A touch signal extraction method and device, electronic equipment and storage medium

Abstract

This application discloses a method, apparatus, electronic device, and storage medium for extracting touch signals. The method includes: during a non-touch scanning cycle, acquiring common-mode electromagnetic noise characteristic waveforms in the environment in real time using a acquisition component disposed around the touch electrode, and establishing a noise feature library; inverting the common-mode electromagnetic noise characteristic waveforms and incorporating them into the main touch signal channel for differential compensation processing with the initial touch signal acquired in the main touch signal channel to obtain an intermediate touch signal; inputting the intermediate touch signal into a preset multi-level digital filter for multi-level filtering processing to obtain a target touch signal; adjusting a preset touch trigger threshold according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, and judging the validity of the target touch signal based on the touch trigger threshold, and outputting a target touch signal that is judged as valid. This application can improve the stability and accuracy of touch signal extraction.

Description

Technical Field

[0001] This application relates to the field of signal processing technology, and in particular to a method, apparatus, electronic device and storage medium for extracting touch signals. Background Technology

[0002] Touch technology, as a convenient human-computer interaction method, has been widely used in various electronic devices, especially in special control platforms such as ships and aircraft. The stable and accurate extraction of touch signals is directly related to the reliability and safety of equipment operation. In existing technologies, touch signal extraction mainly involves processing the signals collected by the touch electrodes to obtain effective touch signals that can be used for equipment control, thus meeting the basic requirements of human-computer interaction.

[0003] In applications such as ships and aviation, strong electromagnetic interference exists in the environment. This interference can adversely affect the touch signals collected by the touch electrodes, leading to problems such as signal distortion and recognition errors during the touch signal extraction process. It is impossible to accurately distinguish between valid touch signals and interference signals, which in turn affects the normal operation of the touch system and makes it difficult to meet the high reliability requirements for touch signal extraction in special scenarios. Summary of the Invention

[0004] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a method, apparatus, electronic device, and storage medium for extracting touch signals, which can improve the stability and accuracy of touch signal extraction.

[0005] Firstly, this application provides a method for extracting touch signals, comprising: During the non-touch scanning cycle, the common-mode electromagnetic noise characteristic waveform in the environment is collected in real time by the acquisition component set on the periphery of the touch electrode, and a noise characteristic library is established. The common-mode electromagnetic noise characteristic waveform is extracted from the noise feature library, and the common-mode electromagnetic noise characteristic waveform is inverted and then incorporated into the touch main signal channel to perform differential compensation processing with the initial touch signal collected in the touch main signal channel to obtain the intermediate touch signal; The intermediate touch signal is input into a preset multi-level digital filter for multi-level filtering to obtain the target touch signal; Based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, the preset touch trigger threshold is adjusted, and the validity of the target touch signal is judged based on the touch trigger threshold. The target touch signal with a valid judgment result is output.

[0006] The touch signal extraction method according to the first aspect of this application has at least the following beneficial effects: First, during a non-touch scanning cycle, a common-mode electromagnetic noise characteristic waveform in the environment is acquired in real time by a collection component disposed on the periphery of the touch electrode, and a noise feature library is established. Then, the common-mode electromagnetic noise characteristic waveform is extracted from the noise feature library, inverted, and incorporated into the touch main signal channel. Differential compensation processing is performed between this waveform and the initial touch signal acquired in the touch main signal channel to obtain an intermediate touch signal. Next, the intermediate touch signal is input into a preset multi-level digital filter for multi-level filtering to obtain the target touch signal. Finally, a preset touch trigger threshold is adjusted based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, and the validity of the target touch signal is determined based on this touch trigger threshold. A target touch signal that is deemed valid is output. This method effectively solves the problems of touch signal distortion and recognition errors caused by strong electromagnetic interference by acquiring common-mode electromagnetic noise, anti-phase differential compensation, multi-level filtering, and dynamic adjustment of touch trigger threshold. It can accurately distinguish between valid touch signals and interference signals, improve the stability and accuracy of touch signal extraction, and meet the high reliability requirements of touch signal extraction in relevant application scenarios.

[0007] According to some embodiments of the first aspect of this application, the step of acquiring common-mode electromagnetic noise characteristic waveforms in the environment in real time through a acquisition component disposed on the periphery of the touch electrode during a non-touch scanning cycle, and establishing a noise characteristic library, includes: When the touch electrode is in a non-collection state, the non-touch scanning cycle begins; During non-touch scanning cycles, the induction coil located on the outer periphery of the touch electrode is activated; The common-mode electromagnetic noise signal in the environment is collected in real time by the induction coil; The common-mode electromagnetic noise signal is amplified and shaped, and the frequency characteristics, amplitude characteristics, and phase characteristics of the common-mode electromagnetic noise signal are extracted to form the common-mode electromagnetic noise characteristic waveform. A noise feature library is established, and the noise feature library is updated based on the common-mode electromagnetic noise feature waveform.

[0008] According to some embodiments of the first aspect of this application, updating the noise feature library based on the common-mode electromagnetic noise characteristic waveform includes: According to the preset update cycle, the common-mode electromagnetic noise signal in the environment is re-acquired and converted to obtain the common-mode electromagnetic noise characteristic waveform; The newly acquired common-mode electromagnetic noise feature waveforms are compared point by point with the common-mode electromagnetic noise feature waveforms stored in the noise feature library, and the feature similarity corresponding to each common-mode electromagnetic noise feature waveform in the noise feature library is obtained. When the feature similarity is greater than or equal to a preset similarity threshold, the newly acquired common-mode electromagnetic noise feature waveform replaces the corresponding common-mode electromagnetic noise feature waveform in the noise feature library, and the current storage duration of the replaced common-mode electromagnetic noise feature waveform is reset. When the feature similarity is less than the similarity threshold, the newly acquired common-mode electromagnetic noise feature waveform is added to the noise feature library, and the current storage duration of the newly added common-mode electromagnetic noise feature waveform is recorded. When the current storage duration reaches the preset effective storage duration, the corresponding common-mode electromagnetic noise feature waveform is deleted from the noise feature library.

[0009] According to some embodiments of the first aspect of this application, the step of extracting the common-mode electromagnetic noise feature waveform from the noise feature library, inverting the common-mode electromagnetic noise feature waveform, and incorporating it into the touch main signal channel for differential compensation processing with the initial touch signal acquired in the touch main signal channel to obtain an intermediate touch signal includes: The phase difference between the current common-mode electromagnetic noise characteristic waveform and the interference component in the initial touch signal is calculated in real time. After inverting the common-mode electromagnetic noise characteristic waveform, and performing dynamic phase fine-tuning based on the phase difference, a noise inversion compensation signal is obtained. The noise inversion compensation signal is incorporated into the touch main signal channel in the analog domain to perform analog domain differential compensation processing with the initial touch signal collected in the touch main signal channel, so as to achieve preliminary hardware-level common-mode noise suppression and obtain the intermediate touch signal.

[0010] According to some embodiments of the first aspect of this application, the multi-stage digital filter includes a band-stop filter and an adaptive Kalman filter; The step of inputting the intermediate touch signal into a preset multi-level digital filter for multi-level filtering processing to obtain the target touch signal includes: Based on the noise feature library, a high-frequency noise band is determined, and the cutoff frequency of the band-stop filter is set based on the high-frequency noise band. The intermediate touch signal is input into the band-stop filter to remove high-frequency noise from the intermediate touch signal, thereby obtaining the secondary touch signal; A set of historical touch signals is acquired, and the legal range of the touch signal at the current moment is predicted using a preset Kalman filter prediction equation; wherein, the legal range includes a reasonable range of the amplitude and rate of change of the touch signal at the current moment; The secondary touch signal is compared with the legal range, the filtering parameters of the adaptive Kalman filter are dynamically adjusted, and the secondary touch signal is input into the adaptive Kalman filter to remove residual low-frequency noise from the secondary touch signal, thereby obtaining the target touch signal.

[0011] According to some embodiments of the first aspect of this application, adjusting a preset touch trigger threshold based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, determining the validity of the target touch signal based on the touch trigger threshold, and outputting a target touch signal that is determined to be valid includes: The preset touch trigger threshold is adjusted based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform; wherein the adjustment ratio of the touch trigger threshold is positively correlated with the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform. When the target touch signal exceeds the touch trigger threshold, the determination result of the target touch signal is valid and is output; If the target touch signal does not reach the touch trigger threshold, the judgment result of the target touch signal is invalid and it is not output.

[0012] According to some embodiments of the first aspect of this application, after the step of outputting a target touch signal whose determination result is valid, the method further includes: Based on the feedback information of the target touch signal and in combination with the preset real touch legal features, the false touch rate and missed touch rate of the touch signal extraction are determined. Based on the false touch rate and the missed touch rate, the filtering parameters of the multi-level filtering process and the adjustment ratio parameters of the touch trigger threshold are adjusted.

[0013] Secondly, this application also provides a touch signal extraction device, comprising: The monitoring unit is used to collect the common-mode electromagnetic noise characteristic waveforms in the environment in real time through the acquisition components set on the periphery of the touch electrode during non-touch scanning cycles, and to establish a noise characteristic library. The compensation unit is used to extract the common-mode electromagnetic noise characteristic waveform from the noise feature library, and invert the common-mode electromagnetic noise characteristic waveform and incorporate it into the touch main signal channel to perform differential compensation processing with the initial touch signal collected in the touch main signal channel to obtain the intermediate touch signal; The filtering unit is used to input the intermediate touch signal into a preset multi-level digital filter for multi-level filtering processing to obtain the target touch signal; The self-determination unit is used to adjust the preset touch trigger threshold according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, and to determine the validity of the target touch signal based on the touch trigger threshold, and output the target touch signal that is determined to be valid.

[0014] Thirdly, this application also provides an electronic device, including: At least one memory; At least one processor; At least one program; The program is stored in the memory, and the processor executes at least one of the programs to implement the method for extracting touch signals as described in any embodiment of the first aspect.

[0015] Fourthly, this application also provides a computer-readable storage medium storing a computer-executable program for performing the touch signal extraction method as described in any embodiment of the first aspect.

[0016] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0017] Additional aspects and advantages of this application will become apparent and readily understood in conjunction with the following description of the embodiments, in which: Figure 1 A flowchart of the touch signal extraction method provided in this application; Figure 2 A schematic diagram of the touch signal extraction device provided in this application. Detailed Implementation

[0018] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0019] In the description of this application, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0020] In the description of this application, the use of "first" and "second" is for the purpose of distinguishing technical features only, and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or the order of the technical features indicated.

[0021] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0022] Touch technology, as a convenient human-computer interaction method, has been widely used in various electronic devices, especially in special control platforms such as ships and aircraft. The stable and accurate extraction of touch signals is directly related to the reliability and safety of equipment operation. In existing technologies, touch signal extraction mainly involves processing the signals collected by the touch electrodes to obtain effective touch signals that can be used for equipment control, thus meeting the basic requirements of human-computer interaction.

[0023] In applications such as ships and aviation, strong electromagnetic interference exists in the environment. This interference can adversely affect the touch signals collected by the touch electrodes, leading to problems such as signal distortion and recognition errors during the touch signal extraction process. It is impossible to accurately distinguish between valid touch signals and interference signals, which in turn affects the normal operation of the touch system and makes it difficult to meet the high reliability requirements for touch signal extraction in special scenarios.

[0024] Based on this, this application provides a method, apparatus, electronic device and storage medium for extracting touch signals to solve the above-mentioned technical problems. The technical solutions provided by this application will be described in detail below.

[0025] Touch technology, as a convenient human-computer interaction method, has been widely used in various electronic devices, especially in special control platforms such as ships and aircraft. The stable and accurate extraction of touch signals is directly related to the reliability and safety of equipment operation. In existing technologies, touch signal extraction mainly involves processing the signals collected by the touch electrodes to obtain effective touch signals that can be used for equipment control, thus meeting the basic requirements of human-computer interaction.

[0026] In applications such as ships and aviation, strong electromagnetic interference exists in the environment. This interference can adversely affect the touch signals collected by the touch electrodes, leading to problems such as signal distortion and recognition errors during the touch signal extraction process. It is impossible to accurately distinguish between valid touch signals and interference signals, which in turn affects the normal operation of the touch system and makes it difficult to meet the high reliability requirements for touch signal extraction in special scenarios.

[0027] In a first aspect, this application provides a method for extracting touch signals, including but not limited to the following steps: Step S110: During the non-touch scanning cycle, the common-mode electromagnetic noise characteristic waveform in the environment is collected in real time by the acquisition component set on the periphery of the touch electrode, and a noise characteristic library is established.

[0028] Step S120: Extract the common-mode electromagnetic noise feature waveform from the noise feature library, and invert the common-mode electromagnetic noise feature waveform before incorporating it into the touch main signal channel to perform differential compensation processing with the initial touch signal collected in the touch main signal channel to obtain the intermediate touch signal.

[0029] Step S130: Input the intermediate touch signal into a preset multi-level digital filter for multi-level filtering processing to obtain the target touch signal.

[0030] Step S140: Adjust the preset touch trigger threshold according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, and judge the validity of the target touch signal based on the touch trigger threshold, and output the target touch signal that is judged to be valid.

[0031] In steps S110 to S140, firstly, during the non-touch scanning cycle, the common-mode electromagnetic noise characteristic waveform in the environment is acquired in real time by a data acquisition component located on the periphery of the touch electrode, and a noise feature library is established. Next, the common-mode electromagnetic noise characteristic waveform is extracted from this noise feature library, inverted, and then incorporated into the touch main signal channel. Differential compensation processing is performed between this waveform and the initial touch signal acquired in the touch main signal channel to obtain an intermediate touch signal. Then, the intermediate touch signal is input into a preset multi-level digital filter for multi-level filtering to obtain the target touch signal. Finally, based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, a preset touch trigger threshold is adjusted, and the validity of the target touch signal is determined based on this threshold. The target touch signal that is deemed valid is output. This method effectively solves the problems of touch signal distortion and recognition errors caused by strong electromagnetic interference by acquiring common-mode electromagnetic noise, anti-phase differential compensation, multi-level filtering, and dynamic adjustment of touch trigger threshold. It can accurately distinguish between valid touch signals and interference signals, improve the stability and accuracy of touch signal extraction, and meet the high reliability requirements of touch signal extraction in relevant application scenarios.

[0032] It should be noted that the touch trigger threshold is used as a criterion for determining whether a target touch signal is a valid touch signal. Its value can be adaptively adjusted according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform. By using this threshold to determine the validity of the target touch signal, it is possible to accurately distinguish between valid touch signals and residual interference signals, avoid the impact of electromagnetic interference on signal recognition, and ensure that the final output touch signal is accurate and reliable.

[0033] It is understood that step S110 may include, but is not limited to, the following steps: Step S210: When the touch electrode is in a non-collection state, enter the non-touch scanning cycle.

[0034] Step S220: During a non-touch scanning cycle, activate the induction coil located on the outer periphery of the touch electrode.

[0035] Step S230: Collect common-mode electromagnetic noise signals in the environment in real time using an induction coil.

[0036] Step S240: Amplify and shape the common-mode electromagnetic noise signal, and extract the frequency characteristics, amplitude characteristics and phase characteristics of the common-mode electromagnetic noise signal to form a common-mode electromagnetic noise characteristic waveform.

[0037] Step S250: Establish a noise feature library and update the noise feature library based on the common-mode electromagnetic noise feature waveform.

[0038] In steps S210 to S250, a non-touch scanning cycle is entered when the touch electrode is in a non-collection state. A common-mode electromagnetic noise signal from the environment is collected using an induction coil located around the touch electrode. This effectively avoids interference from the normal signal acquisition of the touch electrode, ensuring the accuracy and purity of the collected common-mode electromagnetic noise signal. After the common-mode electromagnetic noise signal is collected, it is amplified, shaped, and the corresponding frequency, amplitude, and phase features are extracted to form a common-mode electromagnetic noise feature waveform. Simultaneously, the noise feature library is updated in real-time based on this feature waveform. This ensures that the noise feature library always matches the actual noise state of the current environment, providing a precise and reliable noise data foundation for subsequent differential compensation processing, thereby improving the stability and accuracy of the entire touch signal extraction process.

[0039] It is understood that step S250 may include, but is not limited to, the following steps: Step S310: According to the preset update cycle, re-acquire the common-mode electromagnetic noise signal in the environment and convert it to obtain the common-mode electromagnetic noise characteristic waveform.

[0040] Step S320: Compare the newly acquired common-mode electromagnetic noise feature waveform with the common-mode electromagnetic noise feature waveforms stored in the noise feature library point by point, and obtain the feature similarity corresponding to each common-mode electromagnetic noise feature waveform in the noise feature library.

[0041] Step S330: When the feature similarity is greater than or equal to the preset similarity threshold, replace the corresponding common-mode electromagnetic noise feature waveform in the noise feature library with the newly acquired common-mode electromagnetic noise feature waveform, and reset the current storage duration of the replaced common-mode electromagnetic noise feature waveform. Step S340: When the feature similarity is less than the similarity threshold, add the newly acquired common-mode electromagnetic noise feature waveform to the noise feature library and record the current storage duration of the newly added common-mode electromagnetic noise feature waveform.

[0042] Step S350: When the current storage duration reaches the preset effective storage duration, delete the corresponding common-mode electromagnetic noise feature waveform from the noise feature library.

[0043] In steps S310 to S340, common-mode electromagnetic noise signals in the environment are re-acquired according to a preset update cycle, and the corresponding common-mode electromagnetic noise characteristic waveforms are obtained. The newly acquired waveforms are compared point-by-point with the waveforms stored in the noise feature library to obtain feature similarity. If a feature similarity greater than or equal to the similarity threshold is found, the new common-mode electromagnetic noise characteristic waveform is replaced, ensuring that the common-mode electromagnetic noise characteristic waveforms in the noise feature library always maintain a high degree of matching with the real-time environmental noise, thus ensuring the timeliness and accuracy of the noise data. After completing the similar waveform replacement, the current storage duration of the corresponding common-mode electromagnetic noise characteristic waveform is reset, which allows the latest replaced valid waveform to obtain a complete valid storage period, preventing it from being prematurely deleted due to storage duration calculation issues, and ensuring the stable retention of valid noise characteristic waveforms. When adding a new common-mode electromagnetic noise characteristic waveform, the current storage duration is recorded simultaneously, which provides an accurate basis for subsequent expiration deletion operations based on the preset valid storage duration, realizing the orderly management of the noise feature library. In addition, by accumulating the current storage duration, data redundancy and invalid data accumulation are avoided. The above steps can continuously provide accurate and reliable noise data support for subsequent differential compensation processing, further improving the stability and accuracy of touch signal extraction.

[0044] It should be noted that the update cycle is a pre-set time interval parameter used by the system to periodically perform noise re-acquisition and waveform update operations on the noise feature library.

[0045] It should be noted that the similarity threshold is a pre-set criterion used to determine whether newly acquired common-mode electromagnetic noise feature waveforms belong to the same type of environmental noise as existing waveforms in the noise feature library. Its function is to distinguish whether the waveform acquired this time is an update of existing similar noise in the library or belongs to a new type of noise appearing in the environment. This allows for the appropriate selection of waveform replacement or addition operations in the noise feature library, ensuring the accuracy and relevance of the noise feature library updates. The effective storage duration is a parameter used to define the effective retention period of common-mode electromagnetic noise feature waveforms in the noise feature library. Its function is to determine whether a waveform has expired, enabling the system to promptly clean up old waveforms that have exceeded their effective usage period, avoiding the accumulation of invalid data and storage redundancy in the noise feature library, and ensuring that the library always retains valid and usable noise feature waveforms for the current environment.

[0046] It is understood that step S120 may include, but is not limited to, the following steps: Step S410: Calculate the phase difference between the current common-mode electromagnetic noise characteristic waveform and the interference component in the initial touch signal in real time.

[0047] Step S420: After inverting the common-mode electromagnetic noise characteristic waveform, the phase is dynamically fine-tuned according to the phase difference to obtain the noise inversion compensation signal.

[0048] Step S430: Incorporate the noise inversion compensation signal into the touch main signal channel in the analog domain to perform analog domain differential compensation processing with the initial touch signal collected in the touch main signal channel, so as to achieve preliminary hardware-level common-mode noise suppression and obtain the intermediate touch signal.

[0049] In steps S410 to S430, by calculating the phase difference between the current common-mode electromagnetic noise characteristic waveform and the interference component in the initial touch signal in real time, and performing dynamic phase fine-tuning on the inverted waveform, a noise inversion compensation signal that precisely matches the interference component can be generated. This signal is then differentially compensated with the initial touch signal to achieve preliminary hardware-level common-mode noise suppression. This hardware-level front-end compensation can quickly and efficiently suppress most common-mode electromagnetic interference, reducing interference impact from the signal acquisition source. This setting effectively eliminates the problem of insufficient interference cancellation caused by phase deviation, making the cancellation of common-mode electromagnetic noise more thorough and improving the accuracy and reliability of differential compensation processing. The intermediate touch signal after precise compensation has higher purity, effectively reducing the processing pressure of subsequent filtering stages, while avoiding the adverse effects of residual interference on signal recognition, thus improving the overall stability and accuracy of the touch signal extraction process.

[0050] It should be noted that the interference component in the initial touch signal is extracted and identified by feature matching with an established noise feature library. Since common-mode electromagnetic noise in the environment has fixed frequency, amplitude, and phase characteristics, the system can use the common-mode electromagnetic noise feature waveform in the noise feature library as a reference to match the signal component with consistent characteristics from the initial touch signal that is a mixture of real signal and interference. This component is the interference component. This process only completes the location and identification of the interference component.

[0051] It is understood that the multi-stage digital filter includes band-stop filters and adaptive Kalman filters, and step S130 may include, but is not limited to, the following steps: Step S510: Determine the high-frequency noise band based on the noise feature library, and set the cutoff frequency of the band-stop filter based on the high-frequency noise band.

[0052] Step S520: Input the intermediate touch signal into a band-stop filter to remove high-frequency noise from the intermediate touch signal and obtain the secondary touch signal.

[0053] Step S530: Obtain the set of historical touch signals, and predict the legal range of the touch signal at the current moment through the preset Kalman filter prediction equation; wherein, the legal range includes the reasonable range of the amplitude and rate of change of the touch signal at the current moment.

[0054] Step S540: Compare the secondary touch signal with the legal range, dynamically adjust the filtering parameters of the adaptive Kalman filter, and input the secondary touch signal into the adaptive Kalman filter to remove residual low-frequency noise from the secondary touch signal and obtain the target touch signal.

[0055] In steps S510 to S540, the high-frequency noise band is determined through a noise feature library, and the cutoff frequency of the band-stop filter is set. High-frequency noise is removed from the intermediate touch signal to obtain the secondary touch signal. Then, the legal range of the current touch signal is predicted by combining this with a set of historical touch signals. The filtering parameters of the adaptive Kalman filter are dynamically adjusted to remove residual mid-to-low-frequency noise from the secondary touch signal to obtain the target touch signal. Two-stage filtering is used because the intermediate touch signal still contains two types of interference with different characteristics: high-frequency and mid-to-low-frequency. A single filter cannot accurately remove both types of interference. Two-stage layered processing achieves a more comprehensive de-scratching effect. The band-stop filter mainly targets the high-frequency noise band determined by the noise feature library, accurately removing high-frequency noise from the intermediate touch signal and quickly reducing the impact of high-frequency interference on the signal, thus reducing the burden on subsequent processing. The adaptive Kalman filter predicts the legal range of the current touch signal and dynamically adjusts the filtering parameters, focusing on removing residual mid-to-low-frequency noise from the secondary touch signal. It can also effectively distinguish between residual interference and the real touch signal, avoiding accidental deletion of valid signals and damage to signal integrity. When used together, these two technologies achieve comprehensive, layered interference removal from high frequency to mid-low frequency. This ensures efficient removal of high-frequency interference while accurately filtering residual mid-low frequency interference, significantly improving the purity of the target touch signal. This provides a high-quality signal foundation for subsequent validity assessment based on touch trigger thresholds, further guaranteeing the accuracy and stability of the entire touch signal extraction process.

[0056] It should be noted that if both the amplitude and rate of change of the secondary touch signal fall within the legal range, the current signal is considered closer to the actual touch signal. In this case, the filter parameters are adaptively reduced to suppress minor fluctuations while preserving as much detail and waveform integrity as possible of the actual touch signal, avoiding signal distortion due to over-filtering. If the amplitude or rate of change of the secondary touch signal exceeds the legal range, it is determined that it contains significant residual low-to-mid-frequency noise. In this case, the filter parameters are adaptively increased to expand the range of signals involved in the filtering operation. Through stronger smoothing and suppression, such sudden or slowly changing low-to-mid-frequency interference is eliminated. Through this window adjustment method linked to the legal range, the adaptive Kalman filter can achieve an optimal balance between preserving the effective signal and suppressing residual noise, ultimately obtaining a stable and clean target touch signal.

[0057] It is understood that step S140 may include, but is not limited to, the following steps: Step S610: Adjust the preset touch trigger threshold according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform; wherein the adjustment ratio of the touch trigger threshold is positively correlated with the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform.

[0058] Step S620: When the target touch signal exceeds the touch trigger threshold, the judgment result of the target touch signal is valid and is output.

[0059] Step S630: If the target touch signal does not reach the touch trigger threshold, the judgment result of the target touch signal is invalid and is not output.

[0060] In steps S610 to S630, the preset touch trigger threshold is adjusted according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform. The adjustment ratio of the touch trigger threshold is positively correlated with the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, allowing the touch trigger threshold to dynamically adapt to the actual strength of the ambient noise. This fundamentally avoids the problem of false or missed triggering of the target touch signal caused by noise fluctuations. Furthermore, by comparing the target touch signal with the touch trigger threshold, only signals exceeding the threshold are determined to be valid and output, while signals below the threshold are determined to be invalid and not output. This further eliminates invalid signals caused by residual interference, ensuring that the final output consists of genuine and reliable touch signals, greatly improving the accuracy and stability of the entire touch signal extraction and recognition process.

[0061] It is understood that after step S140, the following steps may be included, but are not limited to: Step S710: Based on the feedback information of the target touch signal and in combination with the preset real touch legal features, determine the false touch rate and missed touch rate of the extracted touch signal.

[0062] Step S720: Adjust the filtering parameters of the multi-level filtering process and the adjustment ratio parameters of the touch trigger threshold according to the false touch rate and the missed touch rate.

[0063] In steps S710 to S720, after the target touch signal is determined to be valid, the false touch rate and missed touch rate are determined based on the feedback information of the target touch signal and in conjunction with the preset true touch validity features. The filtering parameters of the multi-level filtering process and the adjustment ratio parameters of the touch trigger threshold are then adjusted according to the false touch rate and missed touch rate, forming a closed-loop optimization mechanism for touch signal extraction. The preset true touch validity features provide a clear and unified truth source for determining the false touch rate and missed touch rate, serving as benchmark parameter information for defining the authenticity of the true touch signal. Specifically, these parameters cover the reasonable range of touch signal amplitude, the reasonable range of change rate, and the normal waveform change trend, making the identification of false touches and missed touches more accurate and providing a reliable basis for closed-loop adjustment.

[0064] This setting allows the system to autonomously adjust the filtering parameters of multi-level filtering and the adjustment ratio of touch trigger threshold based on the actual signal extraction effect, continuously optimize the signal filtering effect and the accuracy of effectiveness judgment, effectively reduce the false touch rate and missed touch rate in the touch signal extraction process, and enable the entire touch signal extraction method to adapt to interference changes in different environments, always maintain a stable and accurate working state, and further improve the reliability and accuracy of touch signal extraction.

[0065] Specifically, the feedback information for target touch signals is automatically collected, recorded, and compared within the system. The system retains all target touch signal data after multi-level filtering in real time. It also records information related to target touch signals deemed valid and output based on the touch trigger threshold. This information is then combined with preset characteristics of valid real touch signals, including amplitude, reasonable range of change rate, and waveform trend, to form feedback information for evaluating the touch signal extraction effect. Valid target touch signals are compared with preset characteristics of valid real touch signals. If the output signal does not meet these characteristics, it is considered a false touch. The false touch rate is determined by statistically analyzing the number of false touches and the total number of valid signal outputs within a set period. Simultaneously, the system compares target touch signals that are deemed invalid because they do not reach the touch trigger threshold. If such invalid signals actually meet the characteristics of valid real touch signals, they are considered a missed touch. The missed touch rate is determined by statistically analyzing the number of missed touches and the total number of valid touch signals within a set period.

[0066] When the false touch rate of the extracted touch signal is detected to be too high, it indicates that the current multi-level filtering process is not sufficiently eliminating residual interference, or that the adjustment ratio of the touch trigger threshold is too low, making it easy for interference signals to be judged as valid signals. At this time, the system will adjust the filtering parameters of the multi-level filtering process accordingly, enhance the interference suppression capability of the band-stop filter and the adaptive Kalman filter, and at the same time increase the adjustment ratio parameter of the touch trigger threshold, so that the touch trigger threshold changes more significantly with the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, thereby raising the threshold for judging valid signals.

[0067] When the detected missed touch rate of the extracted touch signal is too high, it indicates that the current multi-level filtering process has an over-filtering problem, or the adjustment ratio of the touch trigger threshold is too high, causing the real touch signal to be suppressed or unable to meet the judgment standard. At this time, the system will optimize the filtering parameters of the multi-level filtering process to reduce the impact on the real signal waveform while retaining the interference removal effect. At the same time, the adjustment ratio parameter of the touch trigger threshold will be lowered to reduce the adaptation range of the touch trigger threshold and ensure that the real touch signal can be recognized and output normally.

[0068] Secondly, referring to Figure 2 This application also provides a touch signal extraction device 800, including: a monitoring unit 810, a compensation unit 820, a filtering unit 830 and a self-determination unit 840.

[0069] The monitoring unit 810 is used to collect the common-mode electromagnetic noise characteristic waveforms in the environment in real time through the acquisition component set on the periphery of the touch electrode during the non-touch scanning cycle, and to establish a noise characteristic library.

[0070] The compensation unit 820 is used to extract the common-mode electromagnetic noise feature waveform from the noise feature library, and invert the common-mode electromagnetic noise feature waveform and incorporate it into the touch main signal channel to perform differential compensation processing with the initial touch signal collected in the touch main signal channel to obtain the intermediate touch signal.

[0071] The filtering unit 830 is used to input the intermediate touch signal into a preset multi-level digital filter for multi-level filtering processing to obtain the target touch signal.

[0072] The self-determination unit 840 is used to adjust the preset touch trigger threshold according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, and to determine the validity of the target touch signal based on the touch trigger threshold, and output the target touch signal that is determined to be valid.

[0073] The specific implementation of the touch signal extraction device 800 is basically the same as the specific implementation of the touch signal extraction method described above, and will not be repeated here.

[0074] Thirdly, this application also provides an electronic device, including: at least one memory; at least one processor; at least one program; the program is stored in the memory, and the processor executes the at least one program to implement the method for extracting touch signals as described in any embodiment of the first aspect.

[0075] In this electronic device, during non-touch scanning cycles, a data acquisition component located around the touch electrodes first acquires the common-mode electromagnetic noise characteristic waveforms in the environment in real time and establishes a noise feature library. Next, the common-mode electromagnetic noise characteristic waveforms are extracted from this library, inverted, and then fed into the main touch signal channel. Differential compensation processing is performed between this signal and the initial touch signal acquired in the main touch signal channel to obtain an intermediate touch signal. This intermediate touch signal is then input into a preset multi-level digital filter for multi-level filtering to obtain the target touch signal. Finally, based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveforms, a preset touch trigger threshold is adjusted, and the validity of the target touch signal is determined based on this threshold. Valid target touch signals are output. This method effectively solves the problems of touch signal distortion and recognition errors caused by strong electromagnetic interference by acquiring common-mode electromagnetic noise, anti-phase differential compensation, multi-level filtering, and dynamic adjustment of touch trigger threshold. It can accurately distinguish between valid touch signals and interference signals, improve the stability and accuracy of touch signal extraction, and meet the high reliability requirements of touch signal extraction in relevant application scenarios.

[0076] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and signals, such as the program instructions / signals corresponding to the processing module in the embodiments of this application. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions, and signals stored in the memory, thereby implementing the touch signal extraction method of the above-described method embodiments.

[0077] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data related to the aforementioned touch signal extraction method. Furthermore, the memory may include high-speed random access memory and non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processing module via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0078] One or more signals are stored in a memory, and when executed by one or more processors, the touch signal extraction method in any of the above method embodiments is performed.

[0079] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that is executed by one or more processors, enabling the one or more processors to perform the touch signal extraction method in the above method embodiments.

[0080] The device embodiments described above are merely illustrative. 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0081] Based on the above description of the embodiments, those skilled in the art will understand that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable signals, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible by a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable signals, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0082] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0083] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0084] The units described above as separate components may or may not be physically separate. 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0085] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0086] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] The embodiments of this application have been described in detail above with reference to the accompanying drawings. However, this application is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of this application.

Claims

1. A method for extracting touch signals, characterized in that, include: During the non-touch scanning cycle, the common-mode electromagnetic noise characteristic waveform in the environment is collected in real time by the acquisition component set on the periphery of the touch electrode, and a noise characteristic library is established. The common-mode electromagnetic noise characteristic waveform is extracted from the noise feature library, and the common-mode electromagnetic noise characteristic waveform is inverted and then incorporated into the touch main signal channel to perform differential compensation processing with the initial touch signal collected in the touch main signal channel to obtain the intermediate touch signal; The intermediate touch signal is input into a preset multi-level digital filter for multi-level filtering to obtain the target touch signal; Based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, the preset touch trigger threshold is adjusted, and the validity of the target touch signal is judged based on the touch trigger threshold. The target touch signal with a valid judgment result is output.

2. The method for extracting touch signals according to claim 1, characterized in that, During the non-touch scanning cycle, the common-mode electromagnetic noise characteristic waveforms in the environment are acquired in real time by a data acquisition component located around the touch electrode, and a noise characteristic library is established, including: When the touch electrode is in a non-collection state, the non-touch scanning cycle begins; During non-touch scanning cycles, the induction coil located on the outer periphery of the touch electrode is activated; The common-mode electromagnetic noise signal in the environment is collected in real time by the induction coil; The common-mode electromagnetic noise signal is amplified and shaped, and the frequency characteristics, amplitude characteristics, and phase characteristics of the common-mode electromagnetic noise signal are extracted to form the common-mode electromagnetic noise characteristic waveform. A noise feature library is established, and the noise feature library is updated based on the common-mode electromagnetic noise feature waveform.

3. The method for extracting touch signals according to claim 2, characterized in that, The step of updating the noise feature database based on the common-mode electromagnetic noise characteristic waveform includes: According to the preset update cycle, the common-mode electromagnetic noise signal in the environment is re-acquired and converted to obtain the common-mode electromagnetic noise characteristic waveform; The newly acquired common-mode electromagnetic noise feature waveforms are compared point by point with the common-mode electromagnetic noise feature waveforms stored in the noise feature library, and the feature similarity corresponding to each common-mode electromagnetic noise feature waveform in the noise feature library is obtained. When the feature similarity is greater than or equal to a preset similarity threshold, the newly acquired common-mode electromagnetic noise feature waveform replaces the corresponding common-mode electromagnetic noise feature waveform in the noise feature library, and the current storage duration of the replaced common-mode electromagnetic noise feature waveform is reset. When the feature similarity is less than the similarity threshold, the newly acquired common-mode electromagnetic noise feature waveform is added to the noise feature library, and the current storage duration of the newly added common-mode electromagnetic noise feature waveform is recorded. When the current storage duration reaches the preset effective storage duration, the corresponding common-mode electromagnetic noise feature waveform is deleted from the noise feature library.

4. The method for extracting touch signals according to claim 1, characterized in that, The process of extracting the common-mode electromagnetic noise characteristic waveform from the noise feature library, inverting the common-mode electromagnetic noise characteristic waveform, and incorporating it into the touch main signal channel for differential compensation with the initial touch signal acquired in the touch main signal channel to obtain an intermediate touch signal includes: The phase difference between the current common-mode electromagnetic noise characteristic waveform and the interference component in the initial touch signal is calculated in real time. After inverting the common-mode electromagnetic noise characteristic waveform, and performing dynamic phase fine-tuning based on the phase difference, a noise inversion compensation signal is obtained. The noise inversion compensation signal is incorporated into the touch main signal channel in the analog domain to perform analog domain differential compensation processing with the initial touch signal collected in the touch main signal channel, so as to achieve preliminary hardware-level common-mode noise suppression and obtain the intermediate touch signal.

5. The method for extracting touch signals according to claim 1, characterized in that, The multi-stage digital filter includes a band-stop filter and an adaptive Kalman filter; The step of inputting the intermediate touch signal into a preset multi-level digital filter for multi-level filtering processing to obtain the target touch signal includes: Based on the noise feature library, a high-frequency noise band is determined, and the cutoff frequency of the band-stop filter is set based on the high-frequency noise band. The intermediate touch signal is input into the band-stop filter to remove high-frequency noise from the intermediate touch signal, thereby obtaining the secondary touch signal; A set of historical touch signals is acquired, and the legal range of the touch signal at the current moment is predicted using a preset Kalman filter prediction equation; wherein, the legal range includes a reasonable range of the amplitude and rate of change of the touch signal at the current moment; The secondary touch signal is compared with the legal range, the filtering parameters of the adaptive Kalman filter are dynamically adjusted, and the secondary touch signal is input into the adaptive Kalman filter to remove residual low-frequency noise from the secondary touch signal, thereby obtaining the target touch signal.

6. The method for extracting touch signals according to claim 1, characterized in that, The step of adjusting a preset touch trigger threshold based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, determining the validity of the target touch signal based on the touch trigger threshold, and outputting a target touch signal that is deemed valid includes: The preset touch trigger threshold is adjusted based on the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform; wherein the adjustment ratio of the touch trigger threshold is positively correlated with the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform. When the target touch signal exceeds the touch trigger threshold, the determination result of the target touch signal is valid and is output; If the target touch signal does not reach the touch trigger threshold, the judgment result of the target touch signal is invalid and it is not output.

7. The method for extracting touch signals according to claim 1, characterized in that, After the step of outputting a target touch signal that is determined to be valid, the method further includes: Based on the feedback information of the target touch signal and in combination with the preset real touch legal features, the false touch rate and missed touch rate of the touch signal extraction are determined. Based on the false touch rate and the missed touch rate, the filtering parameters of the multi-level filtering process and the adjustment ratio parameters of the touch trigger threshold are adjusted.

8. A device for extracting touch signals, characterized in that, include: The monitoring unit is used to collect the common-mode electromagnetic noise characteristic waveforms in the environment in real time through the acquisition components set on the periphery of the touch electrode during non-touch scanning cycles, and to establish a noise characteristic library. The compensation unit is used to extract the common-mode electromagnetic noise characteristic waveform from the noise feature library, and invert the common-mode electromagnetic noise characteristic waveform and incorporate it into the touch main signal channel to perform differential compensation processing with the initial touch signal collected in the touch main signal channel to obtain the intermediate touch signal; The filtering unit is used to input the intermediate touch signal into a preset multi-level digital filter for multi-level filtering processing to obtain the target touch signal; The self-determination unit is used to adjust the preset touch trigger threshold according to the fluctuation amplitude of the common-mode electromagnetic noise characteristic waveform, and to determine the validity of the target touch signal based on the touch trigger threshold, and output the target touch signal that is determined to be valid.

9. An electronic device, characterized in that, include: At least one memory; At least one processor; At least one program; The program is stored in the memory, and the processor executes at least one of the programs to implement the method for extracting touch signals as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer-executable program for performing the method for extracting touch signals as described in any one of claims 1 to 7.

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