridge strain gauge collected during the pressure test of the full-bridge strain gauge using a preset standard pressure testing device, mainly including the resistance change value, voltage output change value, etc. of the full-bridge strain gauge under different pressures; the preset standard refers to a series of data or indicators pre-set as a reference benchmark during the calibration of the full-bridge strain gauge, for example, the ideal resistance change value range and linearity requirements (i.e. the degree of linear relationship between resistance change and pressure change) of the full-bridge strain gauge under different pressures all belong to the category of the preset standard; the deviation value refers to the difference between the test data obtained by testing the full-bridge strain gauge using the standard pressure testing device and the preset standard after comparing the two.

[0080] Further, the query of the initial resistance value corresponding to the full-bridge strain gauge can be achieved through a multimeter measurement method, such as: correctly connecting the pins of the full-bridge strain gauge to the test probes of the multimeter to ensure that the connection is good and there is no 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 achieved through a spectrum analyzer, such as: applying an AC signal of a certain frequency to the full-bridge strain gauge, and observing the spectrum changes of the signal after passing through the strain gauge through a spectrum analyzer, which can reflect the frequency response characteristics of the full-bridge strain gauge; the pressure test of the full-bridge strain gauge using a preset standard pressure test device can be achieved through a pneumatic loading device, such as: using a pneumatic loading device to generate compressed air as a pressure source, and accurately adjusting the air pressure through a pressure control system, thereby applying pressure to the full-bridge strain gauge; the analysis of the deviation value between the test data and the preset standard can be achieved through a visualization tool, such as: MATLAB, Python and other tools; the initialization calibration of the full-bridge strain gauge can be achieved through a calibration algorithm, such as: a least squares calibration algorithm, a polynomial fitting calibration algorithm, etc.

[0081] S2. Based on the calibration parameters, the strain data of the full-bridge strain gauge during the touch operation is collected in real time, the pressure value corresponding to the touch pen is calculated according to the strain data, and the operation instruction corresponding to the touch pen is generated based on the pressure value and the touch position information corresponding to the touch pen.

[0082] The present invention collects the strain data of the full-bridge strain gauge during the touch operation in real time based on the calibration parameters, and eliminates the data deviation that may be caused by individual differences in equipment, installation errors, and environmental factors, so that the collected strain data can reflect the various forces and deformations to which the touch pen is subjected during actual use.

[0083] Among them, the strain data refers to the accurate strain information about the full-bridge strain gauge during the touch operation that is finally collected in real time. It is the data that can accurately reflect the mechanical impact of the touch operation on the strain gauge after a series of previous steps, including determining the parameter frequency based on the calibration parameters, detecting the original electrical signal, preprocessing, and analyzing the signal strain sequence.

[0084] As an embodiment of the present invention, the real-time collection of strain data of the full-bridge strain gauge during the touch operation process based on the calibration parameters includes: querying the parameter frequency corresponding to the calibration parameters; based on the parameter frequency, performing electrical signal detection on the full-bridge strain gauge to obtain an original electrical signal; preprocessing the original electrical signal to obtain preprocessed signal data; analyzing the signal strain sequence corresponding to the preprocessed signal data; and based on the signal strain sequence, collecting the strain data of the full-bridge strain gauge during the touch operation process in real time.

[0085] Among them, the parameter frequency refers to the specific operating frequency or data acquisition frequency related to the full-bridge strain gauge when operating based on the calibration parameters; the original electrical signal refers to the initial electrical signal output of the full-bridge strain gauge during the touch operation without any processing or processing. This original electrical signal contains a comprehensive reflection of various original information about the touch operation, such as the pressure size, direction, and duration of the action; the preprocessed signal data refers to the data obtained after a series of preliminary processing of the original electrical signal. The preprocessing process usually includes noise removal, filtering, amplification and other operations; the signal strain sequence refers to an ordered sequence reflecting the change of strain of the full-bridge strain gauge over time during the touch operation obtained by analyzing and calculating the preprocessed signal data. It converts the preprocessed electrical signal data into information related to strain, and each data point in the sequence corresponds to the strain value at a specific moment.

[0086] Furthermore, the query of the parameter frequency corresponding to the calibration parameter can be achieved by querying a database, such as MySQL, Oracle and other databases; the electrical signal detection of the full-bridge strain gauge can be achieved by a strain gauge, such as a resistance strain gauge, an optical fiber strain gauge and other tools; the preprocessing of the original electrical signal can be achieved by a digital filtering algorithm, such as a mean filtering algorithm, a median filtering algorithm, a Kalman filtering algorithm, etc.; the analysis of the signal strain sequence corresponding to the preprocessed signal data can be achieved by a deep learning framework, such as TensorFlow, PyTorch, etc.; the real-time acquisition of the strain data of the full-bridge strain gauge during the touch operation can be achieved by a real-time operating system, such as FreeRTOS, RT-Thread and other system tools.

[0087] The present invention 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 perform personalized adaptation and adjustment, so that the touch pen can exert the best performance in the hands of various users, further expanding the application scope and practicality of the touch pen in various fields.

[0088] The pressure value refers to a quantitative value of the pressure generated when the touch pen is in use due to contact with the touch surface and being acted upon by various forces.

[0089] As an embodiment of the present invention, calculating the pressure value corresponding to the touch pen according to the strain data includes:

[0090] The pressure value corresponding to the touch pen is calculated 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 number 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 touch pen over 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 of the material and structure of the full-bridge strain gauge. The larger the stiffness coefficient, the smaller the strain generated by the strain gauge when subjected to the same external force, that is, the strain gauge is relatively hard and not easy to deform; conversely, the smaller the stiffness coefficient, the easier it is for the strain gauge to generate a 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 touch pen or its related system for measuring strain data; the strain change refers to the change in the full-bridge strain gauge from the initial state to the current state at the "i"th measurement point. The strain value is the change in strain under the state, and strain is the relative change in shape or size of an object when it is subjected to external force; the initial strain value refers to the strain state value of the full-bridge strain gauge when it is not subjected to any external force; the time variable refers to the time history from the start of the touch operation to the current moment; the strain rate refers to the rate of change of strain over time during the use of the touch pen, that is, the change in 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, and there are some factors that cannot be directly calculated through strain data, such as system errors, the influence of environmental factors, etc.

[0094] The present invention generates operation instructions corresponding to the touch pen based on the pressure value and the touch position information corresponding to the touch pen, which can greatly enrich the operation functions and interactivity of the touch pen and realize more delicate and diversified operation instructions. For example, in electronic signatures, by analyzing the dynamic changes of pressure values ​​and touch positions, the authenticity and uniqueness of the signature can be verified to prevent forgery. In short, this method can give full play to the potential of the touch pen and improve the user's interactive experience and work efficiency in various application scenarios.

[0095] The touch position information refers to the specific position coordinates of the touch pen on the surface of the touch device (such as a tablet computer, a touch screen mobile phone, etc.) when the touch pen interacts with the touch device. This position information is usually expressed in the form of two-dimensional plane coordinates. For example, on a touch screen with a resolution of 1920×1080, the touch position can be determined by the values ​​of the horizontal coordinate and the vertical coordinate to determine the specific screen position. For example, (500,300) represents a position 500 pixels away from the left edge of the screen in the horizontal direction and 300 pixels away from the upper edge of the screen in the vertical direction; the operation instruction refers to a command generated based on the pressure value and touch position information of the touch pen for controlling the touch device to perform a specific operation. The operation instruction can have multiple forms. For example, in drawing software, the operation instruction may include drawing lines, filling colors, selecting tools, etc.; in word processing software, the operation instruction may be inputting text, deleting characters, setting font format, etc. Optionally, the generation of the operation instruction corresponding to the touch pen can be implemented by a neural network model, such as: CNN, LSTM and other models.

[0096] S3. Based on the operation instruction, analyze the functional module corresponding to the touch pen, determine the execution operation corresponding to the functional module, detect the pen tip movement and 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 movement and the transmission signal.

[0097] The present invention analyzes the functional modules corresponding to the touch pen based on the operation instructions and determines the execution operations corresponding to the functional modules, so that the touch pen can be flexibly switched and execute different tasks in various application scenarios. In addition, by analyzing the functional modules and determining the execution operations, a basis can be provided for the personalized settings of the touch pen, so that the touch pen can better adapt to the needs of different users.

[0098] Among them, the functional module refers to an independent unit with specific functions inside the touch pen or in a software system associated with it, which can be a specific functional part implemented by a hardware component, or a code module in a software program that is responsible for a specific task. For example, in the functional system of the touch pen, there is a pressure sensing module that is responsible for detecting the pressure value of the touch pen and converting it into an electrical signal; there is also a communication module for transmitting data with the touch device; the drawing function module can draw different shapes and lines on the touch device according to the input instructions; the execution operation refers to the specific action or task performed by the functional module according to the received operation instruction. For example, for the drawing function module, the execution operation may 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 may be sending the current pressure value and touch position information to the touch device; for the pressure sensing module, the execution operation may be real-time updating and providing the current pressure data. Optionally, the analysis of the functional module corresponding to the touch pen can be implemented by an expert system development tool, such as CLIPS, JESS and other tools; the determination of the execution operation corresponding to the functional module can be implemented by a rule engine tool, such as Drools, OpenRules and other tools.

[0099] Furthermore, the present invention detects the pen tip movement and transmission signal corresponding to the touch pen according to the execution operation, thereby realizing accurate monitoring and feedback of the touch pen operation, and can accurately understand the user's specific behaviors such as writing and drawing when using the touch pen, such as the movement trajectory of the pen tip, pressure changes, dwell time, etc., and can ensure stable and accurate communication between the touch pen and the device, and timely convey the user's operating intentions to the device.

[0100] Among them, the pen tip action refers to the specific physical movement and operation of the pen tip of the touch pen on the touch surface, including various forms of action such as moving, clicking, hovering, and pressure changes; the transmission signal refers to the electronic signal for communication between the touch pen and the device, which carries the status information of the touch pen and user operation information, 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 invention, detecting the pen tip movement and transmission signal corresponding to the touch pen according to the execution operation includes: analyzing the usage scenario corresponding to the execution operation; based on the usage scenario, collecting original movement and signal data of the touch pen during use; screening key data segments in the original movement and signal data; extracting pen tip movement characteristics and signal transmission characteristics in the key data segments; and detecting the pen tip movement and transmission signal corresponding to the touch pen based on the pen tip movement characteristics and the signal transmission characteristics.

[0102] The usage scenario refers to the context and environment of the touch pen in a specific application. For example, different situations such as fine drawing in painting software, annotation in documents, and operation in games all belong to different usage scenarios. The original action refers to the unprocessed physical action performance of the touch pen during use, including the movement, click, pressure change and other actions of the pen tip on the touch surface directly generated by the user's operation. The signal data refers to the electronic signal data transmitted and communicated between the touch pen and the device, including the position information, pressure value, button status and other data sent by the touch pen to the device, as well as the feedback signal sent by the device to the touch pen. The key data A fragment refers to a data part that is important and representative and is screened out from the original action and signal data. For example, during the painting process, the data fragment of the time period when the pen tip moves quickly and produces a large pressure change can be considered as a key data fragment; the pen tip action feature refers to the attribute that describes the pen tip action characteristics extracted from the key data fragment. For example, the speed, acceleration, trajectory shape, pressure change curve, etc. of the pen tip movement are all pen tip action features; the signal transmission feature refers to the attribute that describes the signal transmission situation extracted from the key data fragment. For example, the signal strength, stability, delay time, transmission frequency, etc. are all signal transmission features.

[0103] Furthermore, the analysis of the usage scenarios corresponding to the execution operations can be achieved through a classification algorithm, such as: support vector machine (SVM) or random forest, training these data to establish a classification model, and when there is a new execution operation, its features are input into the model, and the model automatically predicts the corresponding usage scenarios; the collection of the original action and signal data of the touch pen during use can be achieved through sensor tools, such as: accelerometers, pressure sensors, gyroscopes and other tools; the screening of key data fragments in the original action and signal data can be achieved through a data analysis library, such as: NumPy, Pandas and other libraries; the extraction of pen tip action features and signal transmission features in the key data fragments can be achieved through a deep learning framework, such as: TensorFlow, PyTorch and other frameworks; the detection of the pen tip action and transmission signal corresponding to the touch pen can be achieved through anomaly detection methods, such as: autoencoders, isolation forests and other methods.

[0104] The present invention generates interactive response data corresponding to the touch pen based on the pen tip action and the transmission signal, and can make accurate responses to user operations in real time. Whether it is the delicate changes in brush strokes when painting, the importance of writing, or clicks, sliding and other operations in various application scenarios, timely and appropriate feedback can be obtained, making the user feel as natural as writing or painting on real paper, greatly improving the user's comfort and immersion.

[0105] Among them, the interactive response data refers to the specific data ultimately generated based on the key interactive elements for feedback to the user or the system. In painting software, the interactive response data can be lines of specific colors and shapes displayed on the screen; in games, the interactive response data can be specific sound effects played, animation effects displayed, etc.

[0106] As an embodiment of the present invention, generating interactive response data corresponding to the touch pen based on the pen tip action and the transmission signal includes: analyzing the operation intention corresponding to the pen tip action and the transmission signal; determining the interactive response type corresponding to the operation intention; collecting interactive response materials corresponding to the interactive response type; screening material fragments in the interactive response materials; extracting key interactive elements in the material fragments; and generating interactive response data corresponding to the touch pen based on the key interactive elements.

[0107] Among them, the operation intention refers to the specific purpose or expected operation result expressed by the user through the pen tip movement and transmission signal of the touch pen. For example, rapid movement of the pen tip accompanied by greater pressure may indicate that the user wants to draw thick lines or make emphasized marks; light tapping of the pen tip accompanied by specific transmission signals may indicate that the user wants to select an object, etc.; the interactive response type refers to different types of interactive feedback methods determined according to the operation intention. For example, for a painting scene, the interactive response type may include line drawing, color filling, eraser erasing, etc.; for a document editing scene, the interactive response type may include text input, deletion, format adjustment, etc.; the interactive response material refers to various resources that may be used and collected to generate interactive response data. This may include graphic elements, color libraries, font libraries, sound effects, etc. For example, in painting In software, interactive response materials may include brushes of different shapes, palettes of various colors, etc.; in games, interactive response materials may include sound effect files, animation effects, etc.; the material fragment refers to a part of the content with a specific purpose selected from the interactive response material, for example, in painting software, a material fragment of a specific color range is selected from the color library according to the user's operating intention; in games, a sound material fragment related to a specific action is selected from the sound effect file; the key interactive element refers to an element extracted from the material fragment that plays a key role in generating interactive response data, for example, in painting, the specific color value extracted from the color material fragment, the brush stroke shape and size extracted from the brush material fragment, etc.; in games, specific audio features extracted from the sound effect material fragment, etc.

[0108] Furthermore, the analysis of the operation intention corresponding to the pen tip action and the transmission signal can be achieved through a classification algorithm, such as: support vector machine (SVM) or random forest, training 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 interactive response type corresponding to the operation intention can be achieved through a decision tree algorithm, such as: using the features of the operation intention as the input node of the decision tree, and the interactive response type as the leaf node of the decision tree; the collection of interactive response materials corresponding to the interactive response type can be achieved through a network request library, such as: Python's requests library and other tools; the screening of material fragments in the interactive response material can be achieved through script programming tools, such as: Python, C++ and other tools; the extraction of key interactive elements in the material fragments can be achieved through element extraction tools, such as: OpenCV, PIL and other tools; the generation of interactive response data corresponding to the touch pen can be achieved through programming languages ​​and related libraries, such as: Python's Jinja2 template engine.

[0109] S4. Analyze feedback parameters corresponding to the interactive response data, identify abnormal operation features in the feedback parameters, and calculate a probability of misoperation corresponding to the touch pen based on the abnormal operation features.

[0110] The present invention analyzes the feedback parameters corresponding to the interactive response data, which may include response time, accuracy, stability, etc., which directly reflects the quality of the interaction between the touch pen and the system. For example, a short response time means that the user operation can be responded to quickly, which improves the fluency and immediacy of the interaction, so that the user will not feel lag or delay when drawing, writing or performing other operations.

[0111] The feedback parameters refer to specific indicators used to evaluate the quality and effect of interactive response data, such as response time, accuracy, stability, resource occupancy rate, etc.

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

[0113] The response target refers to the overall effect or purpose that the interactive response data is expected to achieve. For example, in painting software, the response target may be to quickly and accurately present the user's painting operations, provide a rich selection of colors and brushstrokes, etc.; in game applications, the response target may be to respond to the player's operating instructions in a timely manner, provide a smooth gaming experience, etc.; the detailed sub-target refers to the specific and measurable small goals that the response target is further decomposed into. For example, if the response target is to quickly and accurately present the user's painting operations, the detailed sub-targets may include the smoothness of the painting lines, the accuracy of the colors, the response time, etc.; the target reference value refers to the standard value or range used to measure whether the detailed sub-target has reached the expected standard value, for example For example, for the refined sub-goal of the smoothness of drawing lines, the target reference value can be the length of lines drawn per second, the degree of jitter of the lines within a certain range, etc.; for the refined sub-goal of response time, the target reference value can be a time range of milliseconds; the analysis rule refers to the specific method and standard for analyzing the feedback parameters of interactive response data formulated according to the target reference value. For example, if the target reference value stipulates that the response time should be within 50 milliseconds, the analysis rule can be to count the response time of each operation in the interactive response data and determine whether it exceeds 50 milliseconds; the feedback parameter refers to the specific indicator used to evaluate the quality and effect of interactive response data, such as response time, accuracy, stability, resource occupancy rate, etc.

[0114] Furthermore, the query of the response target corresponding to the interactive response data can be achieved through a scenario simulation tool, such as: using the scenario simulation tool to simulate various actual application scenarios, combined with the demand analysis tool to sort out and determine the response target; the target refinement of the response target can be achieved through a mind mapping tool, such as: XMind, MindManager and other tools; the query of the target reference value corresponding to the refined sub-target can be achieved through industry standard reference methods, such as: industry standard documents, technical specification databases, etc.; the determination of the analysis rules corresponding to the interactive response data can be achieved through data analysis, such as: Excel, SPSS and other tools; the analysis of the feedback parameters corresponding to the interactive response data can be achieved through a simulation test tool, such as: using a simulation test tool to simulate various usage scenarios and user operations, and collect feedback parameters of the interactive response data.

[0115] By identifying abnormal operation characteristics in the feedback parameters, the present invention can promptly discover and solve potential system problems, and can quickly locate abnormal situations occurring during the interaction process, such as sudden response delays, a significant decrease in operation accuracy, etc., which helps technicians to promptly troubleshoot problems and take corresponding measures to repair them, thereby ensuring the stable operation of the touch pen.

[0116] Among them, the abnormal operation characteristics refer to the specific properties or performances of the feedback parameters that deviate from the normal mode or expected range during the interaction between the touch pen and the system. These characteristics can be reflected in many aspects, such as the operation response time is significantly longer than the normal average (such as the normal response time is 50 milliseconds, and it reaches more than 200 milliseconds when abnormal); the accuracy of the operation fluctuates greatly, such as the drawing accuracy of the original drawing line is more than 95%, and suddenly drops to less than 70%; or in terms of pressure sensing, abnormal pressure value changes occur, such as high pressure values ​​are recorded when no obvious pressure is applied, etc. Optionally, the identification of abnormal operation characteristics in the feedback parameters can be achieved through anomaly detection algorithms, such as: Isolation Forest, One-Class SVM and other algorithms.

[0117] Furthermore, the present invention calculates the probability of misoperation corresponding to the touch pen based on the abnormal operation characteristics, and can intuitively understand the operation accuracy during the use of the touch pen. When the probability of misoperation is high, the operation can be performed more cautiously or the operation method can be checked to see whether it is correct, thereby reducing unnecessary troubles and erroneous results caused by misoperation, for example, avoiding content errors or losses caused by misoperation in important document editing or drawing creation.

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

[0119] As an embodiment of the present invention, the calculating the probability of misoperation corresponding to the touch pen based on the abnormal operation feature includes:

[0120] The probability of misoperation corresponding to the touch pen is calculated using the following formula:

[0121]

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

[0123] In detail, the weight coefficient refers to the relative importance of the jth abnormal operation feature representing the i'th operation in judging an erroneous operation. For example, the impact of abnormal pen tip pressure on erroneous operation is greater than that of abnormal pen tip movement speed, so the weight coefficient corresponding to the abnormal pen tip pressure will be greater than the weight coefficient corresponding to the abnormal pen tip movement speed; the feature threshold function refers to a function used to determine 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 value of the jth abnormal operation feature of the i'th operation after time processing. For example, if the abnormal operation feature is the pen tip pressure fluctuation value, then the abnormal operation feature value can be the average value, integral value or other statistic of the pressure fluctuation value within a specific time interval.

[0124] S5. Based on the probability of misoperation, optimize the data of the full-bridge strain gauge during the touch operation to obtain optimized data, analyze the touch operation habits corresponding to the optimized data, and formulate a control plan corresponding to the touch pen based on the touch operation habits.

[0125] Based on the probability of misoperation, the present invention optimizes the data of the full-bridge strain gauge during the touch operation to obtain optimized data, and can identify data patterns or abnormal conditions that may lead to misoperation, and then perform targeted optimization processing on the data of the full-bridge strain gauge, which helps to reduce false triggering caused by inaccurate or abnormal data, ensure that the touch operation can accurately reflect the user's intention, and improve user experience and operating efficiency.

[0126] The optimization data refers to the data of the full-bridge strain gauge during the touch operation obtained after being processed by the optimization strategy.

[0127] As an embodiment of the present invention, the data of the full-bridge strain gauge during the touch operation is optimized based on the probability of misoperation to obtain optimized data, including: determining an optimization target corresponding to the data of the full-bridge strain gauge during the touch operation based on the probability of misoperation; screening points to be optimized in the data of the full-bridge strain gauge during the touch operation according to the optimization target; querying the original data segments corresponding to the points to be optimized; analyzing the optimizable directions corresponding to the original data segments; based on the optimizable directions, constructing an optimization strategy corresponding to the full-bridge strain gauge; based on the optimization strategy, optimizing the data of the full-bridge strain gauge during the touch operation to obtain optimized data.

[0128] Among them, the optimization target refers to the specific purpose to be achieved by optimizing the data of the full-bridge strain gauge during the touch operation process determined according to the probability of misoperation, for example, reducing the noise level of the data, improving the accuracy of the data, enhancing the stability of the data, etc.; the points to be optimized refer to the specific positions or data points in the data of the full-bridge strain gauge during the touch operation process that are determined to need to be optimized; the original data segment refers to a segment of original data containing the points to be optimized; the optimizable direction refers to the direction that can be improved after analyzing the original data segment of the pointer to be optimized, for example, it can be to reduce the fluctuation amplitude of the data, adjust the mean of the data, remove outliers, etc.; the optimization strategy refers to the specific optimization method and steps formulated according to the optimizable direction, for example, using a filtering algorithm to remove noise, using an interpolation method to fill missing values, and performing data standardization.

[0129] Furthermore, the determination of the optimization target corresponding to the data of the full-bridge strain gauge during the touch operation process can be achieved through data analysis tools, such as Excel, SPSS and other tools; the screening of the points to be optimized in the data of the full-bridge strain gauge during the touch operation process can be achieved through an outlier detection algorithm, such as: a statistical method (such as a Z-score method) or a machine learning method (such as an isolation forest algorithm) to detect outliers in the full-bridge strain gauge data; the query of the original data segment corresponding to the point to be optimized can be achieved through a time window method, such as: determining a time window range based on the timestamp of the point to be optimized, and then filtering out the outliers from the original data segment of the full-bridge strain gauge. The data segments within the time window are extracted from the initial data; the analysis of the optimizable directions corresponding to the original data segments can be achieved through the principal component analysis method, such as: using the principal component analysis method to reduce the dimension of the original data segments, analyzing the main components and change trends of the data, and determining the optimizable directions 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 through the data interpolation method, such as: the optimization strategy can be constructed using the data interpolation method; the optimization processing of the data of the full-bridge strain gauge during the touch operation can be achieved through embedded system development tools, such as: Arduino, Raspberry Pi and other tools.

[0130] The present invention helps to further optimize the performance and user experience of the touch device by analyzing the touch operation habits corresponding to the optimization data, and by in-depth understanding of the user's touch operation habits, such as touch strength, frequency, duration, etc., the sensitivity and response mode of the full-bridge strain gauge can be adjusted in a targeted manner, making the touch operation more accurate and smooth, and reducing the occurrence of misoperation.

[0131] Among them, the touch operation habit refers to the touch behavior pattern with certain regularity and repeatability exhibited by the user when using a touch device (such as a touch device with a full-bridge strain gauge), which includes but is not limited to the distribution of the strength of the user's touch, the frequency of touch (such as the number of touches per unit time), the duration of touch, the trajectory characteristics of the touch (such as straight line sliding, curve sliding, etc.), the position preference of touch (for example, frequent touches in a specific area of ​​the screen), etc. Optionally, the analysis of the touch operation habits corresponding to the optimization data can be achieved through 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 time series data to predict the user's touch operation habit type.

[0132] Furthermore, the present invention formulates a control scheme corresponding to the touch pen based on the touch operation habits, which can adjust the sensitivity of the touch pen so that it can respond to such light and fast operations more quickly, thereby allowing users to feel more smooth and natural during use.

[0133] Among them, the control scheme refers to a collection of adjustment and optimization measures formulated for the operation and performance of the touch pen according to the user's touch operation habits, which includes but is not limited to specific provisions on the sensitivity setting of the touch pen, pressure sensing range adjustment, response speed optimization, function triggering method customization, etc. For example, if the user's touch operation habit 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 fast-moving operations. Optionally, the control scheme corresponding to the touch pen can be implemented through a machine learning framework, such as: TensorFlow, Scikit-learn and other tools.

[0134] Firstly, the present invention can make the control of the touch pen more accurately fit the actual usage by acquiring the usage scenario information of the touch pen and analyzing the touch operation requirements in the usage scenario information. For example, in the drawing scenario, by understanding the scenario information, the user's specific operation requirements for line thickness, color selection, pen pressure change, etc. can be analyzed, so that the touch pen can respond to these requirements more accurately during the drawing process. At the same time, based on the calibration parameters, the present invention collects the strain data of the full-bridge strain gauge during the touch operation in real time, and eliminates the data deviation caused by individual differences in equipment, installation errors and environmental factors, so that the collected strain data can reflect the various forces and deformations to which the touch pen is subjected during actual use. Based on the operation instructions, the present invention analyzes the functional modules corresponding to the touch pen and determines the execution operations corresponding to the functional modules, so that the touch pen can flexibly switch and execute different tasks in various application scenarios, and And by analyzing the functional modules and determining the execution operation, it 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. The present invention can include response time, accuracy, stability, etc. by analyzing the feedback parameters corresponding to the interactive response data, which directly reflects the quality of the interaction between the touch pen and the system. For example, a short response time means that the user operation can be responded to quickly, which improves the fluency and immediacy of the interaction, so that the user will not feel stuck or delayed when drawing, writing or performing other operations. Further, based on the probability of misoperation, the present invention optimizes the data of the full-bridge strain gauge during the touch operation to obtain optimized data, which can identify data patterns or abnormal situations that may cause misoperation, and then optimize the data of the full-bridge strain gauge in a targeted manner, which helps to reduce false triggers caused by inaccurate or abnormal data, ensure that the touch operation can accurately reflect the user's intention, and improve user experience and operation efficiency. Therefore, the intelligent control method and system for realizing a touch pen based on a full-bridge strain gauge proposed in the present invention can improve the control fluency of the touch pen in the interaction of electronic devices.

[0135] Embodiment 2:

[0136] like Figure 2 , which is a schematic diagram of a module for realizing an intelligent control system of a touch pen based on a full-bridge strain gauge according to an embodiment of the present invention.

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

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

[0139] The initial calibration module 201 is used to 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 adapted for the touch pen based on the touch operation requirements, and after installing the full-bridge strain gauge at a designated position of the touch pen, initialize and calibrate the full-bridge strain gauge to obtain calibration parameters;

[0140] The instruction generation module 202 is used to collect strain data of the full-bridge strain gauge in the touch operation process in real time based on the calibration parameters, calculate the 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 the touch position information corresponding to the touch pen;

[0141] A data generating module 203 is used to analyze the function module corresponding to the touch pen based on the operation instruction, 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 the interaction 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 used to analyze the feedback parameters corresponding to the interactive response data, identify abnormal operation features in the feedback parameters, and calculate the misoperation probability corresponding to the touch pen based on the abnormal operation features;

[0143] The scheme formulation module 205 is used to optimize the data of the full-bridge strain gauge during the touch operation based on the probability of misoperation, obtain optimized data, analyze the 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, the modules described in the intelligent control system 200 for implementing a touch pen based on a full-bridge strain gauge in the embodiment of the present invention adopt the same technical means as the intelligent control method for implementing a touch pen based on a full-bridge strain gauge described in the accompanying drawings when in use, and can produce the same technical effects, which will not be repeated here.

[0145] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. An intelligent control method for a touch pen based on a full-bridge strain gauge, characterized in that: The method comprises: Acquire usage scenario information of the touch pen, analyze touch operation requirements in the usage scenario information, determine a full-bridge strain gauge adapted 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 initialize and calibrate the full-bridge strain gauge to obtain calibration parameters; Based on the calibration parameters, strain data of the full-bridge strain gauge during the touch operation is collected in real time, a pressure value corresponding to the touch pen is calculated according to the strain data, and an operation instruction corresponding to the touch pen is generated based on the pressure value and touch position information corresponding to the touch pen; Based on the operation instruction, analyzing the functional module corresponding to the touch pen, determining the execution operation corresponding to the functional module, detecting the pen tip movement and the 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 movement and the transmission signal; analyzing feedback parameters corresponding to the interactive response data, identifying abnormal operation features in the feedback parameters, and calculating a probability of misoperation corresponding to the touch pen based on the abnormal operation features; Based on the probability of misoperation, the data of the full-bridge strain gauge during the touch operation is optimized to obtain optimized data, the touch operation habits corresponding to the optimized data are analyzed, and based on the touch operation habits, a control scheme corresponding to the touch pen is formulated.

2. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The initializing and calibrating the full-bridge strain gauge to obtain calibration parameters includes: Querying the initial resistance value corresponding to the full-bridge strain gauge; Analyzing basic electrical characteristics corresponding to the full-bridge strain gauge according to the initial resistance value; Based on the basic electrical characteristics, a pressure test is performed on the full-bridge strain gauge using a preset standard pressure test device to obtain test data; Analyzing the deviation between the test data and the preset standard; Based on the deviation value, the full-bridge strain gauge is initialized and calibrated to obtain calibration parameters.

3. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The real-time acquisition of strain data of the full-bridge strain gauge during the touch operation based on the calibration parameters includes: Querying the parameter frequency corresponding to the calibration parameter; Based on the parameter frequency, performing electrical signal detection on the full-bridge strain gauge to obtain an original electrical signal; Preprocessing the original electrical signal to obtain preprocessed signal data; Analyzing a signal strain sequence corresponding to the preprocessed signal data; Based on the signal strain sequence, strain data of the full-bridge strain gauge during the touch operation is collected in real time.

4. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The calculating, according to the strain data, a pressure value corresponding to the touch pen includes: The pressure value corresponding to the touch pen is calculated using the following formula: 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 number 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 touch pen over time, and C represents a constant compensation term.

5. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The detecting the pen tip movement and the transmission signal corresponding to the touch pen according to the execution operation includes: Analyze the usage scenario corresponding to the execution operation; Based on the usage scenario, collecting original motion and signal data of the touch pen during use; Filtering key data segments from the original action and signal data; Extracting pen tip motion features and signal transmission features in the key data segment; Based on the pen tip motion characteristics and the signal transmission characteristics, the pen tip motion and transmission signal corresponding to the touch pen are detected.

6. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The generating interactive response data corresponding to the touch pen based on the pen tip action and the transmission signal includes: analyzing the pen tip action and the operation intention corresponding to the transmission signal; Determining an interactive response type corresponding to the operation intention; Collecting interactive response materials corresponding to the interactive response type; Filtering material clips in the interactive response material; Extracting key interactive elements from the material clips; Based on the key interactive element, interactive response data corresponding to the touch pen is generated.

7. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The analyzing the feedback parameters corresponding to the interactive response data includes: Querying a response target corresponding to the interactive response data; Refining 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, determining an analysis rule corresponding to the interactive response data; Based on the analysis rule, feedback parameters corresponding to the interactive response data are analyzed.

8. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The calculating, based on the abnormal operation feature, a probability of misoperation corresponding to the touch pen includes: The probability of misoperation corresponding to the touch pen is calculated using the following formula: Wherein, WG represents the probability of misoperation corresponding to the touch pen, n′ represents the total number of touch pen operations, i′ represents the number index of touch pen operations, m represents the number of abnormal operation features, j represents the number index of abnormal operation features, w i′j represents the weight coefficient of the jth abnormal operation feature of the i'th operation, h() represents the feature threshold function, B i′j (t i′ ) represents the abnormal operation characteristic value after time processing, t i′ Indicates the time point of the i'th operation.

9. The intelligent control method for a touch pen based on a full-bridge strain gauge according to claim 1, characterized in that: The optimizing process of the data of the full-bridge strain gauge during the touch operation based on the probability of misoperation to obtain optimized data includes: Based on the probability of misoperation, determining an optimization target corresponding to the data of the full-bridge strain gauge during the touch operation; According to the optimization target, selecting points to be optimized in the data of the full-bridge strain gauge during the touch operation; Querying the original data segment corresponding to the point to be optimized; Analyzing the optimizable direction corresponding to the original data segment; Based on the optimizable direction, construct an optimization strategy corresponding to the full-bridge strain gauge; Based on the optimization strategy, the data of the full-bridge strain gauge during the touch operation is optimized to obtain optimized data.

10. An intelligent control system for a touch pen based on a full-bridge strain gauge is characterized in that: The system is used to implement the intelligent control method of a touch pen based on a full-bridge strain gauge as claimed in any one of claims 1 to 9, the system comprising: An initial calibration module is used to obtain usage scenario information of the touch pen, analyze touch operation requirements in the usage scenario information, determine a full-bridge strain gauge adapted for the touch pen based on the touch operation requirements, and after installing the full-bridge strain gauge at a designated position of the touch pen, initialize and calibrate the full-bridge strain gauge to obtain calibration parameters; an instruction generation module, 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; a data generating module, configured to analyze the function module corresponding to the touch pen based on the operation instruction, determine the execution operation corresponding to the function module, detect the pen tip action and the transmission signal corresponding to the touch pen according to the execution operation, and generate the interaction response data corresponding to the touch pen based on the pen tip action and the transmission signal; an error operation probability calculation module, used to analyze feedback parameters corresponding to the interactive response data, identify abnormal operation features in the feedback parameters, and calculate the error operation probability corresponding to the touch pen based on the abnormal operation features; A scheme formulation module is used to optimize the data of the full-bridge strain gauge during the touch operation based on the probability of misoperation, obtain optimized data, analyze the touch operation habits corresponding to the optimized data, and formulate a control scheme corresponding to the touch pen based on the touch operation habits.

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