Methods and systems for preventing accidental touches on display screens in complex scenarios

Abstract

This application relates to the field of touch detection, specifically to a method and system for preventing accidental touches on displays in complex scenarios. The method includes: sampling multiple times at sampling points in the sensor array of the touchscreen to obtain a sampling sequence for each sampling point; constructing a signal distribution reference model centered on a local peak point of the capacitance change matrix, based on a preset attenuation model; obtaining the capacitance change value at each point in each preset direction of the capacitance change matrix, centered on the local peak point, and weighting the difference between the capacitance change value at that point and the reference value at that point according to a correction weight, to obtain a weighted error value for that point; determining a rigid contact factor based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix; and determining whether the touchscreen is in a rigid contact state based on the rigid contact factor, and outputting an anti-accidental touch strategy based on the determination result. This application can reduce the probability of accidental touches on displays.

Description

Technical Field

[0001] This application relates to the field of touch detection technology, and in particular to a method and system for preventing accidental touches on display touch screens in complex scenarios. Background Technology

[0002] In fields such as industrial control, outdoor operations, and medical equipment, projected capacitive touchscreens often need to operate in high-gain mode. The purpose of enabling this mode is to enhance signal reception sensitivity, ensuring that even when the operator is wearing thick insulating gloves (such as rubber gloves or cotton gloves), weak mutual capacitance changes can still be detected by the system.

[0003] However, while significantly amplifying the weak signal from the glove, it also simultaneously amplifies the signal generated by conductive liquids (such as water droplets, oil, and condensation) adhering to the screen surface. From the perspective of capacitive coupling mechanism, "wet glove pressing" and "stationary water droplet attachment" in high-gain mode will produce similar amplitude changes in mutual capacitance, and their contact areas often highly overlap (both are fingertip-sized areas). Since the signal amplitudes generated by the two are similar, simply increasing the trigger threshold will cause glove operation to result in disconnected touch, while decreasing the trigger threshold will result in water droplet accidental touch. Conventional waterproofing algorithms usually rely on detecting large-area connected water film (Water Rejection) to suppress accidental touches, but for discretely distributed small droplets, their shape is extremely similar to fingertip touch, making it difficult to effectively distinguish them using simple geometric shapes (such as aspect ratio and roundness). Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method and system for preventing accidental touches on display screens in complex scenarios. The specific technical solution adopted is as follows:

[0005] Firstly, a method for preventing accidental touches on a display in complex scenarios is provided, the method comprising:

[0006] The sampling points in the sensor array of the touch screen are sampled multiple times to obtain the sampling sequence of each sampling point;

[0007] Centered on the local peak points of the capacitance change matrix, a signal distribution reference model is constructed according to a preset attenuation model; the value of each element in the capacitance change matrix is ​​determined based on the difference between the mean of the sampling sequence of the corresponding sampling point and the reference value.

[0008] Centered on the local peak point, the capacitance change value of each point in each preset direction of the capacitance change matrix is ​​obtained. Based on the correction weight, the difference between the capacitance change value at that point and the reference value at that point is weighted to obtain the weighted error value for that point. The correction weight is obtained by clamping the element values ​​in the fluctuation variance matrix. Each element value in the fluctuation variance matrix is ​​determined based on the variance of the sampling sequence of the corresponding sampling point. The reference value for each point is determined according to the signal distribution reference model.

[0009] The rigid contact factor is determined based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix; the weighted fitting error value is obtained by weighting the error values ​​of multiple points in multiple preset directions of the capacitance change matrix.

[0010] Based on the rigid contact factor, it determines whether the touch screen is in a rigid contact state, and outputs an anti-accidental touch strategy according to the determination result.

[0011] Optionally, the sampling points in the sensor array of the touch screen are sampled multiple times to obtain a sampling sequence for each sampling point, including:

[0012] In response to the touchscreen being in a contactless state, acquire multiple historical sample values ​​for each sampling point in the touchscreen's sensor array;

[0013] Calculate the mean of multiple historical sample values ​​to obtain the initial baseline value;

[0014] Within the current scanning frame, each sampling point in the touch screen's sensor array is sampled multiple times to obtain the sampling sequence of each sampling point in the current scanning frame;

[0015] Calculate the mean of the sampling sequence for each sampling point in the current scan frame to obtain the sampling mean;

[0016] The initial baseline value and the sample mean are weighted according to the preset weighting coefficients to obtain the baseline value.

[0017] Optionally, before constructing the signal distribution reference model based on a preset attenuation model, using the local peak points of the capacitance change matrix as the center, the following steps are also included:

[0018] Calculate the difference between the sample mean and the baseline value at each sampling point to obtain the capacitance change value at that sampling point;

[0019] A capacitance change matrix is ​​constructed based on the coordinates of each sampling point in the induction array and its capacitance change value; wherein, the row and column indices of each element in the capacitance change matrix correspond one-to-one with the coordinates of each sampling point in the induction array.

[0020] Optionally, a signal distribution reference model is constructed based on a preset attenuation model, centered on the local peak points of the capacitance change matrix, including:

[0021] Based on the intensity capacitance change value at the local peak point and the preset geometric parameters, a signal distribution parameter model is constructed with the local peak point as the center and based on the Gaussian function. The intensity capacitance change value at the local peak point is the center amplitude of the signal distribution parameter model, and the geometric parameters are used to control the attenuation rate of the reference value with spatial distance.

[0022] Optionally, taking the local peak point as the center, the capacitance change value of the capacitance change matrix at each point in each preset direction is obtained, including:

[0023] Centered on the local peak point, a scanning path is established along multiple preset directions in the spatial domain characterized by the capacitance change matrix; wherein each scanning path includes at least one point;

[0024] Obtain the capacitance change value of each point on each scanning path; for points located on the scanning path but not corresponding to a sampling point, the capacitance change value of the point is determined by interpolation based on the capacitance change values ​​of multiple neighboring sampling points.

[0025] Optionally, based on the correction weights, the difference between the capacitance change at that point and the reference value at that point is weighted to obtain the weighted error value at that point, including:

[0026] Calculate the variance of the sampling sequence at each sampling point to obtain the fluctuation variance value of that sampling point;

[0027] Based on the coordinates of each sampling point in the sensing array and its fluctuation variance value, a fluctuation variance matrix is ​​constructed; wherein, the row and column indices of each element in the fluctuation variance matrix correspond one-to-one with the coordinates of each sampling point in the sensing array.

[0028] Based on the scanning path of the capacitance change matrix, the corresponding fluctuation variance value is obtained from the fluctuation variance matrix according to the spatial coordinates of each point on each scanning path. Among them, for points in the fluctuation variance matrix that do not correspond to a sampling point, the fluctuation variance value of the point is determined by interpolation based on the fluctuation variance values ​​of multiple neighboring sampling points. The row and column indices in the capacitance change matrix and the fluctuation variance matrix are the same, and each index corresponds to the same sampling point in the sensing array.

[0029] In response to the fact that the variance value of each point is less than the preset first variance threshold, the correction weight of that point is determined to be the first variance threshold.

[0030] In response to the fact that the variance value of each point is greater than the preset second variance threshold, the correction weight of that point is determined to be the second variance threshold; wherein, the first variance threshold is less than the second variance threshold;

[0031] In response to the fact that the variance value of each point is between the first variance threshold and the second variance threshold, the correction weight of that point is determined to be the variance value of that point;

[0032] Based on the correction weight of each point, the difference between the capacitance change value of that point and the reference value of that point is weighted to obtain the weighted error value of that point.

[0033] Optionally, based on the correction weight of each point, the difference between the capacitance change value at that point and the reference value at that point is weighted to obtain the weighted error value for that point, including:

[0034] Based on the signal distribution reference model, for each point in the capacitance change matrix, the reference value of that point is determined according to the distance between each point and the local peak point.

[0035] Calculate the sum of the reference value and the capacitance change value at each point, and determine the weighted error value at that point as the ratio of the square of the sum to the correction weight of that point.

[0036] Optionally, the rigid contact factor is determined based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix, including:

[0037] Calculate the average of the weighted error values ​​of multiple points on multiple scanning paths to obtain the weighted fitting error value;

[0038] Calculate the product of the weighted fitting error value and the preset coefficient, and use the sum of the product and the preset value as the weighted value;

[0039] The rigid contact factor is obtained by calculating the ratio of the capacitance change value corresponding to the local peak point to the weighted value; the rigid contact factor characterizes the matching degree between the touch event and the contact response of the rigid conductor.

[0040] Optionally, based on the rigid contact factor, determining whether the touchscreen is in a rigid contact state includes:

[0041] In response to the rigid contact factor being not less than a preset first threshold, it is determined that the touch screen is in a rigid contact state;

[0042] In response to the rigid contact factor not being greater than a preset second threshold, it is determined that the touch screen is in a fluid contact state; wherein, the first threshold is less than the second threshold;

[0043] In response to the rigid contact factor being between a first threshold and a second threshold, the touch screen is determined to be in a transition state; the transition state indicates that the state of the touch screen is between a rigid contact state and a fluid contact state.

[0044] Secondly, a system for preventing accidental touches on a display in complex scenarios is provided, the system comprising:

[0045] The sampling module is used to sample the sampling points in the sensor array of the touch screen multiple times to obtain the sampling sequence of each sampling point;

[0046] The module is used to construct a signal distribution reference model centered on the local peak points of the capacitance change matrix and based on a preset attenuation model; the value of each element in the capacitance change matrix is ​​determined based on the difference between the mean of the sampling sequence of the corresponding sampling point and the reference value.

[0047] The weighting module is used to obtain the capacitance change value of each point in the capacitance change matrix in each preset direction, with the local peak point as the center, and to weight the difference between the capacitance change value of the point and the reference value of the point according to the correction weight to obtain the weighted error value of the point; the correction weight is obtained by clamping the element values ​​in the fluctuation variance matrix, and each element value in the fluctuation variance matrix is ​​determined based on the variance of the sampling sequence of the corresponding sampling point; the reference value of each point is determined according to the signal distribution reference model.

[0048] The determination module is used to determine the rigid contact factor based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix; the weighted fitting error value is obtained based on the weighted error value of multiple points in multiple preset directions of the capacitance change matrix;

[0049] The judgment module is used to determine whether the touch screen is in a rigid contact state based on the rigid contact factor, and outputs an anti-accidental touch strategy based on the judgment result.

[0050] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of this application.

[0051] This application offers the following advantages: By acquiring data from sampling points and modulating morphological fitting differences using variance weights, it achieves sensitive shielding against interference from stationary water droplets with similar signal amplitudes in high-gain mode and stable response to wet glove operation without increasing the global amplitude threshold, thus solving the problem of difficulty in distinguishing between the two. By generating corrected weights through bidirectional clamping processing of the fluctuation variance, including lower and upper limits, it effectively prevents algorithm misjudgments caused by weight inaccuracies in extremely low-noise or strong electromagnetic interference environments, ensuring stable system operation from battery-powered quiet devices to industrial environments with strong power frequency interference. By dynamically constructing a signal distribution reference model based on real-time detected local peak point intensity, replacing fixed fingerprint database matching, the system can adaptively compensate for signal differences caused by changes in glove thickness, pressure intensity, and environmental temperature drift, avoiding performance degradation due to parameter fixation and improving long-term reliability in different application scenarios. It improves the ability to distinguish between rigid contact and non-rigid interference, reduces the false positive rate and false negative probability caused by environmental noise and edge touch, and enhances anti-interference robustness while maintaining high sensitivity. Attached Figure Description

[0052] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a flowchart of a method for preventing accidental touches on a display in complex scenarios, as shown in one embodiment.

[0054] Figure 2 This is a schematic diagram of a display touch anti-accidental touch system for complex scenarios in one embodiment;

[0055] Figure 3 This is a schematic diagram of the structure of an electronic device in one embodiment. Detailed Implementation

[0056] To further illustrate the technical means and effects adopted by this application to achieve the intended inventive purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a display touchscreen anti-accidental touch method and system for complex scenarios proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0058] The following description, in conjunction with the accompanying drawings, details a specific solution for an anti-accidental touch method for display touchscreens in complex scenarios provided in this application. For example... Figure 1 As shown, the method includes:

[0059] S11. Sample the sampling points in the sensor array of the touch screen multiple times to obtain the sampling sequence of each sampling point.

[0060] The sampling point is the intersection of the driving electrode and the sensing electrode in the sensing array of the touch screen, that is, the physical intersection of the sensing channel. Each sampling point corresponds to an independent sensing unit in the capacitive touch screen.

[0061] Each sampling yields a raw inductive value (sampled value). The raw inductive value is the unprocessed data obtained from a single signal acquisition at the same sampling point. The magnitude of the raw inductive value reflects the instantaneous capacitive coupling strength of that sampling point at that sampling moment.

[0062] In order to accurately quantify the change in mutual capacitance caused by an external touch object, the system first needs to establish a reference zero point, i.e., a baseline value, in the non-touch state.

[0063] Therefore, in one embodiment, the sampling points in the sensor array of the touch screen are sampled multiple times to obtain a sampling sequence for each sampling point, including:

[0064] In response to the touchscreen being in a contactless state, acquire multiple historical sample values ​​for each sampling point in the touchscreen's sensor array;

[0065] Calculate the mean of multiple historical sample values ​​to obtain the initial baseline value;

[0066] Within the current scanning frame, each sampling point in the touch screen's sensor array is sampled multiple times to obtain the sampling sequence of each sampling point in the current scanning frame;

[0067] Calculate the mean of the sampling sequence for each sampling point in the current scan frame to obtain the sampling mean;

[0068] The initial baseline value and the sample mean are weighted according to the preset weighting coefficients to obtain the baseline value.

[0069] The preset weighting coefficient can be 0.05 to 0.1.

[0070] During the system power-on initialization phase, i.e., when the touchscreen is in a contactless state, the touch controller... Line drive electrode and A sensor array composed of columns of sensing electrodes performs full-screen scanning. For any given column... Line drive electrode and the first The intersection of the sensing channels formed by the series of sensing electrodes, i.e., the sampling point. The system collects multiple historical sample values ​​and calculates their arithmetic mean to obtain the sampling points. initial baseline value .

[0071] Considering that changes in ambient temperature and humidity can cause temperature drift in capacitive sensors, the system needs to... Perform periodic dynamic updates. During system operation, if continuous [updates / updates] are detected... If there are no touch events in the full screen for a frame (e.g., 20 frames), the system will initiate the baseline update logic.

[0072] Within the current scan frame, sampling points in the touchscreen's sensor array. Multiple samplings were performed to obtain sampling points. Calculate the sampling points in the sampling sequence of the current scan frame. The mean of the sampled sequence is obtained. .

[0073] Specifically, in order to capture the transient fluctuation characteristics of the sensing channel within a small time window, the system needs to acquire a sufficiently long sample of raw data. Within the current scan frame... Inside, the touch controller activates the driving electrodes sequentially according to a preset scanning order.

[0074] When the When the row drive electrode is activated, the connection to the first The receiving circuit on the inductive electrode senses the inductive sampling point. Continuous data acquisition is performed. This acquisition operation is completed within an indivisible continuous time window: the transmitter sends an excitation signal containing A pulses to the driving electrode, and the receiver simultaneously performs A analog-to-digital conversion (ADC) samplings. The system thus obtains the sampling points. In the sampling sequence of the current frame The sequence contains A discrete sampled value, denoted as In this embodiment, the value of A is preferably between 16 and 32. This value ensures sufficient sample size for subsequent statistical variance calculations while avoiding excessively long single scan times that could lead to a decrease in the system's reporting rate.

[0075] Based on preset weighting coefficients, the initial baseline value and the sampled mean are weighted to obtain the baseline value. The formula for calculating the baseline value is as follows: .in, Sampling points The baseline value, These are the preset weighting coefficients. Sampling points The initial baseline value, This is the average value from the samples. The mechanism for calculating the baseline value ensures that it can slowly adapt to changes in the environment, thereby guaranteeing that the subsequently calculated capacitance change value accurately reflects the touch intensity.

[0076] S12. Using the local peak points of the capacitance change matrix as the center, construct a signal distribution reference model based on the preset attenuation model.

[0077] In this matrix, each element value is determined based on the difference between the mean of the sampling sequence of the corresponding sampling point and the benchmark value.

[0078] In one embodiment, before constructing a signal distribution reference model based on a preset attenuation model, using the local peak points of the capacitance change matrix as the center, the method further includes:

[0079] Calculate the difference between the sample mean and the baseline value at each sampling point to obtain the capacitance change value at that sampling point;

[0080] A capacitance change matrix is ​​constructed based on the coordinates of each sampling point in the induction array and its capacitance change value; wherein, the row and column indices of each element in the capacitance change matrix correspond one-to-one with the coordinates of each sampling point in the induction array.

[0081] Calculate sampling points sampling sequence The arithmetic mean of the samples is used to obtain the sample mean, and then the sample mean is subtracted from the sample point. The benchmark value The capacitance change value at the sampling point is obtained. capacitance change value The calculation formula is: Where A is the sampling point The number of multiple sampled values ​​in the sampling sequence. For the first Each sample value, For the first The value of each sampled value Sampling points The baseline value is determined by the coordinates of each sampling point in the sensing array and its capacitance change value. A capacitance change matrix is ​​then constructed. In this matrix, the row and column indices of each element correspond one-to-one with the coordinates of each sampling point in the induction array. Each row in the capacitance change matrix corresponds to a driving electrode in the induction array, and each column corresponds to a sensing electrode. The position of any element in the capacitance change matrix (i.e., its row and column indices) strictly corresponds to the coordinates of a specific sampling point in the induction array.

[0082] Capacitance change matrix The value represents the decrease in mutual capacitance at the corresponding physical location due to the coverage of a finger or conductive medium, i.e., the effective strength of the touch signal.

[0083] In one embodiment, a signal distribution reference model is constructed based on a preset attenuation model, centered on the local peak points of the capacitance change matrix, including:

[0084] Based on the intensity capacitance change value at the local peak point and the preset geometric parameters, a signal distribution parameter model is constructed with the local peak point as the center and based on the Gaussian function. The intensity capacitance change value at the local peak point is the center amplitude of the signal distribution parameter model, and the geometric parameters are used to control the attenuation rate of the reference value with spatial distance.

[0085] Traversing the capacitance change matrix Perform a local maximum search. Compare each point in the capacitance change matrix with its 8-neighborhood points. If a point's value is greater than the values ​​of all its neighbors, mark it as a local peak. Local peak points The corresponding change in capacitance is the measured peak intensity. .

[0086] To reduce system power consumption and avoid unnecessary calculations on weak noise levels, the system introduces a basic trigger threshold. This threshold is typically set to 3 to 5 times the system's noise floor level. The system only processes applications that meet the following criteria. The system performs subsequent template construction and rigid solution processes on local peak points. For local peak points below the threshold, the system treats them as invalid background noise and ignores them directly.

[0087] To assess whether the shape of the touched object conforms to the attenuation law of a rigid conductor, the system needs to construct a standardized reference model. Unlike traditional fingerprint recognition methods that rely on comparison with a fixed database, this embodiment employs a dynamic construction strategy based on measured peak values ​​to generate a standard rigid feature template (geometrically represented as an attenuation surface). This template is not intended to precisely reproduce the actual physical microscopic deformation caused by finger pressure, but rather serves as a geometric benchmark to measure the regularity and steepness of the measured signal's spatial distribution. The system is based on current... Using preset geometric parameters, calculate the theoretical values ​​of each point on the template in memory.

[0088] With local peak points Centered on, for any Euclidean distance from the center is At any position, its reference value Defined in Gaussian form, the expression for the signal distribution reference model is:

[0089] ;

[0090] in, To be related to local peak points The distance to point R is a reference value. For the measured peak intensity, i.e., the local peak point The change in capacitance. The power operation is a power operation with the natural constant e (approximately 2.71828) as the base and x as the exponent, where R is the sum of the points and local peaks. distance, These are preset geometric parameters; to ensure the applicability of the scale, The value of is strongly correlated with the physical pitch of the sensing array, and is typically set to 0.8 to 1.2 times the distance between the sensing electrodes. This formula constructs an ideal, centrally symmetric, single-peak attenuation model. If the measured signal distribution highly coincides with this model, it indicates that the energy of the touched object is concentrated, conforming to the characteristics of rigid touch; if the measured signal exhibits a flat top, multiple peaks, or irregular tailing, it deviates significantly from the template. This template data is temporarily stored in memory for use in the next stage of calculating the fitting error.

[0091] S13. Taking the local peak point as the center, obtain the capacitance change value of each point in each preset direction of the capacitance change matrix, and according to the correction weight, weight the difference between the capacitance change value of the point and the reference value of the point to obtain the weighted error value of the point.

[0092] The corrected weights are obtained by clamping the element values ​​in the fluctuation variance matrix.

[0093] Each element in the fluctuation variance matrix is ​​determined based on the variance of the sampling sequence for the corresponding sampling point.

[0094] The reference value for each point is determined based on the signal distribution reference model.

[0095] In one embodiment, taking the local peak point as the center, obtaining the capacitance change value of the capacitance change matrix at each point in each preset direction includes:

[0096] Centered on the local peak point, a scanning path is established along multiple preset directions in the spatial domain characterized by the capacitance change matrix; wherein each scanning path includes at least one point;

[0097] Obtain the capacitance change value of each point on each scanning path; for points located on the scanning path but not corresponding to a sampling point, the capacitance change value of the point is determined by interpolation based on the capacitance change values ​​of multiple neighboring sampling points.

[0098] Because the sensor array is a discrete grid, the system employs a discretized radial scanning strategy to comprehensively capture the morphological features of the touch area edges. The system uses local peak points... Defined around a central point along multiple preset directions. A scanning path that radiates outwards (e.g.) ,cover Each scanning path includes at least one point, and multiple preset directions cover at least two non-parallel directions of the capacitance change matrix, such as 0°, 45°, 90° and 135°, to detect the consistency of the distribution of touch signals in different spatial orientations.

[0099] The scanning path is a finite sequence of discrete points starting from a local peak point and extending along a preset direction. Each point in the scanning path is generated sequentially with a fixed step size, and its spatial coordinates are restricted to the effective rows and columns of the sensing array, with the total number not exceeding a preset upper limit. For example, each scanning path contains no more than 10 points, generated sequentially with a fixed step size. When the scanning path extends to the edge of the array, the generation of subsequent points stops to ensure that all path points can be found in the capacitance change matrix and the fluctuation variance matrix.

[0100] For each scan path, the system selects several discrete sampling points. The coordinates of each point on the scan path can be integers or non-integers. For the i-th... The first scan path If a point's row and column indices are not integers, then that point does not correspond to a sampling point. Based on the capacitance changes of multiple neighboring sampling points, the capacitance change value of that point is determined through interpolation. If the row and column index of the point is an integer, then the point corresponds to the sampling point. Based on the coordinates of the sampling point in the sensing array, the corresponding capacitance change value is obtained from the capacitance change matrix.

[0101] In one embodiment, the difference between the capacitance change at that point and the reference value at that point is weighted according to the correction weight to obtain the weighted error value at that point, including:

[0102] Calculate the variance of the sampling sequence at each sampling point to obtain the fluctuation variance value of that sampling point;

[0103] Based on the coordinates of each sampling point in the sensing array and its fluctuation variance value, a fluctuation variance matrix is ​​constructed; wherein, the row and column indices of each element in the fluctuation variance matrix correspond one-to-one with the coordinates of each sampling point in the sensing array.

[0104] Based on the scanning path of the capacitance change matrix, the corresponding fluctuation variance value is obtained from the fluctuation variance matrix according to the spatial coordinates of each point on each scanning path. Among them, for points in the fluctuation variance matrix that do not correspond to a sampling point, the fluctuation variance value of the point is determined by interpolation based on the fluctuation variance values ​​of multiple neighboring sampling points. The row and column indices in the capacitance change matrix and the fluctuation variance matrix are the same, and each index corresponds to the same sampling point in the sensing array.

[0105] In response to the fact that the variance value of each point is less than the preset first variance threshold, the correction weight of that point is determined to be the first variance threshold.

[0106] In response to the fact that the variance value of each point is greater than the preset second variance threshold, the correction weight of that point is determined to be the second variance threshold; wherein, the first variance threshold is less than the second variance threshold;

[0107] In response to the fact that the variance value of each point is between the first variance threshold and the second variance threshold, the correction weight of that point is determined to be the variance value of that point;

[0108] Based on the correction weight of each point, the difference between the capacitance change value of that point and the reference value of that point is weighted to obtain the weighted error value of that point.

[0109] The preset first variance threshold is used to prevent computational overflow due to the denominator approaching zero, and also to prevent the algorithm from being sensitive to minor background noise. The value of the first variance threshold is set according to the background noise level corresponding to the resolution of the system analog-to-digital converter, and is usually set to 1 to 2 times the variance value corresponding to the minimum resolution of the system analog-to-digital converter.

[0110] The preset second variance threshold is used to prevent the fitting error from being overly suppressed due to an excessively large denominator in extreme electromagnetic interference environments (i.e., to prevent the logical loophole of "the greater the noise, the better"). The value of the second variance threshold is usually set to 3 to 5 times the variance of typical glove operation noise.

[0111] Calculate the variance of the sampled sequence at each sampling point to obtain the fluctuation variance value for that sampling point. The variance of the fluctuation The calculation formula is:

[0112] ;

[0113] in, Sampling points The variance of the fluctuation, Sampling points The number of multiple sampled values ​​in the sampling sequence. For the first Each sample value, For the first The value of each sampled value Sampling points sampling sequence The arithmetic mean.

[0114] Based on the coordinates of each sampling point in the sensing array and its fluctuation variance value, a fluctuation variance matrix is ​​constructed. In this matrix, the row and column indices of each element correspond one-to-one with the coordinates of each sampling point in the induction array. Each row of the fluctuation variance matrix corresponds to a driving electrode in the induction array, and each column corresponds to a sensing electrode. The position of any element in the fluctuation variance matrix (i.e., its row and column indices) strictly corresponds to the coordinates of a specific sampling point in the induction array.

[0115] Based on the scanning path of the capacitance change matrix, the corresponding fluctuation variance value is obtained from the fluctuation variance matrix according to the spatial coordinates of each point on each scanning path. For points in the fluctuation variance matrix that do not correspond to a sampling point, the fluctuation variance value of that point is determined by interpolation based on the fluctuation variance values ​​of multiple neighboring sampling points. It is understandable that since both the capacitance change matrix and the fluctuation variance matrix are constructed based on the same sensing array, they are completely aligned in spatial structure: the row indices of the matrices correspond to the same driving electrodes, and the column indices correspond to the same sensing electrodes. Any position in either matrix represents the signal characteristics of the same physical sampling point in the sensing array. Therefore, the scanning path defined based on the capacitance change matrix—that is, a series of path points with definite spatial coordinates—can be directly applied to the fluctuation variance matrix. Thus, while obtaining the capacitance change value of each point on each scanning path, the system simultaneously obtains the fluctuation variance value of the corresponding position from the fluctuation variance matrix using the exact same spatial coordinates, without needing to redefine or convert the path.

[0116] For the fluctuation variance matrix The variance of the fluctuation at the corresponding point Perform clamping to obtain the corrected weight at that point. Specifically, the adjusted weight for each point The calculation formula is:

[0117] ;

[0118] in, Adjusted weights for each point, The first variance threshold is preset. The second variance threshold is preset. This represents the variance of the fluctuation at that point. Strictly limited to the effective range This ensures the numerical stability and logical correctness of subsequent weighted calculations.

[0119] In one embodiment, the difference between the capacitance change value at a point and the reference value at that point is weighted according to the correction weight of each point to obtain the weighted error value for that point, including:

[0120] Based on the signal distribution reference model, for each point in the capacitance change matrix, the reference value of that point is determined according to the distance between each point and the local peak point.

[0121] Calculate the sum of the reference value and the capacitance change value at each point, and determine the weighted error value at that point as the ratio of the square of the sum to the correction weight of that point.

[0122] For the The first scan path At each point, the capacitance change value is obtained. and corrected weights At the same time, based on the distance from this point to the local peak point... The reference value at that point is calculated using the expression of the signal distribution reference model. . No. The first scan path Weighted error value of each point The calculation formula is:

[0123] ;

[0124] in, For the first The first scan path The weighted error value of each point, This represents the change in capacitance at that point. This is the reference value for that point. This is the corrected weight for that point. The geometric differences between the measured shape and the standard rigid template were quantified. The weight of this difference is adjusted according to the signal stability. The weighted error value characterizes the local deviation of the capacitance change value at each point from the reference value, and the reliability (stability) of the signal at that point has been taken into account.

[0125] If the water droplet is stationary, the signal is extremely stable. The value is extremely small (close to) This significantly amplifies the differences in the numerator terms, leading to a sharp increase in the error term. If wet gloves are used, the signal is accompanied by noise. A larger value suppresses the difference in the numerator, keeping the error term at a low level.

[0126] S14. Determine the rigid contact factor based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix.

[0127] The weighted fitting error value is obtained by weighting the error values ​​of multiple points in multiple preset directions of the capacitance change matrix.

[0128] The rigid contact factor characterizes the degree of matching between touch events and the contact response of a rigid conductor.

[0129] In one embodiment, the rigid contact factor is determined based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix, including:

[0130] Calculate the average of the weighted error values ​​of multiple points on multiple scanning paths to obtain the weighted fitting error value;

[0131] Calculate the product of the weighted fitting error value and the preset coefficient, and use the sum of the product and the preset value as the weighted value;

[0132] The rigid contact factor is obtained by calculating the ratio of the capacitance change value corresponding to the local peak point to the weighted value; the rigid contact factor characterizes the matching degree between the touch event and the contact response of the rigid conductor.

[0133] The weighted fitting error value is obtained by averaging the weighted error values ​​of multiple points along multiple scanning paths. The calculation formula is:

[0134] ;

[0135] in, This represents the weighted fitting error value, where L is the number of multiple scan paths. The number of points on each scan path. For the first Scan path, For the first One point, For the first The first scan path The weighted error value for each point.

[0136] To facilitate subsequent threshold determination, the system maps the weighted fitting error value to a positive, normalized confidence index, namely the rigid contact factor. The calculation formula is:

[0137] ;

[0138] in, For rigid contact factors, This represents the capacitance change value corresponding to the local peak point. This represents the weighted fitting error value. This is a preset coefficient, also known as the sensitivity normalization coefficient, used to balance the magnitudes of the amplitude and error terms.

[0139] Preset coefficients The value of can be calibrated using the following engineering method: Under typical signal-to-noise ratio conditions, press the screen with a standard rigid test body (such as a copper pillar) and measure the typical fitting error value. ,set up This calibration ensures that, under standard rigid touch conditions, the denominator term... The value is approximately 2.0, thus making The dynamic range is mapped to a linear interval that is easily distinguishable. Rigid contact factor Although the numerical dimension of capacitance is retained, its physical meaning has been transformed into the effective signal strength (the amount of capacitance change) after rigid confidence weighting correction.

[0140] Regarding water droplet interference The extreme value leads to a huge denominator. The force is reduced to near zero, which is detrimental to effective touch control. Smaller The capacitance change values ​​corresponding to most of the original local peak points were retained.

[0141] S15. Based on the rigid contact factor, determine whether the touch screen is in a rigid contact state, and output an anti-accidental touch strategy according to the determination result.

[0142] In one embodiment, determining whether the touchscreen is in a rigid contact state based on the rigid contact factor includes:

[0143] In response to the rigid contact factor being not less than a preset first threshold, it is determined that the touch screen is in a rigid contact state;

[0144] In response to the rigid contact factor not being greater than a preset second threshold, it is determined that the touch screen is in a fluid contact state; wherein, the first threshold is less than the second threshold;

[0145] In response to the rigid contact factor being between a first threshold and a second threshold, the touch screen is determined to be in a transition state; the transition state indicates that the state of the touch screen is between a rigid contact state and a fluid contact state.

[0146] Two judgment thresholds are preset: effective judgment threshold. (First threshold) and interference judgment threshold (Second threshold). Among them, The value is greater than These two thresholds are related to the rigid contact factor. Three decision intervals were constructed over the numerical domain.

[0147] Rigid confirmation area ( This range corresponds to a defined rigid touch state. In this state, the touch body is in close contact with the screen, and the spatial distribution of the signal conforms to the rigid feature template. Even if there is noise, its rigidity is sufficient to overwhelm the noise interference, so that the corrected intensity value is still higher than the threshold.

[0148] Fluid confirmation area ( This interval corresponds to a defined fluid interference or accidental touch while suspended in mid-air, i.e., the fluid contact state. In this state, the spatial distribution of the touched object exhibits significant non-rigid characteristics such as flat tops and multiple peaks, and the extremely low background noise amplifies these characteristics through the algorithm, leading to… It decays to an extremely low level.

[0149] Critical hysteresis region ( This range corresponds to the transitional state of touch operation (such as a slight lifting of a finger) or the minute deformation of the fluid edge. Within this area, the signal characteristics are not significant enough, and direct judgment is prone to state jitter.

[0150] The system reads the current scan frame period and the coordinates of the corresponding local peak points In conjunction with the touch state of the previous frame, the following state machine logic is executed:

[0151] Case A: Entering the rigid confirmation zone. If The system determines the current event to be a valid rigid touch. The system immediately resets the debounce counter. The value is set to 0, and the current touch point status is marked as "Tracking". The system then executes the coordinate reporting logic.

[0152] Case B: Enter the fluid confirmation area. If The system determines the current event to be environmental interference. The system resets the debouncing counter. The value is set to 0, and the current touch point's state is marked as "Suppressed". The system then executes coordinate masking logic.

[0153] Case C: In the critical hysteresis region. If The system determines that the current event is in a critical state. At this point, the system does not immediately change the determination result of the previous frame, but instead activates the jitter maintenance mechanism:

[0154] 1. System check debounce counter The value.

[0155] 2. If Less than the preset number of hold frames (For example, 3 frames), the system maintains the judgment state of the previous frame. That is: if the previous frame was "tracking", the coordinates will continue to be reported in this frame; if the previous frame was "suppressing", the masking will continue in this frame. Simultaneously, the system will... Add 1.

[0156] 3. If achieve This indicates that the object has been in a blurred state for a long time. In order to prevent zombie touch point residue, the system forcibly classifies it as environmental interference, stops reporting it, and marks it as "suppressing".

[0157] Based on the above judgment results, the final physical operation is performed. If the judgment result is a valid touch, the system uses an interpolation algorithm (such as the centroid method) to calculate the physical coordinates. The data is converted to high-precision screen pixel coordinates, packaged, and sent to the host processor in real time via an interrupt signal (INT). This operation ensures immediate response and consistency during wet glove operation. If the result indicates interference, the system simply discards the coordinate data internally without generating an interrupt signal or reporting any data packets. This operation eliminates the possibility of accidental touches caused by still water droplets or fluid artifacts at the underlying level, and the host is completely unaware of this.

[0158] This application achieves directional, high-sensitivity shielding against static water droplet interference by leveraging the physical characteristic of "low noise and non-rigidity" without reducing system sensitivity (i.e., without increasing the global amplitude threshold), while retaining the ability to respond to weak glove signals. By introducing variance-based bidirectional clamping logic, the defect of statistical algorithms being prone to failure in extreme electromagnetic interference environments is completely repaired, ensuring stable operation of the system in both quiet environments (battery powered) and noisy environments (power frequency interference). The use of a dynamic template construction mechanism based on measured peak values, rather than fixed fingerprint database matching, allows the algorithm to adapt to gloves of different thicknesses and different pressure levels, avoiding parameter failures caused by environmental temperature drift or aging.

[0159] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0160] This application also provides a display touch anti-accidental touch system for complex scenarios, such as... Figure 2 As shown, the system includes:

[0161] The sampling module 21 is used to sample the sampling points in the sensor array of the touch screen multiple times to obtain the sampling sequence of each sampling point;

[0162] Module 22 is used to construct a signal distribution reference model centered on the local peak points of the capacitance change matrix and based on a preset attenuation model; the value of each element in the capacitance change matrix is ​​determined based on the difference between the mean of the sampling sequence of the corresponding sampling point and the reference value.

[0163] The weighting module 23 is used to obtain the capacitance change value of each point in the capacitance change matrix in each preset direction, with the local peak point as the center, and to weight the difference between the capacitance change value of the point and the reference value of the point according to the correction weight to obtain the weighted error value of the point; the correction weight is obtained by clamping the element values ​​in the fluctuation variance matrix, and each element value in the fluctuation variance matrix is ​​determined based on the variance of the sampling sequence of the corresponding sampling point; the reference value of each point is determined according to the signal distribution reference model.

[0164] The determination module 24 is used to determine the rigid contact factor based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix; the weighted fitting error value is obtained based on the weighted error value of multiple points in multiple preset directions of the capacitance change matrix;

[0165] The judgment module 25 is used to determine whether the touch screen is in a rigid contact state based on the rigid contact factor, and output an anti-accidental touch strategy according to the judgment result.

[0166] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs.

[0167] Figure 3 This is a schematic diagram of the structure of an electronic device according to an example embodiment of this application. The electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, it implements the method described in any of the above embodiments. Figure 3 The electronic device 30 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0168] like Figure 3 As shown, the electronic device 30 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including memory 32 and processor 31).

[0169] Bus 33 includes a data bus, an address bus, and a control bus.

[0170] The memory 32 may include volatile memory, such as random access memory (RAM) 321 and / or cache memory 322, and may further include read-only memory (ROM) 323.

[0171] The memory 32 may also include a program tool 325 (or utility) having a set (at least one) program module 324, such program module 324 including but not limited to: an operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0172] The processor 31 executes various functional applications and data processing, such as the methods provided in any of the above embodiments, by running computer programs stored in the memory 32.

[0173] Electronic device 30 can also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 35. Furthermore, electronic device 30 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public network, such as the Internet) via network adapter 36. As shown, network adapter 36 communicates with other modules of electronic device 30 via bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with electronic device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0174] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0175] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided in any of the above embodiments.

[0176] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0177] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0178] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the above embodiments.

[0179] The program code for executing the computer program product of this application can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0180] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0181] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

[0182] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for preventing accidental touches on a display screen in complex scenarios, characterized in that, The method includes: The sampling points in the sensor array of the touch screen are sampled multiple times to obtain the sampling sequence of each sampling point; Centered on the local peak points of the capacitance change matrix, a signal distribution reference model is constructed according to a preset attenuation model; the value of each element in the capacitance change matrix is ​​determined based on the difference between the mean of the sampling sequence of the corresponding sampling point and the reference value. Centered on the local peak point, the capacitance change value of each point in each preset direction of the capacitance change matrix is ​​obtained. Based on the correction weight, the difference between the capacitance change value at that point and the reference value at that point is weighted to obtain the weighted error value for that point. The correction weight is obtained by clamping the element values ​​in the fluctuation variance matrix. Each element value in the fluctuation variance matrix is ​​determined based on the variance of the sampling sequence of the corresponding sampling point. The reference value for each point is determined according to the signal distribution reference model. The rigid contact factor is determined based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix; the weighted fitting error value is obtained by weighting the error values ​​of multiple points in multiple preset directions of the capacitance change matrix. Based on the rigid contact factor, it determines whether the touch screen is in a rigid contact state, and outputs an anti-accidental touch strategy according to the determination result.

2. The method for preventing accidental touches on a display in complex scenarios as described in claim 1, characterized in that, The sampling of the sampling points in the sensor array of the touch screen is performed multiple times to obtain the sampling sequence of each sampling point, including: In response to the touchscreen being in a contactless state, acquire multiple historical sample values ​​for each sampling point in the touchscreen's sensor array; Calculate the mean of multiple historical sample values ​​to obtain the initial baseline value; Within the current scan frame, each sampling point in the touch screen's sensor array is sampled multiple times to obtain the sampling sequence of each sampling point in the current scan frame; Calculate the mean of the sampling sequence for each sampling point in the current scan frame to obtain the sampling mean; The initial baseline value and the sample mean are weighted according to the preset weighting coefficients to obtain the baseline value.

3. The method for preventing accidental touches on a display in complex scenarios as described in claim 2, characterized in that, Before constructing the signal distribution reference model centered on the local peak points of the capacitance change matrix and based on a preset attenuation model, the following steps are also included: Calculate the difference between the sample mean and the baseline value at each sampling point to obtain the capacitance change value at that sampling point; A capacitance change matrix is ​​constructed based on the coordinates of each sampling point in the induction array and its capacitance change value; wherein, the row and column indices of each element in the capacitance change matrix correspond one-to-one with the coordinates of each sampling point in the induction array.

4. The method for preventing accidental touches on a display in complex scenarios as described in claim 3, characterized in that, The step of constructing a signal distribution reference model centered on the local peak points of the capacitance change matrix and based on a preset attenuation model includes: Based on the intensity capacitance change value at the local peak point and the preset geometric parameters, a signal distribution parameter model is constructed with the local peak point as the center and based on the Gaussian function. The intensity capacitance change value at the local peak point is the center amplitude of the signal distribution parameter model, and the geometric parameters are used to control the attenuation rate of the reference value with spatial distance.

5. The method for preventing accidental touches on a display in complex scenarios as described in claim 1, characterized in that, The step of obtaining the capacitance change value at each point in each preset direction of the capacitance change matrix, centered on the local peak point, includes: Centered on the local peak point, a scanning path is established along multiple preset directions in the spatial domain characterized by the capacitance change matrix; wherein each scanning path includes at least one point; Obtain the capacitance change value of each point on each scanning path; for points located on the scanning path but not corresponding to a sampling point, the capacitance change value of the point is determined by interpolation based on the capacitance change values ​​of multiple neighboring sampling points.

6. The method for preventing accidental touches on a display in complex scenarios as described in claim 5, characterized in that, The step of weighting the difference between the capacitance change value at that point and the reference value at that point according to the correction weight to obtain the weighted error value at that point includes: Calculate the variance of the sampling sequence at each sampling point to obtain the fluctuation variance value of that sampling point; Based on the coordinates of each sampling point in the sensing array and its fluctuation variance value, a fluctuation variance matrix is ​​constructed; wherein, the row and column indices of each element in the fluctuation variance matrix correspond one-to-one with the coordinates of each sampling point in the sensing array. Based on the scanning path of the capacitance change matrix, the corresponding fluctuation variance value is obtained from the fluctuation variance matrix according to the spatial coordinates of each point on each scanning path. Among them, for points in the fluctuation variance matrix that do not correspond to a sampling point, the fluctuation variance value of the point is determined by interpolation based on the fluctuation variance values ​​of multiple neighboring sampling points. The row and column indices in the capacitance change matrix and the fluctuation variance matrix are the same, and each index corresponds to the same sampling point in the sensing array. In response to the fact that the variance value of each point is less than the preset first variance threshold, the correction weight of that point is determined to be the first variance threshold. In response to the fact that the variance value of each point is greater than the preset second variance threshold, the correction weight of that point is determined to be the second variance threshold; wherein, the first variance threshold is less than the second variance threshold; In response to the fact that the variance value of each point is between the first variance threshold and the second variance threshold, the correction weight of that point is determined as the variance value of that point; Based on the correction weight of each point, the difference between the capacitance change value of that point and the reference value of that point is weighted to obtain the weighted error value of that point.

7. The method for preventing accidental touches on a display in complex scenarios as described in claim 6, characterized in that, The step of weighting the difference between the capacitance change value and the reference value at each point according to the correction weight of each point to obtain the weighted error value at that point includes: Based on the signal distribution reference model, for each point in the capacitance change matrix, the reference value of that point is determined according to the distance between each point and the local peak point. Calculate the sum of the reference value and the capacitance change value at each point, and determine the weighted error value at that point as the ratio of the square of the sum to the correction weight of that point.

8. The method for preventing accidental touches on a display in complex scenarios as described in claim 7, characterized in that, The determination of the rigid contact factor based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix includes: Calculate the average of the weighted error values ​​of multiple points on multiple scanning paths to obtain the weighted fitting error value; Calculate the product of the weighted fitting error value and the preset coefficient, and use the sum of the product and the preset value as the weighted value; The rigid contact factor is obtained by calculating the ratio of the capacitance change value corresponding to the local peak point to the weighted value; the rigid contact factor characterizes the matching degree between the touch event and the contact response of the rigid conductor.

9. The method for preventing accidental touches on a display in complex scenarios as described in claim 1, characterized in that, The determination of whether the touchscreen is in a rigid contact state based on the rigid contact factor includes: In response to the rigid contact factor being not less than a preset first threshold, it is determined that the touch screen is in a rigid contact state; In response to the rigid contact factor not being greater than a preset second threshold, it is determined that the touch screen is in a fluid contact state; wherein, the first threshold is less than the second threshold; In response to the rigid contact factor being between a first threshold and a second threshold, the touch screen is determined to be in a transition state; the transition state indicates that the state of the touch screen is between a rigid contact state and a fluid contact state.

10. A display touchscreen anti-accidental touch system for complex scenarios, characterized in that, The system includes: The sampling module is used to sample the sampling points in the sensor array of the touch screen multiple times to obtain the sampling sequence of each sampling point; The module is used to construct a signal distribution reference model centered on the local peak points of the capacitance change matrix and based on a preset attenuation model; the value of each element in the capacitance change matrix is ​​determined based on the difference between the mean of the sampling sequence of the corresponding sampling point and the reference value. The weighting module is used to obtain the capacitance change value of each point in the capacitance change matrix in each preset direction, with the local peak point as the center, and to weight the difference between the capacitance change value of the point and the reference value of the point according to the correction weight to obtain the weighted error value of the point; the correction weight is obtained by clamping the element values ​​in the fluctuation variance matrix, and each element value in the fluctuation variance matrix is ​​determined based on the variance of the sampling sequence of the corresponding sampling point; the reference value of each point is determined according to the signal distribution reference model. The determination module is used to determine the rigid contact factor based on the weighted fitting error value and the capacitance change value corresponding to the local peak point of the capacitance change matrix; the weighted fitting error value is obtained based on the weighted error value of multiple points in multiple preset directions of the capacitance change matrix; The judgment module is used to determine whether the touch screen is in a rigid contact state based on the rigid contact factor, and outputs an anti-accidental touch strategy based on the judgment result.

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