Capacitive touch screen touch adjustment method, device and electronic equipment

Abstract

A capacitive touch screen touch adjustment method, device and electronic device relate to the field of display screens. In the method, environmental parameters of multiple touch points of the capacitive touch screen are obtained; according to the environmental parameters, the calibration touch threshold corresponding to each touch point is determined; the touch signal strength of each touch point is obtained; the touch signal strength of each touch point is compared with the corresponding calibration touch threshold to obtain the touch state of each touch point, and the touch state includes an untouched state and a touched state; based on the touch state of each touch point, a first compensation touch point is generated, and based on the touch state of each touch point, a second compensation touch point is generated; based on the touch state of each touch point and the compensation touch point, a touch event corresponding to the touch operation is generated, and the touch event is sent to a target program to update the user interface corresponding to the target program. The implementation of the technical solution provided by the present application improves the accuracy of touch recognition.

Description

Technical Field

[0001] The present application relates to the field of display screens, and in particular to a capacitive touch screen touch adjustment method, device and electronic equipment. Background Art

[0002] With the rapid development of information technology, capacitive touch screens have become an indispensable interactive interface in smart devices. Capacitive touch screens are widely used in smart phones, tablets, kiosks and many other consumer electronic products due to their intuitive operation and sensitive response characteristics. As users' requirements for device operation experience continue to increase, the performance and accuracy of touch screens are becoming more and more important. Users expect to get a consistent touch experience under various environmental conditions, such as different climates and light environments.

[0003] Although capacitive touch screen technology has made significant progress, there are still some technical challenges and defects. Traditional touch screen systems often use fixed touch thresholds, which may cause touch accuracy to decrease when environmental conditions change (such as changes in temperature, humidity, and light intensity). For example, in high humidity or low temperature environments, the touch screen may be accidentally touched or fail to respond to touch correctly, affecting the accuracy of operation.

[0004] Therefore, there is an urgent need for a capacitive touch screen touch adjustment method, device and electronic equipment. Summary of the invention

[0005] The present application provides a capacitive touch screen touch adjustment method, device and electronic equipment, which improve the accuracy of touch recognition.

[0006] In a first aspect of the present application, a capacitive touch screen touch adjustment method is provided, the method comprising: obtaining environmental parameters of multiple touch points of the capacitive touch screen, the environmental parameters comprising temperature parameters, humidity parameters and light intensity parameters; determining a calibration touch threshold corresponding to each of the touch points according to the environmental parameters, the calibration touch threshold being used to characterize the minimum touch signal strength required to trigger a touch event under the environmental parameters; obtaining the touch signal strength of each of the touch points; comparing the touch signal strength of each of the touch points with the corresponding calibration touch threshold to obtain the touch state of each of the touch points, the touch state comprising an untouched state and a touched state; generating a first compensation touch point based on the touch state of each of the touch points, and generating a second compensation touch point based on the touch state of each of the touch points; generating a touch event corresponding to the touch operation based on the touch state of each of the touch points, the first compensation touch point and the second compensation touch point, and sending the touch event to a target program to update a user interface corresponding to the target program.

[0007] By adopting the above technical solution, by obtaining the environmental parameters of the touch point and determining the calibration touch threshold corresponding to the touch point according to the environmental parameters, the dynamic adjustment of the calibration touch threshold is realized, so that the calibration touch threshold can adapt to different environmental conditions, ensuring the stability of touch sensitivity and touch accuracy. At the same time, the method obtains the touch signal strength of the touch point and compares it with the calibration touch threshold to obtain the touch state of the touch point, thereby realizing accurate judgment of the touch operation and avoiding the problems of false touch and missed touch. In addition, the method also improves the accuracy of the touch position and the continuity of the touch trajectory by generating a first compensation touch point and a second compensation touch point, making the generation of touch events more accurate and complete. Finally, the method sends the generated touch event to the target program, realizes real-time synchronization of the touch operation and the user interface, and provides a smooth and natural interactive experience.

[0008] Optionally, generating a first compensation touch point based on the touch state of each of the touch points specifically includes: obtaining a first touch state of the first touch point and a second touch state of the second touch point, the first touch point and the second touch point being any two adjacent touch points among the multiple touch points; if it is determined that the first touch state and the second touch state are both touched states, obtaining a first touch signal strength corresponding to the first touch point and a second touch signal strength corresponding to the second touch point; generating the first compensation touch point based on the first touch signal strength and the second touch signal strength, the first compensation touch point corresponding to a third touch signal strength, and the third touch signal strength being an average of the first touch signal strength and the second touch signal strength.

[0009] By adopting the above technical solution, by obtaining the touch state and touch signal strength of adjacent touch points, and generating the first compensating touch point based on the average value of the touch signal strength, the fine interpolation of the touch position is achieved, and the touch resolution and positioning accuracy are improved. At the same time, by judging whether the adjacent touch points are in the touched state at the same time, the method avoids generating redundant compensating touch points in the untouched area, reducing the calculation cost and error risk. In addition, the method uses the average value of the touch signal strength as the touch signal strength of the first compensating touch point, ensuring a smooth transition between the compensating touch point and the original touch point, making the touch track more continuous and natural.

[0010] Optionally, generating a second compensating touch point based on the touch state of each of the touch points specifically includes: acquiring the position coordinates of a target touch point, wherein the target touch point is a touch point whose touch state is a touched state among the multiple touch points; determining a connecting line between each of the target touch points according to the position coordinates of each of the target touch points to obtain an initial touch trajectory; determining touch points on the initial touch trajectory that are adjacent to each of the target touch points and whose touch state is a non-touched state, marking them as missing touch points, and generating a second compensating touch point corresponding to the missing touch point.

[0011] By adopting the above technical solution, the initial touch trajectory is extracted and described by obtaining the position coordinates of the target touch points and obtaining the initial touch trajectory based on the connection between the target touch points. At the same time, the method repairs and completes the touch trajectory by determining the missing touch points on the initial touch trajectory and generating second compensating touch points corresponding to the missing touch points, thereby improving the integrity and continuity of the touch trajectory and the reliability of the touch trajectory. Finally, the second compensating touch points generated by the method together with the original touch points constitute a more dense, smooth and complete touch trajectory, providing high-quality data support for gesture recognition, handwriting recording and other functions.

[0012] Optionally, determining the calibrated touch threshold corresponding to each of the touch points based on the environmental parameters specifically includes: obtaining historical environmental parameters and historical touch thresholds corresponding to each of the touch points within a preset time period; constructing a touch threshold prediction model based on the historical environmental parameters and the historical touch thresholds, and the touch threshold prediction model is used to characterize the correspondence between environmental parameters and touch thresholds; and inputting the historical environmental parameters into the touch threshold prediction model to obtain the calibrated touch threshold corresponding to each of the touch points.

[0013] By adopting the above technical solution, by obtaining the historical environmental parameters and historical touch thresholds of the touch points within a preset time period, and building a touch threshold prediction model based on historical data, predictive adjustment of the touch threshold is achieved, so that the touch threshold can respond in advance according to the changing trend of the environmental parameters, thereby improving the timeliness and accuracy of the touch threshold adjustment. At the same time, the method uses environmental parameters as the input of the touch threshold prediction model, and the touch threshold as the output of the touch threshold prediction model, establishes a mapping relationship between environmental parameters and touch thresholds, and realizes quantitative and regular management of touch thresholds. In addition, the method inputs the environmental parameters obtained in real time into the touch threshold prediction model to obtain a calibrated touch threshold that is suitable for the current environmental conditions, thereby realizing adaptive adjustment of the touch threshold and ensuring the stability and reliability of touch sensitivity.

[0014] Optionally, constructing a touch threshold prediction model based on the historical environmental parameters and the historical touch threshold specifically includes: taking the historical environmental parameters as the feature vectors of training samples, taking the historical touch threshold as the target value of training samples, and constructing a training sample set; using the training sample set to train the touch threshold prediction model, the touch threshold prediction model is a neural network model, and the neural network model includes an input layer, at least one hidden layer and an output layer; the input layer is used to receive the historical environmental parameters, and the output layer is used to output the predicted touch threshold corresponding to the current environmental parameters.

[0015] By adopting the above technical solution, a training sample set for touch threshold prediction is constructed by taking historical environmental parameters as feature vectors of training samples and historical touch thresholds as target values ​​of training samples, providing sufficient and targeted data support for the training of touch threshold prediction models. At the same time, the method uses a neural network model as a touch threshold prediction model, receives historical environmental parameters through the input layer, extracts deep features of environmental parameters through the hidden layer, and outputs predicted touch thresholds through the output layer, thereby achieving efficient and accurate modeling of the relationship between environmental parameters and touch thresholds. In addition, the method uses a training sample set to train the neural network model, so that the touch threshold prediction model can automatically learn and extract the correlation between environmental parameters and touch thresholds, continuously optimize model parameters, and improve prediction accuracy. Finally, the touch threshold prediction model trained by the method can quickly and accurately predict the corresponding touch threshold based on the input environmental parameters, thereby achieving adaptive adjustment of the touch threshold.

[0016] Optionally, before obtaining the environmental parameters of multiple touch points of the capacitive touch screen, the method also includes: obtaining a capacitance value change curve of each pixel point of the capacitive touch screen; identifying a noise type of each pixel point according to the capacitance value change curve of each pixel point, the noise type including a random noise type and a fixed frequency noise type; determining a corresponding noise elimination algorithm for the noise type, and using the noise elimination algorithm to perform noise reduction processing on the capacitance value change curve of each pixel point to obtain a capacitance value change curve after noise reduction; and using the capacitance value change curve after noise reduction as the environmental parameter.

[0017] By adopting the above technical solution, by obtaining the capacitance value change curve of each pixel point of the capacitive touch screen, and identifying the noise type of the pixel point according to the capacitance value change curve, the accurate analysis and classification of the capacitance touch screen noise is realized. At the same time, the method determines the corresponding noise elimination algorithm for different noise types, realizes the pertinence and effectiveness of the noise elimination method, and avoids the limitations brought by the use of a single noise elimination method. In addition, the method uses the noise elimination algorithm to perform noise reduction on the capacitance value change curve, obtains the capacitance value change curve after noise reduction, effectively improves the signal-to-noise ratio of the touch signal, and provides a high-quality data basis for subsequent touch state judgment and compensation touch point generation. Finally, the method uses the capacitance value change curve after noise reduction as an environmental parameter, realizes the active suppression of the touch screen noise, and improves the environmental adaptability and stability of the touch screen.

[0018] Optionally, determining a corresponding noise elimination algorithm for the noise type specifically includes: for the pixel points of the random noise type, determining a noise reduction algorithm based on wavelet transform as the corresponding noise elimination algorithm; for the pixel points of the fixed frequency noise type, determining a noise reduction algorithm based on notch filter as the corresponding noise elimination algorithm.

[0019] By adopting the above technical scheme, for the pixels of random noise type, a noise reduction algorithm based on wavelet transform is determined as the corresponding noise elimination algorithm. By using the multi-scale analysis and time-frequency positioning capabilities of wavelet transform, the random noise is effectively filtered out, and the detailed characteristics of the touch signal are retained. At the same time, for the pixels of fixed frequency noise type, the method determines the noise reduction algorithm based on notch filter as the corresponding noise elimination algorithm. By forming a notch point at a specific frequency, the fixed frequency noise is accurately filtered out, avoiding the interference of fixed frequency noise on the touch signal. In addition, the method selects a targeted noise reduction algorithm according to the noise type, avoiding the problem of insufficient applicability caused by the use of a single noise reduction algorithm, and improving the noise reduction effect and noise reduction efficiency. Finally, the method flexibly uses different noise reduction algorithms to perform comprehensive and targeted noise reduction processing on the capacitance value change curve, and obtains a high-quality capacitance value change curve after noise reduction, which lays a foundation for the accurate acquisition of environmental parameters and the reasonable determination of the calibration touch threshold.

[0020] In a second aspect of the present application, a capacitive touch screen touch adjustment device is provided, the device comprising an acquisition module and a processing module, wherein: the acquisition module is used to acquire environmental parameters of multiple touch points of the capacitive touch screen, the environmental parameters comprising temperature parameters, humidity parameters and light intensity parameters; the processing module is used to determine a calibration touch threshold corresponding to each of the touch points according to the environmental parameters, the calibration touch threshold being used to characterize the minimum touch signal strength required to trigger a touch event under the environmental parameters; the acquisition module is also used to acquire the touch signal strength of each of the touch points; the processing module is also used to convert each of the touch points into a calibration touch threshold. The touch signal strength of the control point is compared with the corresponding calibration touch threshold to obtain the touch state of each touch point, and the touch state includes an untouched state and a touched state; the processing module is also used to generate a first compensation touch point based on the touch state of each touch point, and generate a second compensation touch point based on the touch state of each touch point; the processing module is also used to generate a touch event corresponding to the touch operation based on the touch state of each touch point, the first compensation touch point and the second compensation touch point, and send the touch event to the target program to update the user interface corresponding to the target program.

[0021] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any one of the methods described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any of the methods described above is executed.

[0023] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0024] 1. By acquiring the environmental parameters of the touch point and determining the calibration touch threshold corresponding to the touch point according to the environmental parameters, the dynamic adjustment of the calibration touch threshold is realized, so that the calibration touch threshold can adapt to different environmental conditions and ensure the stability of the touch sensitivity. At the same time, the method obtains the touch signal strength of the touch point and compares it with the calibration touch threshold to obtain the touch state of the touch point, thereby realizing accurate judgment of the touch operation and avoiding the problems of false touch and missed touch. In addition, the method also improves the accuracy of the touch position and the continuity of the touch trajectory by generating a first compensation touch point and a second compensation touch point, making the generation of touch events more accurate and complete. Finally, the method sends the generated touch event to the target program, realizes real-time synchronization of the touch operation and the user interface, and provides a smooth and natural interactive experience.

[0025] 2. By acquiring the touch status and touch signal strength of adjacent touch points and generating the first compensating touch point based on the average value of the touch signal strength, the touch position is refined interpolated, and the touch resolution and positioning accuracy are improved. At the same time, by judging whether adjacent touch points are in the touched state at the same time, this method avoids generating redundant compensating touch points in the untouched area, reducing the calculation cost and error risk. In addition, this method uses the average value of the touch signal strength as the touch signal strength of the first compensating touch point, ensuring a smooth transition between the compensating touch point and the original touch point, making the touch track more continuous and natural.

[0026] 3. By acquiring the position coordinates of the target touch points and obtaining the initial touch trajectory based on the connection between the target touch points, the initial touch trajectory is extracted and described. At the same time, the method determines the missing touch points on the initial touch trajectory and generates second compensating touch points corresponding to the missing touch points, thereby repairing and completing the touch trajectory, improving the integrity and continuity of the touch trajectory, and improving the reliability of the touch trajectory. Finally, the second compensating touch points generated by the method together with the original touch points constitute a more dense, smooth, and complete touch trajectory, providing high-quality data support for gesture recognition, handwriting recording and other functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a capacitive touch screen touch adjustment method disclosed in an embodiment of the present application;

[0028] Figure 2 It is a module schematic diagram of a capacitive touch screen touch adjustment device disclosed in an embodiment of the present application;

[0029] Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0030] Explanation of the reference numerals: 201, acquisition module; 202, processing module; 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0031] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0032] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0033] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0034] This application provides a capacitive touch screen touch adjustment method, referring to Figure 1 , Figure 1 1 is a flow chart of a capacitive touch screen touch adjustment method provided in an embodiment of the present application. The method is applied to a server, which is a server that executes a capacitive touch screen touch adjustment program. The server can be a single server, or a server cluster composed of multiple servers, or a cloud computing service center. The method includes steps S101 to S106, which are as follows:

[0035] Step S101: Acquire environmental parameters of multiple touch points of the capacitive touch screen, where the environmental parameters include temperature parameters, humidity parameters, and light intensity parameters.

[0036] In a possible implementation, before step S101, the method further includes: obtaining a capacitance value change curve of each pixel point of the capacitive touch screen; identifying a noise type of each pixel point according to the capacitance value change curve of each pixel point, the noise type including a random noise type and a fixed frequency noise type; determining a corresponding noise elimination algorithm for the noise type, and performing noise reduction processing on the capacitance value change curve of each pixel point using the noise elimination algorithm to obtain a capacitance value change curve after noise reduction; and using the capacitance value change curve after noise reduction as an environmental parameter.

[0037] Specifically, the server first obtains the capacitance value change curve of each pixel of the capacitive touch screen. The server establishes a communication connection with the capacitive touch screen and receives the pixel capacitance value data from the capacitive touch screen regularly or in real time. These data are presented in the form of a time series, recording the change of the capacitance value of each pixel over a period of time. After obtaining the pixel capacitance value change curve, the server analyzes these curves to identify the noise type of each pixel. Noise is one of the important factors affecting the touch performance of the capacitive touch screen. Common noise types include random noise type and fixed frequency noise type. Random noise usually manifests as random fluctuations in capacitance value, and its cause may be related to factors such as electromagnetic interference and temperature changes in the environment where the capacitive touch screen is located. Fixed frequency noise, on the other hand, presents periodic regular changes, which may be caused by factors such as power supply interference and external lighting.

[0038] In order to accurately identify the noise type of the pixel point, the server performs Fourier transform on the capacitance value change curve and determines whether there is a noise component with a fixed frequency by analyzing the spectrum diagram. After identifying the noise type of the pixel point, the server selects an appropriate noise elimination algorithm for different types of noise to perform noise reduction processing on the capacitance value change curve. After the noise reduction processing is completed, the server will obtain the capacitance value change curve after noise reduction.

[0039] In a possible implementation, a corresponding noise elimination algorithm is determined for each noise type, specifically including: for pixels of random noise type, a noise reduction algorithm based on wavelet transform is determined as the corresponding noise elimination algorithm; for pixels of fixed frequency noise type, a noise reduction algorithm based on notch filter is determined as the corresponding noise elimination algorithm.

[0040] Specifically, for pixels of random noise type, the server adopts a noise reduction algorithm based on wavelet transform. Wavelet transform is a time-frequency analysis tool that can perform local analysis on signals in both time domain and frequency domain at the same time, and has multi-resolution characteristics. By performing wavelet decomposition on the capacitance value change curve, the server decomposes the signal into low-frequency approximate coefficients and high-frequency detail coefficients at different scales. Since random noise is mainly concentrated in the high-frequency part, the server can perform threshold processing on the decomposed high-frequency detail coefficients, and set the coefficients less than the preset frequency threshold to zero, thereby achieving effective noise suppression. The selection of the preset frequency threshold can be adaptively adjusted according to the intensity of the noise and the characteristics of the signal to achieve a balance between noise reduction and retaining signal details, and this application does not limit this. After completing the threshold processing, the server reconstructs the modified wavelet coefficients to obtain the capacitance value change curve after noise reduction.

[0041] For pixels of fixed frequency noise type, the server selects a noise reduction algorithm based on a notch filter. A notch filter is a filter that can form a notch (i.e., deep attenuation) at a specific frequency point, which can effectively suppress noise components of a specific frequency. According to the frequency characteristics of fixed frequency noise, the server designs a matching notch filter, and adjusts the filter parameters (such as notch frequency, notch depth, quality factor, etc.) to form the deepest possible notch at the noise frequency point, while maintaining a small attenuation at the signal frequency point, thereby achieving targeted noise suppression.

[0042] Step S102: determining a calibrated touch threshold corresponding to each touch point according to the environmental parameters, where the calibrated touch threshold is used to represent the minimum touch signal strength required to trigger a touch event under the environmental parameters.

[0043] In step S102, the calibrated touch threshold corresponding to each touch point is determined according to the environmental parameters, specifically including: obtaining the historical environmental parameters and historical touch thresholds corresponding to each touch point within a preset time period; constructing a touch threshold prediction model based on the historical environmental parameters and the historical touch thresholds, the touch threshold prediction model is used to characterize the correspondence between the environmental parameters and the touch threshold; the environmental parameters are input into the touch threshold prediction model to obtain the calibrated touch threshold corresponding to each touch point.

[0044] Specifically, the server determines the calibrated touch threshold corresponding to each touch point based on the environmental parameters of the touch point obtained. The calibrated touch threshold refers to the minimum touch signal strength required to trigger a touch event under the current environmental conditions. Since environmental parameters affect the touch sensitivity of the capacitive touch screen, the calibrated touch threshold needs to be dynamically adjusted according to changes in the actual environment to ensure the stability of the touch performance.

[0045] In order to achieve adaptive adjustment of the calibrated touch threshold, the server first presets the historical data of the touch points within a time period, including historical environmental parameters and corresponding historical touch thresholds. After obtaining enough historical data, the server builds a touch threshold prediction model based on these data. The purpose of the touch threshold prediction model is to characterize the correspondence between environmental parameters and the calibrated touch threshold, so that the appropriate calibrated touch threshold can be predicted based on the current environmental parameters. During the training process, the server uses the historical environmental parameters as the input features of the touch threshold prediction model, and the historical touch threshold as the target output of the touch threshold prediction model, and learns the mapping relationship between the historical environmental parameters and the historical touch threshold by minimizing the prediction error.

[0046] When the server obtains the environmental parameters of the current touch point, it can input these environmental parameters into the trained touch threshold prediction model, and the touch threshold prediction model calculates the calibrated touch threshold corresponding to each touch point. The calibrated touch threshold reflects the optimal sensitivity setting of the touch point under the current environmental conditions, which can effectively avoid problems such as touch misoperation or failure caused by environmental changes.

[0047] In one possible implementation, a touch threshold prediction model is constructed based on historical environmental parameters and historical touch thresholds, specifically including: taking historical environmental parameters as feature vectors of training samples, taking historical touch thresholds as target values ​​of training samples, and constructing a training sample set; using the training sample set to train a touch threshold prediction model, the touch threshold prediction model is a neural network model, the neural network model includes an input layer, at least one hidden layer and an output layer; the input layer is used to receive historical environmental parameters, and the output layer is used to output a predicted touch threshold corresponding to the current environmental parameters.

[0048] Specifically, the server prepares a training sample set. The server uses the historical environmental parameters as the feature vectors of the training samples and the corresponding historical touch thresholds as the target values ​​of the training samples. The feature vectors usually include values ​​of multiple dimensions such as temperature, humidity, and light intensity, which characterize the state of the touch point under different environmental conditions. The target value is the actual touch signal strength required to trigger a touch event under the environmental conditions. By sorting and annotating the historical data, the server constructs a training sample set containing a large number of feature vectors and target values. Next, the server designs the structure of the touch threshold prediction model. The server designs a feedforward neural network including an input layer, several hidden layers, and an output layer. The number of neurons in the input layer is the same as the dimension of the feature vector, which is used to receive the historical environmental parameters. The number of neurons and the number of layers in the hidden layer can be adjusted according to the complexity of the task. Usually 1 to 3 layers are used, and each layer contains tens to hundreds of neurons. The hidden layer uses nonlinear activation functions (such as ReLU, sigmoid, etc.) to enhance the expression ability of the network. The output layer contains only one neuron, which is used to output the predicted calibrated touch threshold.

[0049] After the structure of the touch threshold prediction model is determined, the server uses the training sample set to train the neural network. The training process uses the back propagation algorithm to continuously adjust the connection weights and bias terms in the network by minimizing the error between the predicted value and the true value. The server loss function (such as mean square error, cross entropy, etc.) is used to measure the prediction error, and the optimization algorithm (such as gradient descent, Adam, etc.) is used to update the network parameters. After the training is completed, the server obtains the touch threshold prediction model. When new environmental parameters arrive, the server inputs them into the trained touch threshold prediction model, and the corresponding standard touch threshold is given by the output layer.

[0050] Step S103: Acquire the touch signal strength of each touch point.

[0051] In step S103, the server obtains the touch signal strength of each touch point. In the embodiment of the present application, the touch signal strength can be understood as the change in capacitance of the touch point relative to the reference value under touch operation. The reference capacitance value refers to the normal capacitance value of the touch point when no touch operation occurs, which can be obtained in advance by long-term monitoring of the capacitance value of the touch point and averaging it. Then, the server calculates the difference between the real-time capacitance value of each touch point and the reference capacitance value to obtain the capacitance change value of the touch point. Finally, the server divides the capacitance change value by a scaling factor to obtain the normalized touch signal strength.

[0052] Step S104: Compare the touch signal strength of each touch point with the corresponding calibrated touch threshold to obtain the touch state of each touch point, where the touch state includes a non-touch state and a touched state.

[0053] In step S104, the server compares the touch signal strength of each touch point with the corresponding calibrated touch threshold to determine the touch state of each touch point. The touch state refers to whether the touch point is effectively touched, which is usually divided into two states: untouched state and touched state.

[0054] First, the server obtains the calibrated touch threshold of each touch point. The calibrated touch threshold is calculated by the touch threshold prediction model according to the environmental parameters of the touch point in step S102. It represents the minimum touch signal strength required to trigger a valid touch event under the current environmental conditions. Since the environmental parameters of each touch point may be different, the calibrated touch threshold is also different. The server determines the corresponding calibrated touch threshold for each touch point and updates it in real time according to the changes in the environmental parameters.

[0055] Then, the server compares the touch signal strength of each touch point with its corresponding calibrated touch threshold. If the touch signal strength is greater than or equal to the calibrated touch threshold, the server determines the touch state of the touch point as a touched state, indicating that a valid touch operation has occurred on the touch point. Conversely, if the touch signal strength is less than the calibrated touch threshold, the server determines the touch state of the touch point as a non-touch state, indicating that no valid touch operation has occurred on the touch point.

[0056] Step S106: generating a first compensation touch point based on the touch state of each touch point, and generating a second compensation touch point based on the touch state of each touch point.

[0057] In step S106, a first compensation touch point is generated based on the touch state of each touch point, specifically including: obtaining a first touch state of the first touch point and a second touch state of the second touch point, where the first touch point and the second touch point are any two adjacent touch points among the multiple touch points; if it is determined that the first touch state and the second touch state are both touched states, obtaining a first touch signal strength corresponding to the first touch point and a second touch signal strength corresponding to the second touch point; based on the first touch signal strength and the second touch signal strength, a first compensation touch point is generated, where the first compensation touch point corresponds to a third touch signal strength, and the third touch signal strength is an average of the first touch signal strength and the second touch signal strength.

[0058] Specifically, the server generates a first compensation touch point based on the touch state of each touch point. The first compensation touch point is a virtual touch point introduced to improve the spatial resolution and touch accuracy of the capacitive touch screen. It does not correspond to a real physical touch point but is generated by a software algorithm.

[0059] First, the server obtains the touch states of two adjacent touch points. Here, adjacent touch points refer to two touch points that are physically adjacent, such as two touch points that are continuously distributed in the same row or column of the touch screen. The server can determine which touch points are adjacent based on the numbers or coordinates of the touch points. Assume that the server selects two touch points numbered n and n+1, respectively referred to as the first touch point and the second touch point, and obtains their corresponding touch states, recorded as the first touch state and the second touch state.

[0060] Then, the server determines whether the first touch state and the second touch state are in the touched state at the same time. Only when two adjacent touch points are effectively touched, it is necessary to generate a compensating touch point between them. If any of the touch points is in the untouched state, it indicates that there is no continuous touch operation in the area, and there is no need to generate a compensating touch point.

[0061] If both the first touch state and the second touch state are in the touched state, the server obtains the touch signal strengths corresponding to the first touch point and the second touch point, which are recorded as the first touch signal strength and the second touch signal strength respectively. The touch signal strength reflects the degree of contact and pressure between the touch object and the touch screen surface, and is an important basis for interpolating and generating compensation touch points.

[0062] Finally, the server generates a first compensation touch point based on the first touch signal strength and the second touch signal strength. Specifically, the server calculates the arithmetic mean of the first touch signal strength and the second touch signal strength, and uses it as the touch signal strength of the first compensation touch point, recorded as the third touch signal strength. This is equivalent to inserting a new touch point between the first touch point and the second touch point, and its touch signal strength is between the two. The physical position of the first compensation touch point can be calculated based on the coordinates of the first touch point and the second touch point, usually taking the midpoint of the two.

[0063] For example, suppose the server obtains the touch signal strength of the first touch point as 0.6 and the touch signal strength of the second touch point as 0.8. The server calculates the average of the two and obtains the third touch signal strength as 0.7. Then, the server calculates the coordinates of the first compensation touch point based on the coordinates of the first touch point and the second touch point, and sets its touch signal strength to 0.7. In this way, a new compensation touch point is inserted between the original two touch points, improving the spatial resolution of the area.

[0064] The generation of compensation touch points can be performed recursively on the entire touch screen. The server can scan all touch points row by row or column by column, and each time select two adjacent touch points in the touched state to generate compensation touch points between them. In this way, the server can generate a large number of compensation touch points based on the original touch points, thereby improving the touch resolution. The compensation touch points together with the original touch points form a more dense and continuous touch point array, which can more finely characterize the position and shape of the touch object.

[0065] In a possible implementation, a second compensating touch point is generated based on the touch state of each touch point, specifically including: obtaining the position coordinates of a target touch point, where the target touch point is a touch point in a plurality of touch points whose touch state is a touched state; determining the connection between each target touch point according to the position coordinates of each target touch point to obtain an initial touch trajectory; determining touch points on the initial touch trajectory that are adjacent to each target touch point and whose touch state is a non-touched state, marking them as missing touch points, and generating a second compensating touch point corresponding to the missing touch point.

[0066] Specifically, in addition to generating the first compensating touch point, the server also generates a second compensating touch point based on the touch state of each touch point. The second compensating touch point is generated to repair the missing touch points in the touch trajectory and improve the continuity and smoothness of the touch trajectory. First, the server obtains the position coordinates of all touch points in the touched state. These touch points are called target touch points. The server traverses the touch states of all touch points, filters out the touch points in the touched state, and records their position coordinates. The position coordinates are usually expressed in the form of two-dimensional coordinates, including the horizontal and vertical coordinates of the touch point on the touch screen.

[0067] Then, the server determines the connection line between the target touch points according to their position coordinates to obtain the initial touch trajectory. The initial touch trajectory is a broken line formed by connecting the target touch points in chronological order, reflecting the approximate path of the touch object moving on the touch screen. The server uses algorithms such as linear interpolation and spline interpolation to generate a continuous trajectory curve between adjacent target touch points, making the initial touch trajectory smoother and more natural.

[0068] Next, the server searches for touch points adjacent to each target touch point and whose touch state is not touched along the initial touch track, and marks them as missing touch points. Missing touch points refer to touch points that should be touched but are actually not touched in the area passed by the touch track. These touch points may not be effectively triggered due to reasons such as the touch object moving too fast or poor contact, resulting in breakpoints or holes in the touch track. The server identifies these missing touch points by analyzing the initial touch track and the spatial distribution of the touch points.

[0069] Finally, the server generates a corresponding second compensating touch point for each missing touch point. The position coordinates of the second compensating touch point are the same as those of the missing touch point, but its touch state is set to the touched state, and the touch signal strength can be obtained by interpolating the touch signal strengths of the target touch points on both sides of the missing touch point. By inserting the second compensating touch point at the position of the missing touch point, the server repairs and completes the initial touch trajectory, making it more continuous and complete.

[0070] Step S107: generating a touch event corresponding to the touch operation based on the touch state of each touch point, the first compensation touch point and the second compensation touch point, and sending the touch event to the target program to update the user interface corresponding to the target program.

[0071] In step S107, the server generates a touch event corresponding to the touch operation based on the touch state of each touch point and each compensation touch point (the first compensation touch point and the second compensation touch point), and sends the touch event to the target program to update the user interface corresponding to the target program. The touch event is a key information carrier in the touch screen interaction process, carrying the user's operation intention and interaction content.

[0072] First, the server comprehensively analyzes the touch status of each touch point and the distribution of the compensated touch points to identify the user's touch operation type. Touch operation types include click, double-click, long press, slide, zoom, rotate, etc. The server infers the user's operation intention by judging the number, position, and time series characteristics of the touch points. The server generates corresponding touch events based on the identified touch operation type. Touch events are usually represented in the form of structured data, which contains information such as the type, position, timestamp, and touch point parameters of the touch operation. For example, a click event can be represented as (Click, 100, 200, 162, 0.8), indicating that a click operation occurred at the coordinates (100, 200), the timestamp is 162, and the touch signal strength is 0.8. The server fills in the various fields of the touch event according to the specific touch operation type and parameters to accurately describe the user's interactive behavior.

[0073] When generating touch events, the server makes full use of the additional information provided by the compensated touch points. The compensated touch points can improve the accuracy of the touch position and restore the continuity of the touch trajectory, thus providing more accurate and complete parameters for the touch event. For example, when generating a slide event, the server not only considers the position of the original touch point, but also combines the intermediate position obtained by interpolation of the first compensated touch point to generate a smoother and continuous slide trajectory.

[0074] Finally, the server sends the generated touch event to the target program to update the corresponding user interface of the target program. The target program refers to the application that currently accepts user touch operations, such as browsers, document editors, games, etc. The server establishes a communication channel with the target program and transmits the touch event to the target program in a specific data format. After receiving the touch event, the target program performs corresponding interface updates and interactive responses according to the event type and parameters. For example, after receiving a click event, the target program may trigger the click effect of a button, switch pages, or pop up a dialog box; after receiving a slide event, the target program may scroll a list, turn pages, or drag controls; after receiving a zoom event, the target program may zoom in or out an image, adjust the page layout, etc.

[0075] Reference Figure 2 The present application also provides a capacitive touch screen touch adjustment device, which is a server, and the server includes an acquisition module 201 and a processing module 202. The acquisition module 201 is used to acquire environmental parameters of multiple touch points of the capacitive touch screen, and the environmental parameters include temperature parameters, humidity parameters, and light intensity parameters; the processing module 202 is used to determine the calibration touch threshold corresponding to each touch point according to the environmental parameters, and the calibration touch threshold is used to characterize the minimum touch signal strength required to trigger a touch event under the environmental parameters; the processing module 202 is also used to determine whether a touch operation for the capacitive touch screen is detected; the processing module 202 is also used to obtain each touch point if it is determined that a touch operation is detected. The processing module 202 is further used to compare the touch signal strength of each touch point with the corresponding calibration touch threshold to obtain the touch state of each touch point, and the touch state includes an untouched state and a touched state; the processing module 202 is further used to generate a first compensation touch point based on the touch state of each touch point, and to generate a second compensation touch point based on the touch state of each touch point; the processing module 202 is further used to generate a touch event corresponding to the touch operation based on the touch state of each touch point, the first compensation touch point and the second compensation touch point, and send the touch event to the target program to update the user interface corresponding to the target program.

[0076] In a possible implementation, the processing module 202 generates a first compensation touch point based on the touch state of each touch point, specifically including: the acquisition module 201 acquires the first touch state of the first touch point and the second touch state of the second touch point, the first touch point and the second touch point are any two adjacent touch points among the multiple touch points; if the processing module 202 determines that the first touch state and the second touch state are both touched states, then acquires the first touch signal strength corresponding to the first touch point and the second touch signal strength corresponding to the second touch point; the processing module 202 generates a first compensation touch point based on the first touch signal strength and the second touch signal strength, the first compensation touch point corresponds to a third touch signal strength, and the third touch signal strength is the average of the first touch signal strength and the second touch signal strength.

[0077] In a possible implementation, the processing module 202 generates a second compensating touch point based on the touch state of each touch point, specifically including: the acquisition module 201 acquires the position coordinates of the target touch point, the target touch point is a touch point with a touch state in a touched state among multiple touch points; the processing module 202 determines the connection between each target touch point according to the position coordinates of each target touch point to obtain an initial touch trajectory; the processing module 202 determines the touch points on the initial touch trajectory that are adjacent to each target touch point and have a touch state of a non-touched state, marks them as missing touch points, and generates a second compensating touch point corresponding to the missing touch point.

[0078] In a possible implementation, the processing module 202 determines the calibrated touch threshold corresponding to each touch point based on the environmental parameters, specifically including: the acquisition module 201 acquires the historical environmental parameters and the historical touch threshold corresponding to each touch point within a preset time period; the processing module 202 constructs a touch threshold prediction model based on the historical environmental parameters and the historical touch threshold, and the touch threshold prediction model is used to characterize the correspondence between the environmental parameters and the touch threshold; the processing module 202 inputs the historical environmental parameters into the touch threshold prediction model to obtain the calibrated touch threshold corresponding to each touch point.

[0079] In a possible implementation, the processing module 202 constructs a touch threshold prediction model based on historical environmental parameters and historical touch thresholds, specifically including: the processing module 202 uses historical environmental parameters as feature vectors of training samples and historical touch thresholds as target values ​​of training samples to construct a training sample set; the processing module 202 uses the training sample set to train the touch threshold prediction model, and the touch threshold prediction model is a neural network model, which includes an input layer, at least one hidden layer and an output layer; the input layer is used to receive historical environmental parameters, and the output layer is used to output a predicted touch threshold corresponding to the current environmental parameters.

[0080] In a possible implementation, before the acquisition module 201 acquires the environmental parameters of multiple touch points of the capacitive touch screen, the method also includes: the acquisition module 201 acquires the capacitance value change curve of each pixel point of the capacitive touch screen; the processing module 202 identifies the noise type of each pixel point based on the capacitance value change curve of each pixel point, and the noise type includes a random noise type and a fixed frequency noise type; the processing module 202 determines the corresponding noise elimination algorithm according to the noise type, and uses the noise elimination algorithm to perform noise reduction processing on the capacitance value change curve of each pixel point to obtain the capacitance value change curve after noise reduction; the processing module 202 uses the capacitance value change curve after noise reduction as the environmental parameter.

[0081] In a possible implementation, the processing module 202 determines a corresponding noise elimination algorithm for the noise type, specifically including: the processing module 202 determines a noise reduction algorithm based on a wavelet transform as the corresponding noise elimination algorithm for pixels of a random noise type; the processing module 202 determines a noise reduction algorithm based on a notch filter as the corresponding noise elimination algorithm for pixels of a fixed frequency noise type.

[0082] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0083] The present application also provides an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0084] The communication bus 302 is used to realize the connection and communication between these components.

[0085] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0086] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0087] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0088] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a capacitive touch screen touch adjustment method.

[0089] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call an application program storing a capacitive touch screen touch adjustment method in the memory 305, and when executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0090] The present application also provides a computer-readable storage medium, which stores instructions. When executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments.

[0091] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0094] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0095] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0096] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0097] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A capacitive touch screen touch adjustment method, characterized in that: The method comprises: Acquire environmental parameters of multiple touch points of the capacitive touch screen, wherein the environmental parameters include temperature parameters, humidity parameters, and light intensity parameters; Determining, according to the environmental parameters, a calibrated touch threshold corresponding to each of the touch points, wherein the calibrated touch threshold is used to characterize a minimum touch signal strength required to trigger a touch event under the environmental parameters; Acquire the touch signal strength of each touch point; Compare the touch signal strength of each touch point with the corresponding calibrated touch threshold to obtain the touch state of each touch point, wherein the touch state includes a non-touch state and a touched state; generating a first compensating touch point based on the touch state of each of the touch points, and generating a second compensating touch point based on the touch state of each of the touch points; Generate a touch event corresponding to the touch operation based on the touch state of each of the touch points, the first compensation touch point, and the second compensation touch point, and send the touch event to a target program to update a user interface corresponding to the target program; The generating a second compensation touch point based on the touch state of each touch point specifically includes: Acquire the position coordinates of a target touch point, where the target touch point is a touch point in the plurality of touch points whose touch state is a touched state; According to the position coordinates of each of the target touch points, a connection line between the target touch points is determined to obtain an initial touch trajectory; Touch points on the initial touch track that are adjacent to each of the target touch points and whose touch state is a non-touch state are determined, marked as missing touch points, and second compensating touch points corresponding to the missing touch points are generated.

2. The method according to claim 1, characterized in that The generating a first compensation touch point based on the touch state of each of the touch points specifically includes: Acquire a first touch state of a first touch point and a second touch state of a second touch point, where the first touch point and the second touch point are any two adjacent touch points among the plurality of touch points; If it is determined that both the first touch state and the second touch state are in the touched state, obtaining a first touch signal strength corresponding to the first touch point and a second touch signal strength corresponding to the second touch point; The first compensation touch point is generated based on the first touch signal strength and the second touch signal strength, the first compensation touch point corresponds to a third touch signal strength, and the third touch signal strength is an average value of the first touch signal strength and the second touch signal strength.

3. The method according to claim 1, characterized in that Determining the calibration touch threshold corresponding to each of the touch points according to the environmental parameters specifically includes: Obtaining historical environmental parameters and historical touch thresholds corresponding to each of the touch points within a preset time period; Based on the historical environmental parameters and the historical touch thresholds, a touch threshold prediction model is constructed, wherein the touch threshold prediction model is used to characterize the corresponding relationship between the environmental parameters and the touch thresholds; The historical environmental parameters are input into the touch threshold prediction model to obtain the calibrated touch threshold corresponding to each of the touch points.

4. The method according to claim 3, characterized in that The constructing a touch threshold prediction model based on the historical environment parameters and the historical touch threshold specifically includes: Using the historical environment parameters as feature vectors of training samples and the historical touch thresholds as target values ​​of training samples to construct a training sample set; The touch threshold prediction model is trained using the training sample set. The touch threshold prediction model is a neural network model, which includes an input layer, at least one hidden layer and an output layer; the input layer is used to receive the historical environmental parameters, and the output layer is used to output the predicted touch threshold corresponding to the current environmental parameters.

5. The method according to claim 1, characterized in that Before acquiring the environmental parameters of the plurality of touch points of the capacitive touch screen, the method further includes: Obtain the capacitance value change curve of each pixel point of the capacitive touch screen; According to the capacitance value variation curve of each pixel point, the noise type of each pixel point is identified, and the noise type includes a random noise type and a fixed frequency noise type; Determine a corresponding noise elimination algorithm for the noise type, and use the noise elimination algorithm to perform noise reduction processing on the capacitance value change curve of each pixel point to obtain a capacitance value change curve after noise reduction; The capacitance value variation curve after noise reduction is used as the environmental parameter.

6. The method according to claim 5, characterized in that The determining of a corresponding noise elimination algorithm for the noise type specifically includes: For the pixel points of the random noise type, determining a noise reduction algorithm based on wavelet transform as a corresponding noise elimination algorithm; For the pixel points of the fixed frequency noise type, a notch filter-based noise reduction algorithm is determined as the corresponding noise elimination algorithm.

7. A capacitive touch screen touch adjustment device, characterized in that: The device is used to execute the method according to any one of claims 1 to 6, and comprises an acquisition module (201) and a processing module (202), wherein: The acquisition module (201) is used to acquire environmental parameters of multiple touch points of the capacitive touch screen, wherein the environmental parameters include temperature parameters, humidity parameters and light intensity parameters; The processing module (202) is used to determine, according to the environmental parameters, a calibrated touch threshold corresponding to each of the touch points, wherein the calibrated touch threshold is used to characterize the minimum touch signal strength required to trigger a touch event under the environmental parameters; The acquisition module (201) is further used to acquire the touch signal strength of each touch point; The processing module (202) is further used to compare the touch signal strength of each touch point with the corresponding calibration touch threshold to obtain the touch state of each touch point, wherein the touch state includes a non-touch state and a touched state; The processing module (202) is further configured to generate a first compensation touch point based on the touch state of each of the touch points, and to generate a second compensation touch point based on the touch state of each of the touch points; The processing module (202) is also used to generate a touch event corresponding to the touch operation based on the touch state of each of the touch points, the first compensation touch point and the second compensation touch point, and send the touch event to the target program to update the user interface corresponding to the target program.

8. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 6 is performed.

Images