A data processing method and related equipment

Abstract

The present application discloses a data processing method and related equipment. According to the method, before the electronic device inputs the TP data and ACC data related to the user operation into the knuckle recognition model, it can pre-process the acquired data, determine whether the acquired data is abnormal data, and intercept the abnormal data, thereby improving the accuracy of identifying the knuckle tapping operation and avoiding the electronic device from causing erroneous operation due to erroneous identification of the knuckle tapping operation.

Description

Technical Field

[0001] The present application relates to the field of terminal technology, and in particular to a data processing method and related equipment. Background Art

[0002] Mobile phones, tablet computers and other terminals (or electronic devices) are developing rapidly and becoming more and more popular. These terminals have rich and diverse functions, which improve people's quality of life and make people's work and study more efficient. In order to further improve the user experience, many manufacturers have added shortcuts to the terminals, allowing users to use the terminals in a faster way. For example, users can take a screenshot (or screenshot) by tapping the terminal screen with their knuckles. Summary of the invention

[0003] The present application provides a data processing method and related devices. Based on the method, the electronic device can pre-process the TP data and ACC data related to the user operation before inputting the TP data and ACC data into the knuckle recognition model, determine whether the acquired data is abnormal data, and intercept the data in advance if the acquired data is abnormal data, thereby improving the accuracy of identifying the knuckle tapping operation and avoiding erroneous operation caused by the electronic device due to incorrect recognition of the knuckle tapping operation.

[0004] In a first aspect, the present application provides a data processing method. The method can be applied to an electronic device provided with a display screen. The method may include: in response to a first operation on the display screen, the electronic device may obtain TP data and ACC data corresponding to the first operation; when the TP data and ACC data are valid, the electronic device may pre-process the TP data; when the TP data does not meet the constraint condition, the electronic device may input the TP data and ACC data into a finger joint recognition model; when the first operation is determined to be a finger joint tapping operation based on the finger joint recognition model, the electronic device may adopt a preset processing method. Among them, the constraint condition includes one or more of the following: extreme value constraint condition, negative value constraint condition, mean value constraint condition. The extreme value constraint condition is a constraint condition for the maximum and minimum values ​​in the TP data obtained by the electronic device, the negative value constraint condition is a constraint condition for the negative value data in the TP data obtained by the electronic device, and the mean value constraint condition is a constraint condition for the negative value average and positive value average in the TP data obtained by the electronic device.

[0005] In the solution provided in the present application, in response to a user operation on a display screen, the electronic device can obtain corresponding TP data and ACC data, and when the TP data and the ACC data are valid, first pre-process the TP data, determine whether the TP data is abnormal data by setting constraints, and intercept the abnormal TP data. When the TP data does not meet the constraints, the electronic device can further input the obtained TP data and ACC data into a finger joint recognition model, and determine whether the user operation is a finger joint tapping operation through the finger joint recognition model. On the one hand, this method can determine whether the data input to the model is abnormal data before identifying the user operation through the model, further improving the accuracy of identifying the finger joint tapping operation. On the other hand, this method can also intercept abnormal data in advance without having to input it into the model for identification, which can reduce power consumption to a certain extent.

[0006] In some embodiments of the present application, when the function corresponding to the preset processing mode is activated by knuckle tapping, the electronic device can implement the above method or the method described in any of the following implementation modes. In one possible implementation mode, the function corresponding to the preset processing mode is activated by knuckle tapping, which can be: the user opens the setting option corresponding to the function.

[0007] In some embodiments of the present application, the electronic device does not set the setting options corresponding to the above functions, and the electronic device can directly execute the above method or the method described in any of the following implementation methods.

[0008] It is understandable that the electronic device can also implement the above method or the method described in any of the following implementation modes in other situations, and this application does not impose specific limitations on this.

[0009] It is understandable that the specific implementation method of the electronic device determining whether the TP data and the ACC data are valid can be referred to below (for example, step S102), and this application will not elaborate on it here.

[0010] In some embodiments of the present application, the extreme value constraint condition may be the TP abnormal data extreme value constraint mentioned below, the negative value constraint condition may be the TP abnormal data negative value constraint mentioned below, and the mean value constraint condition may be the TP abnormal data extreme value constraint mentioned below.

[0011] In some embodiments of the present application, the electronic device determines that the first operation is a knuckle tapping operation based on the knuckle recognition model, which may specifically include: the electronic device determines that the TP model recognition is successful and the ACC model recognition is successful.

[0012] In some embodiments of the present application, the electronic device determines that the first operation is a knuckle tapping operation based on the knuckle recognition model, which may specifically include: the electronic device determines that the TP model recognition is successful, the ACC model recognition is successful, and the post-processing passes.

[0013] It is understandable that the preset processing method can be set according to actual needs, and the present application does not limit this. For example, the preset processing method can be a screenshot operation. The screenshot operation can be an operation of capturing the entire screen display, or an operation of capturing a specific display area, and the present application does not specifically limit this. For another example, the preset processing method can be starting a specific application. For another example, the preset processing method can be restarting. For another example, the preset processing method can be adding an alarm. For another example, the preset processing method can be adding a schedule.

[0014] It can be understood that the average value of negative values ​​in the TP data is the average value of the negative values ​​in the TP data. Similarly, the average value of positive values ​​in the TP data is the average value of the positive values ​​in the TP data.

[0015] In combination with the first aspect, in a possible implementation method, the electronic device preprocesses the TP data, and when the TP data does not satisfy the constraint conditions, inputs the TP data and the ACC data into the finger joint recognition model. Specifically, it may include: the electronic device may determine whether the maximum value and the minimum value in the TP data satisfy the extreme value constraint conditions; when the maximum value and the minimum value in the TP data do not satisfy the extreme value constraint conditions, the electronic device may determine whether the negative value data in the TP data satisfies the negative value constraint conditions; when the negative value data in the TP data does not satisfy the negative value constraint conditions, the electronic device may determine whether the negative value average value and the positive value average value in the TP data satisfy the mean constraint conditions; when the negative value average value and the positive value average value in the TP data do not satisfy the mean constraint conditions, the electronic device may input the TP data and the ACC data into the finger joint recognition model.

[0016] In the solution provided by the present application, the electronic device pre-processes the acquired TP data, and first determines whether the TP data satisfies the extreme value constraint condition, and if the TP data does not satisfy the extreme value constraint condition, then determines whether the TP data satisfies the negative value constraint condition, and if the TP data does not satisfy the negative value constraint condition, then determines whether the TP data satisfies the mean value constraint condition. This method can intercept abnormal data through three progressive constraints, so that some abnormal data can be detected before being input into the model, which not only further improves the accuracy of identifying the knuckle tapping operation, but also reduces power consumption to a certain extent.

[0017] In conjunction with the first aspect, in a possible implementation, after preprocessing the TP data, the method may further include: when the TP data satisfies the constraint condition, the electronic device may identify whether the first operation is other operations, and the other operations are operations other than the knuckle tapping operation. Wherein, when the constraint condition includes multiple conditions, the electronic device satisfying the constraint condition includes that the electronic device satisfies at least one of the multiple conditions.

[0018] In the solution provided in the present application, when the TP data meets the constraint conditions, the electronic device can determine that the first operation is a non-knuckle tapping operation. In this case, the electronic device can continue to respond to the touch event. Among them, the electronic device continues to respond to the touch event, which can be understood as: the electronic device can continue to determine what the first operation is specifically (for example, long press, click, double click, slide, etc.), and give a corresponding processing method after the judgment is completed (for example, display a new user interface, start the corresponding application, return to the previous page, adjust the volume, adjust the brightness, etc.). This method can intercept and continue to respond to touch events as soon as possible when the user performs operations other than knuckle tapping, without waiting until the relevant data of the operation is input into the knuckle recognition model before determining that the operation is a non-knuckle tapping operation, which can shorten the response time of the touch event to a certain extent.

[0019] In combination with the first aspect, in a possible implementation, the TP data satisfies an extreme value constraint condition, which may specifically include: a product of a first absolute value and a first coefficient is less than a second absolute value. The first absolute value is an absolute value of a maximum value in the TP data, and the second absolute value is an absolute value of a minimum value in the TP data. The first coefficient is greater than 0 and less than 1.

[0020] In the solution provided in the present application, the electronic device can determine whether the maximum and minimum values ​​in the acquired TP data satisfy the extreme value constraint condition, thereby intercepting abnormal data (or TP abnormal data), for example, TP data containing negative data with a large absolute value. This method can intercept TP data with a high degree of abnormality (which can be understood as TP data that obviously does not conform to the distribution rule corresponding to the TP data corresponding to the knuckle tapping operation). In some embodiments of the present application, the electronic device pre-processes the acquired TP data and can first determine whether the TP data satisfies the extreme value constraint condition, so that TP data with a high degree of abnormality can be intercepted more quickly.

[0021] In some embodiments of the present application, the first absolute value may be Abs(max) mentioned below, the first coefficient may be Coeff mentioned below, and the second absolute value may be Abs(min) mentioned below.

[0022] In combination with the first aspect, in a possible implementation manner, the TP data satisfies the extreme value constraint condition, which may specifically include: the first absolute value is less than the second absolute value.

[0023] In combination with the first aspect, in a possible implementation manner, the TP data satisfies the negative value constraint condition, which may specifically include: the first negative value quantity is greater than the first threshold. Wherein, the first threshold is a positive integer; the first negative value quantity is the quantity of data in the TP data that is less than the second threshold; the second threshold is less than 0.

[0024] In the solution provided by this application, the electronic device can determine whether the negative value data in the acquired TP data satisfies the negative value constraint condition, so as to further intercept abnormal data. For example, TP data containing a relatively large number of negative value data. Compared with the abnormal data intercepted by the extreme value constraint condition, this method can further intercept abnormal data, such as TP data with a relatively lower degree of abnormality. In some embodiments of this application, when the electronic device preprocesses the acquired TP data, it can first determine whether the TP data satisfies the extreme value constraint condition, and if it is determined that the TP data does not satisfy the extreme value constraint condition, it can then determine whether the TP data satisfies the negative value constraint condition, so as to further intercept TP data with a relatively higher degree of abnormality.

[0025] In some embodiments of this application, the negative value data in the TP data acquired by the electronic device may be Neg mentioned below. The first negative value quantity may be Num (Neg < thresh1) mentioned below, the first threshold may be Count1 mentioned below, and the second threshold may be thresh1 mentioned below.

[0026] In combination with the first aspect, in a possible implementation manner, the TP data satisfies the mean value constraint condition, which may specifically include: the second negative value quantity is greater than the third threshold, and the third absolute value is greater than the fourth absolute value. Wherein, the third threshold is a positive integer and is greater than or equal to the first threshold; the second negative value quantity is the quantity of data in the TP data that is less than the fourth threshold; the fourth threshold is less than 0 and is greater than the second threshold; the third absolute value is the absolute value of the first mean value, and the first mean value is the mean value of the negative value data in the TP data; the fourth absolute value is the absolute value of the second mean value, and the second mean value is the mean value of the positive value data in the TP data.

[0027] In the solution provided by this application, the electronic device can determine whether the average value of negative values (i.e., the mean of negative value data) and the average value of positive values (i.e., the mean of positive value data) in the acquired TP data satisfy the negative value constraint condition, so as to further intercept abnormal data. For example, TP data containing a relatively large number of negative value data with low absolute values. Compared with the abnormal data intercepted by the extreme value constraint condition and the negative value constraint condition, this method can further intercept abnormal data, such as TP data with a relatively low degree of abnormality (compared with the abnormal data intercepted by the extreme value constraint condition and the negative value constraint condition, the TP data with a lower degree of abnormality). In some embodiments of this application, when the electronic device preprocesses the acquired TP data, it can first determine whether the TP data satisfies the extreme value constraint condition. And when it is determined that the TP data does not satisfy the extreme value constraint condition, it can further determine whether the TP data satisfies the negative value constraint condition. And when it is determined that the TP data does not satisfy the negative value constraint condition, it can further determine whether the TP data satisfies the mean constraint condition. It can be understood that the extreme value constraint condition, the negative value constraint condition, and the mean constraint condition are progressive conditions (the mean constraint condition is the most restrictive condition for abnormal data among these three conditions, while the extreme value constraint condition and the negative value constraint condition are relatively less restrictive). The above method can further intercept TP data with a relatively low degree of abnormality.

[0028] In some embodiments of this application, the second negative value quantity may be Num(Neg<thresh2) mentioned below, the third threshold value may be Count2 mentioned below, and the fourth threshold value may be thresh2 mentioned below. The third absolute value may be Abs(Avg Neg) mentioned below, and the fourth absolute value may be Abs(AvgPos) mentioned below. The first mean value may be Avg Neg mentioned below, that is, the average value of negative values, or the average value of negative value data in the TP data (which can be simply referred to as the mean value). The second mean value may be Avg Pos mentioned below, that is, the average value of positive values, or the average value of positive value data in the TP data.

[0029] Combined with the first aspect, in a possible implementation manner, the TP data acquired by the electronic device may include voltage change values corresponding to multiple sensing points. The multiple sensing points may include a total of a rows and b columns of sensing points centered on the first sensing point. The first sensing point is the sensing point closest to the center point of the first operation on the display screen. The ACC data acquired by the electronic device includes the acceleration value in the vertical direction corresponding to the first operation with the plane where the display screen is located as the horizontal plane.

[0030] In the solution provided in the present application, the electronic device can determine which positions to obtain TP data based on the center point of the first operation on the display screen (for example, the tapping center point mentioned below), and determine which positions to obtain acceleration values ​​based on the first operation. In this way, TP data and ACC data related to the first operation can be obtained as much as possible, thereby improving the accuracy of identifying the knuckle tapping operation.

[0031] The voltage change value corresponding to the sensing point in row a and column b can be understood as the TP data of the a*b matrix mentioned below.

[0032] In some embodiments of the present application, the TP data acquired by the electronic device may include a voltage change value corresponding to a sensing point that is within a certain distance from the center point of the first operation and has a voltage change. It is understood that the certain distance can be set according to actual needs, and the present application does not limit this. For example, the certain distance may be 1 cm.

[0033] In some embodiments of the present application, the first sensing point may be a sensing point that is closest to the tapping center point.

[0034] In combination with the first aspect, in a possible implementation, after the electronic device inputs the acquired TP data and ACC data into the finger joint recognition model, the method may further include: the electronic device may obtain a first recognition result, a second recognition result, and recognition data; if the first recognition result and the second recognition result meet the first preset condition, the electronic device may determine whether the recognition data meets the second preset condition; if the recognition data meets the second preset condition, the electronic device may determine that the first operation is a finger joint tapping operation. The first recognition result is the recognition result corresponding to the TP model in the finger joint recognition model, and the second recognition result is the recognition result corresponding to the ACC model in the finger joint recognition model.

[0035] In the solution provided in the present application, after the electronic device inputs the acquired TP data and ACC data into the knuckle recognition model, it can not only output the knuckle tapping operation recognition results (first recognition result and second recognition result) obtained based on the TP data and ACC data respectively, but also obtain other related data (i.e., recognition data). The electronic device can not only determine whether the first operation is a knuckle tapping operation based on the recognition result, but also determine whether the first operation is a knuckle tapping operation in combination with the recognition result and the recognition data, which can further improve the accuracy of identifying the knuckle tapping operation.

[0036] Among them, the knuckle tapping operation recognition result (i.e., the first recognition result) output by the knuckle recognition model based on the TP data can be understood as the output result of the TP model, which can represent the probability that the first operation is a knuckle tapping operation from the perspective of the TP data. Similarly, the knuckle tapping operation recognition result (i.e., the second recognition result) output by the knuckle recognition model based on the ACC data can be understood as the output result of the ACC model, which can represent the probability that the first operation is a knuckle tapping operation from the perspective of the TP data.

[0037] In some embodiments of the present application, the first recognition result may be an output result of the TP model mentioned below, and the second recognition result may be an output result of the ACC model mentioned below.

[0038] In some embodiments of the present application, the first recognition result and the second recognition result satisfy a first preset condition, which may specifically include: the first recognition result is greater than or equal to x1, and the second recognition result is greater than or equal to x2.

[0039] In some embodiments of the present application, the identification data satisfies the second preset condition, which may specifically include: each item of data in the identification data satisfies the corresponding condition. For details, please refer to the relevant description of step S109 (for example, descriptions related to data such as touch area, tapping force, and tapping response time). This application will not elaborate on this.

[0040] In some embodiments of the present application, when the first recognition result and the second recognition result meet a first preset condition, the electronic device may determine that the first operation is a knuckle tapping operation.

[0041] In some embodiments of the present application, when the first recognition result and the second recognition result meet the first preset condition, and the recognition data meets the second preset condition, the electronic device can determine that the first operation is a knuckle tapping operation.

[0042] In combination with the first aspect, in a possible implementation, before the electronic device obtains TP data and ACC data corresponding to the first operation on the display screen in response to the first operation, the method may further include: the electronic device may subscribe to the data of the ACC drive through the finger joint drive; the electronic device may send ACC data to the finger joint drive at a preset frequency through the ACC drive; after the electronic device receives the ACC data sent by the ACC drive through the finger joint drive, the ACC data sent by the ACC drive may be stored in a buffer corresponding to the finger joint drive. In response to the first operation, the electronic device obtains the ACC data corresponding to the first operation, which may specifically include: in response to the first operation, the electronic device may obtain the latest stored c acceleration values ​​from the buffer corresponding to the finger joint drive.

[0043] In the solution provided by the present application, the knuckle driver can subscribe to the data of the ACC driver and store its data in a corresponding buffer (i.e., the buffer corresponding to the knuckle driver). In response to the first operation, the electronic device can directly retrieve multiple data from the corresponding buffer, i.e., the ACC data corresponding to the first operation, without waiting until the electronic device detects the first operation and then obtains the ACC data from the ACC driver. This method can reduce the response time of obtaining ACC data to a certain extent and improve the efficiency of identifying the knuckle tapping operation.

[0044] In a second aspect, the present application provides an electronic device, comprising one or more memories and one or more processors; the one or more memories are coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the electronic device to perform the method described in the first aspect or any one of the implementations of the first aspect.

[0045] In a third aspect, the present application provides a computer storage medium, which includes computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the method described in the first aspect or any one of the implementations of the first aspect.

[0046] In a fourth aspect, an embodiment of the present application provides a chip. The chip can be applied to an electronic device, and the chip includes one or more processors, and the processor is used to call computer instructions to enable the electronic device to execute the method described in the first aspect or any implementation of the first aspect.

[0047] In some embodiments of the present application, the chip system may be an application processor (AP) or a system on chip (SoC) including an AP. The method described in the first aspect or any one of the implementations of the first aspect may be implemented by an AP, and the method described in the second aspect or any one of the implementations of the second aspect may be implemented by an AP.

[0048] In some other embodiments of the present application, the chip system may include an AP and other modules. The other modules may be a modem processor (Modem, also referred to as a baseband processor).

[0049] In a fifth aspect, an embodiment of the present application provides a computer program product comprising instructions. When the computer program product is run on an electronic device, the electronic device executes the method described in the first aspect or any one of the implementations of the first aspect.

[0050] It is understandable that the electronic device provided in the second aspect, the computer storage medium provided in the third aspect, the chip provided in the fourth aspect, and the computer program product provided in the fifth aspect are all used to execute the method described in the first aspect or any one of the implementations of the first aspect. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of any possible implementation of the first aspect, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1A and Figure 1B A set of user interface schematic diagrams provided for embodiments of the present application;

[0052] Figure 2A A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application;

[0053] Figure 2B A schematic diagram of the software structure of an electronic device provided in an embodiment of the present application;

[0054] Figure 3A A schematic diagram of an axis coordinate sensing unit matrix provided in an embodiment of the present application;

[0055] Figure 3B A schematic diagram of a touch screen provided in an embodiment of the present application;

[0056] Figure 3C A schematic diagram of another touch screen provided in an embodiment of the present application;

[0057] Figure 4 A flowchart of a data processing method provided in an embodiment of the present application;

[0058] Figure 5 A schematic diagram of knuckle tapping provided in an embodiment of the present application;

[0059] Figure 6 A schematic diagram of another touch screen provided in an embodiment of the present application;

[0060] Figure 7 A schematic diagram of the distribution of a set of TP data provided in an embodiment of the present application;

[0061] Figure 8 A distribution diagram of another set of TP data provided in an embodiment of the present application;

[0062] Fig. 9 A distribution diagram of another set of TP data provided in an embodiment of the present application;

[0063] Fig.10 A schematic diagram of software and hardware interaction provided in an embodiment of the present application;

[0064] Fig.11 A flowchart of another data processing method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in the text is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0066] It should be understood that the terms "first", "second", etc. in the specification, claims and drawings of the present application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0067] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0068] In order to further enhance the user experience, many manufacturers have added shortcuts to electronic devices such as mobile phones and tablets, allowing users to use these electronic devices in a more convenient way. For example, a user can tap the screen (or display) of an electronic device with a knuckle to take a screenshot (for example, to capture a picture of the entire screen). For example, the electronic device can display the following: Figure 1A After receiving the user operation of tapping the display screen with the knuckle, the electronic device can take a screenshot and display the screen as shown in FIG. Figure 1B The screenshot interface 11 shown. Optionally, in response to Figure 1A The user operation shown in the figure is to tap the display screen with the knuckles, and the electronic device can display the following Figure 1B The screenshot interface 11 shown. Optionally, the electronic device can detect Figure 1AIn response to the user operation of tapping the display screen with the knuckle shown in FIG. Figure 1B The screenshot interface 11 shown in FIG. 1 may include a screenshot thumbnail 101 .

[0069] Users can also trigger other operations of the electronic device by touching the screen, such as launching an application or sliding a page, etc. Since knuckle tapping and other user operations of touching the screen (e.g., clicking, long pressing, etc.) are user operations on the screen, there may be recognition errors, such as the electronic device recognizing a non-knuckle tapping user operation as a knuckle tapping, or recognizing a knuckle tapping as a non-knuckle tapping user operation, which will cause the electronic device to falsely trigger the screenshot, or fail to respond to the knuckle tapping in time.

[0070] Based on the above content, the embodiment of the present application provides a data processing method and related devices. According to the method, the electronic device can first determine whether the TP data and ACC data related to the user operation are abnormal data before inputting the TP data and ACC data related to the finger joint recognition model, and intercept the abnormal data, thereby improving the accuracy of identifying the finger joint tapping and avoiding the electronic device from erroneously triggering a screenshot due to erroneous identification of the finger joint tapping.

[0071] The following first introduces the device involved in the embodiments of the present application.

[0072] The electronic device involved in the present application may be a terminal device, specifically a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA) or a dedicated camera (for example, a SLR camera, a card camera) and the like. The embodiments of the present application do not impose any restrictions on the specific type of the electronic device.

[0073] The hardware structure of the electronic device involved in the embodiments of the present application is introduced below.

[0074] See also Figure 2A , Figure 2A A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application.

[0075] like Figure 2AAs shown, the electronic device may include: a processor, an audio module, an external memory interface, an internal memory, a Universal Serial Bus (USB) interface, a charging management module, a power management module, a battery, an antenna 1, an antenna 2, a mobile communication module, a wireless communication module, a sensor module, a button, a motor, an indicator, a camera, a display screen, and a Subscriber Identity Module (SIM) card slot, etc. Among them, the audio module may include a speaker, a receiver, a microphone, an earphone interface, etc., and the sensor module may include a pressure sensor, a gyroscope sensor, an air pressure sensor, a magnetic sensor, an acceleration sensor, a distance sensor, a proximity light sensor, a fingerprint sensor, a temperature sensor, a touch sensor, an ambient light sensor, a bone conduction sensor, etc.

[0076] It is to be understood that the structure illustrated in the embodiments of the present application does not constitute a specific limitation on the electronic device. It is to be understood that the illustrated components can be implemented in hardware, software, or a combination of software and hardware. In some embodiments of the present application, the electronic device may include more components than illustrated. Exemplarily, the electronic device may include other types of sensors. In some other embodiments of the present application, the electronic device may include fewer components than illustrated, or combine certain components, or split certain components, or arrange the components differently. The interface connection relationship between the modules illustrated in the embodiments of the present application is only a schematic illustration and does not constitute a structural limitation on the electronic device.

[0077] The processor may include one or more processing units, for example: the processor may include an application processor (AP), a modem (also called a baseband processor), a graphics processor (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), an audio digital signal processor (ADSP), a sensor hub and / or a neural-network processing unit (NPU), etc. Among them, AP is a processor responsible for running the operating system and applications. Modem is a processor responsible for processing various communication protocols.

[0078] The wireless communication function of the electronic device can be implemented through antenna 1, antenna 2, mobile communication module, wireless communication module, and modem. The modem can interact with the base station through antennas (for example, antenna 1, antenna 2, etc.). In some embodiments, the antenna 1 of the electronic device is coupled with the mobile communication module, and the antenna 2 is coupled with the wireless communication module, so that the electronic device can communicate with the network and other devices through wireless communication technology.

[0079] Electronic devices can achieve display functions through GPU, display, and application processor.

[0080] The GPU is a microprocessor for image processing, connected to the display screen and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor may include one or more GPUs, which execute program instructions to generate or change display information. The display screen is used to display images, videos, etc. In some embodiments, the electronic device may include one or more display screens.

[0081] In some embodiments of the present application, a touch sensor may be provided on the display screen. The touch sensor is also called a "touch panel". The touch sensor is used to detect a touch operation acting on or near it. The touch sensor may transmit the detected touch operation to the AP to determine the type of touch event. In the case where the display screen is provided with a touch sensor, the display screen may be understood as a touch screen and may provide visual output related to the touch operation.

[0082] The following is a brief introduction to the touch screen.

[0083] Touch screens can include the following two types: resistive touch screens and capacitive touch screens. Resistive touch screens were more commonly used in the early days, and capacitive touch screens were invented later. At present, resistive touch screens are less used, while capacitive touch screens are more used. Capacitive touch screens mainly include the following two types: surface capacitive touch screens and projected capacitive touch screens. Among them, projected capacitive touch screens will be more used in terminal devices such as mobile phones, tablets, and car computers.

[0084] Projected capacitive touch screens can use multiple layers of indium tin oxide (ITO). These ITO layers are processed to form a matrix of axis-coordinate sensing units. Figure 3A As shown, the axis coordinate sensing unit matrix may include an X-axis slider and a Y-axis slider. The X-axis slider may be composed of a plurality of longitudinal electrodes. The longitudinal electrodes may be composed of a plurality of column sensors (sensing units). The Y-axis slider may be composed of a plurality of transverse electrodes. The transverse electrodes may be composed of a plurality of row sensors (sensing units). Figure 3BAs shown, the projected capacitive touch screen is covered with an axis-coordinate sensing unit matrix. The axial electrodes and the longitudinal electrodes in the axis-coordinate sensing unit matrix intersect with each other. It can be understood that the intersection of the axial electrodes and the longitudinal electrodes in the projected capacitive touch screen will form a sensing point. Exemplarily, the X-axis slider of the projected capacitive touch screen can be composed of M longitudinal electrodes, and its Y-axis slider can be composed of N transverse electrodes. Therefore, the projected capacitive touch screen has M*N sensing points. Figure 3C As shown, a projected capacitive touch screen may include multiple sensing points.

[0085] When a user's finger touches a projected capacitive touch screen, it affects the coupling of electrodes near the touch point, thereby changing the voltage value between the electrodes. This voltage value can be further processed to obtain capacitance change data. In other words, the voltage and capacitance at the sensing point will change. The projected capacitive touch screen can calculate the coordinates of the touch point based on the capacitance change data.

[0086] For an electronic device provided with a projected capacitive touch screen, it is possible to determine whether a touch operation exists through capacitance change data at a sensing point, and to determine the coordinates of the touch point if a touch operation exists.

[0087] In some embodiments of the present application, the display screen may include a projected capacitive touch screen. Of course, the display screen may also include other types of touch screens, which are not specifically limited in the present application.

[0088] The camera is used to capture static images or videos. The ISP is used to process the data fed back by the camera. Light is transmitted to the camera's photosensitive element through the lens, and the light signal is converted into an electrical signal. The camera's photosensitive element transmits the electrical signal to the ISP for processing and converts it into an image visible to the naked eye. An electronic device may include one or more cameras.

[0089] The internal memory may include one or more RAMs and one or more non-volatile memories (NVMs). The RAM can be directly read and written by the processor, and can be used to store executable programs (e.g., machine instructions) of the operating system or other running programs, and can also be used to store user and application data. The NVM can also store executable programs and user and application data, and can be loaded into the RAM in advance for direct reading and writing by the processor.

[0090] In the embodiment of the present application, the code for implementing the method described in the embodiment of the present application may be stored in a non-volatile memory. When the AP is running, the electronic device may load the executable code stored in the non-volatile memory into the random access memory.

[0091] The external memory interface can be used to connect to an external non-volatile memory to expand the storage capacity of the electronic device.

[0092] Electronic devices can implement audio functions through audio modules, speakers, receivers, microphones, headphone jacks, and application processors.

[0093] The operating system of the electronic device may adopt a layered architecture, an event-driven architecture, a micro-kernel architecture, a micro-service architecture, or a cloud architecture. The embodiment of the present application takes the Android operating system of the layered architecture as an example to illustrate the software structure of the electronic device. It should be noted that although the embodiment of the present application takes the Android operating system (which may be referred to as the Android system) as an example for explanation, its basic principles are also applicable to electronic devices based on operating systems such as iOS or Windows.

[0094] Figure 2B A schematic diagram of the software structure of an electronic device provided in an embodiment of the present application.

[0095] The software structure of the electronic device adopts a layered architecture, that is, the software is divided into several layers, each of which has a clear role and division of labor. The layers communicate with each other through software interfaces. Taking the Android system running on the AP as an example, in some embodiments of the present application, the software structure of the Android system is divided into five layers, from top to bottom, namely the application layer, the application framework layer (Framework), the Android runtime (Android runtime) and the system library, the hardware abstraction layer (HAL) and the kernel layer (Kernel).

[0096] Among them, the application layer may include a series of application packages. The application package may include applications such as camera, gallery, calendar, call, map, WLAN, Bluetooth, music, video, short message, etc. The application layer may also include a screenshot application. The screenshot application can be used for screenshots, such as capturing a picture of a specific area on the screen, or capturing a picture of the entire screen, or capturing a picture of the entire window. In some embodiments of the present application, the screenshot application may be a system application. In some embodiments of the present application, the screenshot application may be a third-party application. It is understandable that the name of the screenshot application is only an example given in the present application, and the present application does not limit this. The application layer may also include a system UI (System User Interface, system UI). The system UI is used to display the interface of the electronic device, such as displaying a note interface, displaying a signal icon corresponding to a SIM card, displaying a call interface, etc.

[0097] The application framework layer provides an application programming interface (API) and a programming framework for the applications of the application layer. The application framework layer may include some predefined functions. For example, the application framework layer may include a window manager, a content provider, a view system, a phone manager, a resource manager, a notification manager, etc. The phone manager is used to provide call functions for electronic devices, such as management of call status (including connecting, hanging up, etc.). The application framework layer may also include a finger joint recognition manager (FingerSenseManager) and an input module. The finger joint recognition manager can call the finger joint recognition process to identify whether the user operation is a finger joint tapping operation. The input module can monitor the input events obtained by the kernel layer. In some embodiments of the present application, the input module may include an input reader (InputReader). The input reader can be used to read input events.

[0098] The runtime is responsible for the scheduling and management of the system. The runtime includes the core library and the virtual machine. The core library consists of two parts: one is the function that the programming language (for example, the Java language) needs to call, and the other is the core library of the system. The application layer and the application framework layer run in the virtual machine. The virtual machine executes the programming files (for example, Java files) of the application layer and the application framework layer as binary files. The virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.

[0099] The system library can include multiple functional modules, such as the surface manager, media libraries, 3D graphics processing library (such as OpenGL ES), and 2D graphics engine (such as SGL). The specific meaning and function of these functional modules can be found in the relevant technical documents, which will not be described in detail here.

[0100] The Hardware Abstraction Layer (HAL) is an interface layer between the operating system kernel and the upper-level software. Its purpose is to abstract the hardware. The Hardware Abstraction Layer is an abstract interface driven by the device kernel, which is used to implement the application programming interface that provides access to the underlying device to the higher-level Java API framework. HAL can provide a standard interface to display the device hardware functions to the higher-level Java API framework. HAL contains multiple library modules (for example, camera, audio, Bluetooth, sensor and other related library modules). When the system framework layer API requires access to the hardware of the portable device, the operating system will load the library module for the hardware component.

[0101] The kernel layer is the foundation of the Android system. The kernel layer is responsible for hardware drivers, networks, power, system security, and memory management. The kernel layer is an intermediate layer between hardware and software, and its role is to pass application requests to the hardware. The kernel layer can include touch panel (TP) drivers, acceleration drivers, audio drivers, display drivers, camera drivers, and sensor drivers.

[0102] It should be noted that the application provides Figure 2B The software structure diagram of the electronic device shown is only used as an example, and does not limit the specific module division in different layers of the Android system. For details, please refer to the introduction of the Android system software structure in conventional technology. In addition, the method provided in this application can also be implemented based on other operating systems, and this application will not give examples one by one.

[0103] A data processing method provided by an embodiment of the present application is introduced below.

[0104] See also Figure 4 , Figure 4 A flowchart of a data processing method provided in an embodiment of the present application. The data processing method can be applied to electronic devices. The data processing method may include but is not limited to the following steps:

[0105] S101: In response to a first operation on a display screen, TP data and ACC data are acquired.

[0106] In response to the first operation on the display screen of the electronic device, the electronic device can obtain TP data and ACC data. It can be understood that the first operation can be a knuckle tapping operation, or other operations on the display screen.

[0107] In some embodiments of the present application, the electronic device may obtain TP data through a TP driver, and obtain ACC data through an ACC driver.

[0108] It is understandable that the TP data may represent the voltage change of the sensing point corresponding to the first operation, and may also represent the capacitance change of the sensing point. In some embodiments of the present application, the TP data may be a voltage change value. In some embodiments of the present application, the TP data may also be capacitance change data obtained after further processing of the voltage change.

[0109] In some embodiments of the present application, the electronic device obtains TP data, which may specifically include: the electronic device may obtain a*b voltage change values ​​(or TP data of a*b matrix) with the center point (or center touch point) of the first operation as the center. It is understandable that a and b may be equal or unequal. a and b may be positive integers, and the specific values ​​of a and b may be set according to actual needs, which is not limited by the present application. For example, a=b=7. In this case, in response to the first operation, the electronic device may obtain 7*7 groups of TP data.

[0110] In one possible implementation, Figure 5 As shown, the center point of the first operation can be the tapping center point.

[0111] In some embodiments of the present application, the TP data may be a voltage change value at a sensing point on the touch screen of the electronic device. In this case, in response to the first operation, the electronic device may obtain the voltage change values ​​corresponding to a*b sensing points with the sensing point closest to the center point of the first operation as the center. For example, Figure 6 As shown, in response to the first operation, the electronic device can obtain voltage change values ​​corresponding to 7*7 sensing points with the sensing point closest to the center point of the first operation as the center, that is, obtain 49 voltage change values.

[0112] For example, Figure 7 The TP data of the 7*7 matrix obtained by the electronic device with the center point of the first operation as the center is shown, with a total of 7*7 values. Among them, the 7 values ​​of the first row of the matrix are 2, -6, 3, -15, -14, -8 and -17, the 7 values ​​of the second row of the matrix are 14, 17, -11, 26, 29, 0 and 17, the 7 values ​​of the third row of the matrix are -11, 32, 204, 510, 181, 25 and -3, the 7 values ​​of the fourth row of the matrix are 15, 43, 695, 1789, 598, 38 and -42, the 7 values ​​of the fifth row of the matrix are 10, 61, 318, 618, 247, 54 and 8, the 7 values ​​of the sixth row of the matrix are 9, 40, 74, 61, 60, 12 and 9, and the 7 values ​​of the seventh row of the matrix are -11, 22, 18, -4, 11, 17 and 14. It can be understood that these 49 values ​​are data obtained after further processing of the 7*7 voltage change values, and can represent the voltage change of the sensing point caused by the first operation. Figure 7 As shown, 1789 is the TP data corresponding to the center point of the first operation.

[0113] It can be understood that the ACC data may represent the acceleration of the first operation in the vertical direction when the touch screen of the electronic device is regarded as a horizontal plane.

[0114] Similarly, in some embodiments of the present application, the electronic device obtains ACC data, which may specifically include: the electronic device may obtain c acceleration values ​​centered on the center point of the first operation. It is understandable that c is a positive integer, and the specific value of c can be set according to actual needs, and the present application does not limit this. For example, c=128. In this case, in response to the first operation, the electronic device can obtain 128 acceleration values.

[0115] In some embodiments of the present application, the ACC data may be the acceleration value in the vertical direction (perpendicular to the touch screen) at the sensing point on the touch screen of the electronic device. In this case, in response to the first operation, the electronic device may obtain the acceleration values ​​corresponding to c sensing points perpendicular to the touch screen and pointing to the touch screen, with the sensing point closest to the center point of the first operation as the center.

[0116] It is understandable that the present application does not limit the order in which the electronic device acquires TP data and ACC data. In some embodiments of the present application, the electronic device may first acquire TP data and then acquire ACC data. In other embodiments of the present application, the electronic device may first acquire ACC data and then acquire TP data. In other embodiments of the present application, the electronic device may acquire TP data and ACC data at the same time.

[0117] S102: Determine whether the acquired TP data and ACC data are valid.

[0118] After the electronic device obtains the TP data and the ACC data, it can determine whether the obtained TP data and ACC data are valid. If the TP data and ACC data obtained by the electronic device are both valid, the electronic device can continue to execute step S103. If the TP data and / or the ACC data obtained by the electronic device are invalid, the electronic device can continue to execute step S111, that is, determine that the first operation is a non-knuckle tapping operation. In this case, the electronic device can continue to respond to the first operation, or continue to respond to the input event corresponding to the first operation. It can be understood that the electronic device continues to respond to the first operation, which can specifically include: the electronic device can further process the obtained input event and distribute it to the corresponding module (for example, the corresponding application of the application layer).

[0119] In some embodiments of the present application, the electronic device determines whether the acquired TP data is valid, which may specifically include any one or more of the following: the electronic device may determine whether the acquired TP data is empty, the electronic device may determine whether the acquired TP data is 0, and the electronic device may determine whether the acquired TP data (or the TP data acquired this time) is the same as the previously acquired TP data (for example, the TP data acquired last time, i.e., the a*b voltage change values ​​acquired last time). In some embodiments of the present application, if the TP data acquired by the electronic device is not empty, not 0, and different from the previously acquired TP data, the TP data acquired by the electronic device is valid.

[0120] Similarly, in some embodiments of the present application, the electronic device determines whether the acquired ACC data is valid, which may specifically include any one or more of the following: the electronic device may determine whether the acquired ACC data is empty, the electronic device may determine whether the acquired ACC data is 0, and the electronic device may determine whether the acquired ACC data (or the ACC data acquired this time) is the same as the previously acquired ACC data (for example, the ACC data acquired last time, i.e., the c acceleration values ​​acquired last time). In some embodiments of the present application, if the ACC data acquired by the electronic device is not empty, not 0, and different from the previously acquired ACC data, the ACC data acquired by the electronic device is valid.

[0121] It is understandable that the present application does not limit the order in which the electronic device determines whether the acquired TP data is valid and determines whether the acquired ACC data is valid.

[0122] In some embodiments of the present application, the electronic device may first determine whether the acquired TP data is valid. If the TP data acquired by the electronic device is invalid, the electronic device may execute step S111, and if the TP data acquired by the electronic device is valid, the electronic device may then determine that the acquired ACC data is valid. If the ACC data acquired by the electronic device is valid, the electronic device may continue to execute step S103, and if the ACC data acquired by the electronic device is invalid, the electronic device may execute step S111.

[0123] In some embodiments of the present application, the electronic device may first determine whether the acquired ACC data is valid. If the ACC data acquired by the electronic device is invalid, the electronic device may execute step S111, and if the ACC data acquired by the electronic device is valid, the electronic device may then determine that the acquired TP data is valid. If the TP data acquired by the electronic device is valid, the electronic device may continue to execute step S103, and if the TP data acquired by the electronic device is invalid, the electronic device may execute step S111.

[0124] In some embodiments of the present application, the electronic device may simultaneously determine whether the acquired TP data is valid and whether the acquired ACC data is valid. If the TP data acquired by the electronic device is valid and the ACC data acquired by the electronic device is also valid, the electronic device may continue to execute step S103. However, if the TP data acquired by the electronic device is invalid and / or the ACC data acquired by the electronic device is invalid (or invalid data exists in the TP data and ACC data acquired by the electronic device), the electronic device may execute step S111.

[0125] S103: Determine whether the acquired TP data satisfies the TP abnormal data extreme value constraint.

[0126] When the TP data and ACC data acquired by the electronic device are both valid, the electronic device can determine whether the acquired TP data satisfies the TP abnormal data extreme value constraint. If the TP data acquired by the electronic device satisfies the TP abnormal data extreme value constraint, the electronic device can execute step S111, that is, the electronic device can determine that the first operation is a non-knuckle tapping operation. If the TP data acquired by the electronic device does not satisfy the TP abnormal data extreme value constraint, the electronic device can continue to execute step S104.

[0127] It can be understood that the electronic device can traverse the TP data it obtains, such as the a*b voltage change values ​​mentioned above, record the minimum value as min, record the maximum value as max, and then obtain the absolute value of the minimum value, i.e. Abs(min), and the absolute value of the maximum value, i.e. Abs(max), and then compare Abs(min) with Abs(max).

[0128] In some embodiments of the present application, the electronic device may call an abs() method to determine an absolute value. For example, the electronic device may call an abs() method to determine the absolute value of min.

[0129] In some embodiments of the present application, the electronic device determines whether the acquired TP data satisfies the TP abnormal data extreme value constraint, which may specifically include: The electronic device may determine whether Abs(min) is greater than Abs(max)* Coeff. If Abs(min) is greater than Abs(max)* Coeff, the TP data acquired by the electronic device satisfies the TP abnormal data extreme value constraint; if Abs(min) is not greater than Abs(max)* Coeff, the TP data acquired by the electronic device does not satisfy the TP abnormal data extreme value constraint.

[0130] Wherein, Coeff represents a coefficient. In some embodiments of the present application, Coeff can be obtained based on the original data of the finger joint (for example, the TP data previously acquired by the electronic device). In some embodiments of the present application, Coeff is greater than 0 and less than 1. For example, Coeff can be 0.8. For another example, Coeff can be 0.9. It should be noted that when the hardware configuration of the electronic device is different, the corresponding Coeff can change accordingly.

[0131] For example, Coeff may be 0.8. Figure 7 As shown, Abs(min)=42, Abs(max)=1789. In this case, Abs(min) is less than Abs(max)*0.8, indicating that the TP data obtained by the electronic device does not meet the TP abnormal data extreme value constraint.

[0132] For example, Coeff may be 0.9. Figure 8 As shown, among the 7*7 voltage change values ​​obtained by the electronic device, the minimum value is -675 and the maximum value is 631, then Abs(min)=675, Abs(max)=631, then Abs(min) is greater than Abs(max)*0.9, indicating that the TP data obtained by the electronic device meets the TP abnormal data extreme value constraint. In this case, the electronic device can determine that the first operation is a non-knuckle tapping operation.

[0133] In some embodiments of the present application, the electronic device determines whether the acquired TP data satisfies the TP abnormal data extreme value constraint, which may specifically include: The electronic device may determine whether Abs(min) is greater than Abs(max). If Abs(min) is greater than Abs(max), the TP data acquired by the electronic device satisfies the TP abnormal data extreme value constraint; if Abs(min) is not greater than Abs(max), the TP data acquired by the electronic device does not satisfy the TP abnormal data extreme value constraint.

[0134] S104: Determine whether the acquired TP data satisfies the TP abnormal data negative value constraint.

[0135] In the case where the TP data acquired by the electronic device does not satisfy the TP abnormal data extreme value constraint, the electronic device may determine whether the acquired TP data satisfies the TP abnormal data negative value constraint. If the TP data acquired by the electronic device satisfies the TP abnormal data negative value constraint, the electronic device may execute step S111, that is, the electronic device may determine that the first operation is a non-knuckle tapping operation. If the TP data acquired by the electronic device does not satisfy the TP abnormal data negative value constraint, the electronic device may continue to execute step S105.

[0136] It is understandable that the electronic device can determine the number of TP data it obtains that is less than threshold 1 (thresh1), such as the number of voltage change values less than thresh1 among the a*b voltage change values mentioned above. Among them, thresh1 is a negative number. That is to say, the electronic device can determine the number of negative value data in the TP data it obtains that is less than thresh1. For the convenience of understanding and description, this application records the negative value data in the TP data obtained by the electronic device as Neg, and records the number of data in Neg that is less than thresh1 as Num(Neg<thresh1).

[0137] It is understandable that the specific value of thresh1 can be set according to actual needs, and this application does not limit this. For example, thresh1 can be -100. For another example, thresh1 can be -200.

[0138] In some embodiments of this application, for the electronic device to determine whether the obtained TP data meets the negative value constraint of TP abnormal data, it can specifically include: the electronic device can determine whether Num(Neg<thresh1) is greater than count 1, that is, determine whether Num(Neg<thresh1) is greater than Count1. If Num(Neg<thresh1) is greater than Count1, the TP data obtained by the electronic device meets the negative value constraint of TP abnormal data. If Num(Neg<thresh1) is not greater than Count1, the TP data obtained by the electronic device does not meet the negative value constraint of TP abnormal data.

[0139] It is understandable that the specific value of Count1 can be set according to actual needs, and this application does not limit this. In some embodiments of this application, Count1 is not greater than 10. For example, Count1 can be 8. For another example, Count1 can be 5.

[0140] Exemplarily, thresh1 can be -150 and Count1 can be 7. As Fig. 9 shown, among the 7*7 voltage change values obtained by the electronic device, there are a total of 8 negative values, which are -1152, -1021, -900, -600, -500, -450, -300, and -200 respectively. It is understandable that these 8 negative values are all less than -150. That is to say, there are 8 values in the TP data obtained by the electronic device that are less than thresh1, so Num(Neg<thresh1) is greater than Count1, indicating that the TP data obtained by the electronic device meets the negative value constraint of TP abnormal data. In this case, the electronic device can determine that the first operation is not a knuckle tap operation.

[0141] In some embodiments of the present application, the electronic device determines whether the acquired TP data satisfies the negative value constraint of TP abnormal data, which may specifically include: The electronic device may determine whether the ratio of Num(Neg < thresh1) to the total number of the acquired TP data is greater than m. If the ratio of Num(Neg < thresh1) to the total number of the acquired TP data is greater than m%, then the TP data acquired by the electronic device satisfies the negative value constraint of TP abnormal data. If the ratio of Num(Neg < thresh1) to the total number of the acquired TP data is not greater than m, then the TP data acquired by the electronic device does not satisfy the negative value constraint of TP abnormal data.

[0142] It can be understood that m can be a non - negative number not greater than 1, and the specific value of m can be set according to actual needs, and the present application does not limit this. For example, m can be 0.6. For another example, m can be 0.8.

[0143] It can be understood that the total number of the TP data acquired by the electronic device can be a*b mentioned above (for example, 7*7 = 49).

[0144] S105: Determine whether the acquired TP data satisfies the mean value constraint of TP abnormal data.

[0145] In the case where the TP data acquired by the electronic device does not satisfy the extreme value constraint of TP abnormal data and does not satisfy the negative value constraint of TP abnormal data, the electronic device may determine whether the acquired TP data satisfies the mean value constraint of TP abnormal data. If the TP data acquired by the electronic device satisfies the mean value constraint of TP abnormal data, then the electronic device may execute step S111, that is, the electronic device may determine that the first operation is not a knuckle - tapping operation. If the TP data acquired by the electronic device does not satisfy the mean value constraint of TP abnormal data, then the electronic device may continue to execute step S106.

[0146] It can be understood that the electronic device may determine the number of the TP data it acquires that is less than threshold 2 (thresh2), such as the number of voltage change values less than thresh2 among the a*b voltage change values mentioned above. Among them, thresh2 is a negative number, and thresh2 is greater than thresh1. That is to say, the electronic device may determine the number of the negative - value data in the TP data it acquires that is less than thresh2. For the convenience of understanding and description, the present application records the number of the data in Neg that is less than thresh2 as Num(Neg < thresh2). It can be understood that the specific value of thresh2 can be set according to actual needs, and the present application does not limit this. For example, thresh2 can be - 50. For another example, thresh2 can be - 80.

[0147] It is understandable that the electronic device can also determine the average value of the positive data and the average value of the negative data in the acquired TP data, and determine the absolute values of these two average values respectively. According to the above, in this application, the negative data in the TP data acquired by the electronic device is denoted as Neg. For the convenience of understanding and description, in this application, the positive data in the TP data acquired by the electronic device is denoted as Pos, the average value of Pos is denoted as Avg Pos, the average value of Neg is denoted as Avg Neg, the absolute value of the average value of Pos is denoted as Abs(Avg Pos), and the absolute value of the average value of Neg is denoted as Abs(Avg Neg).

[0148] In some embodiments of this application, for the electronic device to determine whether the acquired TP data meets the TP abnormal data mean constraint, it may specifically include: the electronic device can determine whether Num(Neg < thresh2) is greater than count 2, that is, determine whether Num(Neg < thresh2) is greater than Count2, and determine whether Abs(Avg Neg) is greater than Abs(Avg Pos). If Num(Neg < thresh2) is greater than Count2 and Abs(Avg Neg) is greater than Abs(Avg Pos), then the TP data acquired by the electronic device meets the TP abnormal data mean constraint. If Num(Neg < thresh2) is not greater than Count2 or Abs(Avg Neg) is not greater than Abs(Avg Pos), then the TP data acquired by the electronic device does not meet the TP abnormal data mean constraint. That is to say, if the TP data acquired by the electronic device meets at least one of the two items that Num(Neg < thresh2) is not greater than Count2 and Abs(Avg Neg) is not greater than Abs(Avg Pos), then the TP data acquired by the electronic device does not meet the TP abnormal data mean constraint.

[0149] It is understandable that Count2 is greater than or equal to Count1. The specific value of Count2 can be set according to actual needs, and this application does not limit this. In some embodiments of this application, Count2 is not greater than 20. For example, Count2 can be 12. For another example, Count2 can be 15.

[0150] Exemplarily, Coeff can be 0.8, thresh1 can be -100, thresh2 can be -30, Count1 can be 8, and Count2 can be 15. As Figure 7 shown, Abs(min) = 42, Abs(max) = 1789. In this case, Abs(min) is less than Abs(max) * 0.8, indicating that the TP data acquired by the electronic device does not meet the TP abnormal data extreme value constraint. Further, in such as Figure 7 Among the shown 7*7 voltage change values, there are a total of 11 negative values, which are -6, -15, -14, -8, -17, -11, -11, -3, -42, -11, and -4 respectively. It can be understood that these 11 negative values are all greater than -100. That is to say, there is no value less than thresh1 in the TP data obtained by the electronic device. Then Num(Neg<thresh1) is less than Count1, indicating that the TP data obtained by the electronic device does not meet the TP abnormal data mean constraint. Further, only one of these 11 negative values is less than thresh2, that is, only -42 is less than -30. That is to say, there is 1 value less than thresh1 in the TP data obtained by the electronic device. Then Num(Neg<thresh2) is less than Count2, and Abs(Avg Neg) is less than Abs(Avg Pos), indicating that the TP data obtained by the electronic device does not meet the TP abnormal data mean constraint. In this case, the electronic device can continue to execute step S106, that is, input the obtained TP data and ACC data into the knuckle recognition model.

[0151] In some embodiments of the present application, for the electronic device to determine whether the obtained TP data meets the TP abnormal data mean constraint, it may specifically include: the electronic device can determine whether the ratio of Num(Neg<thresh2) to the total number of the obtained TP data is greater than n, and determine whether Abs(Avg Neg) is greater than Abs(Avg Pos). If Num(Neg<thresh2) is greater than n and Abs(Avg Neg) is greater than Abs(Avg Pos), then the TP data obtained by the electronic device meets the TP abnormal data mean constraint. If Num(Neg<thresh2) is not greater than n, or Abs(Avg Neg) is not greater than Abs(Avg Pos), then the TP data obtained by the electronic device does not meet the TP abnormal data mean constraint. That is to say, if the TP data obtained by the electronic device meets at least one of the two items that Num(Neg<thresh2) is not greater than n and Abs(Avg Neg) is not greater than Abs(Avg Pos), then the TP data obtained by the electronic device does not meet the TP abnormal data mean constraint.

[0152] It can be understood that n can be a non-negative number not greater than 1, and the specific value of n can be set according to actual needs, and the present application does not limit this. In some embodiments of the present application, n is greater than or equal to m. For example, m can be 0.6 and n can be 0.8.

[0153] It should be noted that step S103-step S105 can be understood as preprocessing for TP data. If the TP data acquired by the electronic device does not satisfy the TP abnormal data extreme value constraint, does not satisfy the TP abnormal data negative value constraint, and does not satisfy the TP abnormal data mean value constraint, it means that the preprocessing for the TP data is passed. In this case, the electronic device can continue to input the acquired TP data and ACC data into the finger joint recognition model.

[0154] It is understandable that the present application does not limit the order in which the electronic device executes step S103-step S105. As described above, in some embodiments of the present application, the electronic device may first execute step S103, and if the result of executing step S103 is no (i.e., the acquired TP data does not satisfy the TP abnormal data extreme value constraint), continue to execute step S104, and if the result of executing step S104 is no (i.e., the acquired TP data does not satisfy the TP abnormal data negative value constraint), execute step S105, and if the result of executing step S105 is no (i.e., the acquired TP data does not satisfy the TP abnormal data mean value constraint), execute step S106.

[0155] Similarly, in some other embodiments of the present application, the electronic device may first execute step S103, and if the result of executing step S103 is no, continue to execute step S105, and if the result of executing step S105 is no, execute step S104, and if the result of executing step S104 is no, execute step S106.

[0156] Similarly, in some other embodiments of the present application, the electronic device may first execute step S104, and if the result of executing step S104 is no, continue to execute step S103, and if the result of executing step S103 is no, execute step S105, and if the result of executing step S105 is no, execute step S106.

[0157] Similarly, in some other embodiments of the present application, the electronic device may first execute step S104, and if the result of executing step S104 is no, continue to execute step S105, and if the result of executing step S105 is no, execute step S103, and if the result of executing step S103 is no, execute step S106.

[0158] Similarly, in some other embodiments of the present application, the electronic device may first execute step S105, and if the result of executing step S105 is no, continue to execute step S103, and if the result of executing step S103 is no, execute step S104, and if the result of executing step S104 is no, execute step S106.

[0159] Similarly, in some other embodiments of the present application, the electronic device may first execute step S105, and if the result of executing step S105 is no, continue to execute step S104, and if the result of executing step S104 is no, execute step S103, and if the result of executing step S103 is no, execute step S106.

[0160] In some embodiments of the present application, during the process of the electronic device executing the above three steps (step S103, step S104 and step S105), if the execution result is yes when executing any of the steps, the electronic device can determine that the first operation is a non-knuckle tapping operation, and there is no need to continue to execute subsequent steps.

[0161] In some embodiments of the present application, the electronic device may perform one or more of the above three steps. It is understandable that the order in which the electronic device performs multiple steps of the above three steps can refer to the above, and the present application will not repeat them here. For example, the electronic device may perform step S103 and step S104 of the above three steps. Specifically, the electronic device may first perform step S103, and if the result of performing step S103 is no, perform step S104, and if the result of performing step S104 is no, perform step S106. Similarly, the electronic device may also first perform step S104, and if the result of performing step S104 is no, perform step S103, and if the result of performing step S103 is no, perform step S106.

[0162] S106: Input the acquired TP data and ACC data into the finger joint recognition model.

[0163] When the TP data acquired by the electronic device does not satisfy the extreme value constraint of the TP abnormal data, does not satisfy the mean constraint of the TP abnormal data, and does not satisfy the negative value constraint of the TP abnormal data, the electronic device can input the acquired TP data and ACC data into the finger joint recognition model. It can be understood that the finger joint recognition model may include a TP model and an ACC model. The TP model and ACC model mentioned in the present application can be understood as part of the finger joint recognition model. The TP model can be identified and output results based on the TP data acquired by the electronic device, and the ACC model can be identified and output results based on the ACC data acquired by the electronic device. Among them, the output result of the TP model can represent the probability that the first operation is a finger joint tapping operation. Similarly, the output result of the ACC model can also represent the probability that the first operation is a finger joint tapping operation. The difference is that the TP model is an identification based on the TP data, while the ACC model is an identification based on the ACC data.

[0164] In some embodiments of the present application, the finger joint recognition model is a model obtained by training a neural network.

[0165] S107: Determine whether TP model recognition fails or ACC model recognition fails.

[0166] In some embodiments of the present application, the value range of the output result of the TP model may be 0 to 1. In this case, the closer the output result of the TP model is to 1, the greater the probability that the first operation refers to the joint tapping operation. Similarly, in some embodiments of the present application, the value range of the output result of the ACC model may be 0 to 1. In this case, the closer the output result of the ACC model is to 1, the greater the probability that the first operation refers to the joint tapping operation.

[0167] In some embodiments of the present application, when the output result of the TP model is less than x1, the TP model recognition fails, and when the output result of the TP model is greater than or equal to x1, the TP model recognition succeeds. Similarly, when the output result of the ACC model is less than x2, the ACC model recognition fails, and when the output result of the ACC model is greater than or equal to x2, the ACC model recognition succeeds. It can be understood that x1 and x2 can be equal or unequal. The specific values ​​of x1 and x2 can be set according to actual needs, and the present application does not limit this. For example, x1=0.85, and x2=0.85.

[0168] Of course, the output results of the TP model and the ACC model can be expressed in other forms (for example, percentages), and this application does not limit this. For example, the output results of the TP model and the ACC model can be expressed in percentages. The specific implementation method can be referred to above, and this application will not repeat them here. For another example, the output results of the TP model and the ACC model can be 0 or 1. When the output result of the TP model / ACC model is 0, it means that the model recognition has failed, and when the output result of the TP model / ACC model is 1, it means that the model recognition has succeeded.

[0169] It can be understood that the failure of TP model recognition or ACC model recognition (or the failure of at least one of the TP model and the ACC model recognition) can indicate that the result of the knuckle recognition model recognition is that the first operation is a non-knuckle tapping operation. That is, if the electronic device determines that the TP model recognition fails or the ACC model recognition fails, the electronic device can execute step S111, that is, the electronic device can determine that the first operation is a non-knuckle tapping operation, and if the electronic device determines that the TP model recognition is successful and the ACC model recognition is successful, the electronic device can continue to execute step S108.

[0170] S108: Post-processing the output data of the finger joint recognition model.

[0171] When the TP model recognition is successful and the ACC model recognition is successful, the electronic device can post-process the output data of the finger joint recognition model. It can be understood that the finger joint recognition model not only outputs the output results corresponding to the TP model and the output results corresponding to the ACC model, but also outputs other related data. If the TP model recognition is successful and the ACC model recognition is successful, the electronic device can post-process the other related data (for example, touch area, tapping force, tapping response time, etc.).

[0172] S109: Determine whether the post-processing is passed.

[0173] The electronic device may determine whether the post-processing of other data related to the TP data and the ACC data output by the finger joint recognition model passes, or whether the post-processing is successful. If the post-processing passes, the electronic device may continue to execute step S110, and if the post-processing fails, the electronic device may continue to execute step S111.

[0174] In some embodiments of the present application, if the electronic device determines through post-processing that the touch area is greater than a certain area, and / or the electronic device determines through post-processing that the tapping force is greater than a certain force, and / or the electronic device determines through post-processing that the tapping response duration is within a certain duration range, then the electronic device can determine that the post-processing is passed, otherwise, the electronic device can determine that the post-processing is not passed. It is understandable that the above-mentioned certain area, certain force and certain duration range can be set according to actual needs, and the present application does not limit this. Among them, the tapping response duration can be understood as the duration between detecting the first operation and obtaining the ACC data.

[0175] In some embodiments of the present application, step S108 and step S109 are optional steps. After the electronic device executes step S107 and determines that both the TP model and the ACC model are successfully identified, step S110 may be executed.

[0176] S110: Determine that the first operation is a knuckle tapping operation, and perform screenshot processing.

[0177] If the TP data and ACC data are valid, the preprocessing is passed, the TP model recognition is successful, the ACC model recognition is successful, and the postprocessing is passed, the electronic device can determine that the first operation is a knuckle tapping operation. In this case, the electronic device can respond to the knuckle tapping operation and perform a screenshot process. It is understandable that the screenshot scenario can be specifically referred to Figure 1A and Figure 1B , this application will not be repeated here.

[0178] S111: Determine that the first operation is a non-knuckle tapping operation.

[0179] When it is determined that the first operation is a non-knuckle tapping operation, the electronic device may continue to respond to the first operation, such as reading and distributing the input event corresponding to the first operation, processing the input event, and responding (for example, launching the corresponding application, displaying a new interface, switching to other applications, etc., which is not limited in this application).

[0180] The following is based on Figure 2A and Figure 2B The software and hardware structure of the electronic device shown is used to introduce a specific implementation method of the above embodiment from the perspective of software and hardware interaction.

[0181] like Fig.10 As shown, the screenshot application, the knuckle recognition manager, the input module, the library module of the hardware abstraction layer and the driver of the kernel layer in the electronic device are all running in the AP of the electronic device. In response to the user's first operation on the display screen, the kernel layer of the electronic device can collect the corresponding original input event and transmit it to the device node. The input module in the electronic device can monitor the original input event of the device node. In the case where the electronic device turns on the function of triggering the screenshot by tapping the knuckles, if the input module in the electronic device detects that the device node has the original input event collected by the kernel layer, the input module can notify the knuckle recognition manager to call the knuckle recognition process. The knuckle recognition manager can call the knuckle recognition process to determine whether the first operation is a knuckle tapping operation. And, in the case of judging that the first operation is a knuckle tapping operation, the knuckle recognition manager can notify the screenshot application to take a screenshot.

[0182] See also Fig.11 , Fig.11 A flowchart of another data processing method provided in an embodiment of the present application. The method may include but is not limited to the following steps:

[0183] S201: In response to a first operation performed on a display screen, a kernel layer may obtain an input event.

[0184] It is understandable that in response to the first operation acting on the display screen, the kernel layer in the electronic device can collect (or obtain) the corresponding input event. It is understandable that the input event obtained by the kernel layer can be the original input event mentioned above. In this case, if the upload module relative to the kernel layer in the electronic device can monitor and obtain the original input event, and process the original input event (for example, preprocessing and classification of the original input event), a processed input event (for example, InputEvent object) is obtained. The upper-level module in the electronic device can read the processed input event and perform corresponding processing on the processed input event.

[0185] S202: When the input module detects that the kernel layer obtains an input event, the input module notifies the knuckle recognition manager to call a knuckle recognition process.

[0186] When the input module detects that the kernel layer obtains an input event, the input module can notify the knuckle recognition manager to call the knuckle recognition process. The knuckle recognition manager can specifically execute steps S203 to S213 when calling the knuckle recognition process. It can be understood that the input event can be an original input event or a processed input event.

[0187] In some embodiments of the present application, after the input module notifies the knuckle recognition manager to call the knuckle recognition process, the knuckle recognition manager may call the knuckle recognition library (FingerSenseLib) to specifically identify whether the first operation is a knuckle tapping operation.

[0188] S203: The knuckle recognition manager may obtain TP data from the kernel layer.

[0189] After the knuckle recognition manager calls the knuckle recognition process, it can obtain TP data from the kernel layer. It is understandable that the relevant description of TP data can refer to the above, and this application will not repeat it here.

[0190] S204: The kernel layer obtains TP data through the TP driver.

[0191] It can be understood that the knuckle recognition manager obtains the TP data from the kernel layer, which may specifically include: the knuckle recognition manager may obtain the TP data through the TP driver in the kernel layer.

[0192] S205: The kernel layer returns the TP data to the knuckle recognition manager.

[0193] After the kernel layer obtains the TP data through the TP driver, it can return (or send) the obtained TP data to the knuckle recognition manager. Correspondingly, the knuckle recognition manager can receive the TP data returned by the kernel layer.

[0194] S206: The knuckle recognition manager may obtain ACC data from the sensorhub.

[0195] After the knuckle recognition manager calls the knuckle recognition process, it can obtain ACC data from the sensorhub through the AP. It is understandable that the relevant description of ACC data can refer to the above, and this application will not repeat it here.

[0196] S207: sensorhub obtains ACC data through knuckle drive.

[0197] In some embodiments of the present application, the knuckle driver can subscribe to the data of the ACC driver, so that the ACC driver can send the ACC data it obtains to the knuckle driver. For example, the ACC driver can send the ACC data to the knuckle driver at a preset frequency. In some embodiments of the present application, the knuckle driver will only be called when the knuckle recognition manager obtains ACC data from the sensorhub. In some embodiments of the present application, the knuckle driver can store the ACC data sent by the ACC driver that it receives in a buffer. Once the knuckle recognition manager obtains ACC data from the sensorhub, the sensorhub can directly take the latest received ACC data (for example, the latest received c acceleration values) from the buffer corresponding to the knuckle driver.

[0198] S208: sensorhub returns ACC data.

[0199] After the sensorhub obtains the ACC data through the knuckle driver, it can return the obtained ACC data to the knuckle recognition manager. Correspondingly, the knuckle recognition manager in the AP can receive the ACC data returned by the sensorhub.

[0200] S209: The finger joint recognition manager determines whether the acquired TP data and ACC data are valid.

[0201] After the finger joint recognition manager obtains the TP data and the ACC data, it can determine whether the TP data and the ACC data it obtains are valid. If the TP data and the ACC data obtained by the finger joint recognition manager are valid, the finger joint recognition manager can process the obtained TP data (for details, refer to step S210). It can be understood that the specific implementation method of determining whether the obtained TP data and ACC data are valid can refer to step S102, and this application will not repeat it.

[0202] S210: When the acquired TP data and ACC data are both valid, the finger joint recognition manager pre-processes the acquired TP data.

[0203] It is understandable that when the acquired TP data and ACC data are both valid, the finger joint recognition manager can preprocess the acquired TP data. The preprocessing may include steps S103 to S105. For details, please refer to the above, and this application will not repeat them here.

[0204] S211: When the preprocessing is successful, the knuckle recognition manager inputs the acquired TP data and ACC data into the knuckle recognition model.

[0205] If the acquired TP data does not satisfy the extreme value constraint of the TP abnormal data, does not satisfy the negative value constraint of the TP abnormal data, and does not satisfy the mean constraint of the TP abnormal data, it means that the preprocessing is passed. In this case, the knuckle recognition manager inputs the acquired TP data and ACC data into the knuckle recognition model. The specific implementation method can refer to step S106, and this application will not go into details.

[0206] S212: When the TP model recognition is successful and the ACC model recognition is successful, the finger joint recognition manager performs post-processing on the output data of the finger joint recognition model.

[0207] After the finger joint recognition manager inputs the acquired TP data and ACC data into the finger joint recognition model, if the TP model recognition is successful and the ACC model recognition is successful, the finger joint recognition manager performs post-processing on the output data of the finger joint recognition model. It can be understood that the relevant description of the successful TP model recognition and the successful ACC model recognition can refer to step S107, and the relevant description of the post-processing can refer to step S108, which will not be repeated in this application.

[0208] S213: If the post-processing passes, notify the screenshot application to take the screenshot.

[0209] If the post-processing passes, the knuckle recognition manager may determine that the first operation is a knuckle tapping operation. In this case, the knuckle recognition manager may notify the screenshot application to take a screenshot.

[0210] S214: The screenshot application takes a screenshot and notifies the display screen to display the screenshot.

[0211] After the knuckle recognition manager notifies the screenshot application to take a screenshot, you can take a screenshot and notify the display to display the screenshot. For details, please refer to Figure 1B The relevant description of this application will not be repeated here.

[0212] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A data processing method, characterized in that: The method is applied to an electronic device provided with a display screen, and the method comprises: In response to a first operation on the display screen, acquiring TP data and ACC data corresponding to the first operation; In the case that the TP data and the ACC data are valid, determining whether a product of an absolute value of a maximum value in the TP data and a first coefficient is less than an absolute value of a minimum value in the TP data; If the product of the absolute value of the maximum value in the TP data and the first coefficient is less than the absolute value of the minimum value in the TP data, respond to the touch event corresponding to the first operation; if the product of the absolute value of the maximum value in the TP data and the first coefficient is greater than or equal to the absolute value of the minimum value in the TP data, determine whether the number of negative data in the TP data that is less than the second threshold is greater than the first threshold; If the number of negative data less than the second threshold in the TP data is greater than the first threshold, respond to the touch event corresponding to the first operation; if the number of negative data less than the second threshold in the TP data is less than or equal to the first threshold, determine whether the number of negative data less than a fourth threshold in the TP data is greater than a third threshold, and whether the absolute value of the mean of the negative data in the TP data is greater than the absolute value of the mean of the positive data in the TP data; If the number of negative data less than the fourth threshold in the TP data is greater than the third threshold, and the absolute value of the mean of the negative data in the TP data is greater than the absolute value of the mean of the positive data in the TP data, respond to the touch event corresponding to the first operation; if the number of negative data less than the fourth threshold in the TP data is less than or equal to the third threshold, or the absolute value of the mean of the negative data in the TP data is less than or equal to the absolute value of the mean of the positive data in the TP data, input the TP data and the ACC data into a finger joint recognition model; In the case where the first operation is determined to be a knuckle tapping operation based on the knuckle recognition model, adopting a preset processing method corresponding to the knuckle tapping operation; Among them, the first coefficient is greater than 0 and less than 1; the first threshold is a positive integer, and the second threshold is less than 0; the third threshold is a positive integer, and the third threshold is greater than or equal to the first threshold, the fourth threshold is less than 0, and the fourth threshold is greater than the second threshold; the negative value data in the TP data is the voltage change value less than 0 in the voltage change value of the sensing point corresponding to the first operation, and the positive value data in the TP data is the voltage change value greater than 0 in the voltage change value of the sensing point corresponding to the first operation.

2. The method according to claim 1, characterized in that The TP data includes voltage change values ​​corresponding to multiple sensing points; the multiple sensing points include a total of a rows and b columns of sensing points centered on a first sensing point; the first sensing point is the sensing point closest to the center point of the first operation on the display screen; a and b are both positive integers; the ACC data includes an acceleration value in the vertical direction corresponding to the first operation with the plane where the display screen is located as a horizontal plane.

3. The method according to claim 1 or 2, characterized in that After inputting the TP data and the ACC data into the finger joint recognition model, the method further comprises: Obtaining a first recognition result, a second recognition result and recognition data; the first recognition result is a recognition result corresponding to the TP model in the finger joint recognition model, and the second recognition result is a recognition result corresponding to the ACC model in the finger joint recognition model; In the case where the first recognition result and the second recognition result meet the first preset condition, determining whether the recognition data meets the second preset condition; When the identification data satisfies the second preset condition, the first operation is determined to be the knuckle tapping operation.

4. The method according to claim 1 or 2, characterized in that: Before obtaining TP data and ACC data corresponding to the first operation in response to the first operation on the display screen, the method further includes: Subscribe ACC data to ACC driver through knuckle driver; Sending ACC data to the knuckle driver at a preset frequency through the ACC driver; After receiving the ACC data sent by the ACC driver through the finger joint driver, storing the ACC data sent by the ACC driver in a buffer corresponding to the finger joint driver; In response to the first operation, acquiring ACC data corresponding to the first operation specifically includes: in response to the first operation, acquiring the latest stored c acceleration values ​​from the buffer corresponding to the finger joint drive.

5. An electronic device, characterized in that: The electronic device includes one or more memories and one or more processors; the one or more memories are coupled to the one or more processors, the memories are used to store computer program codes, the computer program codes include computer instructions, and the processor calls the computer instructions to execute the method described in any one of claims 1-4.

6. A computer-readable storage medium, characterized in that: Used to store computer instructions, when the computer instructions are executed on an electronic device, the electronic device executes any one of the methods of claims 1-4.

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