A high-sensitivity touch capacitive chip device and system

Abstract

The present invention discloses a highly sensitive touch capacitor chip device and system, which relates to the field of touch technology. The method includes: collecting the original capacitance signal matrix through mixed frequency band excitation, performing environmental compensation on the original capacitance signal through a nonlinear compensation mechanism, and generating an effective capacitance matrix; extracting a pure touch signal in the time domain through fractional-order time-frequency combined 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 spatiotemporal feature tensor; using adaptive convolution kernel generation and multimodal attention mechanism, taking the spatiotemporal feature tensor as input, and the touch behavior classification probability distribution as output, and generating the final touch instruction according to the category corresponding to the maximum value of the probability distribution. By suppressing environmental interference through multi-frequency excitation and frequency domain decoupling, and introducing temperature and humidity coupling compensation to improve signal stability, a multi-dimensional spatiotemporal feature is constructed, which significantly enhances the recognition accuracy and robustness of the capacitive touch system in complex environments.

Description

Technical Field

[0001] The present invention relates to the field of touch technology, and in particular to a high-sensitivity touch capacitor chip device and system. Background Art

[0002] With the rapid development of human-computer interaction technology, touch technology has been widely used in a variety of fields, including smartphones, wearable devices, industrial control panels, and medical devices. In particular, with the convergence of the Internet of Things and artificial intelligence, higher requirements are being placed on touch devices for their responsiveness, anti-interference capabilities, and intelligent recognition accuracy. Capacitive touch technology, due to its fast response, simple structure, and low cost, has become a mainstream solution. However, traditional capacitive touch systems still face numerous challenges in practical applications.

[0003] Existing technologies typically suppress environmental interference signals through frequency isolation, low-pass filtering, and temperature and humidity compensation. However, these methods are mostly based on linear compensation models, which struggle to accurately reflect the nonlinear effects of environmental factors like temperature and humidity on capacitive signals. This can easily lead to under- or over-compensation, especially under conditions of rapid temperature and humidity fluctuations. Furthermore, traditional methods often employ static baseline models, lacking the ability to track baseline drift in real time. This can lead to misidentification or delayed detection of touch signals in highly sensitive applications.

[0004] Therefore, there is an urgent need for a touch capacitor chip device with the following capabilities: the ability to perform nonlinear modeling and compensation for environmental parameters such as temperature and humidity; the ability to separate fractional-order noise and estimate dynamic baselines to improve the purity of time-domain signals; the ability to combine spatial curvature changes and phase stability to extract multi-dimensional touch features; and the ability to achieve highly robust and accurate touch behavior recognition through adaptive convolution kernels and multimodal attention mechanisms. Summary of the Invention

[0005] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a highly sensitive touch capacitor chip device and system to solve the above-mentioned technical problems.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a highly sensitive touch capacitor chip device, comprising:

[0007] Through mixed frequency band excitation, the touch signal and environmental interference signal are separated, the original capacitance signal matrix is collected, and the nonlinear compensation mechanism is used to perform environmental compensation on the original capacitance signal matrix according to the temperature and humidity coupling factor to generate an effective capacitance matrix.

[0008] Based on the effective capacitance matrix, the pure touch signal in the time domain is extracted through fractional-order time-frequency joint noise suppression and dynamic baseline tracking.

[0009] Through the pure touch signal in the time domain, the deformation curvature characteristics of the contact area are extracted and the spatiotemporal feature tensor is constructed;

[0010] Through adaptive convolution kernel generation and multimodal attention mechanism, the spatiotemporal feature tensor is used as input, the touch behavior classification probability distribution is used as output, and the final touch instruction is generated according to the category corresponding to the maximum value of the probability distribution.

[0011] The present invention is further configured such that generating the effective capacitance matrix comprises:

[0012] Through mixed frequency band excitation, dual-frequency time division multiplexing driving mode is adopted, and rectangular window function is alternately activated;

[0013] During the signal acquisition phase, random phase offsets are injected into the high-frequency carrier signal to suppress electromagnetic standing wave interference;

[0014] The high-frequency touch signal and the low-frequency environmental interference signal are separated by a frequency domain mask matrix to generate the original capacitance signal matrix;

[0015] A nonlinear humidity sensitivity function is defined to model the exponential perturbation of humidity on the capacitance baseline. The temperature drift term is combined to construct a temperature-humidity coupling factor. The effective capacitance matrix is generated by applying the temperature-humidity coupling factor to the original capacitance signal matrix.

[0016] The present invention is further configured such that the construction of the temperature and humidity coupling factor includes:

[0017] Define the nonlinear humidity sensitivity function, the formula is: ,in, is a nonlinear humidity sensitivity function, For real-time humidity, The preset optimal humidity is is the humidity bandwidth;

[0018] Combined with the temperature drift term, the temperature and humidity coupling factor is constructed: ,in, is the temperature and humidity coupling factor, is the reference temperature, is the real-time temperature, is the temperature saturation range, To compensate for the residual constant term, it compensates for the residual error after nonlinear compensation.

[0019] The present invention is further configured such that the step of extracting a time-domain pure touch signal includes:

[0020] Based on the effective capacitance matrix, fractional derivatives are used to separate noise and extract high-frequency transient noise components. Combined with Hilbert transform, a time-varying noise weight function is defined.

[0021] The global energy of the effective capacitance matrix is integrated with the reference baseline to define the baseline error. Based on the baseline error, a fractional-order differential equation is designed to estimate the baseline drift and calculate the baseline drift estimate.

[0022] The time domain pure touch signal is extracted through adaptive filtering and baseline drift estimation.

[0023] The present invention is further configured such that the calculation of the baseline drift estimate includes:

[0024] The effective capacitance matrix is separated into baseline component and touch component through variational mode decomposition;

[0025] Use fractional-order PID control algorithm to adjust the proportional coefficient, integral coefficient and differential coefficient;

[0026] The proportional coefficient, integral coefficient, and differential coefficient meet the constraints, and the algebraic sum of the square of the proportional coefficient, the reciprocal square root of the integral coefficient, and the gamma function correction value of the differential coefficient does not exceed the preset threshold;

[0027] The baseline drift estimation value is obtained based on the proportional coefficient, integral coefficient, differential coefficient, fractional order integral, and baseline error calculation.

[0028] The present invention is further configured such that the step of constructing the spatiotemporal feature tensor comprises:

[0029] Based on the pure touch signal in the time domain, 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;

[0030] Define the third-order curvature tensor and integrate the first-order and second-order derivative information;

[0031] Normalized Hermite orthogonal polynomial basis functions are used to project the third-order curvature tensor for dimensionality reduction.

[0032] Based on the pure touch signal in the time domain, the phase coherence entropy is calculated, the curvature tensor is fused, and the spatiotemporal feature tensor is constructed.

[0033] The present invention is further configured such that the calculation of the phase coherence entropy includes:

[0034] Perform short-time fractional Fourier transform on the time-domain pure touch signal to obtain the time-frequency domain phase distribution;

[0035] Generate a global reference phase based on phase vector averaging, and calculate the coherence measure between the local phase of each frequency band and the reference phase;

[0036] The phase coherence entropy value is calculated according to the probability distribution of the coherence measurement, and the magnitude of the entropy value represents the phase stability of the touch signal.

[0037] The present invention is further configured such that the generation and constraint of the adaptive convolution kernel includes:

[0038] The spatiotemporal feature tensor is converted into convolution kernel basis vectors through latent space parameter mapping;

[0039] Apply spectral normalization constraints to dynamically generated convolution kernels;

[0040] The power iteration method is used to calculate the maximum singular value of the convolution kernel weight in real time to ensure that the spectral norm constraint condition holds.

[0041] The present invention is further configured such that the multimodal attention mechanism and classification decision include:

[0042] Construct a dual-modal collaborative processing structure of spatial attention head and temporal attention head;

[0043] The bimodal attention features are fused through the gating weight coefficient, and the gating weight is dynamically generated by the Sigmoid function;

[0044] Output multi-task probabilities through fully connected layers and Softmax activation;

[0045] Select the category corresponding to the maximum probability as the final instruction, set the probability threshold, and trigger invalid touch judgment when the maximum probability is lower than the threshold.

[0046] The present invention also provides a highly sensitive touch capacitor chip system, the system comprising:

[0047] Capacitive signal acquisition and compensation module: This module uses mixed frequency band excitation to separate touch signals from environmental interference signals, acquires the original capacitance signal matrix, and uses a nonlinear compensation mechanism to perform environmental compensation on the original capacitance signal matrix based on the temperature and humidity coupling factor to generate an effective capacitance matrix.

[0048] Time-domain pure touch signal extraction module: Based on the effective capacitance matrix, it extracts time-domain pure touch signals through fractional-order time-frequency joint noise suppression and dynamic baseline tracking;

[0049] Feature extraction and construction module: Extracts the deformation curvature features of the contact area through pure touch signals in the time domain and constructs a spatiotemporal feature tensor;

[0050] Generate instruction module: Through adaptive convolution kernel generation and multimodal attention mechanism, it takes the spatiotemporal feature tensor as input and the touch behavior classification probability distribution as output, and generates the final touch instruction according to the category corresponding to the maximum value of the probability distribution.

[0051] The present invention provides a highly sensitive touch capacitive chip device and system. This device uses mixed-band excitation to separate touch signals from environmental interference signals, collects an original capacitance signal matrix, and uses a nonlinear compensation mechanism to perform environmental compensation on the original capacitance signal matrix based on the temperature and humidity coupling factor to generate an effective capacitance matrix. Based on the effective capacitance matrix, a fractional-order time-frequency combined noise suppression and dynamic baseline tracking are used to extract a pure touch signal in the time domain. The pure touch signal in the time domain is used to extract the deformation curvature characteristics of the contact area and construct a spatiotemporal feature tensor. Using adaptive convolution kernel generation and a multimodal attention mechanism, the spatiotemporal feature tensor is used as input, and a touch behavior classification probability distribution is used as output. The final touch command is generated based on the category corresponding to the maximum value of the probability distribution. The resulting beneficial effects include:

[0052] 1. Strong environmental interference suppression capability: Through mixed-band excitation and dual-frequency time-division multiplexing mechanisms, random phase perturbations are introduced during the acquisition phase. Combined with frequency domain masking technology, high-frequency touch signals are effectively separated from low-frequency environmental interference signals, improving the signal-to-noise ratio of capacitive signal acquisition.

[0053] 2. Accurate temperature and humidity nonlinear compensation mechanism: A nonlinear humidity sensitivity function is used to model the exponential perturbation of humidity on the capacitance baseline. A temperature and humidity coupling factor is constructed in combination with the temperature drift term to achieve dynamic, nonlinear compensation for temperature and humidity perturbations, ensuring the comparability and stability of the original signal under different environments.

[0054] 3. Strong ability to construct multi-dimensional spatiotemporal features: The third-order curvature tensor is constructed using high-order derivative information in the two-dimensional space of the touch panel, and frequency domain stability indicators such as phase coherence entropy are integrated to form a more expressive spatiotemporal feature tensor, providing a solid feature foundation for the accurate recognition of complex touch behaviors.

[0055] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without inventive efforts. In the drawings:

[0057] Figure 1 This is a flow chart of the highly sensitive touch capacitor chip device of the present invention;

[0058] Figure 2This is a principle block diagram of the high-sensitivity touch capacitor chip system of the present invention. DETAILED DESCRIPTION

[0059] The following describes the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art will readily appreciate the other advantages and benefits of the present invention from the disclosure herein. The present invention may also be implemented or applied through various other specific embodiments, and the various details in this specification may be modified or altered based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are intended only to illustrate the present invention and are not intended to limit the scope of protection of the present invention.

[0060] It should be noted that the illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present invention. Therefore, the illustrations only show components related to the present invention and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0061] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the embodiments of the present invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring the embodiments of the present invention.

[0062] Example 1

[0063] A highly sensitive touch capacitor chip device, such as Figure 1 As shown, it includes: separating the touch signal and the environmental interference signal through mixed frequency 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 nonlinear compensation mechanism to generate an effective capacitance matrix;

[0064] Based on the effective capacitance matrix, the pure touch signal in the time domain is extracted through fractional-order time-frequency joint noise suppression and dynamic baseline tracking.

[0065] Through the pure touch signal in the time domain, the deformation curvature characteristics of the contact area are extracted and the spatiotemporal feature tensor is constructed;

[0066] Through adaptive convolution kernel generation and multimodal attention mechanism, the spatiotemporal feature tensor is used as input, the touch behavior classification probability distribution is used as output, and the final touch instruction is generated according to the category corresponding to the maximum value of the probability distribution.

[0067] The present invention is further configured such that generating the effective capacitance matrix comprises:

[0068] Through mixed frequency band excitation, dual-frequency time-division multiplexing driving mode is adopted, and rectangular window function is alternately activated. Specifically, the high-frequency carrier signal frequency is 10 MHz and the low-frequency carrier signal frequency is 1 MHz, which significantly improves the ability to distinguish between environmental interference and real touch.

[0069] During the signal acquisition phase, random phase offsets are injected into the high-frequency carrier signal to suppress electromagnetic standing wave interference, effectively suppressing standing wave interference and improving the stability and consistency of the high-frequency signal;

[0070] The high-frequency touch signal and the low-frequency environmental interference signal are separated by the frequency domain mask matrix to generate the original capacitance signal matrix. Specifically, the high and low frequency components are separated by synchronous demodulation, and the high frequency component is Capture touch micro-current changes and low-frequency components Establish an environmental baseline model and use fast Fourier transform to extract the frequency domain energy distribution: ,in, is the energy distribution in the frequency domain, 、 are the high and low frequency band mask matrices respectively, It is a fast Fourier transform function that accurately extracts the target frequency band and reduces the contamination of capacitance data by out-of-band noise;

[0071] Define a nonlinear humidity sensitivity function, model the exponential perturbation of humidity on the capacitance baseline, combine the temperature drift term, and construct the temperature-humidity coupling factor. Then, apply the temperature-humidity coupling factor to the original capacitance signal matrix to generate an effective capacitance matrix. Specifically, the formula for generating the effective capacitance matrix is: ,in, is the effective capacitance matrix, is the original capacitance signal matrix, is the temperature and humidity coupling factor, It is the temperature gradient sensitivity matrix obtained through calibration experiments. It can maintain the accuracy and stability of touch detection results under drastic environmental changes.

[0072] The present invention is further configured such that the construction of the temperature and humidity coupling factor includes:

[0073] Define the nonlinear humidity sensitivity function, the formula is: ,in, is a nonlinear humidity sensitivity function, For real-time humidity, The preset optimal humidity is is the humidity bandwidth;

[0074] Combined with the temperature drift term, the temperature and humidity coupling factor is constructed: ,in, is the temperature and humidity coupling factor, is the reference temperature, is the real-time temperature, is the temperature saturation range, To compensate for the residual constant term, it compensates for the residual error after nonlinear compensation;

[0075] Nonlinear modeling of humidity effects can more accurately reflect the amplified interference characteristics of the capacitance baseline when humidity is far from the optimal value. The temperature saturation modeling mechanism is introduced by The touch capacitance measurement function more realistically simulates the drift curve of capacitance, which first changes dramatically and then stabilizes as temperature rises, avoiding over-correction. Dynamic coupling of temperature and humidity factors effectively reduces the interference of environmental fluctuations on touch capacitance measurement, improving detection sensitivity and stability.

[0076] The present invention is further configured such that the step of extracting a time-domain pure touch signal includes:

[0077] Based on the effective capacitance matrix, fractional derivatives are used to separate noise and extract high-frequency transient noise components.

[0078] Combined with Hilbert transform, the time-varying noise weight function is defined. Specifically, it is defined based on Caputo fractional derivative. ,in, For function of fractional derivatives, , The gamma function is The value of , For the current moment, For function The first integer derivative of , ,in, is the noise-sensitive area mask matrix, is the effective capacitance matrix; the time-varying noise weight function ,in, is a sliding time window that matches the power frequency noise period, is the complex exponential frequency domain modulation factor, For a specific frequency point, is the imaginary unit, is the principal value integral, is the weighted coefficient of the steady-state suppression term. The fractional-order derivative can be used to extract complex, non-stationary high-frequency disturbance information, which is more suitable for processing capacitance mutation characteristics than traditional integer-order differentials.

[0079] The global energy of the effective capacitance matrix is integrated with the reference baseline to define the baseline error. Based on the baseline error, a fractional-order differential equation is designed to estimate the baseline drift and calculate the baseline drift estimate. Specifically, the baseline error formula is: , ,in, is the baseline error, is the Frobenius norm, As a dynamic reference benchmark, it is calculated by sliding average of historical data. The time window length for baseline calculation uses fractional order modeling of baseline error to avoid false triggering caused by baseline drift due to environmental changes;

[0080] The time domain pure touch signal is extracted through adaptive filtering and baseline drift estimation. Specifically, a frequency domain transfer function is constructed to dynamically suppress noise energy: , ,in, is the frequency domain transfer function, is the time-varying noise weight function, is an adaptive step size that balances noise suppression and signal distortion. and are the signal and noise powers, respectively, estimated by power spectral density;

[0081] The formula for pure touch signal in the time domain is: ,in, is an estimate of the baseline drift.

[0082] The present invention is further configured such that the calculation of the baseline drift estimate includes:

[0083] The effective capacitance matrix is separated into baseline component and touch component through variational mode decomposition;

[0084] Use fractional-order PID control algorithm to adjust the proportional coefficient, integral coefficient and differential coefficient;

[0085] The proportional coefficient, integral coefficient, and differential coefficient meet the constraints, and the algebraic sum of the square of the proportional coefficient, the reciprocal square root of the integral coefficient, and the gamma function correction value of the differential coefficient does not exceed the preset threshold;

[0086] 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: ,in, is the proportionality coefficient, is the integration coefficient, Differential coefficient, For fractional integration, the coefficient constraints are: , to avoid overshoot and oscillation.

[0087] The present invention is further configured such that the step of constructing the spatiotemporal feature tensor comprises:

[0088] According to the time domain pure touch signal, in the two-dimensional space domain of the touch panel Calculate the high-order partial derivatives of the signal and construct a high-order spatial gradient field. Specifically, the high-order partial derivatives of the signal are , , , , ,in, It is a pure touch signal in the time domain;

[0089] Define the third-order curvature tensor, integrate the first-order and second-order derivative information, and the third-order curvature tensor , through the mixed operations of outer product, direct sum and Hadamard product, a third-order curvature tensor containing spatial gradient direction, Hessian matrix structure and time-varying characteristics is generated;

[0090] The normalized Hermite orthogonal polynomial basis function is used to project the third-order curvature tensor for dimensionality reduction: ,in, is the curvature tensor after dimensionality reduction, is a polynomial basis function, 、 、 Corresponding to the polynomial order, 、 Represents the coordinate index of a discrete point in two-dimensional space;

[0091] Based on the pure touch signal in the time domain, the phase coherence entropy is calculated, the curvature tensor is fused, and the spatiotemporal feature tensor is constructed. Specifically, the curvature invariant and the phase feature are spliced into a high-order tensor, and the fused high-dimensional tensor is linearly reduced in dimension: ,in, is the concatenated high-order tensor, is the principal component analysis transformation matrix, is the transpose of the principal component analysis transformation matrix, is the spatiotemporal feature tensor.

[0092] The present invention is further configured such that the calculation of the phase coherence entropy includes:

[0093] Perform short-time fractional Fourier transform on the time-domain pure touch signal to obtain the time-frequency domain phase distribution;

[0094] A global reference phase is generated based on phase vector averaging, and the coherence measure between the local phase of each frequency band and the reference phase is calculated. The formula is: ,in, is the local phase coherence measure, For the The instantaneous phase of the frequency band, For the The instantaneous phase of the frequency band, is the global reference phase, obtained by phase vector averaging, is the total number of frequency bands, is the inner product on the complex plane, which is equivalent to calculating and Phase difference projection, It represents the sum of the synchronization strength of all frequency band phases with the reference phase;

[0095] The phase coherence entropy value is calculated based on the probability distribution of the coherence metric. The entropy value represents the phase stability of the touch signal. Specifically, ,in, is the phase coherence entropy. The lower the value, the stronger the phase synchronization, which represents the touch stability.

[0096] The present invention is further configured such that the generation and constraint of the adaptive convolution kernel includes:

[0097] The spatiotemporal feature tensor is converted into convolution kernel basis vectors through latent space parameter mapping;

[0098] Apply spectral normalization constraints to the dynamically generated convolution kernel to generate adaptive convolution kernel ;

[0099] The power iteration method is used to calculate the maximum singular value of the convolution kernel weight in real time to ensure that the spectral norm constraint condition holds.

[0100] The present invention is further configured such that the multimodal attention mechanism and classification decision include:

[0101] Construct a dual-modal collaborative processing structure of spatial attention head and temporal attention head;

[0102] The bimodal attention features are fused through the gating weight coefficient, and the gating weight is dynamically generated by the Sigmoid function;

[0103] Output multi-task probabilities through fully connected layers and Softmax activation;

[0104] The category corresponding to the maximum probability is selected as the final instruction, and a probability threshold is set. When the maximum probability is lower than the threshold, an invalid touch judgment is triggered. 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;

[0105] Gating weight generation: ,in, is the spatial attention matrix, is the temporal attention vector, is the learnable weight matrix, For the Sigmoid activation function, attention is enhanced feature output: ;

[0106] Output multi-task probability through the fully connected layer and Softmax activation: , ,in, To enhance the feature of attention, is the activation function, is the classification weight matrix, is the classification bias vector, providing a learnable threshold offset for each category, is the total number of target categories for the classification task;

[0107] Select the category corresponding to the maximum probability as the final instruction: , Set the probability threshold for the final instruction ,like , then trigger invalid touch judgment.

[0108] Example 2

[0109] See also Figure 2 , the exemplary high-sensitivity touch capacitor chip system includes:

[0110] Capacitive signal acquisition and compensation module: This module uses mixed frequency band excitation to separate touch signals from environmental interference signals, acquires the original capacitance signal matrix, and uses a nonlinear compensation mechanism to perform environmental compensation on the original capacitance signal based on the temperature and humidity coupling factor to generate an effective capacitance matrix.

[0111] Time-domain pure touch signal extraction module: Based on the effective capacitance matrix, it extracts time-domain pure touch signals through fractional-order time-frequency joint noise suppression and dynamic baseline tracking;

[0112] Feature extraction and construction module: Extracts the deformation curvature features of the contact area through pure touch signals in the time domain and constructs a spatiotemporal feature tensor;

[0113] Generate instruction module: Through adaptive convolution kernel generation and multimodal attention mechanism, it takes the spatiotemporal feature tensor as input and the touch behavior classification probability distribution as output, and generates the final touch instruction according to the category corresponding to the maximum value of the probability distribution.

[0114] It should be noted that the highly sensitive touch capacitor chip system provided in the above embodiment and the highly sensitive touch capacitor chip device provided in the above embodiment share the same concept. The specific manner in which each module and unit performs operations has been described in detail in the method embodiments and will not be repeated here. In actual applications, the highly sensitive touch capacitor chip system provided in the above embodiment can, as needed, allocate the above functions to different functional modules, i.e., divide the internal structure of the system into different functional modules to complete all or part of the functions described above. This is not a limitation herein.

[0115] 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 program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0116] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0117] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0118] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0119] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] Those skilled in the art will 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 aforementioned method embodiments and will not be repeated here.

[0121] In the several embodiments provided in this application, it should be understood that the disclosed system can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0122] The units described as separate components may or may not be physically separate, and the components shown 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0123] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0124] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling 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 method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0125] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A highly sensitive touch capacitor chip device, characterized in that: include: Through mixed frequency band excitation, the touch signal and environmental interference signal are separated, the original capacitance signal matrix is collected, and the nonlinear compensation mechanism is used to 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, the pure touch signal in the time domain is extracted through fractional-order time-frequency joint noise suppression and dynamic baseline tracking. Through the pure touch signal in the time domain, the deformation curvature characteristics of the contact area are extracted and the spatiotemporal feature tensor is constructed; Through adaptive convolution kernel generation and multimodal attention mechanism, the spatiotemporal feature tensor is used as input, the touch behavior classification probability distribution is used as output, and the final touch instruction is generated according to the category corresponding to the maximum value of the probability distribution.

2. The high-sensitivity touch capacitor chip device according to claim 1, characterized in that: Through mixed frequency band excitation, dual-frequency time division multiplexing driving mode is adopted, and rectangular window function is alternately activated; During the signal acquisition phase, random phase offsets are injected into the high-frequency carrier signal to suppress electromagnetic standing wave interference; The high-frequency touch signal and the low-frequency environmental interference signal are separated by a frequency domain mask matrix to generate the original capacitance signal matrix; A nonlinear humidity sensitivity function is defined to model the exponential perturbation of humidity on the capacitance baseline. The temperature drift term is combined to construct a temperature-humidity coupling factor. The effective capacitance matrix is generated by applying the temperature-humidity coupling factor to the original capacitance signal matrix.

3. The high-sensitivity touch capacitor chip device according to claim 2, characterized in that: The construction of temperature and humidity coupling factors includes: Define the nonlinear humidity sensitivity function, the formula is: ,in, is a nonlinear humidity sensitivity function, For real-time humidity, The preset optimal humidity is is the humidity bandwidth; Combined with the temperature drift term, the temperature and humidity coupling factor is constructed: ,in, is the temperature and humidity coupling factor, is the reference temperature, is the real-time temperature, is the temperature saturation range, To compensate for the residual constant term, it compensates for the residual error after nonlinear compensation.

4. The high-sensitivity touch capacitor chip device according to claim 2, characterized in that: Extracting pure touch signals in the time domain includes: Based on the effective capacitance matrix, fractional derivatives are used to separate noise and extract high-frequency transient noise components. Combined with Hilbert transform, a time-varying noise weight function is defined. The global energy of the effective capacitance matrix is integrated with the reference baseline to define the baseline error. Based on the baseline error, a fractional-order differential equation is designed to estimate the baseline drift and calculate the baseline drift estimate. The time domain pure touch signal is extracted through adaptive filtering and baseline drift estimation.

5. The high-sensitivity touch capacitor chip device according to claim 4, characterized in that: The calculation of the baseline drift estimate includes: The effective capacitance matrix is separated into baseline component and touch component through variational mode decomposition; Use fractional-order PID control algorithm to adjust the proportional coefficient, integral coefficient and differential coefficient; The proportional coefficient, integral coefficient, and differential coefficient meet the constraints, and the algebraic sum of the square of the proportional coefficient, the reciprocal square root of the integral coefficient, and the gamma function correction value of the differential coefficient does not exceed the preset threshold; The baseline drift estimation value is obtained based on the proportional coefficient, integral coefficient, differential coefficient, fractional order integral, and baseline error calculation.

6. The high-sensitivity touch capacitor chip device according to claim 4, characterized in that: The steps to construct the spatiotemporal feature tensor include: Based on the pure touch signal in the time domain, 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 the third-order curvature tensor and integrate the first-order and second-order derivative information; Normalized Hermite orthogonal polynomial basis functions are used to project the third-order curvature tensor for dimensionality reduction. Based on the pure touch signal in the time domain, the phase coherence entropy is calculated, the curvature tensor is fused, and the spatiotemporal feature tensor is constructed.

7. The high-sensitivity touch capacitor chip device according to claim 6, characterized in that: The calculation of phase coherence entropy includes: Perform 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 phase vector averaging, and calculate the coherence measure between the local phase of each frequency band and the reference phase; The phase coherence entropy value is calculated according to the probability distribution of the coherence measurement, and the magnitude of the entropy value represents the phase stability of the touch signal.

8. The high-sensitivity touch capacitor chip device according to claim 6, characterized in that: The generation and constraints of adaptive convolution kernels include: The spatiotemporal feature tensor is converted into convolution kernel basis vectors through latent space parameter mapping; Apply spectral normalization constraints to dynamically generated convolution kernels; The power iteration method is used 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 capacitor chip device according to claim 1, characterized in that: Multimodal attention mechanism and classification decision include: Construct a dual-modal collaborative processing structure of spatial attention head and temporal attention head; The bimodal attention features are fused through the gating weight coefficient, and the gating weight is dynamically generated by the Sigmoid function; Output multi-task probabilities through fully connected layers and Softmax activation; Select the category corresponding to the maximum probability as the final instruction, set the probability threshold, and trigger invalid touch judgment when the maximum probability is lower than the threshold.

10. A high-sensitivity touch capacitor chip system, used to implement the high-sensitivity touch capacitor chip device according to any one of claims 1 to 9, characterized in that: include: Capacitive signal acquisition and compensation module: This module uses mixed frequency band excitation to separate touch signals from environmental interference signals, acquires the original capacitance signal matrix, and uses a nonlinear compensation mechanism to perform environmental compensation on the original capacitance signal matrix based on 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, it extracts time-domain pure touch signals through fractional-order time-frequency joint noise suppression and dynamic baseline tracking; Feature extraction and construction module: Extracts the deformation curvature features of the contact area through pure touch signals in the time domain and constructs a spatiotemporal feature tensor; Generate instruction module: Through adaptive convolution kernel generation and multimodal attention mechanism, it takes the spatiotemporal feature tensor as input and the touch behavior classification probability distribution as output, and generates the final touch instruction according to the category corresponding to the maximum value of the probability distribution.

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