High-sensitivity touch capacitor chip device and system

Abstract

The invention discloses a high-sensitivity touch control capacitor chip device and system, and relates to the technical field of touch control. The method comprises the steps that an original capacitance signal matrix is collected through mixed frequency band excitation, environment compensation is conducted on original capacitance signals through a nonlinear compensation mechanism, and an effective capacitance matrix is generated; extracting a time-domain pure touch signal through fractional order time-frequency combined noise suppression and dynamic baseline tracking; the method comprises the following steps: extracting deformation curvature characteristics of a contact area through a time-domain pure touch signal, and constructing a spatial-temporal characteristic tensor; and through self-adaptive convolution kernel generation and a multi-modal attention mechanism, taking the spatial-temporal feature tensor as input, taking the touch behavior classification probability distribution as output, and generating a final touch instruction according to the category corresponding to the maximum value of the probability distribution. Environmental interference is suppressed through multi-frequency excitation and frequency domain decoupling, temperature and humidity coupling compensation is introduced to improve signal stability, multi-dimensional spatial-temporal characteristics are constructed, and the recognition precision and robustness of the capacitive touch control system in a complex environment are remarkably enhanced.

Description

Technical Field

[0001] The present invention relates to the field of touch technology, and specifically to a highly sensitive touch capacitive chip device and system. Background Art

[0002] With the rapid development of human-computer interaction technology, touch technology has been widely applied in many fields such as smart phones, wearable devices, industrial control panels, and medical devices. Especially in the context of the integration of the Internet of Things and artificial intelligence, higher requirements are put forward for the response sensitivity, anti-interference ability, and intelligent recognition accuracy of touch devices. Capacitive touch technology has become one of the mainstream solutions due to its advantages such as fast response, simple structure, and low cost. However, traditional capacitive touch systems still face multiple challenges in practical applications.

[0003] In the prior art, to suppress environmental interference signals, methods such as frequency isolation, low-pass filtering, and temperature and humidity compensation are usually used for processing. However, most of these methods are based on linear compensation models and are difficult to accurately reflect the non-linear influence of environmental factors such as temperature and humidity on capacitive signals. Especially under the condition of rapid changes in temperature and humidity, it is easy to cause insufficient compensation or over-compensation. In addition, traditional methods mostly adopt static baseline models and lack the ability to track baseline drift in real time, which may lead to misidentification or delayed judgment of touch signals in high-sensitivity applications.

[0004] Therefore, there is an urgent need for a touch capacitive chip device with the following capabilities: being able to perform non-linear modeling and compensation on environmental parameters such as temperature and humidity; having the ability of fractional-order noise separation and dynamic baseline estimation to improve the purity of time-domain signals; being able to combine spatial curvature changes and phase stability to extract multi-dimensional touch features; and realizing highly robust and highly accurate touch behavior recognition through adaptive convolution kernels and multi-modal attention mechanisms. Summary of the Invention

[0005] Based on the above-mentioned disadvantages of the prior art, the purpose of the present invention is to provide a highly sensitive touch capacitive chip device and system to solve the above technical problems.

[0006] To achieve the above purpose, the present invention provides the following technical solution: A highly sensitive touch capacitive chip device, comprising: By means of mixed-band excitation, separating touch signals and environmental interference signals, collecting the original capacitive signal matrix, and through a non-linear compensation mechanism, performing environmental compensation on the original capacitive signal matrix according to the temperature and humidity coupling factor to generate an effective capacitance matrix; Based on the effective capacitance matrix, extracting the pure touch signal in the time domain through fractional-order time-frequency joint noise suppression and dynamic baseline tracking; Extracting the deformation curvature feature of the contact area through the pure touch signal in the time domain and constructing a spatio-temporal feature tensor; Generate through an adaptive convolution kernel and a multi-modal attention mechanism, take the spatio-temporal feature tensor as the input, and the touch behavior classification probability distribution as the output, and generate the final touch command according to the category corresponding to the maximum value of the probability distribution.

[0007] The present invention is further configured such that the generation of the effective capacitance matrix includes: Through hybrid frequency band excitation, adopt a dual-frequency time division multiplexing driving method, and alternately activate through a rectangular window function; In the signal acquisition stage, inject a random phase offset into the high-frequency carrier signal to suppress electromagnetic standing wave interference; Separate the high-frequency touch signal and the low-frequency environmental interference signal through a frequency domain mask matrix to generate the original capacitance signal matrix; Define a non-linear humidity sensitive function, model the exponential perturbation of humidity on the capacitance baseline, combine the temperature drift term, construct a temperature and humidity coupling factor, and generate an effective capacitance matrix according to the action of the temperature and humidity coupling factor on the original capacitance signal matrix.

[0008] The present invention is further configured such that the construction of the temperature and humidity coupling factor includes: Define a non-linear humidity sensitive function, and the formula is: , where is the non-linear humidity sensitive function, is the real-time humidity, is the preset optimal humidity, is the humidity bandwidth; Combine the temperature drift term to construct the temperature and humidity coupling factor: , where is the temperature and humidity coupling factor, is the reference temperature, is the real-time temperature, is the temperature saturation interval, is the compensation residual constant term to compensate for the residual error after non-linear compensation.

[0009] The present invention is further configured such that the extraction of the time-domain pure touch signal includes: Based on the effective capacitance matrix, use fractional order derivatives to separate noise, extract high-frequency transient noise components, and combine with Hilbert transform to define a time-varying noise weight function; Fuse the global energy of the effective capacitance matrix and the reference baseline, define the baseline error, and according to the baseline error, design a fractional order differential equation to estimate the baseline drift and calculate the baseline drift estimate value; Extract the time-domain pure touch signal through an adaptive filter and the baseline drift estimate value.

[0010] The present invention is further configured such that the calculation of the baseline drift estimate value includes: The effective capacitance matrix is separated into a baseline component and a touch component through variational mode decomposition; The fractional-order PID control algorithm is used to adjust the proportional coefficient, integral coefficient, and differential coefficient; The proportional coefficient, integral coefficient, and differential coefficient satisfy the constraint conditions, and the algebraic sum of the square of the proportional coefficient, the square root of the reciprocal of the integral coefficient, and the gamma function correction value of the differential coefficient does not exceed a preset threshold; Based on the proportional coefficient, integral coefficient, differential coefficient, fractional-order integration, and baseline error, the baseline drift estimate value is calculated.

[0011] The present invention is further configured such that the step of constructing the spatio-temporal feature tensor includes: According to the time-domain pure touch signal, the high-order partial derivatives of the signal are calculated in the two-dimensional spatial domain of the touch panel to construct a high-order spatial gradient field; Define a third-order curvature tensor to fuse the first-order and second-order derivative information; Use the normalized Hermite orthogonal polynomial basis function to project and reduce the dimension of the third-order curvature tensor; According to the time-domain pure touch signal, calculate the phase coherence entropy, fuse the curvature tensor, and construct the spatio-temporal feature tensor.

[0012] The present invention is further configured such that the calculation of the phase coherence entropy includes: Perform a short-time fractional Fourier transform on the time-domain pure touch signal to obtain the time-frequency domain phase distribution; Generate a global reference phase based on the phase vector average, and calculate the coherence measure between the local phase of each frequency band and the reference phase; Calculate the phase coherence entropy value according to the probability distribution of the coherence measure, and the magnitude of the entropy value characterizes the phase stability of the touch signal.

[0013] The present invention is further configured such that the generation and constraint of the adaptive convolution kernel include: Convert the spatio-temporal feature tensor into a convolution kernel basis vector through implicit space parameter mapping; Apply spectral normalization constraints to the dynamically generated convolution kernel; Use the power iteration method to calculate the maximum singular value of the convolution kernel weight in real time to ensure that the spectral norm constraint condition is satisfied.

[0014] The present invention is further configured such that the multi-modal attention mechanism and classification decision include: Construct a dual-modal collaborative processing structure of a spatial attention head and a temporal attention head; Fuse the dual-modal attention features through the gating weight coefficient, and the gating weight is dynamically generated by the Sigmoid function; Output the multi-task probability through the fully connected layer and the Softmax activation; Select the category corresponding to the maximum probability as the final instruction, set a probability threshold, and trigger an invalid touch determination when the maximum probability is lower than the threshold.

[0015] The present invention also provides a highly sensitive touch capacitive chip system, and the system includes: Capacitance signal acquisition and compensation module: Through mixed-frequency band excitation, separate the touch signal and the environmental interference signal, collect the original capacitance signal matrix, and through a non-linear compensation mechanism, perform environmental compensation on the original capacitance signal matrix according to the temperature and humidity coupling factor to generate an effective capacitance matrix; Time-domain pure touch signal extraction module: Based on the effective capacitance matrix, extract the time-domain pure touch signal through fractional-order time-frequency joint noise suppression and dynamic baseline tracking; Feature extraction and construction module: Extract the deformation curvature feature of the contact area through the time-domain pure touch signal and construct a spatio-temporal feature tensor; Instruction generation module: Through the generation of an adaptive convolution kernel and a multi-modal attention mechanism, use the spatio-temporal feature tensor as the input and the classification probability distribution of touch behavior as the output, and generate the final touch instruction according to the category corresponding to the maximum value of the probability distribution.

[0016] The present invention provides a highly sensitive touch capacitive chip device and system. Through mixed-frequency band excitation, separate the touch signal and the environmental interference signal, collect the original capacitance signal matrix, and through a non-linear compensation mechanism, perform environmental compensation on the original capacitance signal matrix according to the temperature and humidity coupling factor to generate an effective capacitance matrix; Based on the effective capacitance matrix, extract the time-domain pure touch signal through fractional-order time-frequency joint noise suppression and dynamic baseline tracking; Through the time-domain pure touch signal, extract the deformation curvature feature of the contact area and construct a spatio-temporal feature tensor; Through the generation of an adaptive convolution kernel and a multi-modal attention mechanism, use the spatio-temporal feature tensor as the input and the classification probability distribution of touch behavior as the output, and generate the final touch instruction according to the category corresponding to the maximum value of the probability distribution. The beneficial effects produced include: 1. Strong environmental interference suppression ability: Through mixed-frequency band excitation and a dual-frequency time-division multiplexing mechanism, introduce random phase perturbation in the acquisition stage, and combine with frequency-domain masking technology to effectively separate high-frequency touch signals and low-frequency environmental interference signals, improving the signal-to-noise ratio of capacitance signal acquisition; 2. Precise temperature and humidity non-linear compensation mechanism: Use a non-linear humidity-sensitive function to model the exponential perturbation of humidity on the capacitance baseline, and combine with the temperature drift term to construct a temperature and humidity coupling factor to achieve dynamic and non-linear compensation for temperature and humidity perturbations, ensuring the comparability and stability of the original signal in different environments; 3. Strong ability to construct multi-dimensional spatio-temporal features: Use the high-order derivative information in the two-dimensional space of the touch panel to construct a third-order curvature tensor, and fuse frequency-domain stability indicators such as phase coherence entropy to form a spatio-temporal feature tensor with stronger expressive ability, providing a solid feature basis for the accurate recognition of complex touch behaviors.

[0017] The above description is only an overview of the technical solution of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically illustrates the specific implementation manners of this application. Brief Description of the Drawings

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. In the drawings: Figure 1 is the flowchart of the high-sensitivity touch capacitive chip device of the present invention; Figure 2 is the principle block diagram of the high-sensitivity touch capacitive chip system of the present invention. Detailed Embodiments

[0019] The following will describe the embodiments of the present invention with reference to the drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for explaining the present invention, rather than for limiting the protection scope of the present invention.

[0020] It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Therefore, only the components related to the present invention are shown in the diagrams, rather than being drawn according to the number, shape and size of the components in actual implementation. The type, quantity and ratio of each component in its actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0021] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0022] Example 1

[0023] A highly sensitive touch capacitive chip device, as Figure 1 shown, includes: separating touch signals from environmental interference signals through hybrid band excitation, collecting the original capacitance signal matrix, and performing environmental compensation on the original capacitance signal matrix according to the temperature and humidity coupling factor through a non-linear compensation mechanism to generate an effective capacitance matrix; Based on the effective capacitance matrix, extracting the pure touch signal in the time domain through fractional-order time-frequency joint noise suppression and dynamic baseline tracking; Extracting the deformation curvature characteristics of the contact area through the pure touch signal in the time domain and constructing a spatio-temporal feature tensor; Using the adaptive convolution kernel generation and multi-modal attention mechanism, taking the spatio-temporal feature tensor as the input and the classification probability distribution of touch behaviors as the output, and generating the final touch command according to the category corresponding to the maximum value of the probability distribution.

[0024] The present invention is further configured such that the generating of the effective capacitance matrix includes: Through hybrid band excitation, adopting a dual-frequency time-division multiplexing driving method, and alternately activating through a rectangular window function. Specifically, the frequency of the high-frequency carrier signal is 10 MHz, and the frequency of the low-frequency carrier signal is 1 MHz, significantly improving the ability to distinguish environmental interference from real touches; In the signal acquisition stage, injecting a random phase offset into the high-frequency carrier signal to suppress electromagnetic standing wave interference, effectively suppressing standing wave interference and improving the stability and consistency of high-frequency signals; Separating high-frequency touch signals from low-frequency environmental interference signals through a frequency-domain mask matrix to generate the original capacitance signal matrix. Specifically, separating high and low frequency components through synchronous demodulation. The high-frequency component captures the change in touch micro-current, and the low-frequency component establishes an environmental baseline model and uses the fast Fourier transform to extract the frequency-domain energy distribution: , where is the frequency-domain energy distribution, , are the high and low frequency band mask matrices respectively, is the fast Fourier transform function, accurately extracting the target frequency band and reducing the contamination of capacitance data by out-of-band noise; Defining a non-linear humidity-sensitive function, modeling the exponential perturbation of humidity on the capacitance baseline, combining with the temperature drift term, constructing a temperature and humidity coupling factor, and generating an effective capacitance matrix according to the action of the temperature and humidity coupling factor on the original capacitance signal matrix. Specifically, the formula for generating the effective capacitance matrix is: , where is the effective capacitance matrix, is the original capacitance signal matrix, is the temperature and humidity coupling factor, is the temperature gradient sensitivity matrix, which is obtained through a calibration experiment and can still maintain the accuracy and stability of the touch detection result under drastic environmental changes.

[0025] The present invention is further configured such that the construction of the temperature and humidity coupling factor includes: Define a non-linear humidity sensitive function, the formula is: , where is the non-linear humidity sensitive function, is the real-time humidity, is the preset optimal humidity, is the humidity bandwidth; Combine the temperature drift term to construct the temperature and humidity coupling factor: , where is the temperature and humidity coupling factor, is the reference temperature, is the real-time temperature, is the temperature saturation interval, is the compensation residual constant term to compensate for the residual error after non-linear compensation; The non-linear modeling of the humidity effect can more accurately reflect the amplification interference characteristics of the humidity on the capacitance baseline when the humidity is far from the optimal value. The temperature saturation modeling mechanism, by introducing function, more realistically simulates the drift curve of the capacitance that first increases sharply and then stabilizes as the temperature rises, avoids overcorrection, dynamically couples the temperature and humidity factors, effectively weakens the interference of environmental fluctuations on the touch capacitance measurement, and improves the detection sensitivity and stability.

[0026] The present invention is further configured such that the extraction of the pure touch signal in the time domain includes: Based on the effective capacitance matrix, use fractional-order derivative to separate noise and extract the high-frequency transient noise component, Combine the Hilbert transform to define a time-varying noise weight function. Specifically, based on the definition of the Caputo fractional-order derivative, , where is the -th order fractional-order derivative of the function , represents the value of the gamma function at , , is the current time, is the first-order integer-order derivative of the function , , where is the noise sensitive area mask matrix, is the effective capacitance matrix; the time-varying noise weight function , where is a sliding time window for matching the power frequency noise period, is a complex exponential frequency domain modulation factor, is a specific frequency point, is the imaginary unit, is the principal value integral, is the weighting coefficient of the steady-state suppression term. Using fractional-order derivatives can extract complex and non-stationary high-frequency perturbation information, which is more suitable for dealing with the capacitance mutation characteristics than traditional integer-order differentiation.

[0027] Fuse the global energy of the effective capacitance matrix and the reference baseline, define the baseline error, and design a fractional-order differential equation to estimate the baseline drift according to the baseline error, and calculate the baseline drift estimation value. Specifically, the baseline error formula is: , , where is the baseline error, is the Frobenius norm, is the dynamic reference benchmark, calculated by the sliding average of historical data, is the time window length for benchmark calculation. Using the fractional-order modeling method of the baseline error can avoid false triggering caused by baseline drift due to environmental changes; Extract the time-domain pure touch signal through an adaptive filter and the baseline drift estimation value. Specifically, construct a frequency-domain transfer function to dynamically suppress the noise energy: , , where is the frequency-domain transfer function, is the time-varying noise weight function, is the adaptive step size to balance noise suppression and signal distortion, and are the signal and noise powers respectively, estimated by the power spectral density; The formula for the time-domain pure touch signal is: , where is the baseline drift estimation value.

[0028] The present invention is further set such that the calculation of the baseline drift estimation value includes: Separate the effective capacitance matrix into a baseline component and a touch component through variational mode decomposition; Adopt a fractional-order PID control algorithm to adjust the proportional coefficient, integral coefficient, and differential coefficient; The proportional coefficient, integral coefficient, and differential coefficient satisfy the constraint conditions, and the algebraic sum of the square of the proportional coefficient, the square root of the reciprocal of the integral coefficient, and the gamma function correction value of the differential coefficient does not exceed a preset threshold; The baseline drift estimation value is calculated based on the proportional coefficient, integral coefficient, differential coefficient, fractional-order integral, and baseline error. Specifically, the formula for the baseline drift estimation value is: , where is the proportional coefficient, is the integral coefficient, Differential coefficient, is the fractional-order integral, and the coefficient constraint is: , to avoid overshoot and oscillation.

[0029] The present invention is further configured such that the step of constructing the spatio-temporal feature tensor includes: According to the time-domain pure touch signal, calculate the high-order partial derivatives of the signal in the two-dimensional spatial domain of the touch panel to construct a high-order spatial gradient field. Specifically, the high-order partial derivatives of the signal are , , , , , where is the time-domain pure touch signal; Define a third-order curvature tensor to fuse the first-order and second-order derivative information. The third-order curvature tensor , and through a mixed operation of outer product, direct sum, and Hadamard product, generate a third-order curvature tensor containing the spatial gradient direction, Hessian matrix structure, and time-varying characteristics; Use the normalized Hermite orthogonal polynomial basis function to project and reduce the dimension of the third-order curvature tensor: , where is the curvature tensor after dimension reduction, is the polynomial basis function, , , respectively correspond to the polynomial orders, , represent the discrete point coordinate indices in the two-dimensional space; According to the time-domain pure touch signal, calculate the phase coherence entropy, fuse the curvature tensor, and construct the spatio-temporal feature tensor. Specifically, splice the curvature invariant and the phase feature into a high-order tensor, and perform linear dimension reduction on the fused high-dimensional tensor: , where is the spliced high-order tensor, is the principal component analysis transformation matrix, is the transpose of the principal component analysis transformation matrix, is the spatio-temporal feature tensor.

[0030] The present invention is further configured such that the calculation of the phase coherence entropy includes: Perform a short-time fractional Fourier transform on the pure touch signal in the time domain to obtain the phase distribution in the time-frequency domain; Generate a global reference phase based on the average of phase vectors, and calculate the coherence measure between the local phase of each frequency band and the reference phase. The formula is: , where is the local phase coherence measure, is the instantaneous phase of the th frequency band, is the instantaneous phase of the th frequency band, is the global reference phase, obtained by averaging the phase vectors, is the total number of frequency bands, is the inner product on the complex plane, equivalent to calculating the phase difference projection of and , represents the sum of the synchronization strengths of the phases of all frequency bands with the reference phase; Calculate the phase coherence entropy value according to the probability distribution of the coherence measure. The magnitude of the entropy value characterizes the phase stability of the touch signal. Specifically, , where is the phase coherence entropy. The lower the value, the stronger the phase synchronization, indicating touch stability.

[0031] The present invention is further configured such that the generation and constraint of the adaptive convolution kernel include: Convert the spatio-temporal feature tensor into a convolution kernel basis vector through implicit space parameter mapping; Apply spectral normalization constraints to the dynamically generated convolution kernel to generate an adaptive convolution kernel ; Adopt the power iteration method to calculate the maximum singular value of the convolution kernel weight in real time to ensure that the spectral norm constraint condition is satisfied.

[0032] The present invention is further configured such that the multi-modal attention mechanism and classification decision include: Construct a dual-modal collaborative processing structure of a spatial attention head and a temporal attention head; Fuse the dual-modal attention features through a gated weight coefficient, and the gated weight is dynamically generated by the Sigmoid function; Output multi-task probabilities through a fully connected layer and a Softmax activation; Select the category corresponding to the maximum probability as the final instruction, set a probability threshold, and trigger an invalid touch determination when the maximum probability is lower than the threshold. Specifically, the spatial attention head focuses on the spatial distribution characteristics of the touch area, and the temporal attention head captures the dynamic temporal correlation of the touch behavior; Gated weight generation: , where is the spatial attention matrix, is the time attention vector, is the learnable weight matrix, is the Sigmoid activation function, and the attention-enhanced feature output: ; Output the multitask probability through the fully connected layer and the Softmax activation: , , where is the attention-enhanced feature, is the activation function, is the classification weight matrix, is the classification bias vector, providing a learnable threshold offset for each class, is the total number of target classes for the classification task; Select the class corresponding to the maximum probability as the final instruction: , is the final instruction, set the probability threshold , if , then trigger the invalid touch judgment.

[0033] Embodiment 2

[0034] Please refer to Figure 2 , the exemplary high-sensitivity touch capacitive chip system includes: Capacitance signal acquisition and compensation module: Through mixed-band excitation, separate the touch signal and the environmental interference signal, acquire the original capacitance signal matrix, and through the nonlinear compensation mechanism, perform environmental compensation on the original capacitance signal according to the temperature and humidity coupling factor to generate an effective capacitance matrix; Time-domain pure touch signal extraction module: Based on the effective capacitance matrix, extract the time-domain pure touch signal through fractional-order time-frequency joint noise suppression and dynamic baseline tracking; Feature extraction and construction module: Extract the deformation curvature feature of the contact area through the time-domain pure touch signal and construct a spatio-temporal feature tensor; Instruction generation module: Through the adaptive convolution kernel generation and the multimodal attention mechanism, use the spatio-temporal feature tensor as the input and the touch behavior classification probability distribution as the output, and generate the final touch instruction according to the class corresponding to the maximum value of the probability distribution.

[0035] It should be noted that a highly sensitive touch capacitive chip system provided by the above embodiments and a highly sensitive touch capacitive chip device provided by the above embodiments belong to the same concept. The specific ways in which each module and unit perform operations have been described in detail in the method embodiments and will not be elaborated here. In practical applications, a highly sensitive touch capacitive chip system provided by the above embodiments can, according to needs, allocate the above functions to different functional modules, that is, divide the internal structure of the system into different functional modules to complete all or part of the functions described above. This is not limited here either.

[0036] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that includes one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0037] It should be understood that the term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context before and after.

[0038] In this application, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or a similar expression means any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or plural.

[0039] It should be understood that in various embodiments of this application, the magnitudes of the serial numbers of the above processes do not imply the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of this application.

[0040] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0041] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0042] In several embodiments provided in this application, it should be understood that the disclosed systems can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0043] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0044] In addition, in each embodiment of the present application, each functional unit can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0045] If the above-mentioned function 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 storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0046] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A high-sensitivity touch capacitive chip device, characterized in that, Including: Through mixed - band excitation, separating touch signals from environmental interference signals, collecting the original capacitance signal matrix, and through a non - linear compensation mechanism, performing environmental compensation on the original capacitance signal matrix according to the temperature - humidity coupling factor to generate an effective capacitance matrix; Based on the effective capacitance matrix, extracting the pure touch signal in the time domain through fractional - order time - frequency joint noise suppression and dynamic baseline tracking; Through the pure touch signal in the time domain, extracting the deformation curvature characteristics of the contact area and constructing a spatio - temporal feature tensor; Through the generation of an adaptive convolution kernel and a multi - modal attention mechanism, using the spatio - temporal feature tensor as the input and the classification probability distribution of touch behaviors as the output, generating the final touch command according to the category corresponding to the maximum value of the probability distribution.

2. The highly sensitive touch capacitive chip device according to claim 1, characterized in that Through mixed - band excitation, adopting a dual - frequency time - division multiplexing driving method and alternately activating through a rectangular window function; In the signal acquisition stage, injecting a random phase offset into the high - frequency carrier signal to suppress electromagnetic standing - wave interference; Separating high - frequency touch signals and low - frequency environmental interference signals through a frequency - domain mask matrix to generate the original capacitance signal matrix; Defining a non - linear humidity - sensitive function, modeling the exponential perturbation of humidity on the capacitance baseline, combining with the temperature drift term, constructing a temperature - humidity coupling factor, and generating an effective capacitance matrix according to the action of the temperature - humidity coupling factor on the original capacitance signal matrix.

3. The highly sensitive touch capacitive chip device according to claim 2, wherein The construction of the temperature - humidity coupling factor includes: Define the non-linear humidity sensitive function, the formula is: , where is the non-linear humidity sensitive function, is the real-time humidity, is the preset optimal humidity, is the humidity bandwidth; Construct a temperature-humidity coupling factor by combining the temperature drift terms: , where is the temperature-humidity coupling factor, is the reference temperature, is the real-time temperature, is the temperature saturation range, is the compensation residual constant term, which compensates for the residual error after non-linear compensation.

4. A highly sensitive touch capacitive chip device according to claim 2, characterized in that, The extraction of the pure touch signal in the time domain includes: Based on the effective capacitance matrix, separating noise using fractional - order derivatives, extracting high - frequency transient noise components, and combining with the Hilbert transform to define a time - varying noise weight function; Fusing the global energy of the effective capacitance matrix and the reference baseline, defining the baseline error, and according to the baseline error, designing a fractional - order differential equation to estimate the baseline drift and calculating the baseline drift estimate value; Extracting the pure touch signal in the time domain through an adaptive filter and the baseline drift estimate value.

5. A highly sensitive touch capacitive chip device according to claim 4, characterized in that, The calculation of the baseline drift estimate value includes: Separating the effective capacitance matrix into a baseline component and a touch component through variational mode decomposition; Adopting a fractional - order PID control algorithm to adjust the proportional coefficient, integral coefficient, and differential coefficient; The proportional coefficient, integral coefficient, and differential coefficient satisfy the constraint conditions, and the algebraic sum of the square of the proportional coefficient, the square root of the reciprocal of the integral coefficient, and the modified value of the gamma function of the differential coefficient does not exceed a preset threshold; According to the proportional coefficient, integral coefficient, and differential coefficient, through fractional - order integration and the baseline error, calculating the baseline drift estimate value.

6. The high-sensitivity touch capacitive chip device according to claim 4, wherein The steps of constructing the spatio - temporal feature tensor include: According to the pure touch signal in the time domain, calculating the high - order partial derivatives of the signal in the two - dimensional spatial domain of the touch panel to construct a high - order spatial gradient field; Defining a third - order curvature tensor and fusing the first - order and second - order derivative information; Using a normalized Hermite orthogonal polynomial basis function to project and reduce the dimension of the third - order curvature tensor; According to the pure touch signal in the time domain, calculating the phase coherence entropy and fusing the curvature tensor to construct the spatio - temporal feature tensor.

7. A highly sensitive touch capacitive chip device according to claim 6, characterized in that, The calculation of the phase coherence entropy includes: Performing a short - time fractional - order Fourier transform on the pure touch signal in the time domain to obtain the time - frequency domain phase distribution; Generating a global reference phase based on the average of phase vectors and calculating the coherence measure between the local phases of each frequency band and the reference phase; Calculate the phase coherence entropy value according to the probability distribution of the coherence metric, and the magnitude of the entropy value characterizes the phase stability of the touch signal.

8. The highly sensitive touch capacitive chip device according to claim 6, wherein The generation and constraint of the adaptive convolution kernel include: Convert the spatio-temporal feature tensor into a convolution kernel basis vector through latent space parameter mapping; Apply spectral normalization constraints to the dynamically generated convolution kernel; Use the power iteration method to calculate the maximum singular value of the convolution kernel weight in real time to ensure that the spectral norm constraint condition holds.

9. The high-sensitivity touch capacitive chip device according to claim 1, wherein The multi-modal attention mechanism and classification decision include: Construct a dual-modal collaborative processing structure of spatial attention head and temporal attention head; Fuse the dual-modal attention features through the gating weight coefficient, and the gating weight is dynamically generated by the Sigmoid function; Output the multi-task probability through the fully connected layer and Softmax activation; Select the category corresponding to the maximum probability as the final instruction, set the probability threshold, and trigger the invalid touch determination when the maximum probability is lower than the threshold.

10. A highly sensitive touch capacitive chip system for implementing the highly sensitive touch capacitive chip device according to any one of claims 1-9, characterized in that, Include: Capacitance signal acquisition and compensation module: Separate the touch signal and the environmental interference signal through mixed-band excitation, acquire the original capacitance signal matrix, and perform environmental compensation on the original capacitance signal matrix according to the temperature and humidity coupling factor through the non-linear compensation mechanism to generate an effective capacitance matrix; Time-domain pure touch signal extraction module: Based on the effective capacitance matrix, extract the time-domain pure touch signal through fractional-order time-frequency joint noise suppression and dynamic baseline tracking; Feature extraction and construction module: Extract the deformation curvature feature of the contact area through the time-domain pure touch signal and construct the spatio-temporal feature tensor; Instruction generation module: Use the generation of the adaptive convolution kernel and the multi-modal attention mechanism, take the spatio-temporal feature tensor as the input, and the touch behavior classification probability distribution as the output, and generate the final touch instruction according to the category corresponding to the maximum value of the probability distribution.

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