Application Interface Display Method and Device

Abstract

This application provides an application interface display method and apparatus, relating to the field of wearable device technology. The application interface display method, while in identity registration mode, pre-collects a first surface electromyography (SEMG) signal and a first pulse signal to generate a first identity feature vector. After exiting identity registration mode, it collects a second SEMG signal and a second pulse signal to generate a second identity feature vector. The user's identity verification result is determined based on the similarity between the first and second identity feature vectors. Since the first pulse signal better expresses the user's identity characteristics and the first SEMG signal is not affected by muscle movement, the reliability of the identity feature vector is enhanced. When responding to a trigger operation on the icon of a target application in the first interface, the application interface of the target application is displayed only if identity verification is successful, improving the security of the target application's privacy information and / or payment functions.

Description

Technical Field

[0001] This application relates to the field of wearable device technology, and in particular to an application interface display method and apparatus. Background Technology

[0002] Currently, with the development of wearable device technology, wearable devices have become an integral part of people's work and life. As the functionality of wearable devices increases, the functions that wearable device applications can perform and the user information they can record also increase. Typically, the recorded user information can be authenticated, and the functions can be triggered within the application interface. Some applications can display users' private information and perform payment functions. For example, WeChat can display users' chat history and payment records, SMS can display users' information records, and applications like WeChat and Alipay can perform payment functions.

[0003] Normally, users can trigger the application icon in the main interface of the wearable device's system, causing the wearable device's display to show the application interface associated with the application icon.

[0004] However, the above methods may result in the leakage of users' privacy information in the application to others; or others may use the password-free payment function in the application to cause users to suffer financial losses. Summary of the Invention

[0005] This application provides an application interface display method and apparatus that can verify the user's identity before displaying the application's interface. This, in turn, can protect the user's privacy information or assets within the application.

[0006] Firstly, this application provides an application interface display method for wearable devices. The application interface display method provided by this application includes: when the wearable device is in an identity registration mode, the wearable device acquires a first acceleration signal. When the first acceleration signal meets preset conditions, the wearable device acquires a first surface electromyography (SEMG) signal and / or a first pulse signal. The wearable device, based on the first SEMG signal and / or the first pulse signal, registers a first identity feature vector for identifying the user's identity. When the wearable device exits the identity registration mode and acquires a second acceleration signal that meets preset conditions, it acquires a second SEMG signal and / or a second pulse signal, and the wearable device displays a first interface. The first interface includes an icon of a target application. The wearable device, based on the second SEMG signal and / or the second pulse signal, generates a second identity feature vector for identifying the user's identity. When the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the application interface of the target application is displayed.

[0007] In this way, the user's first surface electromyography (SEMG) signal and first pulse signal can be pre-collected when the first acceleration signal collected by the wearable device meets preset conditions, and a first identity feature vector can be generated based on the first SEMG signal and / or the first pulse signal. Then, when the wearable device detects that the first acceleration signal meets the preset conditions again, the user's second SEMG signal and second pulse signal can be collected to generate a second identity feature vector. Furthermore, the similarity between the first and second identity feature vectors is determined, and the user's identity verification result is determined based on the determined similarity and a preset similarity threshold. Since the first pulse signal includes signal features in multiple dimensions, it better expresses the user's identity characteristics, thus enhancing the reliability of the identity feature vector. Additionally, the first SEMG signal collected by the wearable device remains unaffected by different user actions, further enhancing the reliability of the identity feature vector. When the wearable device responds to a trigger operation on a target application in the first interface, if the verification result indicates successful authentication, the application interface of the target application is displayed, satisfying the user's need to browse the target application's interface while improving the security of the target application's privacy information and / or payment functions.

[0008] In one possible implementation, when the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the application interface of the target application is displayed. This includes: the wearable device determining the similarity between the second identity feature vector and the first identity feature vector; if the similarity is greater than the preset similarity threshold, the wearable device generating and storing a first verification result. The first verification result indicates that the user's authentication has passed. If the wearable device responds to the trigger operation on the icon of the target application within a preset time period, it checks whether the first verification result is stored. If the first verification result is stored, the application interface of the target application is displayed. The first verification result of user authentication is stored so that it can be used as a basis for displaying the application interface of the target application later.

[0009] Furthermore, after the wearable device generates and stores the first verification result, the application interface display method provided in this application further includes: if no user trigger operation is responded to within a preset time period, the wearable device turns off the screen and deletes the stored first verification result. If a third acceleration signal that meets preset conditions is collected, the wearable device collects the user's third surface electromyography signal and / or third pulse signal, and displays the first interface. The wearable device generates a third identity feature vector for identifying the user's identity based on the third surface electromyography signal and / or third pulse signal. If the similarity between the third identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the wearable device generates and stores the first verification result. Thus, after the wearable device turns off the screen, the stored first verification result is deleted; after the wearable device is turned on again, the first verification result is generated and stored only after the user authentication is passed again, further improving the security of the target application's privacy information and / or payment function.

[0010] Alternatively, after the wearable device generates and stores the first verification result, the application interface display method provided in this application further includes: if the wearable device does not respond to the user's trigger operation within a preset time period, the wearable device screen turns off. If a third acceleration signal that meets preset conditions is collected, the wearable device displays the first interface. Since the first verification result has already been stored, there is no need for user authentication after the wearable device screen turns off and then on again, saving computing resources.

[0011] Alternatively, the wearable device collects multiple first identity feature vectors of the same user. The wearable device determines the similarity between a second identity feature vector and the first identity feature vectors. If the similarity is greater than a preset similarity threshold, the wearable device generates and stores a first verification result, including: the wearable device determines the similarity between the second identity feature vector and each of the multiple first identity feature vectors. If the similarity between the second identity feature vector and one of the first identity feature vectors is greater than the preset similarity threshold, the wearable device generates and stores the first verification result. Alternatively, if the proportion of similarities greater than the preset similarity threshold among the determined similarities is higher than a preset proportion, the wearable device generates and stores the first verification result. In this way, multiple users can be granted permission to open the target application.

[0012] In one possible implementation, the target application is an application of the target type. The application interface display method provided in this application further includes setting the target application to be an application of the target type. In this way, in applications on wearable devices, user authentication is only performed when the icon of an application of the target type is triggered; otherwise, user authentication is not performed when the icon of an application that is not the target type is triggered, thus saving computing resources.

[0013] Furthermore, setting the target application as a target type application includes: the wearable device displaying a second interface, which includes privacy settings options. In response to a triggering operation on the privacy settings options, the wearable device displays a third interface. This third interface displays multiple different application names, each with a toggle button next to it. In response to a triggering operation on at least one toggle button, the wearable device sets the application corresponding to the application name next to the triggered toggle button as the target type application. This allows users to select and set the target type application from among the applications on the wearable device according to their personal needs.

[0014] Alternatively, the target application can be set to a target type of application, including: the wearable device defaults to setting at least one application as the target type of application. This saves the user time and effort.

[0015] In one possible implementation, when the wearable device is in identity registration mode and before it collects the first acceleration signal, the application interface display method provided in this application further includes: the wearable device displaying a fourth interface, wherein the fourth interface includes an identity registration option. In response to a trigger operation on the identity registration option, the wearable device displays a fifth interface. The fifth interface includes operation prompts to instruct the user to raise their hand. When the fifth interface is displayed, the wearable device is in identity registration mode. Thus, the operation prompts can guide the user to perform only the identity registration operation.

[0016] In one possible implementation, the application interface display method provided in this application further includes: when the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is less than or equal to a preset similarity threshold, displaying a second prompt message on the first interface, wherein the second prompt message is used to indicate that there is no permission to open the target application. In this way, when user authentication fails, the application display interface of the target application will not be displayed, thus improving the security of the target application's privacy information and / or payment functions.

[0017] In one possible implementation, the application interface display method provided in this application further includes: the wearable device displays a third prompt message on the first interface, wherein the third prompt message is used to indicate password input. The wearable device receives the password entered on the first interface. If it is determined that the entered password matches the stored password, the wearable device displays the application display interface of the target application. In this way, the user can also authenticate using a password.

[0018] In one possible implementation, the wearable device generates a first identity feature vector to identify the user based on a first surface electromyography (SEMG) signal and / or a first pulse signal. This includes: filtering the first SEMG signal and the first pulse signal respectively to reduce noise in both signals; extracting a first feature vector from the filtered first SEMG signal and a second feature vector from the filtered first pulse signal using a pre-trained feature extraction model; assigning different weights to the first and second feature vectors using a pre-trained feature weighting model, and fusing these weighted vectors into a single identity feature vector; and mapping the identity feature vector to a sample label space using a fully connected layer to generate the first identity feature vector for identifying the user.

[0019] In one possible implementation, the preset conditions are: the component of the first acceleration signal on the X-axis is within a set first value range, the component on the Y-axis is within a set second value range, and the component on the Z-axis is within a set third value range.

[0020] Secondly, this application also provides an application interface display device for wearable devices. The application interface display device provided by this application includes: a processing unit, configured to acquire a first acceleration signal when the wearable device is in an identity registration mode. The processing unit is further configured to acquire a first surface electromyography (SEMG) signal and / or a first pulse signal when the first acceleration signal meets preset conditions. The processing unit is further configured to allow the wearable device to register a first identity feature vector for identifying the user's identity based on the first SEMG signal and / or the first pulse signal. When the wearable device exits the identity registration mode and acquires a second acceleration signal that meets preset conditions, the processing unit is further configured to acquire a second SEMG signal and / or a second pulse signal. A display unit is configured to display a first interface. The first interface includes an icon of a target application. The processing unit is further configured to generate a second identity feature vector for identifying the user's identity based on the second SEMG signal and / or the second pulse signal. When the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the display unit is configured to display the application interface of the target application.

[0021] Thirdly, this application also provides a wearable device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the wearable device performs the method as described in the first aspect of this application.

[0022] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the computer to perform the method as described in the first aspect of this application.

[0023] Fifthly, this application also provides a computer program product, including a computer program that, when run, causes a computer to perform the method as described in the first aspect of this application.

[0024] It should be understood that the second to fifth aspects of this application correspond to the technical solutions of the first aspect of this application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation are similar, and will not be repeated here.

[0025] Additionally, it should be noted that the first interface is the system main interface in the following embodiments, the second interface is the settings list interface in the following embodiments, the third interface is the application list interface in the following embodiments, the fourth interface can also be the settings list interface in the following embodiments, and the fifth interface can be the identity entry interface in the following embodiments. Attached Figure Description

[0026] Figure 1 A schematic diagram of the application interface displayed when opening SMS for the user;

[0027] Figure 2 This is a schematic diagram of the hardware system architecture of a smartwatch.

[0028] Figure 3 This is a schematic diagram of the software system architecture of a smartwatch.

[0029] Figure 4 A flowchart illustrating the application interface display method provided in this application embodiment;

[0030] Figure 5 A waveform diagram of the first acceleration signal provided in an embodiment of this application;

[0031] Figure 6 A waveform diagram of the first pulse signal provided in an embodiment of this application;

[0032] Figure 7 A waveform diagram of the first surface electromyography signal provided in the embodiments of this application;

[0033] Figure 8 A block diagram for generating a first identity feature vector provided in an embodiment of this application;

[0034] Figure 9 A block diagram illustrating user authentication when multiple first identity feature vectors are stored, as provided in this application embodiment;

[0035] Figure 10 A schematic diagram of the interface for entering identity feature vectors provided in an embodiment of this application;

[0036] Figure 11 A schematic diagram of the interface for setting up risk applications provided in an embodiment of this application;

[0037] Figure 12 One of the schematic diagrams of the application display interface for displaying SMS messages provided in the embodiments of this application;

[0038] Figure 13 A second schematic diagram of the application display interface for displaying SMS messages provided in an embodiment of this application;

[0039] Figure 14 A schematic diagram of the application display interface for displaying WeChat provided in an embodiment of this application;

[0040] Figure 15 This is a schematic diagram of the structure of an identity verification device provided in an embodiment of this application;

[0041] Figure 16 A schematic diagram of a wearable hardware structure provided in an embodiment of this application;

[0042] Figure 17 This is a schematic diagram of the structure of a chip provided in an embodiment of this application. Detailed Implementation

[0043] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. For example, the first value and the second value are only used to distinguish different values ​​and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0044] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0045] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0046] Currently, with the development of wearable device technology, wearable devices have become an integral part of people's work and life. Typically, users can trigger the application icon on the main interface of the wearable device, causing the device's display to show the interface associated with that application icon. Taking the smartwatch 100 as an example, for instance... Figure 1 As shown in (a), when a user needs to view text messages received by the smartwatch 100, they can trigger the text message icon 102 on the system main interface 101 of the smartwatch 100. Figure 1 As shown in (b), the smartwatch 100 can respond to the user's triggering operation on the SMS icon 102 in the system main interface 101 to display the SMS list interface 103. The user can then view the SMS messages sent and received by the smartwatch 100.

[0047] As can be seen, during the above process, regardless of who triggers the SMS icon 102 on the smartwatch 100's main system interface 101, the smartwatch 100 will display the SMS list interface 103. This could potentially lead to the leakage of the user's SMS records to others.

[0048] In view of this, embodiments of this application provide an application interface display method. In identity registration mode, when a hand-raising motion is detected, the wearable device collects the user's first surface electromyography (EMG) signal and first pulse signal. Then, a first identity feature vector is generated and stored based on the first EMG signal and the first pulse signal. If the wearable device exits identity registration mode and another hand-raising motion is detected, the user's second EMG signal and second pulse signal are collected. Then, a second identity feature vector is generated based on the second EMG signal and the second pulse signal.

[0049] If the similarity between the second identity feature vector and the first identity feature vector is greater than a preset similarity threshold, a first authentication result is generated and stored, indicating successful authentication. The application interface of the risky application is only displayed if a trigger action is received from the user's risky application icon and the stored first authentication result is detected. In this way, the smartwatch 100 displays the application interface of the risky application, satisfying the user's need to browse the application interface of risky applications while improving the security of the privacy information of the risky application. If the similarity between the second identity feature vector and the first identity feature vector is less than or equal to a preset similarity threshold, a second authentication result is generated and stored, indicating unsuccessful authentication. If a trigger action is received from the user's risky application icon and the stored second authentication result is detected, the application interface of the risky application is not displayed, further improving the security of the privacy information of the risky application.

[0050] It is understood that the aforementioned wearable devices can also be smart bracelets, augmented reality (AR) wearable devices, etc. The embodiments of this application do not limit the specific technology or device form used in the wearable devices.

[0051] To better understand the embodiments of this application, the following description uses a smartwatch 100 as an example of the wearable device in this application. For example, Figure 2 This is a schematic diagram of the structure of a smartwatch 100 provided in an embodiment of this application.

[0052] The smartwatch 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, antenna 1, antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, a sensor module 180, buttons 190, an indicator 192, and a display screen 194, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an electromyography (EMG) sensor 180C, a pulse sensor 180D, an accelerometer 180E, a proximity sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, etc.

[0053] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the smartwatch 100. In other embodiments of this application, the smartwatch 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0054] The processor 110 may include one or more processing units. These processing units may be independent devices or integrated within one or more processors. The processor 110 may also include memory for storing instructions and data.

[0055] USB port 130 is a USB standard compliant interface, specifically a Mini USB port, Micro USB port, USB Type-C port, etc. USB port 130 can be used to connect a charger to charge the smartwatch 100, and can also be used for data transfer between the smartwatch 100 and peripheral devices.

[0056] The charging management module 140 receives charging input from the charger. The charger can be a wireless charger or a wired charger. The power management module 141 connects the charging management module 140 to the processor 110.

[0057] The wireless communication function of the smartwatch 100 can be achieved through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor.

[0058] Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. The antennas in the smartwatch 100 can be used to cover one or more communication frequency bands. Different antennas can also be reused to improve antenna utilization.

[0059] The mobile communication module 150 can provide wireless communication solutions, including 2G / 3G / 4G / 5G, for use in the smartwatch 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves via antenna 1, and perform filtering, amplification, and other processing on the received electromagnetic waves before transmitting them to a modem processor for demodulation.

[0060] The wireless communication module 160 can provide wireless communication solutions for smartwatches 100, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), and global navigation satellite system (GNSS).

[0061] The smartwatch 100 utilizes an audio-visual processor, a display screen 194, and an application processor to achieve its display function. The GPU, a microprocessor for image processing, connects the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations and for graphics rendering.

[0062] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. In some embodiments, the smartwatch 100 may include one or N displays screens 194, where N is a positive integer greater than 1.

[0063] The external storage interface 120 can be used to connect an external storage card, such as a Micro SD card, to expand the storage capacity of the smartwatch 100. The external storage card communicates with the processor 110 through the external storage interface 120 to perform data storage functions. For example, music, video, and other files can be saved on the external storage card.

[0064] Internal memory 121 can be used to store computer executable program code, including instructions. Internal memory 121 may include a program storage area and a data storage area. For example, internal memory 121 may store a list of application categories. The application category list includes multiple application names and identifiers corresponding to each application name. As another example, internal memory 121 may also store verification results for user identity verification. The verification results may include a first verification result indicating successful authentication or a second verification result indicating unsuccessful authentication. Additionally, internal memory 121 may store a first identity feature vector generated based on a first surface electromyography signal and a first pulse signal. The principle and process of generating the first identity feature vector can be described in the following embodiments and will not be detailed here.

[0065] The smartwatch 100 can achieve audio functions such as music playback and recording through an audio module 170, speaker 170A, receiver 170B, microphone 170C, and application processor.

[0066] Audio module 170 is used to convert digital audio information into analog audio signal output, and also to convert analog audio input into digital audio signal. Speaker 170A, also called a "loudspeaker," is used to convert audio electrical signals into sound signals. Smartwatch 100 can listen to music or make hands-free calls through speaker 170A. Transceiver 170B, also called a "handpiece," is used to convert audio electrical signals into sound signals. When smartwatch 100 answers a call or voice message, it can listen to the voice by bringing the transceiver 170B close to its ear. Microphone 170C, also called a "microphone" or "voice transducer," is used to convert sound signals into electrical signals.

[0067] A pressure sensor 180A is used to sense pressure signals and convert them into electrical signals. In some embodiments, the pressure sensor 180A may be located on the display screen 194. A gyroscope sensor 180B can be used to determine the motion posture of the smartwatch 100. An electromyography (EMG) sensor 180C can be used to collect bioelectrical signals generated by the contraction of muscles on the human body surface, and a pulse signal sensor 180D can collect the pulse wave waveform signal of the human pulse. An accelerometer sensor 180E can detect the magnitude of the acceleration of the smartwatch 100 in various directions (generally three axes). A distance sensor 180F is used to measure distance. A proximity sensor 180G may include, for example, a light-emitting diode (LED) and a photodetector, such as a photodiode. An ambient light sensor 180L is used to sense ambient light intensity. A fingerprint sensor 180H is used to collect fingerprints. A temperature sensor 180J is used to detect temperature. A touch sensor 180K, also known as a "touch device". The touch sensor 180K can be set on the display screen 194. The touch sensor 180K and the display screen 194 together form a touch screen, also known as a "touch screen".

[0068] Buttons 190 include a power button, volume buttons, etc. Buttons 190 can be mechanical buttons or touch buttons. The smartwatch 100 can receive button input and generate key signal inputs related to user settings and function control of the smartwatch 100. Indicator 192 can be an indicator light, used to indicate charging status, battery level changes, and also to indicate messages, missed calls, notifications, etc.

[0069] The software system of the Smartwatch 100 can adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture, etc., which will not be elaborated here.

[0070] This application uses the layered architecture of the Android system as an example to illustrate the software structure of the smartwatch 100. Figure 3This is a software architecture block diagram of a smartwatch 100 to which this application's embodiments apply. The layered architecture divides the smartwatch 100's software system into several layers, each with a clear role and division of labor. Layers communicate with each other through software interfaces. In some embodiments, the Android system can be divided into five layers: applications, application framework, Android runtime and system libraries, hardware abstraction layer (HAL), and kernel.

[0071] The application layer can include a series of application packages. The application layer runs applications by calling the application programming interface (API) provided by the application framework layer. For example... Figure 3 As shown, the application package can include applications such as gallery, WeChat, phone, map, navigation, WLAN, Bluetooth, alarm clock, contacts, and messages.

[0072] The application framework layer provides APIs and a programming framework for applications within the application layer. The application framework layer includes predefined functions. For example... Figure 3 As shown, the application framework layer may include a window manager, content provider, view system, phone manager, resource manager, notification manager, etc.

[0073] The window manager manages windowed applications. It can retrieve screen size, determine the presence of a status bar, lock the screen, and capture screenshots. The content provider stores and retrieves data, making it accessible to applications. This data can include videos, images, audio, made and received calls, browsing history and bookmarks, and phone books. The view system includes visual controls, such as controls for displaying text and controls for displaying images. The view system is used to build applications. A display interface can consist of one or more views. For example, a display interface including a text notification icon can include views for displaying text and views for displaying images. The phone manager provides communication functionality for the smartwatch 100, such as managing call status (including connection and disconnection). The resource manager provides applications with various resources, such as localized strings, icons, images, layout files, and video files. The notification manager allows applications to display notifications in the status bar, conveying informational messages that disappear automatically after a short pause without user interaction. For example, the notification manager can be used to notify of download completion or message alerts. The notification manager can also display notifications as icons or scrolling text in the system's top status bar, such as notifications from background applications, or as dialog windows on the screen. Examples include displaying text messages in the status bar, emitting alert sounds, vibrating on a smartwatch, and flashing indicator lights.

[0074] The Android runtime consists of core libraries and a virtual machine. The Android runtime is responsible for scheduling and managing the Android system. The core libraries comprise two parts: one part contains the functionalities that Java calls, and the other part consists of the Android core libraries. The application layer and application framework layer run in the virtual machine. The virtual machine executes the Java files of the application layer and application framework layer as binary files. The virtual machine is used to perform functions such as object lifecycle management, stack management, thread management, security and exception management, and garbage collection. System libraries can include multiple functional modules. Examples include: surface manager, media libraries, 3D graphics processing libraries (e.g., OpenGL ES), and 2D graphics engines (e.g., SGL).

[0075] The hardware abstraction layer can contain multiple library modules, such as camera and motor libraries. The Android system can load the corresponding library modules for the device hardware, thereby enabling the application framework layer to access the device hardware. Device hardware can include, for example, the speaker and display in a smartwatch.

[0076] The kernel layer is the layer between hardware and software. It drives the hardware, enabling it to function. The kernel layer includes at least display drivers, audio drivers, and sensor drivers, but this embodiment does not limit this.

[0077] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be implemented independently or in combination with each other. The same or similar concepts or processes may not be described again in some embodiments.

[0078] Definitions of terms in the embodiments of this application:

[0079] Surface electromyography (SEMG) signals are the electrical signals that accompany muscle contraction. These signals vary from person to person. Therefore, SEMG signals can be used as a biometric feature for user identification.

[0080] Pulse wave signal: Pulse wave signal (photo plethysmo graphy, PPG) pulse sensor detects the pressure changes generated when an artery pulsates and converts them into light signals that can be observed and detected more intuitively.

[0081] Wavelet Transform: The wavelet transform (WT) can transform a time signal to the time-frequency domain, allowing for better observation of the signal's local characteristics and simultaneous observation of both time and frequency information. The wavelet transform inherits and develops the localization concept of the short-time Fourier transform while overcoming the drawback of the window size not changing with frequency. It provides a frequency-varying "time-frequency" window, making it an ideal tool for time-frequency signal analysis and processing. Its main characteristics are: it can fully highlight certain features of a problem through transformation; it enables localized analysis of time (space) and frequency; and it progressively refines the signal (function) at multiple scales through scaling and translation operations, ultimately achieving time subdivision at high frequencies and frequency subdivision at low frequencies. It can automatically adapt to the requirements of time-frequency signal analysis, thus focusing on any detail of the signal.

[0082] The following description uses a smartwatch 100 as an example to illustrate the application interface display method provided in this application embodiment. This example does not constitute a limitation on the embodiments of this application. The following embodiments can be combined with each other, and the same or similar concepts or processes will not be described again. Figure 4 This is a flowchart illustrating one embodiment of the application interface display method provided in this application. It should be noted that, for ease of reading, Figure 4 The application interfaces that may be involved in the steps will be described in detail in subsequent embodiments. Figure 4The corresponding implementation examples will not be described in detail. Figure 4 As shown, the application interface display method provided in this application embodiment may include:

[0083] S401: The smartwatch 100 displays an identity entry interface, which includes an exit control.

[0084] When a user needs to avoid sharing private information or payment functions on the smartwatch 100 with others, they need to open the identity registration interface to put the smartwatch 100 into identity registration mode. In identity registration mode, the smartwatch 100 can collect first surface electromyography (EMG) signals and first pulse signals to characterize the user's identity. Additionally, the smartwatch 100 exits identity registration mode when the exit control is triggered.

[0085] S402: When the smartwatch 100 detects a hand-raising motion, the smartwatch 100 collects a first surface electromyography signal and a first pulse signal.

[0086] For example, the accelerometer of the smartwatch 100 can collect a first acceleration signal from the user's arm. The processor of the smartwatch 100 can analyze the collected first acceleration signal from the arm based on a pre-trained arm-raising motion recognition model and determine whether the first acceleration signal meets preset conditions. For example, the smartwatch 100 can detect whether the first acceleration signal indicates that the user wearing the smartwatch 100 has raised their arm. For instance, the smartwatch 100 can determine that the user wearing the smartwatch 100 has raised their arm if it detects that the component of the first acceleration signal on the X-axis is within a set first value range, the component on the Y-axis is within a set second value range, and the component on the Z-axis is within a set third value range. Figure 5 As shown, in Figure 5 From top to bottom, the waveforms represent the first acceleration signal, including the X-axis component, the Y-axis component, the Z-axis component, and the first acceleration signal waveform.

[0087] Once it is determined that the user is raising their hand, the pulse signal sensor of the smartwatch 100 collects the user's first pulse signal during the hand-raising motion. Figure 6 The waveform of the first pulse signal collected from the user during the arm-raising motion is shown. The surface electromyography (EMG) sensor of the smartwatch 100 collects the first surface EMG signal from the user during the arm-raising motion. Figure 7 The waveform of the first surface electromyography signal acquired during the user's arm raising motion is shown.

[0088] It should be noted that when the smartwatch 100 is worn on a user's wrist, the first pulse signal collected by the smartwatch 100 will differ depending on the user's movements. This demonstrates that the first pulse signal is easily affected by muscle contractions during exercise. Since users typically raise their wrist to see the smartwatch 100's display before using the target type of application, the smartwatch 100 can use the first pulse signal collected during this wrist-raising motion as a reference factor for verifying the user's identity using the first identity feature vector before accessing the target type of application. Furthermore, because the first pulse signal includes multi-dimensional signal features, it is more expressive of the user's identity characteristics. Therefore, the first pulse signal can enhance the reliability of the first identity feature vector.

[0089] Furthermore, the first surface electromyography (EMG) signal is less susceptible to the effects of muscle contraction during exercise. Therefore, using the first EMG signal as another reference factor in the first identity feature vector for verifying user identity, and fusing it with the aforementioned first pulse signal to more accurately express the user's identity characteristics, can further enhance the reliability of the first identity feature vector.

[0090] Understandably, the smartwatch 100 does not cause any wounds to the arm when collecting the first surface electromyography signal and the first pulse signal. It is a non-invasive collection method with a high user experience. Moreover, it only requires the user to raise their hand to collect the signal, which is in line with the user's usage habits.

[0091] S403: The smartwatch 100 generates and stores a first identity feature vector based on the first surface electromyography signal and the first pulse signal.

[0092] For example, the specific implementation process of S403 can be as follows: Figure 8As shown, the smartwatch 100 performs wavelet transform on the first surface electromyography (EMG) signal to filter it and reduce noise. The smartwatch 100 also performs wavelet transform on the first pulse signal to filter it and reduce noise. The smartwatch 100 can input the filtered first EMG signal into a pre-trained first feature extraction model and the first pulse signal into a pre-trained second feature extraction module. The first feature extraction model extracts the first feature vector of the filtered first EMG signal and inputs it into a pre-trained feature weighting model; the second feature extraction module extracts the second feature vector of the filtered first pulse signal and inputs it into the pre-trained feature weighting model. The pre-trained feature weighting model assigns different weights to the first and second feature vectors and merges them into a single identity feature vector. A fully connected layer maps the identity feature vector to the sample label space to enhance its robustness. This completes the process of generating the first identity feature vector. Understandably, the generated first identity feature vector is also a feature vector.

[0093] It should be noted that both the first and second feature extraction models described above can be gated recurrent unit (GRU) networks. Understandably, using two GRU networks to extract the first feature vector of the filtered first surface electromyography (SEMG) signal and the second feature vector of the first pulse signal respectively allows the first and second feature vectors to have different expressive power. Alternatively, the first and second feature extraction models described above can also be the same feature extraction model, that is, a single GRU network can be used to extract the first feature vector of the filtered first SEMG signal and the second feature vector of the first pulse signal; this is not limited here. Understandably, the first and second feature extraction models are not limited to GRU networks; other temporal neural networks or deep neural networks can also be used, and this is not limited here.

[0094] It should be noted that the feature weighting model described above can be a pre-trained attention network. The method of weighting the features described above can be as follows: Assume the first feature vector of the first pulse wave signal is P, where P = [p1, p2, ..., p...]. n The second feature vector of the first surface electromyography signal is E, where E = [e1, e2, ..., e] nP and E are both n*1 vectors; the Attention network expression is: Y = F(W, C, P, E)·P + (1 - F(W, C, P, E))·E. Understandably, a pre-trained Attention network can be calculated using the formula Y = softmax(P*E). T *W+C)·P+(1-softmax(P*E T The *W+C))·E algorithm weights and fuses the first surface electromyography signal and the first pulse signal to obtain an identity feature vector. Here, Y is the fused identity feature vector, and W and C are trainable network parameters. softmax(P*E T *W+C) is the weight function. Where,

[0095]

[0096] Let be the weighting function, then the expression for the identity feature vector is:

[0097]

[0098] Furthermore, the degree of wrist raising may vary each time a user raises their wrist while using the smartwatch 100. Thus, the smartwatch 100 can repeatedly execute steps S402-S403 to store multiple distinct first identity feature vectors for the same user. This allows for subsequent verification of the same user's identity using multiple first identity feature vectors, resulting in higher reliability.

[0099] In addition, after generating the first identity feature information, the smartwatch 100 stores the first identity feature vector for later use as a reference to verify the user's identity. After successfully storing the first identity feature vector, the smartwatch 100 can display a first prompt message on the identity entry interface to indicate that the identity feature vector has been successfully entered. The first prompt message indicates successful identity entry; for example, the first prompt message can be the text message "Registration successful" or "Entry successful".

[0100] S404: Smartwatch 100 responds to the exit control trigger operation and exits the identity registration interface.

[0101] After the first identity feature vector is successfully entered, the smartwatch 100 can also exit the identity entry interface in response to the user's triggering of the exit control. In this way, the smartwatch 100 also exits the identity entry mode.

[0102] In addition, the smartphone 100 can also, in response to the user's authorization operation on the identity registration interface, collect the first surface electromyography signal and the first pulse signal of other users (e.g., family members, classmates, and friends) to generate and store the first identity feature vector. This allows other users to also have access to applications of the target type.

[0103] Sections S401-S404 above describe the process of inputting the first identity feature vector. Below, sections S405-S409 describe the process of verifying user identity.

[0104] S405: When the smartwatch 100 detects a hand-raising motion, it collects second surface electromyography signals and second pulse signals.

[0105] Generally, users will habitually raise their wrist before viewing the application interface of the target type of application on the smartwatch 100, so that they can see the display screen of the smartwatch 100. In this way, the smartwatch 100 can detect whether there is a wrist raising action in advance. The method of detecting the wrist raising action is the same as the method of detecting the wrist raising action in S402 mentioned above, and will not be repeated here.

[0106] Upon detecting a hand-raising motion, the smartwatch 100 collects a second surface electromyography (EMG) signal and a second pulse signal. The method for collecting the second EMG signal and the second pulse signal is the same as the method for collecting the first EMG signal and the first pulse signal in S402 described above, and will not be repeated here.

[0107] S406: The smartwatch 100 generates a second identity feature vector based on the second surface electromyography signal and the second pulse signal.

[0108] The method by which the smartwatch 100 generates the second identity feature vector based on the second surface electromyography signal and the second pulse signal is the same as the method in S403 above, and will not be repeated here. Understandably, like the first identity feature vector, the second identity feature vector is also a feature vector.

[0109] S407: The smartwatch 100 determines the similarity between the second identity feature vector and the stored first identity feature vector, and judges whether the similarity is greater than the preset similarity threshold. If yes, then execute S408; otherwise, execute S409.

[0110] Understandably, when only one stored first identity feature vector is included, if the similarity is greater than a preset similarity threshold, it can be determined that the first identity feature vector and the second identity feature vector are similar; if the similarity is less than or equal to the preset similarity threshold, it can be determined that the first identity feature vector and the second identity feature vector are not similar.

[0111] In addition, when multiple stored first identity feature vectors of the same user are included, S407 can be replaced by: the smartwatch 100 can determine the similarity between the second identity feature vector and multiple first identity feature vectors respectively, and determine that each similarity is compared with a preset similarity threshold. If any similarity is greater than the preset similarity threshold, the first identity feature vector and the second identity feature vector are determined to be similar; or, by using a voting decision, if the similarity exceeds a preset proportion (such as 50%) of the similarity is greater than the preset similarity threshold, the first identity feature vector and the second identity feature vector are determined to be similar.

[0112] For example, since both the first identity feature vector and the second identity feature vector are feature vectors, the above-mentioned method for calculating the similarity between the second identity feature vector and the first identity feature vector can be: calculating the cosine similarity, Euclidean distance, or Pearson correlation coefficient between the second identity feature vector and the first identity feature vector, etc., which are not limited here.

[0113] The following is combined with Figure 9 Explain how to verify a user's identity when multiple stored first identity feature vectors of the same user are included. For example... Figure 9 As shown, when the smartwatch 100 stores first identity feature vector 1, first identity feature vector 2, and first identity feature vector 3, it can calculate the similarity between the second identity feature vector and the first identity feature vector 1, first identity feature vector 2, and first identity feature vector 3, respectively, to obtain similarity 1, similarity 2, and similarity 3. Then, the smartwatch 100 compares similarity 1, similarity 2, and similarity 3 with preset similarity thresholds. If there is a similarity greater than the preset similarity threshold, the user authentication is deemed successful; otherwise, if there is no similarity greater than the preset similarity threshold, the user authentication is deemed unsuccessful.

[0114] S408: Smartwatch 100 generates and stores the first verification result, which is used to indicate that the authentication is successful.

[0115] If the first identity feature vector and the second identity feature vector are determined to be similar, authentication can be considered successful. Thus, a first verification result can be generated and stored. This stored first verification result can serve as a reference for subsequently opening applications of the target type.

[0116] S409: Smartwatch 100 generates and stores a second verification result, which is used to indicate that authentication has failed.

[0117] If the first identity feature vector and the second identity feature vector are determined to be dissimilar, authentication is considered unsuccessful. In this case, a second verification result can be generated and stored. This stored second verification result can serve as a reference for subsequently preventing the opening of applications of the target type.

[0118] The following section, in conjunction with S410-S412, describes the process of opening the application display interface of the target type application based on the verification results.

[0119] S410: In response to the trigger operation of the target application icon in the system main interface, the smartwatch 100 detects whether the target application is the target type application. If so, it executes S411 or S412.

[0120] The smartwatch 100 can pre-store a list of application categories to identify whether each application on the smartwatch 100 is a target type application. For example, applications identified by a binary field "0" are target type applications, while those identified by a binary field "1" are not. Taking an application with user privacy information or payment functions as an example, the specific content of the application category list can be, but is not limited to, as shown in Table 1 below:

[0121]

[0122] Table 1

[0123] Understandably, in Table 1 above, (Features include chat history, payment records, and other private information or payment functions), SMS (features include message history and other private information or payment functions), (with features such as chat history, payment records, and other privacy information, or payment functions), and Applications (containing private information such as call logs or payment functions) are identified as target types. It is understood that the target applications in S410 above can be, but are not limited to, applications containing private information such as call logs or payment functions. Short message, as well as Any application within the app; Weather, Alarm Clock, Health & Fitness, and Notes apps not identified as target types. It should be noted that the app identifiers in Table 1 above can be user-configured or configured at the factory for the smartwatch 100; this is not limited here. Furthermore, when a user needs to change the app identifier, they must enter a login password or register facial information. Changes can only be made after successful password or facial authentication.

[0124] S411: If the first verification result is stored, the smartwatch 100 displays the application interface of the target application.

[0125] Since the first verification result indicates that identity verification is successful, it means that the user who opened the target application's interface using the smartwatch 100 is the same user who previously entered the first identity feature vector. Thus, the smartwatch 100 displays the application interface of the target type of application, satisfying the user's need to browse the application interface of that type of application, and ensuring that the privacy information of the target type of application is not leaked to others or that their property is not lost.

[0126] S412: If the second verification result is stored, the smartwatch 100 displays a second prompt message on the system's main interface. This second prompt message indicates that the target application does not have permission to be opened.

[0127] Since the second verification result indicates that identity verification failed, meaning that the user who opened the target application's interface using the smartwatch 100 is not the user who previously entered the first identity feature vector, the smartwatch 100 will not display the target application's interface. Instead, it will display a second prompt message, which can indicate that the user does not have permission to open the target application. This ensures that the privacy information of the target application is not leaked to others or that their property is not harmed. The second prompt message can be, but is not limited to, text messages such as "No permission to open" or "Unauthorized."

[0128] Alternatively, when the smartwatch 100 responds to a user's trigger action on the icon of a non-target type application marked "1", the smartwatch 100 does not need to check the stored authentication result, but directly displays the application interface of the non-target type application. Since the non-target type application does not contain the user's privacy information or payment functions, it will not cause the user's privacy information to be leaked to others or cause property loss.

[0129] In summary, the smartwatch 100 can pre-collect the first surface electromyography (EMG) signal and the first pulse signal when the user raises their hand, and generate a first identity feature vector based on these signals. Then, when the smartwatch 100 detects another hand-raising motion, it can collect the second EMG signal and the second pulse signal when the user raises their hand, generating a second identity feature vector. Furthermore, the similarity between the first and second identity feature vectors is determined, and the verification result is determined based on the determined similarity and a preset similarity threshold. Since the first pulse signal includes signal features across multiple dimensions, it better expresses the user's identity characteristics, enhancing the reliability of the identity feature vector. Additionally, the first EMG signal collected by the smartwatch 100 remains unaffected by different user actions, further enhancing the reliability of the identity feature vector. When the smartwatch 100 responds to a trigger operation on a target type application on the system's main interface, if the verification result indicates successful authentication, the application interface of the target type application is displayed. This satisfies the user's need to browse the application interface of the target type application while improving the security of the application's privacy information and / or payment functions. If authentication fails, the smartwatch 100 will not display the application interface of the target type of application, thereby improving the security of the target type of application's privacy information and / or payment functions.

[0130] Below, we will take the wearable device as a smartwatch 100 and the target application as SMS as an example, combined with... Figures 10-14 The interface operation diagram illustrates how to achieve this. Figure 4 The corresponding embodiment describes the application interface display method.

[0131] For example, combined Figure 10 This explains how the smartwatch 100 records the first identity feature vector.

[0132] After the user wears the smartwatch 100 on their wrist, such as Figure 10 As shown in (a), the smartwatch 100 can respond to the user's trigger operation on the "Settings" icon in the system main interface 101, such as... Figure 10 As shown in (b), the settings list interface 105 is displayed. The settings list interface 105 includes an identity entry option 106. In response to the user's triggering of the identity entry option 106, the smartwatch 100 displays an identity entry interface 107 and simultaneously enters identity entry mode. The identity entry interface 107 displays operation prompts 108 indicating the wrist-raising operation, such as the text message "Please raise your hand." Additionally, the smartwatch 100 may also play a voice message saying "Please raise your hand," which is not limited here.

[0133] Once the user perceives the operation prompt information 108, they can perform a hand-raising action. The smartwatch 100 can then detect this hand-raising action and simultaneously collect the first surface electromyography (EMG) signal and the first pulse signal during the hand-raising process. The process and principle of the smartwatch 100 detecting the hand-raising action and collecting the first EMG signal and the first pulse signal can be referred to the description in S402 above, and will not be repeated here.

[0134] Then, the smartwatch 100 generates and stores a first identity feature vector based on the first surface electromyography signal and the first pulse signal to complete the input of the first identity feature vector, which will be used as a reference for verifying the user's identity later. The process and principle of the smartwatch 100 generating the first identity feature vector based on the first surface electromyography signal and the first pulse signal can be referred to the description in S403 above, and will not be repeated here.

[0135] After storing the first identity feature vector, the smartwatch 100, such as Figure 10 As shown in (c), the identity entry interface 107 displays the text message "Identity entry successful" to notify the user that identity entry was successful. Alternatively, the text message "Identity entry successful" can be replaced with messages such as "Registration successful" or "Entry complete," etc., without limitation. Understandably, the first identity feature vector can serve as one of the reference bases for verifying the user's identity before displaying the application's interface for the target type.

[0136] Furthermore, such as Figure 10 As shown in (d), after a preset time (e.g., 3s, 5s), the smartwatch 100 cancels the "Identity entry successful" message on the identity entry interface 107. Then, the smartwatch 100 displays a prompt message on the identity entry interface 107 instructing the user to enter a password. This includes the text "Please enter password," a password input box, and a save control. The smartwatch 100 can receive the password entered by the user in the password input box and, in response to the user's triggering of the save control, store the entered password. Understandably, the entered password can serve as another reference for verifying the user's identity before displaying the application interface of the target type.

[0137] like Figure 10 As shown in (e), an "Exit" control is also displayed on the identity entry interface 107. Figure 10 As shown in (f), after the first identity feature vector and password are successfully stored, the smartwatch 100 can respond to the user's trigger operation of the "exit" control, return to the system main interface 101, and exit the identity entry mode.

[0138] In addition, Figure 10 Based on the embodiment provided in (b), users can also set the target type of application according to their personal needs. Figure 10 The settings list interface 105 provided in (b) also includes privacy settings option 701. For example... Figure 11 As shown in (a), the smartwatch 100 can also display an application list interface 702 in response to the user's triggering of the privacy settings option 701. The application list interface 702 includes multiple different application names, such as WeChat, SMS, alarm clock, and phone, and a switch button 703 is provided next to each of the application names such as WeChat, SMS, alarm clock, and phone.

[0139] like Figure 11 As shown in (b), if the user feels that WeChat, SMS, and phone calls involve personal privacy information or payment functions, they can trigger the switch button 703 on the WeChat, SMS, and phone call side. The smartwatch 100 responds to the user's triggering of the switch button, turning the switch button on the WeChat, SMS, and phone call side on, while keeping the switch button on the alarm clock side off. Then, the smartwatch 100 updates the identifiers of WeChat, SMS, and phone calls in the pre-stored application category list from binary number "1" to binary number "0", while the identifier of the alarm clock in the pre-stored application category list remains binary number "1". This achieves the setting of WeChat, SMS, and phone calls as target type applications. Additionally, the smartwatch 100 can also set other applications as target type applications according to the user's needs, which is not limited here.

[0140] In addition, the identifiers for WeChat, SMS, and phone calls in the pre-stored application category list can also be identified as binary number "0" when the smartwatch 100 is manufactured. That is, WeChat, SMS, and phone calls are set as target type applications when the smartwatch 100 is manufactured, without any limitation.

[0141] Below, in conjunction with Figures 12-13 This explains how to display the SMS application interface on a smartwatch 100.

[0142] like Figure 12 As shown in (a), if the smartwatch 100 responds to any trigger operation within a preset time after the user exits the identity registration interface 107, the smartwatch 100 screen will turn off. After the smartwatch 100 screen turns off, if the user wants to view the text messages they have received, they need to raise their hand to view the smartwatch 100 display screen.

[0143] The smartwatch 100 collects a second acceleration signal. If the second acceleration signal meets preset conditions, it determines that the user wearing the smartwatch 100 has raised their hand. The method for determining the user's hand-raising action is the same as the method described above for determining the user's hand-raising action based on the first acceleration signal, and will not be repeated here. Upon detecting the hand-raising action, the smartwatch 100 collects a second surface electromyography (EMG) signal and a second pulse signal. The method for detecting the hand-raising action is the same as the method described in S402 above, and will not be repeated here. The method for the smartwatch 100 to collect the second EMG signal and the second pulse signal is the same as the method for collecting the first EMG signal and the first pulse signal in S402 above, and will not be repeated here.

[0144] The smartwatch 100 generates a second identity feature vector based on the second surface electromyography signal and the second pulse signal. The method by which the smartwatch 100 generates the second identity feature vector based on the second surface electromyography signal and the second pulse signal is the same as the method in S403 above, and will not be repeated here.

[0145] Then, the smartwatch 100 begins to verify the user's identity. For example, the method of verifying user identity can be as follows: the smartwatch 100 determines the similarity between the second identity feature vector and the stored first identity feature vector, and judges whether the similarity is greater than a preset similarity threshold. If so, the smartwatch 100 generates and stores a first verification result, which indicates that the identity verification is successful; if not, the smartwatch 100 generates and stores a second verification result, which indicates that the identity verification is unsuccessful. The process of the smartwatch 100 verifying user identity is the same as the process of the smartwatch 100 verifying user identity in S407-S409 above, and is not limited here.

[0146] Furthermore, after verifying the user's identity, the smartwatch 100 can be divided into... Figure 12 and Figure 13 The text shows two different scenarios of the SMS application display interface.

[0147] The first scenario: (e.g.) Figure 12 As shown in (a) and (b), after storing the first verification result and detecting a wrist raise, the smartwatch 100 lights up its display screen. Still as... Figure 12As shown in (b), after the smartwatch 100 lights up its display, it displays the system main interface 101, which includes an icon 102 for text messages. Furthermore, in response to the user's triggering operation on the text message icon 102, the smartwatch 100 can retrieve the text message identified as "0" from the pre-stored application category list, meaning the text message is identified as an application of the target type. The specific contents of the application category list can be found in the description of Table 1 in S410 above, and will not be repeated here. Then, the smartwatch 100 checks the stored verification results. Figure 12 As shown in (c), if the smartwatch 100 detects that the stored verification result is the first verification result, the smartwatch 100 displays the SMS application display interface 103.

[0148] Since the first verification result indicates successful identity verification, it means that the user who opened the SMS application interface using the smartwatch 100 is the same user who previously entered the first identity feature vector. Thus, the smartwatch 100 displaying the SMS application interface satisfies the user's need to browse the SMS application interface while ensuring that the privacy information in the SMS messages is not leaked to others.

[0149] The second scenario: Figure 13 As shown in (a) and (b), after storing the second verification result and detecting a wrist raise, the smartwatch 100 lights up its display. Still as... Figure 13 As shown in (b), after the smartwatch 100 lights up its display, it displays the system main interface 101, which includes an icon 102 for text messages. Furthermore, in response to the user's triggering operation on the text message icon 102, the smartwatch 100 can retrieve the text message identified as "0" from the pre-stored application category list, indicating that the text message is identified as an application of the target type. Then, the smartwatch 100 checks the stored verification results. Figure 13 As shown in (c), if the smartwatch 100 detects that the stored verification result is the second verification result, the system main interface 101 displays the second prompt message 901 "Unauthorized" to indicate that the user's identity verification failed.

[0150] Understandably, since the second verification result indicates that identity verification failed, meaning that the user who opened the target application interface using the smartwatch 100 is not the user who previously entered the first identity feature vector, the smartwatch 100 will not display the SMS application interface, ensuring that the privacy information of the SMS message is not leaked to others.

[0151] Additionally, if user authentication fails based on the second identity feature vector of the second surface electromyography signal and the second pulse signal, the smartwatch 100 can also provide a channel for user authentication based on a password. The following is in conjunction with... Figure 13 Sections (c)-(e) describe how to verify a user's identity based on a password in order to display the application's interface for the SMS message.

[0152] Upon receiving the second error message 901, the user will know that authentication has failed. For example, such as... Figure 13 As shown in (c), after the smartwatch 100 displays the second prompt message 901 on the system main interface 101 for a preset time (e.g., 2s, 3s, etc.), it cancels the display of the second prompt message 901 and displays the third prompt message 110. The third prompt message 110 is used to indicate the input of a password. The third prompt message 110 may include the text "Please enter your login password," a password input area 111, and a confirmation control 112. Figure 13 As shown in (d), the smartwatch 100 can receive the password entered by the user in the password input area 111, and in response to the user's triggering operation on the confirmation control 112, determine whether the password entered in the password input area 111 matches the stored password. If they match, as shown in (d), the smartwatch 100 can receive the password entered by the user in the password input area 111, and in response to the user's triggering operation on the confirmation control 112, determine whether the password entered in the password input area 111 matches the stored password. If they match, the smartwatch 100 can receive the password entered ... Figure 13 As shown in (e), the smartwatch 100 confirms successful user authentication and displays the SMS application display interface 103. Optionally, if not, the smartwatch 100 does not display the SMS application display interface 103, but instead displays the text message "Password entered incorrectly" on the system main interface 101. Figure 13 (Not shown in the image). After receiving the message "Incorrect password," the user will know that the application failed to open the SMS application, displaying error code 103.

[0153] Understandably, if the password entered in password input area 111 matches the stored password, it can be determined that the user opening the SMS application interface on the smartwatch 100 is the same user who previously entered the password in identity verification interface 107. Thus, displaying the SMS application interface on the smartwatch 100 satisfies the user's need to browse SMS messages, and the privacy information in the SMS messages is not leaked to others, improving the security of SMS privacy information. Conversely, if the password entered in password input area 111 does not match the stored password, it can be determined that the user opening the SMS application interface on the smartwatch 100 is not the same user who previously entered the password in identity verification interface 107. Therefore, not displaying the SMS application interface on the smartwatch 100 ensures that the privacy information in the SMS messages is not leaked to others, improving the security of SMS privacy information.

[0154] Understandably, in the above Figures 10-13The described embodiment uses SMS as the target application. Below, we will use SMS as the target application. For example, and in combination Figure 14 This describes another embodiment of the application interface display method provided in this application.

[0155] like Figure 14 As shown in (a)-(b), when a user wearing smartwatch 100 is queuing in a supermarket to pay electronically for purchased goods, they can raise their hand. The smartwatch 100 can then detect this hand-raising motion and illuminate its display screen to show the system's main interface. Simultaneously, the smartwatch 100 collects second surface electromyography (EMG) signals and second pulse signals, and generates a second identity feature vector based on these signals. The process and principle of the smartwatch 100 detecting the hand-raising motion and collecting the second EMG and pulse signals can be found in the descriptions in S402-S403 above, and will not be repeated here.

[0156] Then, the smartwatch 100 begins to verify the user's identity. For example, the method of verifying the user's identity may be as follows: the smartwatch 100 determines the similarity between the second identity feature vector and the stored first identity feature vector, determines whether the similarity is greater than a preset similarity threshold, and if so, the smartwatch 100 generates a first verification result and stores it. The first verification result is used to indicate that the identity verification is successful.

[0157] If a user has not yet been called to pay within the preset time period (e.g., 1 minute, 2 minutes), the user will not trigger the event on the system's main interface 101. The icon. Thus, as... Figure 14 As shown in (c), if the smartwatch 100 does not respond to the user's trigger operation, the smartwatch 100 will turn off the screen again and delete the stored first verification result.

[0158] When it's a user's turn to pay in the payment queue, it still works as before. Figure 14 As shown in (c) and (d), the user re-performs the hand-raising action. The smartwatch 100 collects a third acceleration signal. If the third acceleration signal meets preset conditions, it determines that the user wearing the smartwatch 100 has performed a hand-raising action. The method for determining that the user has performed a hand-raising action is the same as the method described above for determining the user has performed a hand-raising action based on the first acceleration signal, and will not be repeated here. After detecting the hand-raising action, the smartwatch 100 re-lights the display screen and displays the system main interface 101. Simultaneously, the smartwatch 100 collects the user's third surface electromyography (EMG) signal and third pulse signal, and generates a third identity feature vector based on the third EMG signal and third pulse signal.

[0159] Then, the smartwatch 100 verifies the user's identity again. For example, the method of verifying the user's identity may be as follows: the smartwatch 100 determines the similarity between the third identity feature vector and the stored first identity feature vector, determines whether the similarity is greater than a preset similarity threshold, and if so, the smartwatch 100 generates a first verification result and stores it. The first verification result is used to indicate that the identity verification is successful.

[0160] Furthermore, the smartwatch 100 responds to user requests The trigger action of the icon is retrieved from the pre-stored list of application categories. The identifier is "0", that is... Applications identified as target types are also detected. Furthermore, the smartwatch 100 checks the stored verification results. For example... Figure 14 As shown in (e), if the smartwatch 100 detects that the stored verification result is the first verification result, then the smartwatch 100 displays... The application display interface is 113. Thus, users can... The application's display interface 113 triggers the "Scan" function, allowing users to scan a payment QR code to complete the process. Payment function.

[0161] Understandably, Figure 14 The provided application interface display method requires successful user authentication before displaying the application interface when the smartwatch 100 is off. The application display interface 113. This further ensures... Others cannot use WeChat's payment function. Of course, user identity verification may also be unnecessary; the smartwatch 100 responds to user requests... After the icon is triggered, it will display The application display interface 113 can save computing resources.

[0162] In addition, the above Figures 4-14 The application interface display method provided in the embodiments of this application is illustrated by using two reference factors—a first surface electromyography (SEMG) signal and a first pulse signal—to generate a first identity feature vector, and two reference factors—a second surface electromyography (SEMG) signal and a second pulse signal—to generate a second identity feature vector to verify user identity. Alternatively, user identity can be verified by using only one reference factor—the first surface electromyography (SEMG) signal—to generate a first identity feature vector, and by using only one reference factor—the second surface electromyography (SEMG) signal—to generate a second identity feature vector. This is not limited to these methods.

[0163] In addition, the above Figures 4-14 In the application interface display method described in the embodiments of this application, the smartwatch 100, in identity registration mode, collects a user's first surface electromyography (EMG) signal and first pulse signal to generate a first identity feature vector to verify the user's identity. Alternatively, the smartwatch 100 can also collect the first EMG signals and first pulse signals of multiple users in identity registration mode and generate multiple first identity feature vectors. When verifying the user's identity, if the similarity between the second identity feature vector and one of the first identity feature vectors is greater than a preset similarity threshold, the user's identity verification is deemed successful.

[0164] In addition, the above Figures 4-14 In the description of the application interface display method provided in the embodiments of this application, the triggering operation mentioned may include: click operation, long press operation, and gesture triggering operation, etc., which are not limited here.

[0165] Please see Figure 15 This application also provides an application interface display device, including: a processing unit 1502, configured to acquire a first acceleration signal when the wearable device is in identity registration mode. The processing unit 1502 is further configured to acquire a first surface electromyography (SEMG) signal and / or a first pulse signal when the first acceleration signal meets preset conditions. In one possible implementation, the preset conditions may be: the component of the first acceleration signal on the X-axis is within a set first value range, the component on the Y-axis is within a set second value range, and the component on the Z-axis is within a set third value range. The processing unit 1502 is further configured to have the wearable device input a first identity feature vector for identifying the user's identity based on the first SEMG signal and / or the first pulse signal. When the wearable device exits the identity registration mode and acquires a second acceleration signal that meets preset conditions, the processing unit 1502 is further configured to acquire a second SEMG signal and / or a second pulse signal. A display unit 1501 is configured to display a first interface, wherein the first interface includes an icon of the target application. The processing unit 1502 is further configured to generate a second identity feature vector for identifying the user based on the second surface electromyography signal and / or the second pulse signal. When the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the display unit 1501 displays the application interface of the target application.

[0166] In one possible implementation, the processing unit 1502 is further configured to determine the similarity between the second identity feature vector and the first identity feature vector. If the similarity is greater than a preset similarity threshold, a first verification result is generated. The first verification result indicates that the user's identity verification is successful. The application interface display device further includes a storage unit 1503 for storing the first verification result. The processing unit 1502 is further configured to detect whether the first verification result is stored if the wearable device responds to a trigger operation of the target application's icon within a preset time period. The display unit 1501 is further configured to display the application interface of the target application if the first verification result is stored.

[0167] Furthermore, the processing unit 1502 is also configured to, if no user trigger operation is received within a preset time period, control the wearable device to turn off the screen and delete the stored first verification result. The processing unit 1502 is also configured to, if a third acceleration signal meeting preset conditions is collected, collect the user's third surface electromyography signal and / or third pulse signal. The display unit 1501 is also configured to display a first interface. The processing unit 1502 is also configured to, based on the third surface electromyography signal and / or the third pulse signal, generate a third identity feature vector for identifying the user's identity. The processing unit 1502 is also configured to, if the similarity between the third identity feature vector and the first identity feature vector is greater than a preset similarity threshold, generate a first verification result. The storage unit 1503 is also configured to store the first verification result.

[0168] Alternatively, the processing unit 1502 is further configured to control the wearable device to turn off its screen if the wearable device does not respond to the user's trigger operation within a preset time period. The display unit 1501 is further configured to display the first interface on the wearable device if a third acceleration signal that meets preset conditions is collected.

[0169] Alternatively, the processing unit 1502 is further configured to determine the similarity between the second identity feature vector and multiple first identity feature vectors respectively; if the similarity between the second identity feature vector and one of the first identity feature vectors is greater than a preset similarity threshold, the wearable device generates a first verification result; the storage unit 1503 is configured to store the first verification result.

[0170] Alternatively, processing unit 1502 is further configured to, when determining the proportion of similarities among a plurality of determined similarities that are greater than a preset similarity threshold, generate a first verification result if the proportion exceeds the preset threshold. Storage unit 1503 is configured to store the first verification result.

[0171] In one possible implementation, the processing unit 1502 is also configured to set the target application as an application of the target type.

[0172] Furthermore, the display unit 1501 is also configured to display a second interface, wherein the second interface includes privacy settings options. The display unit 1501 is also configured to display a third interface in response to a trigger operation on the privacy settings options. The third interface displays multiple different application names, each application name having a switch button on one side. The processing unit 1502 is also configured to, in response to a trigger operation on at least one switch button, set the application corresponding to the application name on the side of the triggered switch button as an application of the target type.

[0173] Alternatively, the processing unit 1502 is also configured to default at least one application as an application of the target type.

[0174] In one possible implementation, display unit 1501 is further configured to display a fourth interface, wherein the fourth interface includes an identity registration option. Display unit 1501 is also configured to display a fifth interface in response to a trigger operation on the identity registration option. The fifth interface includes operation prompt information to instruct the user to raise their hand. Processing unit 1502 is further configured to control the wearable device to enter an identity registration mode when the fifth interface is displayed.

[0175] The display unit 1501 is further configured to display a second prompt message on the first interface when the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is less than or equal to a preset similarity threshold. The second prompt message indicates that the user does not have permission to open the target application.

[0176] Furthermore, the display unit 1501 is also used to display a third prompt message on the first interface of the wearable device. The third prompt message is used to indicate the input of a password. The processing unit 1502 is also used to receive the password input on the first interface; if it is determined that the input password matches the stored password, then the application display interface of the target application is displayed.

[0177] In one possible implementation, processing unit 1502 is further configured to filter the first surface electromyography signal and the first pulse signal, respectively. Processing unit 1502 is further configured to extract a first feature vector of the filtered first surface electromyography signal and a second feature vector of the filtered first pulse signal using a pre-trained feature extraction model. Processing unit 1502 is further configured to assign different weights to the first feature vector and the second feature vector respectively using a pre-trained feature weighting model, and to fuse the first feature vector and the second feature vector with different weights into a single identity feature vector. Processing unit 1502 is further configured to map the identity feature vector to a sample label space through a fully connected layer to generate a first identity feature vector for identifying the user's identity.

[0178] For example, Figure 16 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application, such as... Figure 16 As shown, the electronic device includes a processor 1601, a communication line 1604, and at least one communication interface. Figure 16 (The example provided uses communication interface 1603 as an example.)

[0179] The processor 1601 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present application.

[0180] Communication line 1604 may include circuitry for transmitting information between the aforementioned components.

[0181] Communication interface 1603 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, wireless local area networks (WLAN), etc.

[0182] Possibly, the electronic device may also include a memory 1602.

[0183] The memory 1602 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory may exist independently and be connected to the processor via communication line 1604. The memory may also be integrated with the processor.

[0184] The memory 1602 stores computer execution instructions for implementing the scheme of this application, and the processor 1601 controls the execution. The processor 1601 executes the computer execution instructions stored in the memory 1602, thereby implementing the application interface display method provided in the embodiments of this application.

[0185] It is possible that the computer execution instructions in the embodiments of this application may also be referred to as application code, and the embodiments of this application do not specifically limit this.

[0186] In a specific implementation, as one example, the processor 1601 may include one or more CPUs, for example... Figure 16 CPU0 and CPU1 in the CPU.

[0187] In a specific implementation, as one example, an electronic device may include multiple processors, for example... Figure 16 Processors 1601 and 1605 are mentioned. Each of these processors can be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor here can refer to one or more devices, circuits, and / or processing cores used to process data (such as computer program instructions).

[0188] For example, Figure 17 This is a schematic diagram of a chip structure provided in an embodiment of this application. Chip 170 includes one or more processors 1710 and a communication interface 1730.

[0189] In some implementations, memory 1740 stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof.

[0190] In this embodiment, memory 1740 may include read-only memory and random access memory, and provides instructions and data to processor 1710. A portion of memory 1740 may also include non-volatile random access memory (NVRAM).

[0191] In this embodiment, the memory 1740, the communication interface 1730, and the memory 1740 are coupled together via a bus system 1720. The bus system 1720 may include a data bus, a power bus, a control bus, and a status signal bus, in addition to the data bus. For ease of description, in... Figure 17 The general labeled all buses as Bus System 1720.

[0192] The methods described in the embodiments of this application can be applied to or implemented by processor 1710. Processor 1710 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuit in the hardware of processor 1710 or by instructions in software form. The processor 1710 may be a general-purpose processor (e.g., a microprocessor or conventional processor), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates, transistor logic devices, or discrete hardware components. Processor 1710 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention.

[0193] The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can be located in mature storage media in the art, such as random access memory, read-only memory, programmable read-only memory, or electrically erasable programmable read-only memory (EEPROM). This storage medium is located in memory 1740, and processor 1710 reads information from memory 1740 and, in conjunction with its hardware, completes the steps of the above method.

[0194] In the above embodiments, the instructions stored in the memory for execution by the processor can be implemented in the form of a computer program product. This computer program product can be pre-written into the memory, or it can be downloaded and installed into the memory as software.

[0195] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. For example, available media may include magnetic media (e.g., floppy disks, hard disks, or magnetic tapes), optical media (e.g., digital versatile discs (DVDs)), or semiconductor media (e.g., solid-state disks (SSDs)).

[0196] This application also provides a computer-readable storage medium. The methods described in the above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any combination thereof. The computer-readable medium may include computer storage media and communication media, and may also include any medium capable of transferring a computer program from one place to another. The storage medium can be any target medium accessible by a computer.

[0197] As one possible design, computer-readable media may include compact disc read-only memory (CD-ROM), RAM, ROM, EEPROM, or other optical disc storage; computer-readable media may also include disk storage or other disk storage devices. Furthermore, any connecting cable may also be appropriately referred to as computer-readable media. For example, if software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of media. As used herein, disks and optical discs include optical discs (CD), laser discs, optical discs, digital versatile discs (DVD), floppy disks, and Blu-ray discs, where disks typically reproduce data magnetically, while optical discs optically reproduce data using lasers.

[0198] The above combinations should also be included within the scope of computer-readable media. The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for displaying an application interface, characterized in that, Applied to wearable devices, the method includes: When the wearable device is in identity registration mode, the wearable device collects a first acceleration signal; When the first acceleration signal meets the preset conditions, the wearable device acquires the first surface electromyography signal and / or the first pulse signal; wherein, the first surface electromyography signal and / or the first pulse signal are signals acquired during the user's arm raising action; The wearable device records a first identity feature vector for identifying the user based on the first surface electromyography signal and / or the first pulse signal; When the wearable device exits the identity registration mode and the wearable device acquires a second acceleration signal that meets the preset conditions, it acquires a second surface electromyography signal and / or a second pulse signal, and the wearable device displays a first interface, wherein the first interface includes an icon of the target application; The wearable device generates a second identity feature vector for identifying the user based on the second surface electromyography signal and / or the second pulse signal; When the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the application interface of the target application is displayed. The wearable device generates a first identity feature vector for identifying the user based on a first surface electromyography signal and / or a first pulse signal, including: The wearable device filters the first surface electromyography signal and the first pulse signal, respectively. The wearable device extracts the first feature vector of the filtered first surface electromyography signal and the second feature vector of the filtered first pulse signal through a pre-trained feature extraction model. The wearable device assigns different weights to the first feature vector and the second feature vector respectively through a pre-trained feature weighting model, and merges the first feature vector and the second feature vector with different weights into a single identity feature vector. The wearable device maps the identity feature vector to the sample label space through a fully connected layer to generate a first identity feature vector for identifying the user.

2. The method according to claim 1, characterized in that, When the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the application interface of the target application is displayed, including: The wearable device determines the similarity between the second identity feature vector and the first identity feature vector; If the similarity is greater than a preset similarity threshold, the wearable device generates and stores a first verification result, wherein the first verification result is used to indicate that the user's identity verification is successful; If the wearable device responds to the trigger operation of the target application's icon within a preset time period, it is then checked whether the first verification result is stored. If the first verification result is stored, the application interface of the target application is displayed.

3. The method according to claim 2, characterized in that, After the wearable device generates and stores the first verification result, the method further includes: If no response is received from the user within a preset time period, the wearable device will turn off its screen and delete the stored first verification result. If a third acceleration signal that meets the preset conditions is acquired, the wearable device acquires the user's third surface electromyography signal and / or third pulse signal, and displays the first interface; The wearable device generates a third identity feature vector for identifying the user based on the third surface electromyography signal and / or the third pulse signal. If the similarity between the third identity feature vector and the first identity feature vector is greater than a preset similarity threshold, the wearable device generates and stores a first verification result.

4. The method according to claim 2, characterized in that, After the wearable device generates and stores the first verification result, the method further includes: If the wearable device does not respond to the user's trigger operation within a preset time period, the wearable device screen will turn off. If a third acceleration signal that meets the preset conditions is collected, the wearable device displays the first interface.

5. The method according to claim 2, characterized in that, The wearable device collects multiple first identity feature vectors of the same user. The wearable device determines the similarity between the second identity feature vector and the first identity feature vector. If the similarity is greater than a preset similarity threshold, the wearable device generates and stores a first verification result, including: The wearable device determines the similarity between the second identity feature vector and multiple first identity feature vectors, respectively; If the similarity between the second identity feature vector and one of the first identity feature vectors is greater than a preset similarity threshold, the wearable device generates and stores the first verification result. Alternatively, if the proportion of similarities among a given plurality of similarities that are greater than a preset similarity threshold is higher than a preset proportion, the wearable device generates and stores the first verification result.

6. The method according to claim 1, characterized in that, The target application is a target type of application, and the method further includes: Set the target application to the target type.

7. The method according to claim 6, characterized in that, Setting the target application to be an application of the target type includes: The wearable device displays a second interface, which includes privacy settings options; In response to a triggering operation of the privacy settings option, the wearable device displays a third interface, which displays multiple different application names, each with a switch button on one side. In response to a triggering operation of at least one of the switch buttons, the wearable device sets the application corresponding to the application name on the side of the triggered switch button as the application of the target type.

8. The method according to claim 7, characterized in that, Setting the target application to be the target type includes: The wearable device is configured by default to have at least one application of the target type.

9. The method according to claim 1, characterized in that, Before the wearable device acquires the first acceleration signal while in identity registration mode, the method further includes: The wearable device displays a fourth interface, which includes an identity entry option; In response to the triggering operation of the identity registration option, the wearable device displays a fifth interface, wherein the fifth interface includes operation prompt information, which is used to instruct the user to raise their hand; When the fifth interface is displayed, the wearable device is in identity registration mode.

10. The method according to claim 1, characterized in that, The method further includes: When the wearable device receives a trigger operation on the icon of the target application, and the similarity between the second identity feature vector and the first identity feature vector is less than or equal to a preset similarity threshold, a second prompt message is displayed on the first interface, wherein the second prompt message is used to indicate that there is no permission to open the target application.

11. The method according to claim 10, characterized in that, The method further includes: The wearable device displays a third prompt message on the first interface, wherein the third prompt message is used to indicate the input of a password; The wearable device receives the password entered on the first interface; If the entered password matches the stored password, the wearable device will display the application interface of the target application.

12. The method according to any one of claims 1-10, characterized in that, The preset conditions are: the component of the first acceleration signal on the X-axis is within a set first value range, the component on the Y-axis is within a set second value range, and the component on the Z-axis is within a set third value range.

13. A wearable device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it causes the wearable device to perform the method as described in any one of claims 1 to 12.

14. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it causes the computer to perform the method as described in any one of claims 1 to 12.

15. A computer program product, characterized in that, Includes a computer program that, when run, causes a computer to perform the method as described in any one of claims 1 to 12.

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