A balance ability detection method and device

Abstract

The application provides a balance ability detection method and device. A wearable device and a foot movement sensor establish a communication connection, the wearable device is worn on the wrist of a user, and the foot movement sensor is worn on the right ankle of the user. The wearable device receives first movement data sent by the foot movement sensor, the first movement data being movement data when the user walks naturally; the wearable device obtains a dynamic balance score when the user walks naturally based on the first movement data; the wearable device collects second movement data, the second movement data being movement data when the user stands on one leg with eyes closed; the wearable device obtains a static balance score when the user stands on one leg with eyes closed based on the second movement data; and the wearable device obtains a comprehensive score of the balance ability of the user based on the dynamic balance score and the static balance score. The comprehensive score of the balance ability of the user is obtained through the combination of static balance detection and dynamic balance detection, and the accuracy of the balance ability detection of the user is improved.

Description

Technical Field

[0001] This application relates to the field of wearable technology, and in particular to a method and device for detecting balance ability. Background Technology

[0002] Good motor skills are an important factor in children's healthy growth, and motor skills are mainly affected by the development of the nervous and muscular systems. Poor coordination of the nervous and muscular systems often manifests as poor balance.

[0003] The industry typically uses professional balance devices to measure users' balance abilities. Users, guided by voice commands, sequentially perform actions such as standing with their eyes open and closed, and walking in a straight line. The device then calculates the user's balance health based on changes in plantar pressure. However, professional balance devices are expensive and their use is limited in certain locations. Some universities and research institutions use force-measuring devices such as six-dimensional force plates and pressure treadmills to measure plantar pressure, combining this with self-developed algorithms to analyze users' balance abilities. However, these testing conditions are quite complex. Further research is needed to develop a simple, convenient, and low-cost method for monitoring balance abilities. Summary of the Invention

[0004] This application provides a method and device for testing balance ability, which realizes the comprehensive score of the user's balance ability by combining static balance test and dynamic balance test, thereby improving the accuracy of the user's balance ability test.

[0005] In a first aspect, this application provides a balance ability detection method. The method is applied to a wearable device and a foot motion sensor, wherein the wearable device and the foot motion sensor establish a communication connection. The wearable device is worn on the user's wrist, and the foot motion sensor includes a first foot motion sensor and a second foot motion sensor. The first foot motion sensor is worn on the user's left ankle, and the second foot motion sensor is worn on the user's right ankle. The foot motion sensor includes one or more motion sensors. The method includes: the wearable device receiving first motion data sent by the foot motion sensor, the first motion data being motion data of the user during natural walking; the wearable device obtaining a dynamic balance score during natural walking based on the first motion data; the wearable device collecting second motion data, the second motion data being motion data of the user standing on one leg with eyes closed; the wearable device obtaining a static balance score during standing on one leg with eyes closed based on the second motion data; and the wearable device obtaining a comprehensive balance ability score for the user based on the dynamic balance score and the static balance score.

[0006] Wearable devices can be devices such as smartwatches / smart bracelets.

[0007] The communication connection can be a Bluetooth connection or other communication connection.

[0008] In this application, dynamic balance can be measured first, followed by static balance. Alternatively, static balance can be measured first, followed by dynamic balance; this application does not limit the choice.

[0009] The first motion data is the motion data of the user's feet collected by the foot motion sensor.

[0010] The second type of motion data is motion data collected from the user's wrist by wearable devices.

[0011] This technology enables wearable devices to obtain a comprehensive score of a user's balance ability by combining static and dynamic balance detection, thereby improving the accuracy of user balance ability detection.

[0012] In conjunction with the first aspect, in one possible implementation, before the wearable device receives the first motion data sent by the foot motion sensor, the method further includes: the wearable device receiving third motion data sent by the foot motion sensor, the third motion data being motion data of the user walking; if the wearable device determines gait parameters based on the third motion data, the wearable device outputs a first audio signal, the first audio signal being used to prompt the user to start walking naturally and measure dynamic balance; the wearable device receiving the first motion data sent by the foot motion sensor specifically includes: in response to the first audio signal, the wearable device receiving the first motion data sent by the foot motion sensor.

[0013] If gait parameters are available, meaning that each different gait parameter has a value, then it can be determined that the user is walking.

[0014] If there are no gait parameters, that is, no gait parameters are detected or each different gait parameter is 0, it can be determined that the user is not walking or the foot motion sensor is not worn properly.

[0015] Before starting the dynamic balance measurement, the wearable device can first detect the presence of gait parameters, thereby verifying whether the foot motion sensors are properly worn. Once gait parameters are detected, it can be confirmed that the foot motion sensors are worn correctly, and the wearable device can output a voice prompt to the user to begin walking naturally to measure the dynamic balance. This prevents inaccurate measurements caused by the wearable device not being properly worn before starting the dynamic balance measurement.

[0016] In conjunction with the first aspect, in one possible implementation, gait parameters include one or more of the following: stride length, swing time, ground contact time, ground contact angle, ground lift angle, cadence, gait speed, foot force, knee force, and foot roll angle.

[0017] In conjunction with the first aspect, in one possible implementation, the first motion data includes motion data of M gaits, of which p are valid gaits and q are invalid gaits, where p is greater than or equal to a preset number of steps. The wearable device obtains a dynamic balance score for natural walking based on the first motion data, specifically including: the wearable device discarding motion data of the q invalid gaits; the wearable device obtaining gait parameters of the p valid gaits based on the motion data of the p valid gaits; and the wearable device obtaining a dynamic balance score for natural walking based on the gait parameters of the p valid gaits.

[0018] In this way, invalid gait patterns may occur during a user's natural walking process. Wearable devices can discard the motion data of invalid gait patterns and obtain a dynamic balance score based solely on the motion data of valid gait patterns during natural walking. This can improve the accuracy of dynamic balance measurements.

[0019] In conjunction with the first aspect, in one possible implementation, the wearable device obtains a dynamic balance score for natural walking based on the gait parameters of p effective gaits. Specifically, this includes: the wearable device obtaining the gait symmetry and gait variability of p effective gaits based on the gait parameters of p effective gaits; and the wearable device obtaining a dynamic balance score for natural walking based on the gait symmetry and gait variability of p effective gaits.

[0020] In this way, the user's dynamic balance score can be obtained based on the gait symmetry and gait variability of p effective gaits.

[0021] In conjunction with the first aspect, in one possible implementation, before the wearable device collects the second motion data, the method further includes: when the wearable device determines that a finger on the wrist not wearing the wearable device is touching the screen of the wearable device, the wearable device outputs a second audio signal to prompt the user to close their eyes and stand on one leg and measure static balance; the wearable device collects the second motion data, specifically including: in response to the second audio signal, the wearable device collects the second motion data.

[0022] Here, the touch of the fingers on the wrist of the user not wearing the wearable device to the wearable device screen can serve as a trigger condition for starting the static balance measurement. If the wearable device detects that the fingers on the wrist of the user not wearing the wearable device are not touching the wearable device screen, the wearable device can prompt the user via voice to place both hands in front of their chest and touch the fingers on the wearable device screen. If the fingers on the wrist of the user not wearing the wearable device are touching the wearable device screen, the wearable device can prompt the user via voice to begin measuring static balance by closing their eyes and standing on one leg.

[0023] In conjunction with the first aspect, in one possible implementation, before the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data, the method further includes: the wearable device obtaining real-time swing amplitude and real-time swing frequency based on the second motion data; and if the real-time swing amplitude and real-time swing frequency meet preset values, the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data.

[0024] Real-time swing amplitude and real-time swing frequency can be the user's real-time swing amplitude and real-time swing frequency.

[0025] This allows for the determination of whether a user's posture while standing on one leg with their eyes closed is stable based on real-time swing amplitude and frequency. If the real-time swing amplitude and frequency do not meet preset values, it indicates that the user's body is swaying significantly and they are not yet stable. In this case, static balance cannot be measured. Once the user's posture while standing on one leg with their eyes closed is stable, i.e., after the real-time swing amplitude and frequency meet the preset values, a static balance score can be obtained based on the collected motion data. This improves the accuracy of static balance measurements.

[0026] In conjunction with the first aspect, in one possible implementation, after the wearable device collects the second motion data, the method further includes: the wearable device stopping the collection of motion data.

[0027] After both static and dynamic balance measurements are completed, the wearable device can stop collecting motion data to reduce its power consumption.

[0028] In some embodiments, after the dynamic balance measurement is completed, such as after obtaining a dynamic balance score, or after the wearable device acquires the first motion data, the wearable device can send a message to the foot motion sensor, instructing the foot motion sensor to stop collecting motion data, in order to reduce the power consumption of the foot motion sensor.

[0029] In conjunction with the first aspect, in one possible implementation, the wearable device stops collecting motion data, specifically including: during the period when the wearable device is collecting second motion data, if it is detected that the fingers of the wrist not wearing the wearable device are constantly touching the screen of the wearable device, and the duration of the second motion data is longer than the first duration, the wearable device stops collecting motion data.

[0030] In other words, when measuring static balance, if the fingers of the wrist not wearing the wearable device remain on the screen of the wearable device, and the data collection time for motion data while standing on one leg exceeds a preset duration (the first duration), then the second data can confirm static balance. In other words, the fact that the fingers of the wrist not wearing the wearable device remain on the screen and the duration of the second motion data exceeds the first duration can serve as a trigger condition for ending the static balance measurement. The wearable device can then stop collecting motion data to reduce its power consumption.

[0031] In other possible implementations, the wearable device could stop collecting motion data after obtaining a static balance score, in order to reduce the power consumption of the wearable device.

[0032] In conjunction with the first aspect, in one possible implementation, the wearable device stops collecting motion data, specifically including: after the wearable device collects second motion data, the fingers of the wrist not wearing the wearable device stop touching the screen of the wearable device, and the duration of the second motion data is greater than the second duration but less than the first duration, at which point the wearable device stops collecting motion data.

[0033] The termination of static balance measurement can also be triggered when the fingers on the wrist not wearing the wearable device stop touching the screen of the wearable device and the duration of the second motion data is greater than the second duration but less than the first duration.

[0034] In conjunction with the first aspect, in one possible implementation, the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data, specifically including: the wearable device obtaining the average swing amplitude and average swing frequency based on the second motion data; and the wearable device obtaining a static balance score for standing on one leg with eyes closed based on the duration, average swing amplitude, and average swing frequency of the second motion data.

[0035] The average swing amplitude and average swing frequency can be the average swing amplitude and average swing frequency of the user's body.

[0036] In this way, a static balance score can be obtained when the user stands on one leg with their eyes closed, based on the average swing amplitude and average swing frequency when the user stands on one leg, and the duration of the second motion data.

[0037] In conjunction with the first aspect, in one possible implementation, the method further includes: the wearable device receiving third motion data sent by the foot motion sensor; the wearable device obtaining the motion trajectory of the user's two feet based on the third motion data; and, if the motion trajectory satisfies a first condition, the wearable device determining that the user is in a single-leg standing state.

[0038] The first condition can be the movement trajectory from standing on both feet to slowly raising the other foot to standing on one foot.

[0039] In this way, during the static balance measurement process, the wearable device can determine whether the user is in a single-leg standing posture based on the motion data collected by the foot motion sensor.

[0040] In conjunction with the first aspect, in one possible implementation, the method further includes: the wearable device receiving multiple image frames sent by the first electronic device, the multiple image frames being image frames captured by the camera of the first electronic device when facing the user; the wearable device obtaining the movement trajectory of the user's two feet based on the multiple image frames; and, if the movement trajectory satisfies a second condition, the wearable device determining that the user is in a single-leg standing state.

[0041] The second condition can be the movement trajectory from standing on both feet to slowly lifting the other foot back to standing on one foot. The second condition can be the same as or different from the first condition.

[0042] The first electronic device can be a mobile phone, tablet, or other electronic device.

[0043] In this way, other electronic devices can determine whether a user is standing on one leg.

[0044] In conjunction with the first aspect, in one possible implementation, the method further includes: the wearable device obtaining the real-time swaying frequency of the user's torso during the acquisition of the second motion data based on the second motion data; and determining that the user is in a closed-eye state when the real-time swaying frequency is greater than a preset frequency.

[0045] In this way, wearable devices can determine whether a user is in a closed-eye state based on the second motion data.

[0046] In one possible implementation, the method further includes: the wearable device receiving multiple image frames sent by the first electronic device, the multiple image frames being image frames captured by the camera of the first electronic device when facing the user; the wearable device determining, based on the multiple image frames, that both of the user's eyes are closed, and the wearable device being able to determine that the user is in a closed-eye state.

[0047] Secondly, this application provides a balance ability detection system, which includes a wearable device and a foot motion sensor. The wearable device and the foot motion sensor establish a communication connection. The wearable device is worn on the user's wrist. The foot motion sensor includes a first foot motion sensor and a second foot motion sensor. The first foot motion sensor is worn on the user's left ankle, and the second foot motion sensor is worn on the user's right ankle. The foot motion sensor includes one or more motion sensors.

[0048] Among them, the foot motion sensor is used to collect the first motion data and send the first motion data to the wearable device. The first motion data is the motion data when the user walks naturally.

[0049] Wearable devices are used to receive initial motion data from foot motion sensors.

[0050] Wearable devices are also used to obtain dynamic balance scores during natural walking based on the first motion data.

[0051] Wearable devices are also used to collect second motion data, which is the motion data of a user standing on one leg with their eyes closed.

[0052] Wearable devices are also used to obtain static balance scores when standing on one leg with eyes closed, based on second motion data.

[0053] Wearable devices are also used to obtain a user's overall balance score based on dynamic and static balance scores.

[0054] Wearable devices can be devices such as smartwatches / smart bracelets.

[0055] The communication connection can be a Bluetooth connection or other communication connection.

[0056] In this application, dynamic balance can be measured first, followed by static balance. Alternatively, static balance can be measured first, followed by dynamic balance; this application does not limit the choice.

[0057] In conjunction with the second aspect, in one possible implementation, the foot motion sensor is also used to: collect third motion data and send the third motion data to the wearable device, wherein the third motion data is motion data of the user walking.

[0058] The wearable device is also used to output a first audio signal when gait parameters are determined based on third motion data. The first audio signal is used to prompt the user to start walking naturally and to measure dynamic balance.

[0059] A wearable device, specifically used to receive first motion data sent by a foot motion sensor in response to a first audio signal.

[0060] In conjunction with the second aspect, in one possible implementation, gait parameters include one or more of the following: stride length, swing time, ground contact time, ground contact angle, ground lift angle, cadence, gait speed, foot force, knee force, and foot roll angle.

[0061] In conjunction with the second aspect, in one possible implementation, a motion data set includes motion data for M gaits, of which p are valid gaits and q are invalid gaits, where p is greater than or equal to a preset number of steps.

[0062] Wearable devices are specifically used for:

[0063] Discard the motion data of q invalid gaits.

[0064] Gait parameters for p effective gait states are obtained based on the motion data of p effective gait states.

[0065] The dynamic balance score during natural walking is obtained based on the gait parameters of p effective gaits.

[0066] In conjunction with the second aspect, in one possible implementation, the wearable device is specifically used for:

[0067] Based on the gait parameters of p effective gaits, we obtain the gait symmetry and gait variability of p effective gaits.

[0068] The dynamic balance score during natural walking is obtained based on the gait symmetry and gait variability of p effective gaits.

[0069] In conjunction with the second aspect, in one possible implementation, the wearable device is also used to output a second audio signal when it is determined that a finger on the wrist of the user not wearing the wearable device is touching the screen of the wearable device. The second audio signal is used to prompt the user to begin closing their eyes and standing on one leg and measuring static balance.

[0070] Wearable devices, specifically used to collect second motion data in response to a second audio signal.

[0071] In conjunction with the second aspect, in one possible implementation, the wearable device is also used for:

[0072] The real-time swing amplitude and real-time swing frequency are obtained based on the second motion data.

[0073] When the real-time swing amplitude and real-time swing frequency meet the preset values, the wearable device obtains a static balance score when standing on one leg with eyes closed based on the second motion data.

[0074] In conjunction with the second aspect, in one possible implementation, the wearable device is also used to: stop collecting motion data.

[0075] In conjunction with the second aspect, in one possible implementation, the wearable device is specifically configured to stop collecting motion data if, during the period when the wearable device is collecting second motion data, it detects that the fingers of the wrist not wearing the wearable device are constantly touching the screen of the wearable device, and the duration of the second motion data is longer than the first duration.

[0076] Another possible implementation is to stop collecting motion data after obtaining a static balance score, in order to reduce the power consumption of the wearable device.

[0077] In conjunction with the second aspect, in one possible implementation, the wearable device is specifically used such that, after collecting the second motion data, the fingers of the wrist not wearing the wearable device stop touching the screen of the wearable device, and the duration of the second motion data is greater than the second duration but less than the first duration, and the collection of motion data stops.

[0078] In conjunction with the second aspect, in one possible implementation, the wearable device is specifically used for:

[0079] The average swing amplitude and average swing frequency are obtained based on the second motion data.

[0080] The static balance score for standing on one leg with eyes closed is obtained based on the duration, average swing amplitude, and average swing frequency of the second motion data.

[0081] In conjunction with the second aspect, in one possible implementation, the wearable device is further configured to: receive third motion data sent by the foot motion sensor; obtain the motion trajectory of the user's two feet based on the third motion data; and determine that the user is in a single-leg standing state if the motion trajectory meets a first condition.

[0082] In conjunction with the second aspect, in one possible implementation, the wearable device is further configured to: receive multiple image frames sent by a first electronic device, the multiple image frames being image frames captured by the camera of the first electronic device when facing the user; obtain the movement trajectory of the user's two feet based on the multiple image frames; and determine that the user is in a single-leg standing state if the movement trajectory satisfies a second condition.

[0083] In conjunction with the second aspect, in one possible implementation, the wearable device is further configured to: obtain, based on the second motion data, the real-time swaying frequency of the user's torso during the acquisition of the second motion data; and determine, if the real-time swaying frequency is greater than a preset frequency, that the user is in a closed-eye state.

[0084] In conjunction with the second aspect, in one possible implementation, the wearable device is further configured to: receive multiple image frames sent by a first electronic device, the multiple image frames being image frames captured by the camera of the first electronic device when facing the user; and determine, based on the multiple image frames, that the user's eyes are both closed, that the user is in an open-eyed state.

[0085] Thirdly, this application provides a wearable device, which includes one or more displays, a processor, and a memory; the memory is coupled to the processor, the one or more displays are used to store computer program code, the computer program code including computer instructions, and the processor calls the computer instructions to execute a balance ability detection method provided in any possible implementation of the first aspect above.

[0086] Fourthly, this application provides a computer-readable storage medium for storing computer instructions that, when executed on a wearable device, cause the wearable device to perform a balance ability detection method provided in any possible implementation of the first aspect above.

[0087] Fifthly, this application provides a computer program product that, when run on a wearable device, causes the wearable device to execute a balance ability detection method provided in any possible implementation of the first aspect above.

[0088] For the description of the beneficial effects in aspects two through five, please refer to the description of the beneficial effects in aspect one; this application will not repeat it here. Attached Figure Description

[0089] Figure 1 A schematic diagram of a functional module for assessing body balance provided in an embodiment of this application;

[0090] Figure 2 A schematic diagram of a system architecture provided for an embodiment of this application;

[0091] Figure 3 This is a schematic diagram of the structure of a wearable device 100 provided in an embodiment of this application;

[0092] Figure 4 A schematic diagram of the hardware structure of a wearable device 100 provided in an embodiment of this application;

[0093] Figure 5 A schematic diagram illustrating the interaction between a foot motion sensor and a wearable device, provided as an embodiment of this application;

[0094] Figure 6A schematic diagram illustrating the activation of the balance detection function of a wearable device 100 according to an embodiment of this application;

[0095] Figures 7-9 A set of schematic diagrams showing the balance detection function of wearable device 100 being enabled on electronic device 200, provided for embodiments of this application;

[0096] Figure 10 A schematic diagram illustrating another way to enable the balance detection function of the wearable device 100 according to an embodiment of this application;

[0097] Figures 11-15 A schematic diagram illustrating a set of recorded motion data provided in an embodiment of this application;

[0098] Figure 16 A UI diagram provided for an embodiment of this application;

[0099] Figures 17A-17B A set of UI diagrams provided for embodiments of this application;

[0100] Figures 18A-18D A schematic diagram of a set of gait parameters provided for embodiments of this application;

[0101] Figure 19A This application provides a schematic flowchart of a method for measuring a user's dynamic balance score in an embodiment of the present application.

[0102] Figure 19B A schematic diagram illustrating a user's natural walking as provided in an embodiment of this application;

[0103] Figure 20A This is a schematic flowchart of a method for measuring static balance provided in an embodiment of this application;

[0104] Figure 20B A schematic diagram illustrating a user standing on both legs with eyes open and a user standing on one leg with eyes closed, provided for embodiments of this application;

[0105] Figure 21 A schematic diagram provided for an embodiment of this application;

[0106] Figures 22-25 A set of UI schematic diagrams provided for embodiments of this application;

[0107] Figure 26 This is a schematic diagram of the structure of an electronic device 200 provided in an embodiment of this application;

[0108] Figure 27 This is a flowchart illustrating a balance ability testing method provided in this application. Detailed Implementation

[0109] The technical solutions in the embodiments of this application will now be described clearly and in detail with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B; the "or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0110] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0111] The term "user interface (UI)" used in the specification, claims, and drawings of this application refers to the medium through which an application or operating system interacts and exchanges information with the user. It converts information from its internal form to a form acceptable to the user. The user interface of an application is source code written in a specific computer language such as Java or Extensible Markup Language (XML). This source code is parsed and rendered on the terminal device, ultimately presenting user-recognizable content such as images, text, and buttons. Controls, also known as widgets, are the basic elements of the user interface. Typical controls include toolbars, menu bars, text boxes, buttons, scroll bars, images, and text. The attributes and content of controls in the interface are defined using tags or nodes, such as XML tags. <textview> 、 <imgview> 、 <videoview>Nodes define the controls contained in the interface. A node corresponds to a control or property in the interface, and after parsing and rendering, the node is presented as the content visible to the user. In addition, many applications, such as hybrid applications, often contain web pages within their interfaces. A web page, also known as a webpage, can be understood as a special control embedded in the application interface. Web pages are source code written in a specific computer language, such as Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), JavaScript (JS), etc. Web page source code can be loaded and displayed as user-readable content by a browser or a web page display component with browser-like functionality. The specific content contained in a webpage is also defined through tags or nodes in the webpage source code; for example, HTML uses tags or nodes to define the content. 、 、 <video> 、 <canvas>Used to define the elements and attributes of a webpage.

[0112] The most common form of user interface is the graphical user interface (GUI), which refers to a user interface related to computer operation displayed graphically. It can be an icon, window, control, or other interface element displayed on the screen of an electronic device. Controls can include visual interface elements such as icons, buttons, menus, tabs, text boxes, dialog boxes, status bars, navigation bars, and widgets.

[0113] Figure 1 A schematic diagram of a functional module for assessing body balance provided in this application.

[0114] The system comprises a pressure plate to detect the pressure distribution on the subject's body, obtaining plantar pressure information; a first posture sensor to detect head data, obtaining first posture information; and a second posture sensor to detect torso data, obtaining second posture information. All information is transmitted to a host computer via a communication device, which calculates the movement of the subject's center of gravity, thus assessing the subject's vestibular system and proprioceptive abilities. The first and second posture sensors can be inertial sensors.

[0115] However, existing methods that use force plates and inertial sensors to detect the pressure on the feet of a user while standing and the swinging trajectory of the subject's head and torso to calculate the movement of the subject's center of gravity are limited in application scenarios and do not impose constraints on the user's measurement conditions, thus failing to guarantee the reliability of the results.

[0116] Furthermore, the above method can only detect the static balance of the subject and does not consider the dynamic balance of the user.

[0117] Static balance and dynamic balance are important indicators of a person's motor ability. Poor static balance is manifested as instability when standing or moving at low speed, and a lack of perception and adaptation to force fields such as gravity. Poor dynamic balance is manifested as easy fatigue when walking and poor coordination of limbs. In children and the elderly, it often manifests as a tendency to fall when walking.

[0118] Therefore, by combining static and dynamic balance, a comprehensive score of the user's balance ability is obtained, resulting in a more comprehensive and accurate test result.

[0119] This application provides a method for detecting a user's balance ability based on a combination of static and dynamic balance. The user wears wrist and foot sensors to complete specific actions under voice guidance, and completes the detection of single-leg standing time, swing amplitude, swing frequency, gait symmetry, and gait variability, thereby establishing a more comprehensive human balance ability assessment model.

[0120] Specifically, this application includes a wearable device and foot motion sensors. The wearable device is worn on the user's wrist, and the foot motion sensors are worn on the user's ankles. Both the wearable device and the foot motion sensors are used to collect motion data. Optionally, one foot motion sensor can be worn on each of the two ankles. The foot motion sensors transmit the collected motion data to the wearable device, which can then evaluate the user's movements based on this data to perform a dynamic balance test. The wearable device can also evaluate the user's movements based on the motion data collected to perform a static balance test.

[0121] In this embodiment of the application, in measuring the user's dynamic balance, the motion data of the user's feet collected by the foot motion sensor can be referred to as the first motion data.

[0122] In this embodiment of the application, the motion data of the user's wrist collected by the wearable device during the measurement of the user's static balance can be referred to as the second motion data.

[0123] This method improves the accuracy of user balance ability testing. Furthermore, it is not limited by specific balance ability testing scenarios, making it a low-cost, convenient, and quick way to measure a user's balance ability.

[0124] Users can conduct corresponding balance training based on the methods provided in this application, and improve their balance ability based on the feedback data.

[0125] Figure 2 A schematic diagram of a system architecture provided in this application is shown.

[0126] The system includes a wearable device and foot motion sensors. The wearable device can be worn on the user's wrist, and there can be multiple foot motion sensors. These sensors can be worn on the user's left and right ankles respectively. The foot motion sensors collect motion data from the user's left and right ankles. The foot motion sensors then send the collected motion data to the wearable device.

[0127] Wearable devices are used to collect motion data from the user's wrist.

[0128] Optionally, multiple foot sensors can also be attached to the user's left and right shoes using clips.

[0129] After receiving the first motion data sent by the foot motion sensor, the wearable device can obtain characteristic data such as gait symmetry and gait variability based on the first motion data.

[0130] After collecting second motion data, wearable devices can obtain characteristic data such as single-leg standing time, body swing amplitude, body swing frequency, gait symmetry, and gait variability based on the second motion data.

[0131] Afterwards, the wearable device can obtain a comprehensive balance ability score based on the above feature data and provide feedback to the user.

[0132] The wearable device of the present application embodiment is described below. Please refer to... Figure 3 , Figure 3 A schematic diagram of the structure of a wearable device 100 is shown. The wearable device 100 may include a device body 110 and wearable components 120. Wherein:

[0133] The main body of the device 110 may include a display screen 111 and a touch control 112. The display screen 111 can be used to display the time, the battery level of the main body of the device 110, the Bluetooth identifier, received messages, and user exercise data, etc. The touch control 112 can be used to receive user click operations to turn on the display screen, start and stop exercise modes, etc.

[0134] The main body of the device 110 can also record the number of steps the user takes and the calories burned, and has basic functions such as call reminders and message notifications.

[0135] The main body of the device 110 can establish a communication connection with the foot motion sensor, such as establishing a Bluetooth connection.

[0136] In one possible implementation, the device body 110 can establish a wireless communication connection with the foot motion sensor via Bluetooth. The foot motion sensor can then send the collected motion data to the connected device body 110.

[0137] Wearable component 120 is used to mount the main body of device 110. For example, wearable component 120 can be a device such as a wristband or watch strap. Wearable component 120 is a device that allows the main body of device 110 to be attached to the user's wrist. Wearable device 100 is attached to the user's wrist.

[0138] The hardware structure of the wearable device involved in the embodiments of this application is described below.

[0139] Figure 4 A schematic diagram of the hardware structure of the wearable device 100 is shown.

[0140] Wearable device 100 can refer to wearable devices such as smart bracelets and smartwatches. This application does not limit the specific type of wearable device 100. This application uses a smart bracelet as an example for illustration.

[0141] Wearable device 100 may include processor 101, memory 102, sensor 103, display screen 104, motor 105, wireless communication module 106, etc. Among them:

[0142] Processor 101 may include one or more processing units, such as application processors (APs), modem processors, graphics processing units (GPUs), image signal processors (ISPs), controllers, video codecs, digital signal processors (DSPs), baseband processors, and / or neural network processing units (NPUs). These different processing units may be independent devices or integrated into one or more processors.

[0143] The controller can generate operation control signals based on the instruction opcode and timing signals to complete the control of instruction fetching and execution.

[0144] The processor 101 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 101 is a cache memory. This memory can store instructions or data that the processor 101 has just used or that are used repeatedly. If the processor 101 needs to use the instruction or data again, it can directly retrieve it from the memory. This avoids repeated accesses, reduces the waiting time of the processor 101, and thus improves the efficiency of the system.

[0145] In this embodiment, the processor 101 can be used to determine the number of times a user experiences abnormal blood glucose levels, and / or the risk of abnormal blood glucose levels, etc., based on the PPG signal. The number of times abnormal blood glucose levels may include instances of hyperglycemia and / or hypoglycemia. The risk of abnormal blood glucose levels can be used to indicate the frequency of hyperglycemia and / or hypoglycemia experienced by the user. A detailed description of determining the number of times abnormal blood glucose levels and / or the risk of abnormal blood glucose levels based on the PPG signal will be provided later and will not be elaborated upon here.

[0146] The memory 102 may include one or more random access memories (RAM) and one or more non-volatile memories (NVM).

[0147] The random access memory can be directly read and written by the processor 101. It can be used to store executable programs (such as machine instructions) of the operating system or other running programs, as well as user and application data.

[0148] Non-volatile memory can also store executable programs and user and application data, and can be pre-loaded into random access memory for direct reading and writing by the processor 101.

[0149] Sensor 103 may include: a gyroscope sensor 1031, an accelerometer sensor 1032, a skin conduction sensor 1033, a touch sensor 1034, a bone conduction sensor 1035, a photoelectric sensor 1036, and other sensors. Among them:

[0150] The gyroscope sensor 1031 can be used to determine the motion posture of the wearable device 100. In some embodiments, the angular velocity of the wearable device 100 about three axes (i.e., the x, y, and z axes) can be determined by the gyroscope sensor 1031.

[0151] Accelerometer 1032 detects the magnitude of acceleration of wearable device 100 in various directions (typically three axes). When wearable device 100 is stationary, it can detect the magnitude and direction of gravity. It can also be used to identify the posture of electronic devices, and can be applied to applications such as screen orientation switching and pedometers.

[0152] The skin conductance sensor 1033 can be used to measure a user's skin conductance data, which reflects changes in the user's stress and mood.

[0153] Touch sensor 1034, also known as a "touch device," can be disposed on display screen 104. The touch sensor 1034 and display screen 104 together form a touchscreen, also known as a "touchscreen." Touch sensor 1034 is used to detect touch operations applied to or near it. The touch sensor can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through display screen 104. In other embodiments, touch sensor 1034 may also be disposed on the surface of wearable device 100, in a different location than display screen 104.

[0154] In this embodiment, the wearable device 100 can detect the user's touch operation on the display screen 104 through the touch sensor 1034.

[0155] The bone conduction sensor 1035 can acquire vibration signals. In some embodiments, the bone conduction sensor 1035 can acquire vibration signals from vibrating bone segments in the human vocal cords. The bone conduction sensor 1035 can also contact the human pulse to receive blood pressure signals. In some embodiments, the bone conduction sensor 1035 can also be incorporated into headphones to form bone conduction headphones. The application processor can analyze heart rate information based on the blood pressure signals acquired by the bone conduction sensor 1035 to implement heart rate detection functionality.

[0156] The photoelectric sensor 1036 is used to monitor cardiovascular vital signs. The photoelectric sensor 1036 consists of at least one pair of light-emitting diodes (LEDs) and a photodetector. The LEDs act as a light source to illuminate the skin, and the photodetector detects the transmitted or reflected light after absorption by blood and tissue during penetration, converting it into an electrical signal to obtain a PPG signal. Since the intensity of the transmitted or reflected light varies with arterial pulsation, the PPG signal also follows the arterial pulsation, i.e., the rhythmic fluctuations of the user's heartbeat. This PPG signal can be used to calculate parameters such as the user's heart rate, blood oxygen saturation, and blood pressure.

[0157] It is understood that sensor 103 may include more or fewer sensors, and this application embodiment does not limit this.

[0158] The display screen 104 can be used to display images, videos, etc.

[0159] Motor 105 can generate vibration alerts. Motor 105 can be used for incoming call vibration alerts or for touch vibration feedback. For example, different vibration feedback effects can be corresponding to touch operations applied to different applications (such as taking photos, playing audio, etc.).

[0160] The wireless communication module 106 can provide solutions for wireless communication applications on the wearable device 100, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR) technologies. The wireless communication module 106 can be one or more devices integrating at least one communication processing module. The wireless communication module 106 receives electromagnetic waves via an antenna, demodulates and filters the electromagnetic wave signals, and sends the processed signal to the processor 101. The wireless communication module 106 can also receive signals to be transmitted from the processor 101, frequency modulate and amplify them, and then convert them into electromagnetic waves for radiation via the antenna.

[0161] In some embodiments, the antenna of the wearable device 100 is coupled to the wireless communication module 106, enabling the wearable device 100 to communicate with networks and other devices via wireless communication technologies. The wireless communication technologies may include Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time-Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technologies. The GNSS may include Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), BeiDou Navigation Satellite System (BDS), Quasi-Zenith Satellite System (QZSS), and / or Satellite Based Augmentation Systems (SBAS).

[0162] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the wearable device 100. In other embodiments of this application, the wearable device 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.

[0163] Figure 5 This illustration shows a schematic diagram of the interaction between a foot motion sensor and a wearable device provided in this application.

[0164] like Figure 5 As shown, the foot motion sensor includes a Bluetooth communication module and a data acquisition module.

[0165] Wearable devices include a Bluetooth communication module, a feature detection module, a motion recognition module, a touch / display module, and a voice broadcast module.

[0166] Wearable devices can establish a Bluetooth communication connection with the Bluetooth communication module on the foot motion sensor via the Bluetooth communication module.

[0167] The touch / display module on wearable devices can start or stop detecting a user's balance ability based on the user's actions.

[0168] In response to user actions, the wearable device can prompt the user to perform corresponding actions through a voice broadcast module to complete the balance ability test.

[0169] After the wearable device starts detecting the user's balance ability, it can send start and stop commands to the foot motion sensor via Bluetooth connection, so that the foot motion sensor can start collecting running data or stop collecting running data.

[0170] Foot motion sensors can collect motion data from the user's ankles via a data acquisition module and send the collected motion data to wearable devices via Bluetooth.

[0171] After receiving motion data from foot motion sensors, wearable devices can use feature detection modules to combine the motion data to complete gait detection and dynamic balance scoring.

[0172] Wearable devices can obtain motion data collected by the wearable device and then use a feature detection module to combine the motion data to complete the static balance test of standing on one leg with eyes closed and score the balance.

[0173] Wearable devices combine static balance ability scores and dynamic balance ability scores to obtain a comprehensive balance ability score.

[0174] During the detection process, the wearable device can use its motion recognition module to identify whether the actions meet the detection requirements and determine whether the detection completion conditions are met. For example, in gait detection and dynamic balance scoring, it is necessary to detect whether walking has occurred and whether the gait is valid. If these conditions are met, the steps are recorded as valid; otherwise, they are recorded as invalid. During gait detection, the wearable device can also use its motion recognition module to determine whether the gait detection is complete. Once the number of valid steps reaches a preset number, the motion recognition module can determine that the gait detection is complete. After the detection is completed, the feature detection module can calculate the gait symmetry and gait variability within the valid steps, and then combine the gait symmetry and gait variability to obtain the dynamic balance score.

[0175] For example, when testing static balance by standing on one leg with eyes closed, it is necessary to detect whether the eyes are open and whether the person is standing on one leg. If the conditions are met, the action is recorded as valid. The feature detection module can calculate the swing amplitude and swing frequency within a certain time to obtain the static balance score.

[0176] Finally, the feature detection module can combine dynamic balance scoring and static balance scoring to obtain a comprehensive balance ability score, which can then be displayed to the user via a touch / display module.

[0177] Optionally, if during the above detection process, the action recognition module detects that the action does not meet the detection requirements or has completed a certain measurement sub-step, the action recognition module can remind or guide the user through the voice broadcast module to prompt the user to pay attention to the standardization of the action or to start the action detection of the next sub-step.

[0178] First, the wearable device 100 needs to establish a communication connection with the foot motion sensor, such as a Bluetooth connection. After the Bluetooth on both the wearable device 100 and the foot motion sensor is enabled, the wearable device 100 can establish a Bluetooth connection with the foot motion sensor.

[0179] After the wearable device 100 and the foot motion sensor establish a Bluetooth connection, the foot motion sensor can send the collected motion data to the wearable device 100. The wearable device 100 can analyze the motion data collected by the foot motion sensor and the motion data collected by the wearable device 100 to obtain a comprehensive score of the user's balance ability, thereby completing the user's balance ability test.

[0180] When the wearable device 100 enables the balance detection function, it can determine that the collected motion data originates from balance detection rather than other activities such as running. Specifically, the wearable device 100 can receive user input to enable the balance detection function.

[0181] Wearable device 100 receives and responds to user input to enable balance ability detection function.

[0182] In some embodiments, the wearable device 100 can enable the balance ability detection function by monitoring user operations on the touch control 112.

[0183] For example, such as Figure 6 As shown, when the wearable device 100 detects a long press operation on the touch control 112, the wearable device 100 can enable or disable the balance ability detection function. When the wearable device 100 has not enabled the balance ability detection function, but detects a long press operation on the touch control 112, the wearable device 100 can enable the balance ability detection function after a certain countdown time (e.g., three seconds) following the vibration. When the balance ability detection function is enabled, the wearable device 100 can display the balance ability detection function icon and the text "Balance Ability Detection Mode" on the display screen 111. This serves as a notification to the user that the wearable device 100 has enabled the balance ability detection function.

[0184] When the wearable device 100 has enabled the balance detection function and detects a long press operation on the touch control 112, the wearable device 100 can disable the balance detection function after a certain countdown time (e.g., three seconds) following the vibration.

[0185] In one possible implementation, the wearable device 100 can automatically turn off the display screen 111 after activating the balance detection function for a period of time (e.g., 1 minute or 2 minutes). When a short press operation is detected on the touch control 112, the wearable device 100 can turn on the display screen 111. Once turned on, the display screen 111 can display, for example... Figure 6 The icon for the balance detection function and the text "Balance Detection Mode" are shown. Furthermore, if a long press operation is detected on the touch control 112, the wearable device 100 can turn off the balance detection function after a certain countdown time (e.g., 3 seconds) following the vibration.

[0186] In one possible implementation, the wearable device 100 automatically turns off the display 111 after the balance detection function has been enabled for a period of time, which can effectively save the power consumption of the wearable device 100.

[0187] In other embodiments, the wearable device 100 can establish a binding relationship with the electronic device 200. For example, if the wearable device 100 and the electronic device 200 are logged into the same account, the wearable device 100 can communicate with the electronic device 200. Alternatively, the wearable device 100 can also establish a Bluetooth connection with the electronic device 200, enabling the wearable device 100 and the electronic device 200 to communicate via Bluetooth.

[0188] When the wearable device 100 can communicate with the electronic device 200, the wearable device 100 can also enable the balance capability detection function by receiving a request from the electronic device 200 to enable the balance capability detection function.

[0189] Wearable device 100 can establish a communication connection with electronic device 200 (such as a mobile phone, tablet computer, etc.). When a user operation is detected to turn the balance ability detection function on or off, electronic device 200 can send a command to wearable device 100 to turn on the balance ability detection function. When wearable device 100 receives the command to turn on the balance ability detection function, wearable device 100 can turn on the balance ability detection function.

[0190] like Figure 7 As shown, the electronic device 200 displays a main screen user interface 700. The user interface 700 may include: a status bar 710, a tray 720 with icons of frequently used applications, and other application icons. The status bar 710 may include a time indicator 7001, a battery status indicator 7002, one or more Wi-Fi signal strength indicators 7003, and one or more cellular signal strength indicators 7004. The tray 720 with icons of frequently used applications may display: a camera icon 7011, a phone icon 7012, a contacts icon 7013, and a text message icon 7014. Other application icons may include, for example: a clock icon 7005, a calendar icon 7006, a gallery icon 7007, a memo icon 7008, a Huawei Video icon 7009, and a Health icon 7010. The Health icon 7010 and icons for other applications (such as the gallery) are also included. An application icon can be used to respond to user actions (such as a click), causing the electronic device 200 to launch the application corresponding to the icon. Specifically, the Health & Fitness icon 7010 can be used to launch the Health & Fitness application. The Health & Fitness application can be used by the electronic device 200 to establish a communication connection with the wearable device 100. The electronic device 200 can display the user's exercise data to the user through the Health & Fitness application.

[0191] Electronic device 200 receives and responds to user actions (e.g., clicks) on the fitness and health icon 7010, and can display, for example, a... Figure 8 The sports and health application interface shown is 800.

[0192] like Figure 8 As shown, the application interface 800 may include a status bar 710 and interface viewing options 810. The interface viewing options 810 may include motion options 8101, device options 8102, discovery options 8103, and my options 8104. Any option can be used to respond to a user action (e.g., a click), causing the electronic device 200 to display the corresponding content on the application interface 800. For example, the content corresponding to device option 8102 may include information about devices already added to the electronic device and controls for adding new devices. When the electronic device 200 detects a user action (e.g., a click) on device option 8102, the electronic device 200 may display added device option 820 and device added option 830.

[0193] The device addition option 830 can be used to trigger the electronic device 200 to add a new device. This new device is the device with which the electronic device 200 establishes a communication connection for the first time. When the electronic device 200 detects a user operation (e.g., a click) applied to the device addition option 830, it can display an add device settings interface, allowing the electronic device 200 to establish a communication connection with the new device. This add device settings interface allows the user to search for new devices and specify the method of establishing a communication connection, such as Bluetooth connection. This embodiment does not limit the process by which the electronic device 200 establishes a communication connection with a new device.

[0194] The added device option 820 may contain identifiers for multiple wearable devices. All of these wearable devices have established communication connections with the electronic device 200. For example, the electronic device 200 has established communication connections with wearable device 100 and wearable device A. When a user action (e.g., a click) is detected on any device option in the added device option 820, the electronic device can display relevant information corresponding to that device.

[0195] When electronic device 200 detects a user action (e.g., a click) applied to the wearable device 100 identifier in the added device option 820, electronic device 200 can display, as shown below. Figure 9 The application interface shown is 900.

[0196] like Figure 9 As shown, the application interface 900 may include a status bar 710, a device status bar 910, exercise data 920, and exercise mode options 930. The device status bar 910 can be used to display the connection status between the wearable device 100 and the electronic device 200, as well as the battery level of the wearable device 100. For example, when it is detected that the electronic device 200 has established a communication connection with the wearable device 100 via Bluetooth, the device status bar 910 can indicate that the connection method is Bluetooth and the connection status is "connected". Furthermore, the electronic device 200 can obtain the battery information of the wearable device 100. The device status bar 910 can indicate the current battery level of the wearable device 100 (e.g., 77%). The content displayed by the device status bar 910 may also include more information, which is not limited in this embodiment. The exercise data 920 may include the number of steps taken, calories burned, and distance traveled by the user as recorded by the wearable device 100. The data in the exercise data 920 is the user's data recorded by the wearable device 100 during the day while it is in working condition (e.g., including the user's daily walking, balance test data, and total number of steps, calories burned, and distance traveled during activities such as running).

[0197] The sports mode option 930 can be used to turn the balance ability detection function, running mode, and swimming mode on or off. The sports mode option 930 may include a balance ability indicator 9301 and a control 9304 for turning on the balance ability detection function, a running mode indicator 9302 and a control 9305 for running mode, and a swimming mode indicator 9303 and a control 9306 for turning on swimming mode. In response to a user operation (e.g., a click) on the control 9304 for turning on the balance ability detection function, the electronic device 200 can send a command to the wearable device 100 to turn on the balance ability detection function. Upon receiving the command from the electronic device 200, the wearable device 100 can turn on the balance ability detection function after a certain time following vibration (e.g., a 3-second countdown). Once the balance ability detection function is turned on, the wearable device 100 can display a balance ability detection icon and the text "Balance Ability Detection" on the display screen 111. This serves as a notification to the user that the wearable device 100 has turned on the balance ability detection function.

[0198] When the wearable device 100 receives a command from the electronic device 200 to turn off the balance detection function, it can turn off the balance detection function after a certain period of time (e.g., a 3-second countdown) after the vibration.

[0199] Additionally, when the balance detection function is enabled, the wearable device 100 can automatically activate Do Not Disturb mode. For example, when Do Not Disturb mode is enabled, if the electronic device 200 receives an incoming call or message notification, the wearable device 100 can block the notification instructions sent by the electronic device. That is, the wearable device 100 will not alert the user to an incoming call or message notification through vibration or ringing. Thus, when the wearable device 100 has its balance detection function enabled and there is an incoming call or message notification, the wearable device 100 will not interfere with the user's balance detection.

[0200] In some embodiments, the wearable device 100 may detect whether the foot motion sensor is in operation before activating the balance detection function.

[0201] Figure 10 This diagram illustrates another wearable device 100 activating its balance detection function. When a user action is detected to activate the balance detection function (e.g., a long press on the touch control 112), the wearable device 100 can display the following on the display screen 111: Figure 14 The user interface shown may include a prompt box 113, a confirmation control 114, and a cancellation control 115. Wherein:

[0202] The prompt box 113 includes a prompt message indicating that when the balance ability detection function is enabled, the motion sensors (such as accelerometers and gyroscopes) in the foot motion sensor will be activated to determine whether the user needs to enable the balance ability detection function. The motion sensors may also include magnetometers, barometers, etc.

[0203] The confirmation control 114 can be used to activate the balance detection function. In response to a user action (e.g., a click) on the confirmation control 114, the wearable device 100 can detect whether the motion sensors in the foot motion sensor are active. If the motion sensors (such as accelerometers and gyroscopes) are not active, the wearable device 100 can send a message to the foot motion sensor indicating that the motion sensors (such as accelerometers and gyroscopes) in the foot motion sensor are active. In this way, the wearable device 100 can activate the balance detection function and vibrate for a period of time (e.g., three seconds) after activating the balance detection function to remind the user that the balance detection function is enabled.

[0204] Cancel control 115 can be used to disable the balance ability detection function. In response to a user action (such as a click) on the confirmation control 114, the wearable device 100 disables the balance ability detection function.

[0205] After the wearable device 100 activates its balance ability detection function, it can also prompt the user to select a time for personal exercise data recording. In this way, the wearable device 100 can record the user's balance ability detection data within a predetermined time.

[0206] Wearable device 100 can record the user's balance ability test data in either of the following two ways.

[0207] Method 1: Wearable device 100 receives user input of balance ability test data.

[0208] Method 2: The wearable device prompts the user to enter balance ability test data.

[0209] First, we will introduce how the wearable device 100 receives and inputs the user's balance ability test data.

[0210] When the wearable device 100 first activates the balance ability detection function, the wearable device 100 can prompt the user to enter the balance ability detection data.

[0211] In some embodiments, after the wearable device 100 activates the balance detection function, the wearable device 100 can display the following on the display screen 111: Figure 11 The user interface shown in the figure. The user interface may include a prompt box 116, a confirmation control 117, and a cancel control 118. Wherein:

[0212] The prompt box 116 includes a prompt message that prompts the wearable device 100 to input exercise data after the balance ability detection function is activated. The prompt message may include: "This is the first time using the balance ability detection function. Please input your balance ability detection data first. Input now?"

[0213] The confirmation control 117 can be used to receive user actions (e.g., clicks), and in response to a user action (e.g., a click) applied to the confirmation control 117, the wearable device 100 can display on the display screen 111 such as... Figure 16 The user interface shown.

[0214] The cancel control 118 can be used to cancel the entry of personal exercise data. In response to a user action (e.g., a click) on the cancel control 118, the wearable device 100 can display the following on the display screen 111: Figure 6 The icon and text "Balance Ability Detection Function" are shown.

[0215] If the user wants to enter personal exercise data, they can click the confirmation control 117. If the user does not want to enter personal exercise data, they can click the cancel control 118.

[0216] like Figure 12 As shown, when a user action (e.g., a click) is detected on the confirmation control 117, the wearable device 100 displays the following on the display screen 111: Figure 13 The user interface shown is used by the user to select the length of time for personal exercise data entry. The user interface may include a prompt box 119. Wherein:

[0217] The prompt box 119 may contain a 5-minute option 120, a 10-minute option 121, and a 30-minute option 122. The prompt box 119 may also contain more or fewer options, which is not limited herein.

[0218] In response to a user action (e.g., a click) on any option in the prompt 119, the wearable device 100 can display on the display screen 111 such as Figure 14 The user interface shown is a prompt box 123 that prompts the user that data entry will begin after the wristband vibrates. The prompt box 123 includes the message "Data entry will begin after the wristband vibrates".

[0219] When a user action is detected on any of the options in prompt boxes 123, the wearable device 100 displays the user interface and vibrates. After the vibration ends, the wearable device 100 begins recording personal exercise data.

[0220] When the wearable device 100 detects that the time elapsed since the start of personal exercise data entry has been equal to the time corresponding to the selected option in the prompt box 123, the wearable device 100 may vibrate and display the following on the display screen 111: Figure 15 The user interface shown is used to indicate to the user that personal exercise data entry is complete.

[0221] Figure 15 The user interface shown includes a prompt box 124, which prompts the user that personal exercise data entry is complete. The prompt box 124 includes the message "Personal exercise data entry complete".

[0222] When a user is entering personal exercise data, specifically during a balance test, it's inconvenient for them to directly see the content on display screen 111. Wearable device 100 can use vibration to indicate the end of personal exercise data entry. This allows the user to stop the balance test after the wearable device 100 vibrates.

[0223] This application does not limit the method by which the wearable device 100 starts and stops recording personal exercise data. Besides using vibration to indicate the start and end of personal exercise data recording, other methods are also possible.

[0224] The following explains how electronic device 200 prompts the user to enter personal exercise data after the wearable device 100 first activates the balance ability detection function.

[0225] In some embodiments, when the electronic device 200 detects that the user has enabled the balance ability detection function in the sports and health application and no personal exercise data of the user is detected, the electronic device may prompt the user to enter personal exercise data.

[0226] Electronic device 200 can display on user interface 900 such as Figure 16 The prompt box 2001 shown is a notification box. The prompt box 2001 includes a message prompting the user to enter exercise data after the balance ability detection function is activated. The message may include: "This is the first time using the balance ability detection function. Please enter your balance ability detection data first. Enter now?". The prompt box 2001 also includes a control 2002, which can be used to receive user actions (e.g., clicks). In response to a user action (e.g., a click) on the control 2002, the electronic device 200 can display the following on the user interface 900: Figure 17A The prompt box 2101 is shown. Prompt box 2001 also includes a control 2003, which can be used to cancel personal exercise data entry. If the user wants to enter personal exercise data, the user can click control 2002. If the user does not want to enter personal exercise data, the user can click control 2003.

[0227] When a user action is detected on control 2002, electronic device 200 displays the following on user interface 900: Figure 17A The prompt box shown is 2101.

[0228] like Figure 17A As shown, the prompt box 2101 may contain a 5-minute option 2102, a 10-minute option 2103, and a 30-minute option 2104. The prompt box 2101 may also contain more or fewer options, which is not limited herein.

[0229] In response to a user action (e.g., a click) on any option in the prompt 2101, the electronic device 200 can display on the user interface 900 as follows: Figure 17B The prompt box shown is 2201.

[0230] like Figure 17B As shown, the prompt box 2201 is used to prompt the user that data entry will begin after the wristband vibrates. The prompt box 2201 includes the prompt content "Data entry will begin after the wristband vibrates".

[0231] When a user action is detected on any of the options in prompt boxes 123, the wearable device 100 displays the user interface and vibrates. After the vibration ends, the wearable device 100 begins recording personal exercise data.

[0232] The following explains the motion parameters involved in balance ability testing.

[0233] 1. Step length

[0234] Stride length, also known as stride length, refers to the straight-line distance between the point where the heel of the same foot lands on the ground and the next adjacent point where the heel of the same foot lands on the ground.

[0235] like Figure 18A As shown, the stride length is the straight-line distance between two consecutive points where the heel of the right foot lands.

[0236] 2. Time to contact

[0237] Ground contact time can refer to the time from when the heel of the same foot begins to touch the ground until the toe of the same foot leaves the ground.

[0238] like Figure 18B As shown, the user's left heel begins to touch the ground at time t1, and the user's left toe begins to leave the ground at time t2. Therefore, the difference between time t1 and time t2 is the contact time of the user's left foot.

[0239] 3. Angle of elevation above ground

[0240] The angle of elevation can be defined as the angle between the sole of the foot and the ground when the toes leave the ground along the direction of travel.

[0241] like Figure 18C As shown, the ground elevation angle can be the angle α between the sole of the user's left foot and the ground along the forward direction when the user's left foot leaves the ground.

[0242] 4. Angle of elevation upon contact with the ground

[0243] The angle of elevation refers to the angle between the sole of the foot and the ground when the heel contacts the ground along the direction of movement.

[0244] like Figure 18D As shown, the ground elevation angle can be the angle β between the sole of the user's left foot and the ground along the forward direction when the user's left foot contacts the ground.

[0245] 5. Swing time

[0246] Swing time can refer to the time between the point where the toes of the same foot leave the ground and the point where the heel of the same foot touches the ground again.

[0247] 6. Walking speed

[0248] Walking speed, also known as pace, can refer to the distance traveled per unit of time, such as the distance traveled per minute.

[0249] 7. Step frequency

[0250] Step frequency, or walking frequency, refers to the number of steps taken per unit of time. For example, the number of steps taken per minute.

[0251] 8. Swing amplitude

[0252] Swing amplitude refers to the range of motion of a user's torso when standing on one leg. Swing amplitude can include forward and backward swing amplitude and left and right swing amplitude.

[0253] The average swing amplitude can refer to the average forward and backward swing amplitude of the user's torso during the duration of standing on one leg, and the average left and right swing amplitude of the user's torso during the duration of standing on one leg. For example, in the embodiments of this application, the average swing amplitude can be greater than or equal to 0 degrees and less than or equal to 70 degrees.

[0254] Real-time swing amplitude can refer to the swing amplitude of the body trunk at any given moment.

[0255] 9. Oscillation frequency

[0256] Oscillation frequency can refer to the number of times the body's torso oscillates within a certain period of time.

[0257] The average swing frequency can refer to the average number of swings of a user's torso during the duration of standing on one leg. For example, in the embodiments of this application, the average swing frequency of the torso can be greater than or equal to 0.05Hz and less than or equal to 2Hz.

[0258] Real-time oscillation frequency can refer to the oscillation frequency of the body's torso at any given moment.

[0259] 10. Gait symmetry

[0260] Gait symmetry refers to the gait symmetry between two adjacent strides. Gait symmetry can be assessed using ground contact time.

[0261] In this application, gait symmetry is used to obtain a dynamic balance score. Gait symmetry can be obtained by measuring the average ground contact time of the left foot and the average ground contact time of the right foot within an effective gait during a user's natural walking process.

[0262] For example, if a user's effective gait on one side during natural walking is 5 steps, with 5 steps on the left foot and 5 steps on the right foot, then the average ground contact time of the left foot and the average ground contact time of the right foot in the 5 effective gait steps can be calculated. A gait symmetry score can then be obtained based on the average ground contact time of the left and right feet.

[0263] Optionally, the gait symmetry score can be obtained using formula (1).

[0264]

[0265] As shown in formula (1), S represents the gait symmetry score, where S is greater than or equal to 0 and less than or equal to 100%, and T touch-left T represents the average ground contact time of the left foot. touch-right This represents the average ground contact time of the right foot, with the symbol "||" indicating the absolute value. The symbol "MAX" indicates that the maximum value of the average ground contact time of the left foot and the average ground contact time of the right foot is taken.

[0266] According to formula (1), the gait symmetry score within the effective gait during the user's natural walking process can be obtained.

[0267] It should be noted that, in addition to the average ground contact time, gait symmetry can also be obtained based on other gait parameters, which are not limited in this application.

[0268] 11. Gait variability

[0269] Gait variability can refer to the gait variation between two consecutive stride lengths. Gait variability can be assessed using stride length.

[0270] In this application, gait variability is used to obtain a dynamic balance score. Gait variability can be obtained by measuring the stride length within the effective gait during a user's natural walking process.

[0271] For example, if a user's effective gait on one side during natural walking is 5 steps, then we can obtain the effective gait of the left foot as 5 steps and the effective gait of the right foot as 5 steps. The stride length of each of these 10 effective gaits is then calculated. A gait variability score is then obtained based on the stride length of each of these 10 effective gaits.

[0272] Optionally, the gait variability score can be obtained using formula (2).

[0273]

[0274] As shown in formula (1), V represents gait variability, where V is greater than or equal to 0 and less than or equal to 100%, and L stride-length This represents the stride length in each of the 10 valid gait steps, with "STD" indicating the standard deviation. "MEAN" indicates...

[0275] It should be noted that gait variability can be obtained based on other gait parameters, not just stride length, and this application does not limit this.

[0276] This application provides a method for detecting balance ability, in which a foot motion sensor and a wearable device establish a communication connection. The foot motion sensor is worn on the user's ankle, and the wearable device is worn on the user's wrist. The foot motion sensor can collect motion data from the user's ankle and send it to the wearable device. The wearable device can score the motion data collected by the foot motion sensor to obtain the user's dynamic balance score. The wearable device then obtains the user's static balance score based on the motion data collected by the wearable device from the wrist. Finally, the static balance score and the dynamic balance score are combined to obtain a comprehensive balance ability score.

[0277] The user's static balance score can be checked first, followed by the user's dynamic balance score. Alternatively, the user's dynamic balance score can be checked first, followed by the user's static balance score. This application does not impose any restrictions on the order of these checks.

[0278] For example, the user's dynamic balance score can be detected first. Specifically, the user begins to walk naturally, and foot motion sensors start collecting motion data during this process, sending it to a wearable device. The wearable device analyzes this data to obtain gait parameters. It then determines the validity of the gait, discarding invalid gaits and retaining valid ones. Once a preset number of valid steps is reached, the dynamic balance score detection ends, calculating gait symmetry and gait variability within the valid step count. Based on these gait symmetry and gait variability, the wearable device can then obtain the user's dynamic balance score for walking naturally with their eyes closed.

[0279] Next, the user's static balance score can be measured. Specifically, the user completes a single-leg standing exercise with eyes closed. The wearable device begins collecting motion data from the user's wrists during this exercise. The wearable device can analyze this motion data to obtain monitoring parameters for the single-leg standing exercise, including, but not limited to, the average swing amplitude and average swing frequency over the monitoring time. The wearable device can then determine the user's static balance score based on the average swing amplitude and average swing frequency.

[0280] Finally, the wearable device can obtain a comprehensive balance ability score based on dynamic and static balance scores. This comprehensive balance ability score is the user's score for this balance ability monitoring.

[0281] The following sections will provide a detailed introduction to how wearable devices monitor users' dynamic balance scores and static balance scores.

[0282] First, let's explain how wearable devices obtain users' dynamic balance scores.

[0283] Figure 19A A flowchart illustrating the method for measuring a user's dynamic balance score is shown.

[0284] S1901. The wearable device establishes a communication connection with the foot motion sensor.

[0285] The foot motion sensor includes a first foot motion sensor and a second foot motion sensor. The first foot motion sensor is worn on the user's left foot, and the second foot motion sensor is worn on the user's right foot.

[0286] Wearable devices can establish communication connections with a first foot motion sensor and a second foot motion sensor. For example, wearable devices can establish communication connections with the first and second foot motion sensors via Bluetooth.

[0287] Wearable devices can also establish communication connections with foot motion sensors through other means, not limited to Bluetooth.

[0288] S1902, The wearable device sends an activation notification to the foot motion sensor.

[0289] Wearable devices can send activation notifications to foot motion sensors via a communication connection.

[0290] This application does not limit the scope of sending activation notifications from wearable devices to foot motion sensors; it also allows other devices that have established a communication connection with the wearable device to send activation notifications to the foot motion sensors.

[0291] S1903, Foot motion sensor activated.

[0292] In response to the activation notification sent by the wearable device, the foot motion sensor turns on and begins to detect the user's foot movement data.

[0293] S1904. Wearable devices guide users to try out the device via voice commands.

[0294] The wearable device guides the user through a trial walk using voice commands to check if the foot motion sensors are properly worn. Once properly worn, the device guides the user to begin measuring dynamic balance. This avoids inaccurate measurements caused by starting dynamic balance measurement directly if the foot motion sensors are not properly worn.

[0295] S1905, Foot motion sensor collects motion data during natural walking.

[0296] S1906, the foot motion sensor sends motion data from the user's natural walking to the wearable device.

[0297] After the wearable device guides the user to try walking via voice, the user begins to walk, and the foot motion sensor begins to collect the user's natural walking motion data and send the user's natural walking motion data to the wearable device.

[0298] Figure 19B A diagram illustrating a user's natural walking motion is shown.

[0299] It should be noted that S1905-S1906 can be performed periodically, in real time, or not in real time.

[0300] S1907. Wearable devices must be able to determine whether there is gait.

[0301] After receiving motion data from foot motion sensors during natural walking, wearable devices use this motion data to detect whether there is gait, that is, to detect whether the user is walking.

[0302] Once gait is detected, the wearable device can confirm that it is properly worn and the user has begun walking naturally. At this point, the user's dynamic balance score during natural walking can be measured. Then, step S1908 can be executed.

[0303] If no gait is detected, it's possible the user hasn't started walking yet, so steps S1904-S1907 can continue. The system will then check for gait. If, after a certain time, no gait is still detected, and the user has started walking naturally, it indicates the wearable device is not properly worn, leading to inaccurate measurements. In this case, the wearable device can prompt the user via voice to check if the foot motion sensor is worn correctly; the voice message could be "Activation failed, please check the fit." Afterward, steps S1904-S1907 will be executed again, and gait will be monitored until it is detected.

[0304] Optionally, the gait can also be determined by foot motion sensors based on collected running data, and the determination result is sent to a wearable device. The wearable device can then confirm the presence of a gait based on the determination result sent by the foot motion sensors.

[0305] In some embodiments, gait detection can also be achieved using other devices. For example, another device (such as a mobile phone or a large screen) is positioned directly in front of the user, with its camera facing the user's face. The other device can determine the presence of gait using images captured by the camera. Gait detection via camera will yield more accurate results.

[0306] S1908, Wearable devices guide users to begin walking naturally and monitor dynamic balance via voice commands.

[0307] Once gait is confirmed, it means the user has started walking naturally and the foot motion sensors are properly worn, at which point the wearable device can begin monitoring dynamic balance.

[0308] Optionally, the wearable device can guide the user to begin walking naturally and monitor dynamic balance via voice. The voice prompt could be "3, 2, 1, please begin walking naturally." This serves as a prompt for the user to begin monitoring their dynamic balance.

[0309] S1909. Wearable devices obtain gait parameters based on motion data during natural walking.

[0310] Once gait is determined, wearable devices can obtain gait parameters based on motion data from natural walking. These gait parameters are then used to determine the effective number of steps taken.

[0311] In some embodiments, the foot motion sensor can collect motion data and send it to a wearable device. The wearable device can obtain gait parameters based on the motion data, which can be the gait parameters for each step the user takes. Optionally, the foot motion sensor can send motion data to the user after each step. For example, when the user takes a step forward with their left foot, the foot motion sensor worn on the left foot sends the motion data collected during this step to the wearable device, and the wearable device can obtain the gait parameters of the left foot based on the motion data collected by the foot motion sensor worn on the left foot.

[0312] Similarly, when a user takes a step forward with their right foot, the foot motion sensor worn on the right foot sends the motion data collected during this walking process to the wearable device. The wearable device can then obtain the gait parameters of the right foot based on the motion data collected by the foot motion sensor worn on the right foot.

[0313] In other embodiments, foot motion sensors can collect motion data and derive gait parameters based on the motion parameters. These gait parameters can be the gait parameters for each step the user takes. The foot motion sensors then send the obtained gait parameters to a wearable device. For example, when a user takes a step forward with their left foot, the foot motion sensor worn on the left foot can collect the motion data generated during this step and derive the gait parameters generated during this step. The foot motion sensor worn on the left foot then sends the gait parameters generated during this step to the wearable device.

[0314] Similarly, when a user takes a step forward with their right foot, the foot motion sensor worn on the right foot can collect the motion data generated during this walking process and obtain the gait parameters generated during this walking process based on the motion data generated during this walking process. The foot motion sensor worn on the right foot then sends the gait parameters generated during this walking process to the wearable device.

[0315] S1910 Wearable devices must verify whether gait detection is effective.

[0316] If the gait is determined to be valid, execute S1911. If the gait is determined to be invalid, execute S1909.

[0317] As can be seen from S1909, wearable devices can obtain gait parameters from motion data, and wearable devices can also receive gait parameters sent by foot motion sensors.

[0318] After acquiring gait parameters, wearable devices need to determine whether the gait is valid. Removing invalid gaits and scoring the user's dynamic balance based solely on valid gaits can improve the accuracy of the dynamic balance score.

[0319] Specifically, after acquiring gait parameters, the wearable device can compare the real-time detected gait parameter values ​​with standard gait parameter values ​​to determine whether the current gait is effective.

[0320] Gait parameters, but not limited to stride length, ground contact time, ground contact angle, ground lift angle, swing time, gait speed, and cadence.

[0321] In other embodiments, gait parameters may also include foot force, knee joint force, and foot roll angle. These parameters can also be used to measure gait effectiveness.

[0322] For example, standard values ​​for gait parameters may include: stride length of 3 meters, ground contact time of 2 seconds, ground contact angle of 60 degrees, ground lift angle of 120 degrees, swing time of 0.1 seconds, walking speed of 7 km / h, and cadence of 220 steps / minute.

[0323] For example, the criteria for judging gait effectiveness may include: stride length less than 3 meters, ground contact time less than 2 seconds, ground contact angle less than 60 degrees, ground lift angle less than 120 degrees, swing time greater than 0.1 seconds, walking speed less than 7 km / h, and cadence less than 220 steps / minute.

[0324] Once a valid gait is determined, the number of valid gaits is incremented by 1. Once an invalid gait is determined, the motion parameters of the current gait are discarded and not used as parameters for calculating the dynamic balance score.

[0325] For example, when a user takes a step forward with their left foot, the wearable device acquires the gait parameters and compares the value of the gait parameters for this left foot step with the standard value of the gait parameters. If the value of the gait parameters for this left foot step does not meet the judgment condition for gait validity, the wearable device discards the data for this left foot step, so the number of effective steps remains unchanged.

[0326] For example, when a user takes a step forward with their left foot, the wearable device acquires the gait parameters and compares the value of the gait parameters for this left foot step with the standard value of the gait parameters. If the value of the gait parameters for this left foot step meets the judgment condition for gait validity, the wearable device retains the data for this left foot step, and the number of valid steps increases by 1.

[0327] Optionally, if invalid gait is detected for a certain period of time (e.g., 5 seconds), the wearable device can prompt the user via voice that the detection has failed and to restart the monitoring. The voice message could be "Detection failed, please try again." S1904-S1910 can be executed again.

[0328] S1911 Wearable devices must confirm whether the number of valid steps has reached the preset number of steps.

[0329] By obtaining dynamic balance scores based on data within a certain number of valid steps, the accuracy of dynamic balance scoring can be improved.

[0330] Once the number of valid steps reaches the preset number, the user's dynamic balance score can be obtained based on the data within the preset number of steps.

[0331] After determining that the number of valid steps has reached the preset number of steps, execute S1912-S1913.

[0332] If the number of valid steps has not yet reached the preset number of steps, execute S1909.

[0333] S1912, The wearable device sends an end notification to the foot motion sensor.

[0334] S1913, In response to the termination notification, the foot motion sensor stops collecting motion data.

[0335] Once the wearable device confirms that the number of valid steps has reached the preset number, it can send an end notification to the foot motion sensor.

[0336] In response to a termination notification, the foot motion sensor can stop collecting motion data to reduce power consumption.

[0337] In some embodiments, the foot motion sensor can be turned off in response to an end notification.

[0338] Optionally, S1912-S1913 may not be executed.

[0339] Optionally, S1912-S1913 can also be executed after S1915.

[0340] S1914. Wearable devices calculate gait symmetry and gait variability within the effective gait.

[0341] In dynamic balance testing, the motion data obtained by wearable devices, including gait symmetry and gait variability, can be referred to as the first motion data.

[0342] S1915. Wearable devices obtain dynamic balance scores based on gait symmetry and gait variability.

[0343] Based on the foregoing introduction, the gait symmetry score S and gait variability score V within the effective gait can be obtained through formulas (1) and (2).

[0344] After obtaining the gait symmetry score S and gait variability score V within the effective gait range, the wearable device can obtain a dynamic balance score based on the gait symmetry and gait variability.

[0345] Optionally, the gait symmetry score S and gait variability score V can be further processed to obtain the gait symmetry score S1 and gait variability score V1. Where S1 = 50 * S, V1 = 50 - 50 * V.

[0346] Wearable devices can obtain dynamic balance scores using formula (3).

[0347] Gd=50*(S1-V1)+50 Formula (3)

[0348] As shown in formula (3), Gd is the dynamic balance score.

[0349] In some embodiments, the wearable device may also obtain the dynamic balance score based solely on the gait symmetry score S and the gait variability score V using formula (3). Not limited to formula (3), the wearable device may also obtain the dynamic balance score using other formulas, which are not limited in this application.

[0350] After obtaining the dynamic balance score, the wearable device can guide the user to begin measuring the static balance.

[0351] Figure 20A A schematic diagram of the method for measuring static balance is shown.

[0352] S2001. Wearable devices guide users to place their hands in front of their chest, touch the screen with their fingers, and close their eyes via voice commands.

[0353] After the wearable device obtains the user's dynamic balance score, the user's static balance score can be measured.

[0354] To improve the accuracy of static balance measurements, the wearable device can provide voice prompts to the user to prepare before starting the measurement. These preparation actions could include placing both hands in front of the chest, placing the fingers of the side without the wearable device on the touchscreen, and closing the eyes.

[0355] S2002. Wearable devices need to determine whether the user's finger is touching the screen.

[0356] After guiding the user through voice commands to prepare, the wearable device needs to determine whether the user's finger has touched the screen.

[0357] A user's finger touching the screen can be the trigger condition for starting static balance detection.

[0358] Furthermore, if the user's arms are extended during static balance measurement, it will affect the measurement results. Therefore, the user's arms need to be in a closed state, such as with hands placed in front of the chest. In this way, the frequency or amplitude of the user's wrist swing can be determined based on the motion data collected by the wearable device. Since the hands are placed in front of the chest, the frequency or amplitude of the user's wrist swing can also be used to measure the frequency or amplitude of the user's torso swing. If the wearable device detects that the user's fingers are on the screen of the wearable device, it can determine that the user's hands are placed in front of the chest and that the user has actively triggered the start of static balance monitoring.

[0359] After determining that the user's finger is touching the screen of the wearable device, S2003 is executed.

[0360] If it is determined that the user's finger is not touching the screen of the wearable device, execute S2001.

[0361] Optionally, S2001 and S2002 can be skipped, and S2003 can be executed directly. This application does not limit this.

[0362] S2003: Wearable devices guide users to start standing on one leg with their eyes closed and begin static balance testing via voice commands.

[0363] Figure 20B The illustrations show a user standing with both legs open and a user standing with one leg closed.

[0364] To prompt users to begin measuring static balance, wearable devices can use voice prompts to guide users to perform the measurement action and check static balance. The voice prompt could be "3, 2, 1, please lift one leg and start timing."

[0365] S2004. Wearable devices must be able to determine whether the user is standing on one leg with their eyes closed.

[0366] If standing on one leg with eyes closed, then execute S2005.

[0367] If not standing on one leg with eyes closed, then execute S2003.

[0368] In some embodiments, the foot motion sensor can determine the single-leg standing state based on the collected motion data by obtaining the foot lift trajectory. If no foot lift is detected, in one possible implementation, the foot motion sensor can prompt the user to stand on one leg via voice, such as "Please lift one leg." In other possible implementations, when the foot motion sensor determines that the foot is not lifted, it can send a message to the wearable device. In response to this message, the wearable device can prompt the user to stand on one leg via voice, such as "Please lift one leg."

[0369] In some embodiments, foot motion sensors can send collected motion data to a wearable device. The wearable device can determine the single-leg standing state based on the motion data and the foot lift trajectory. If no foot lift is detected, the wearable device can prompt the user to stand on one leg via voice, such as "Please lift one leg."

[0370] In some embodiments, a single-leg standing posture can also be identified using other devices. For example, another device (such as a mobile phone or a large screen) is positioned in front of the user, with its camera facing directly at the user. The other device can determine whether the user is standing on one leg based on the images captured by the camera. Identifying the user's single-leg standing posture through the camera will yield more accurate results. If no foot is detected, the other device can prompt the user to stand on one leg via voice, such as "Please lift one leg."

[0371] Optionally, during the static balance test, in addition to detecting whether the user is standing on one leg in real time, it is also necessary to detect whether the user has closed their eyes.

[0372] A user's ability to maintain balance differs when standing on one leg with their eyes open versus with their eyes closed. A user's balance is better when standing on one leg with their eyes open than when standing on one leg with their eyes closed. Furthermore, the user's conscious interference is less when their eyes are closed than when their eyes are open. Therefore, measurements of static balance are more accurate when the user's eyes are closed.

[0373] In some embodiments, eye-opening or eye-closing can also be detected using other devices. For example, another device (such as a mobile phone or a large screen) is positioned directly in front of the user, with its camera facing the user's face. The other device can determine whether the user's eyes are open or closed based on the images captured by the camera. Recognizing whether a user's eyes are open or closed via a camera will yield more accurate results.

[0374] In other embodiments, the user's eyes may be open or closed based on the frequency of the swinging of the user's body parts.

[0375] Figure 21 The first image in the document shows a schematic diagram illustrating the correspondence between sensation and frequency band.

[0376] Figure 21 The second image shows a schematic diagram of the leg swing frequency with eyes closed.

[0377] Figure 21 The third image in the diagram shows a schematic of the leg swing frequency when the eyes are open.

[0378] Depend on Figure 21 It is known that the amplitude of eye movement is greater when eyes are closed than when eyes are open, therefore the corresponding eye movement frequency is higher when eyes are closed than when eyes are open. The eye movement frequency can be used to monitor whether the user's eyes are open or closed. When the eye movement frequency is greater than a preset frequency for a continuous period of time, it can be determined that the user's eyes are closed. When the eye movement frequency is less than the preset frequency for a continuous period of time, it can be determined that the user's eyes are open. Upon determining that the user's eyes are open, the wearable device can remind the user to close their eyes via voice prompts; the voice prompt could be "Please keep your eyes closed during measurement." Optionally, the wearable device can also display the text "Suspected to have eyes open."

[0379] While the user is standing on one leg, the wearable device can calculate the spectrum of the swing amplitude within a time window of a certain duration (e.g., 5 seconds), and calculate the frequency corresponding to the maximum amplitude within this spectrum as the swing frequency. If the amplitude is less than 0.25, it can be interpreted as no swing, and the swing frequency is 0. If the swing frequency is consistently 0 for a certain duration (e.g., 5 seconds), the wearable device can remind the user to close their eyes via voice, with the voice message being "Please keep your eyes closed during measurement." Optionally, the wearable device can also display the text "Appears to have eyes open."

[0380] If, during the static balance test, the lifted foot touches the ground again, the static balance measurement ends, and S2001 is executed again to start the static balance measurement.

[0381] If the user's eyes are detected to be open during the static balance measurement process, a prompt message can be output to remind the user to keep their eyes closed during the measurement. This prompt message can be a voice reminder such as "Please keep your eyes closed during the measurement," or it can be text, vibration, or flashing lights. If the user is detected to need to open their eyes for a certain period of time, the static balance measurement ends, and step S2001 is executed again to begin measuring static balance once more.

[0382] If, during the static balance detection process, the proportion of signals whose acceleration modulus values ​​at all sampling points are higher than the preset acceleration value (e.g., 0.1g) exceeds the preset ratio (e.g., 10%) within a certain time period (e.g., within 2 seconds), then the static balance measurement ends, and S2001 is executed again to start the static balance measurement.

[0383] S2005. Wearable devices calculate real-time swing amplitude and real-time swing frequency based on motion data.

[0384] Here, motion data can be motion data of the user's wrist collected by wearable devices.

[0385] S2006. Wearable devices need to determine whether the real-time swing amplitude and real-time swing frequency meet the preset values.

[0386] If the real-time swing amplitude and real-time swing frequency do not meet the preset values, for example, if the real-time swing amplitude is greater than the preset amplitude and the real-time swing frequency is less than the preset frequency, it means that the user is unstable standing on one leg and the user's body is swaying violently and has not maintained balance. Then, execute S2009 to determine whether the static balance measurement time meets the second duration.

[0387] If the real-time swing amplitude and real-time swing frequency meet the preset values, it means that the user is stable and balanced when standing on one leg, and execute S2007.

[0388] S2007. Wearable devices need to determine whether the duration of standing on one leg with eyes closed is greater than the first duration.

[0389] Optionally, S2007 may be executed before S2006. This application does not impose any restrictions on this.

[0390] After determining that the duration of standing on one leg with eyes closed exceeds the first duration, execute S2011 to automatically end the static balance measurement and calculate the static balance score for this measurement.

[0391] After determining that the duration of standing on one leg with eyes closed is less than the first duration, execute S2008 to continue measuring static balance.

[0392] S2008 Wearable devices must be able to determine whether a user's finger is touching the screen.

[0393] If it is determined that the user's finger is not touching the screen, it indicates that the user has actively triggered the termination of this static balance measurement. Execute S2010.

[0394] If it is determined that the user's finger continues to touch the screen, it means that the user has not actively triggered the termination of this static balance measurement. The static balance test duration has not exceeded the first duration, so S2009 is executed to continue this static balance test.

[0395] Therefore, if the static balance detection data entry time is greater than the second duration but less than the first duration, and the fingers on the wrist not wearing the wearable device stop touching the screen of the wearable device, this can be used as a trigger condition to end the static balance detection.

[0396] S2009, End timing, wearable device calculates static balance test duration.

[0397] As described above, the wearable device starts timing in S2003. In S2009, the user's finger does not touch the screen, indicating that the user actively triggers the end of this static balance measurement, at which point timing stops. The static balance test duration can be calculated based on S2003 and S2009.

[0398] S2010. For wearable devices, it is necessary to determine whether the static balance test duration is greater than the second duration.

[0399] The second duration is shorter than the first duration. For example, the first duration could be 30 seconds, and the second duration could be 5 seconds.

[0400] If the fingers on the wrist of a person not wearing the wearable device are constantly touching the screen of the wearable device, and the static balance detection data entry time has reached the first duration, the wearable device can automatically end the static balance detection.

[0401] If the fingers of the wrist not wearing the wearable device are constantly touching the screen of the wearable device and the static balance test duration is longer than the first duration, this can also be used as a trigger condition to end the static balance test.

[0402] For wearable devices, it is necessary to determine whether the static balance test duration is greater than the second duration, which is the shortest time to record static balance data. The first duration is the longest time to record static balance data.

[0403] If the static balance test duration is longer than the second duration, execute S2011.

[0404] If the static balance test duration is less than the second duration, it means that the duration of static balance data entry is less than the minimum time for static balance data entry. Data needs to be re-entered and static balance measured, and S2001 needs to be executed.

[0405] S2011. Wearable devices can calculate the average swing amplitude and average swing frequency during the static balance test duration.

[0406] Wearable devices can obtain the average swing amplitude and average swing frequency during the static balance test based on the motion data collected by the wearable device.

[0407] In this embodiment of the application, the motion data collected by the wearable device for calculating the average swing amplitude and average swing frequency during the static balance test can be referred to as the second motion data.

[0408] S2012. Wearable devices need to determine whether the average swing amplitude and average swing frequency within the static balance test duration meet the preset values.

[0409] If the average oscillation amplitude and average oscillation frequency during the static balance test meet the preset values, it indicates that the static balance test is effective, and S2013 is executed.

[0410] If the average oscillation amplitude and average oscillation frequency during the static balance test do not meet the preset values, the static balance test is invalid. Execute S2001, re-enter the data, and measure the static balance.

[0411] S2013. Wearable devices can obtain a static balance score based on the static balance test duration, average swing amplitude, and average swing frequency.

[0412] After obtaining the static balance test duration T, average swing amplitude A, and average swing frequency F, the wearable device can further process these parameters to obtain the static balance test duration T1, average swing amplitude A1, and average swing frequency F1. Where T1 = 2T - 10, A1 = -A + 30, and F1 = -50F + 30.

[0413] Wearable devices can obtain static balance scores using formula (4).

[0414] Gs=2T1-A1-50F1+50 Formula (4)

[0415] As shown in formula (4), Gs is the static balance score.

[0416] In some embodiments, the wearable device may also obtain a static balance score based solely on the static balance test duration T, average swing amplitude A, and average swing frequency F using formula (4). Not limited to formula (4), the wearable device may also obtain a static balance score using other formulas, and this application does not limit this to any particular formula.

[0417] pass Figure 19A and Figure 20A The method shown in the embodiment allows the wearable device to combine dynamic and static balance scores to obtain a comprehensive balance ability score for the user. This comprehensive balance ability score serves as the user's balance ability assessment score for this monitoring session.

[0418] Wearable devices can obtain the user's balance ability score for this monitoring using formula (5).

[0419] G=(Gd+Gs)*50% formula (5)

[0420] As shown in formula (5), G is the overall balance score, Gd is the dynamic balance score, and Gs is the static balance score. This application does not limit the use of formula (5) to other formulas for obtaining the overall balance score.

[0421] After obtaining the overall balance ability score, the wearable device can display the user's overall balance ability score, which can also be displayed in the electronic device 200.

[0422] The following section introduces the overall score for balance ability displayed by wearable devices.

[0423] In some embodiments, after obtaining the user's overall balance score, the wearable device can display the most recent overall balance score on the display screen 111.

[0424] Wearable device 100 may include multiple applications, such as Figure 22 The application shown is "Balance Ability Test Data". In response to a user action (e.g., a click) on the "Balance Ability Test Data" icon 125, the wearable device 100 can display, as shown below. Figure 23 The application interface shown.

[0425] The application interface can include a static balance score of 40, a dynamic balance score of 40, and a comprehensive balance ability score of 40.

[0426] The application interface of the wearable device 100 may also display more or less motion data, and this application embodiment does not limit this.

[0427] The following is an introduction to the test data of the balance capability of the electronic device 200 display.

[0428] Electronic device 200 can display such as Figure 24 The application interface 1000 is shown. The application interface 1000 may include a status bar 710, a device status bar 910, and a motion data bar 1010 corresponding to the motion mode.

[0429] The sports data column 1010 corresponding to the sports mode may include balance ability test data option 1001, running sports data selection, and swimming sports data option.

[0430] In response to a user action (e.g., a click) on the balance ability test data option 1001, the electronic device 200 can display, as shown below: Figure 25 The application interface shown is 1100. Among them:

[0431] Balance ability test data includes overall balance ability score, average swing amplitude, average swing frequency, gait symmetry, and gait variability, etc.

[0432] Among them, the overall balance score was 40, the average swing amplitude was 25 degrees, the average swing frequency was 0.4 Hz, the gait symmetry was 70%, and the gait variability was 70%.

[0433] Optionally, users can also view other balance ability test data, which will not be elaborated here.

[0434] Next, the hardware architecture of the electronic device 200 mentioned in the embodiments of this application will be described.

[0435] Figure 26 A schematic diagram of the structure of the electronic device 200 is shown.

[0436] The following describes the embodiment using electronic device 200 as an example. The device types of electronic device 200 may include mobile phones, televisions, tablet computers, speakers, watches, desktop computers, laptops, handheld computers, notebook computers, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), augmented reality (AR) / virtual reality (VR) devices, etc. This application embodiment does not impose any special limitations on the device type of electronic device 200.

[0437] It should be understood that, Figure 26 The electronic device 200 shown is merely an example, and the electronic device 200 may have more than... Figure 26 The more or fewer components shown can be combined into two or more components, or they can have different component configurations. The various components shown in the figure can be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and / or application-specific integrated circuits.

[0438] Electronic device 200 may include: processor 1110, external memory interface 120, internal memory 121, universal serial bus (USB) interface 130, charging management module 140, power management module 141, battery 142, antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, sensor module 180, button 190, motor 191, indicator 192, camera 193, display screen 194, and subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, a barometric pressure sensor 180C, a magnetic sensor 180D, an accelerometer sensor 180E, a distance sensor 180F, a proximity sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0439] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the electronic device 200. In other embodiments of this application, the electronic device 200 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.

[0440] Processor 1110 may include one or more processing units, such as an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, memory, a video codec, a digital signal processor (DSP), a baseband processor, or a neural network processing unit (NPU). These different processing units may be independent devices or integrated into one or more processors.

[0441] The controller can be the nerve center and command center of the electronic device 200. The controller can generate operation control signals based on the instruction opcode and timing signals to control the fetching and execution of instructions.

[0442] The processor 1110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 1110 is a cache memory. This memory can store instructions or data that the processor 1110 has just used or that are used repeatedly. If the processor 1110 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 1110, and thus improves the efficiency of the system.

[0443] In some embodiments, the processor 1110 may include one or more interfaces. Interfaces may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, or a universal serial bus (USB) interface, etc.

[0444] The charging management module 140 receives charging input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 receives charging input from the wired charger via the USB interface 130. In some wireless charging embodiments, the charging management module 140 receives wireless charging input via the wireless charging coil of the electronic device 200. While charging the battery 142, the charging management module 140 can also supply power to the electronic device via the power management module 141.

[0445] The power management module 141 connects the battery 142, the charging management module 140, and the processor 1110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, providing power to the processor 1110, internal memory 121, external memory, display screen 194, camera 193, and wireless communication module 160, etc. The power management module 141 can also monitor parameters such as battery capacity, battery cycle count, and battery health status (leakage current, impedance). In some other embodiments, the power management module 141 may also be located within the processor 1110. In other embodiments, the power management module 141 and the charging management module 140 may be located in the same device.

[0446] The wireless communication function of electronic device 200 can be implemented through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor, and baseband processor.

[0447] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 200 can be used to cover one or more communication frequency bands. Different antennas can also be reused to improve antenna utilization.

[0448] The mobile communication module 150 can provide solutions for wireless communication, including 2G / 3G / 4G / 5G, applied to the electronic device 200. 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. The mobile communication module 150 can also amplify the signal modulated by the modem processor and convert it into electromagnetic waves for radiation via antenna 1.

[0449] A modem processor may include a modulator and a demodulator. The modulator modulates the low-frequency baseband signal to be transmitted into a mid-to-high frequency signal. The demodulator demodulates the received electromagnetic wave signal into a low-frequency baseband signal.

[0450] The wireless communication module 160 can provide solutions for wireless communication applications on the electronic device 200, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR) technologies. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via antenna 2, performs frequency modulation and filtering of the electromagnetic wave signals, and sends the processed signal to processor 1110. The wireless communication module 160 can also receive signals to be transmitted from processor 1110, perform frequency modulation and amplification, and convert them into electromagnetic waves for radiation via antenna 2.

[0451] Electronic device 200 implements display functions through a GPU, display screen 194, and application processor. Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel.

[0452] Electronic device 200 can perform shooting functions through ISP, camera 193, video codec, GPU, display 194 and application processor.

[0453] The ISP is used to process data fed back from the camera. For example, when taking a picture, the shutter is opened, and light is transmitted through the lens to the camera's image sensor. The light signal is converted into an electrical signal, and the image sensor transmits the electrical signal to the ISP for processing, transforming it into an image visible to the naked eye.

[0454] Camera 193 is used to capture still images or videos. An object passes through the lens to generate an optical image that is projected onto a photosensitive element.

[0455] A digital signal processor is used to process digital signals. In addition to processing digital image signals, it can also process other digital signals.

[0456] NPU stands for Neural-Network (NN) Computing Processor. By drawing inspiration from the structure of biological neural networks, such as the transmission patterns between neurons in the human brain, it can quickly process input information and continuously learn on its own.

[0457] 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 electronic device 200.

[0458] Internal memory 121 can be used to store computer executable program code, which includes instructions. Processor 1110 executes various functional applications and data processing of electronic device 200 by running the instructions stored in internal memory 121.

[0459] Electronic device 200 can implement audio functions such as music playback and recording through audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, and application processor.

[0460] 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. Audio module 170 can also be used for encoding and decoding audio signals.

[0461] The speaker 170A, also known as a "loudspeaker," is used to convert audio electrical signals into sound signals. The electronic device 200 can listen to music or make hands-free calls through the speaker 170A.

[0462] The receiver 170B, also known as the "earpiece," is used to convert audio electrical signals into sound signals. When the electronic device 200 answers a telephone call or voice message, the receiver 170B can be brought close to the ear to listen to the voice.

[0463] Microphone 170C, also known as a "microphone" or "voice transducer," is used to convert sound signals into electrical signals. When making a phone call or sending a voice message, the user can speak by bringing their mouth close to microphone 170C, inputting the sound signal into microphone 170C. Electronic device 200 may have at least one microphone 170C. In some embodiments, electronic device 200 may have two microphones 170C, which, in addition to collecting sound signals, can also perform noise reduction. In other embodiments, electronic device 200 may have three, four, or more microphones 170C, which can collect sound signals, reduce noise, identify the sound source, and perform directional recording, etc.

[0464] In this embodiment, the electronic device 200 collects sound signals through the microphone 170C and transmits the sound signals to the application in the electronic device 200.

[0465] The 170D headphone jack is used to connect wired headphones. The 170D headphone jack can be a USB 130 interface or a 3.5mm Open Mobile Terminal Platform (OMTP) standard interface, a CTIA (Cellular Telecommunications Industry Association of the USA) standard interface.

[0466] Pressure sensor 180A is used to sense pressure signals and convert them into electrical signals. In some embodiments, pressure sensor 180A can be disposed on display screen 194. There are many types of pressure sensors 180A, such as resistive pressure sensors, inductive pressure sensors, and capacitive pressure sensors. A capacitive pressure sensor may include at least two parallel plates with conductive material. When force is applied to pressure sensor 180A, the capacitance between the electrodes changes. Electronic device 200 determines the pressure intensity based on the change in capacitance. When a touch operation is applied to display screen 194, electronic device 200 detects the intensity of the touch operation based on pressure sensor 180A. Electronic device 200 can also calculate the touch position based on the detection signal from pressure sensor 180A. In some embodiments, touch operations applied to the same touch position but with different touch operation intensities can correspond to different operation commands. For example: when a touch operation with an intensity less than a first pressure threshold is applied to the SMS application icon, a command to view an SMS is executed. When a touch operation with an intensity greater than or equal to the first pressure threshold is applied to the SMS application icon, a command to create a new SMS is executed.

[0467] The gyroscope sensor 180B can be used to determine the motion attitude of the electronic device 200. In some embodiments, the gyroscope sensor 180B can determine the angular velocity of the electronic device 200 about three axes (i.e., the x, y, and z axes). The gyroscope sensor 180B can be used for image stabilization. For example, when the shutter is pressed, the gyroscope sensor 180B detects the angle of the shake of the electronic device 200, calculates the distance that the lens module needs to compensate based on the angle, and allows the lens to counteract the shake of the electronic device 200 by moving in the opposite direction, thus achieving image stabilization. The gyroscope sensor 180B can also be used in navigation and motion-sensing game scenarios.

[0468] The barometric pressure sensor 180C is used to measure air pressure. In some embodiments, the electronic device 200 calculates altitude using the air pressure value measured by the barometric pressure sensor 180C to assist in positioning and navigation.

[0469] The magnetic sensor 180D includes a Hall effect sensor. The electronic device 200 can use the magnetic sensor 180D to detect the opening and closing of the flip cover. In some embodiments, when the electronic device 200 is a flip phone, the electronic device 200 can detect the opening and closing of the flip cover using the magnetic sensor 180D. Then, based on the detected opening and closing state of the cover or the flip cover, features such as automatic flip unlocking can be set.

[0470] The accelerometer 180E can detect the magnitude of acceleration of electronic device 200 in various directions (typically three axes). When electronic device 200 is stationary, it can detect the magnitude and direction of gravity. It can also be used to identify the posture of electronic device, and can be applied to applications such as screen orientation switching and pedometers.

[0471] A distance sensor 180F is used to measure distance. Electronic device 200 can measure distance via infrared or laser. In some embodiments, during a shooting scene, electronic device 200 can utilize the distance sensor 180F for distance measurement to achieve fast focusing.

[0472] The proximity sensor 180G may include, for example, a light-emitting diode (LED) and a light detector, such as a photodiode. The LED may be an infrared LED. The electronic device 200 emits infrared light outward through the LED. The electronic device 200 uses the photodiode to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that an object is near the electronic device 200. When insufficient reflected light is detected, the electronic device 200 can determine that no object is near the electronic device 200. The electronic device 200 may use the proximity sensor 180G to detect when a user holds the electronic device 200 close to their ear for a call, so as to automatically turn off the screen to save power. The proximity sensor 180G can also be used in holster mode and pocket mode for automatic unlocking and locking of the screen.

[0473] The ambient light sensor 180L is used to sense the brightness of ambient light. The electronic device 200 can adaptively adjust the brightness of the display screen 194 according to the sensed ambient light brightness. The ambient light sensor 180L can also be used to automatically adjust the white balance when taking pictures. The ambient light sensor 180L can also be used in conjunction with the proximity sensor 180G to detect whether the electronic device 200 is in a pocket to prevent accidental touches.

[0474] The fingerprint sensor 180H is used to collect fingerprints. The electronic device 200 can utilize the characteristics of the collected fingerprints to achieve fingerprint unlocking, accessing application locks, taking photos with fingerprints, answering calls with fingerprints, etc.

[0475] Temperature sensor 180J is used to detect temperature. In some embodiments, electronic device 200 uses the temperature detected by temperature sensor 180J to execute a temperature handling strategy. For example, when the temperature reported by temperature sensor 180J exceeds a threshold, electronic device 200 performs thermal protection by reducing the performance of a processor located near temperature sensor 180J to reduce power consumption. In other embodiments, when the temperature is below another threshold, electronic device 200 heats battery 142 to prevent abnormal shutdown of electronic device 200 due to low temperature. In still other embodiments, when the temperature is below yet another threshold, electronic device 200 boosts the output voltage of battery 142 to prevent abnormal shutdown due to low temperature.

[0476] Touch sensor 180K, also known as a touch panel or touch-sensitive surface, can be located on display screen 194. The touch sensor 180K and display screen 194 together form a touchscreen, also called a "touchscreen." Touch sensor 180K detects touch operations applied to or near it. The touch sensor can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through display screen 194. In other embodiments, touch sensor 180K may also be located on the surface of electronic device 200, in a different position than display screen 194.

[0477] The bone conduction sensor 180M can acquire vibration signals. In some embodiments, the bone conduction sensor 180M can acquire vibration signals from the vibrating bone segments of the human vocal cords. The bone conduction sensor 180M can also contact the human pulse to receive blood pressure signals. In some embodiments, the bone conduction sensor 180M can also be incorporated into headphones to form bone conduction headphones. The audio module 170 can parse the voice signals from the vibrating bone segments of the vocal cords acquired by the bone conduction sensor 180M to realize voice functionality. The application processor can parse heart rate information from the blood pressure signals acquired by the bone conduction sensor 180M to realize heart rate detection functionality.

[0478] Buttons 190 include a power button, volume buttons, etc. Buttons 190 can be mechanical buttons or touch-sensitive buttons. Electronic device 200 can receive button input and generate key signal inputs related to user settings and function control of electronic device 200.

[0479] Motor 191 can generate vibration alerts. Motor 191 can be used for incoming call vibration alerts or for touch vibration feedback. For example, different vibration feedback effects can correspond to touch operations performed on different applications (such as taking photos, playing audio, etc.). Motor 191 can also correspond to different vibration feedback effects for touch operations performed on different areas of the display screen 194. Different application scenarios (such as time reminders, receiving messages, alarm clocks, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also be customized.

[0480] Indicator 192 can be an indicator light, used to indicate charging status, power changes, or to indicate messages, missed calls, notifications, etc.

[0481] The SIM card interface 195 is used to connect a SIM card. The SIM card can be inserted into or removed from the SIM card interface 195 to make contact with and separate from the electronic device 200. The electronic device 200 can support one or N SIM card interfaces, where N is a positive integer greater than 1. The SIM card interface 195 can support Nano SIM cards, Micro SIM cards, SIM cards, etc. Multiple cards can be inserted into the same SIM card interface 195 simultaneously. The multiple cards can be of the same or different types. The SIM card interface 195 is also compatible with different types of SIM cards. The SIM card interface 195 is also compatible with external memory cards. The electronic device 200 interacts with the network through the SIM card to realize functions such as calls and data communication. In some embodiments, the electronic device 200 uses an eSIM, i.e., an embedded SIM card. The eSIM card can be embedded in the electronic device 200 and cannot be separated from the electronic device 200.

[0482] Figure 27 This is a flowchart illustrating a balance ability testing method provided in this application.

[0483] This method is applied to wearable devices and foot motion sensors. The wearable device and foot motion sensors establish a communication connection. The wearable device is worn on the user's wrist. The foot motion sensor includes a first foot motion sensor and a second foot motion sensor. The first foot motion sensor is worn on the user's left ankle, and the second foot motion sensor is worn on the user's right ankle. The foot motion sensor includes one or more motion sensors.

[0484] The communication connection can be a Bluetooth connection or other communication methods. This application does not limit the specific communication method used.

[0485] S2701, The wearable device receives first motion data sent by the foot motion sensor, the first motion data being the motion data of the user walking naturally.

[0486] Wearable devices can be devices such as smartwatches / smart bracelets.

[0487] In one possible implementation, before the wearable device receives the first motion data sent by the foot motion sensor, the method further includes: the wearable device receiving third motion data sent by the foot motion sensor, the third motion data being motion data of the user walking; if the wearable device determines gait parameters based on the third motion data, the wearable device outputs a first audio signal, the first audio signal being used to prompt the user to start walking naturally and measure dynamic balance; the wearable device receiving the first motion data sent by the foot motion sensor specifically includes: in response to the first audio signal, the wearable device receiving the first motion data sent by the foot motion sensor.

[0488] Before starting the dynamic balance measurement, the wearable device can first detect the presence of gait parameters, thereby verifying whether the foot motion sensors are properly worn. Once gait parameters are detected, it can be confirmed that the foot motion sensors are worn correctly, and the wearable device can output a voice prompt to the user to begin walking naturally to measure the dynamic balance. This prevents inaccurate measurements caused by the wearable device not being properly worn before starting the dynamic balance measurement.

[0489] In one possible implementation, gait parameters include one or more of the following: stride length, swing time, ground contact time, ground contact angle, ground lift angle, cadence, gait speed, foot force, knee force, and foot roll angle.

[0490] S2702, The wearable device obtains a dynamic balance score during natural walking based on the first motion data.

[0491] In one possible implementation, the first motion data includes motion data of M gaits, of which p are valid gaits and q are invalid gaits, where p is greater than or equal to a preset number of steps. The wearable device obtains a dynamic balance score for natural walking based on the first motion data, specifically including: the wearable device discarding the motion data of the q invalid gaits; the wearable device obtaining gait parameters of the p valid gaits based on the motion data of the p valid gaits; and the wearable device obtaining a dynamic balance score for natural walking based on the gait parameters of the p valid gaits.

[0492] In this way, invalid gait patterns may occur during a user's natural walking process. Wearable devices can discard the motion data of invalid gait patterns and obtain a dynamic balance score based solely on the motion data of valid gait patterns during natural walking. This can improve the accuracy of dynamic balance measurements.

[0493] In one possible implementation, the wearable device obtains a dynamic balance score for natural walking based on the gait parameters of p effective gaits. Specifically, this includes: the wearable device obtaining the gait symmetry and gait variability of p effective gaits based on the gait parameters of p effective gaits; and the wearable device obtaining a dynamic balance score for natural walking based on the gait symmetry and gait variability of p effective gaits.

[0494] In this way, the user's dynamic balance score can be obtained based on the gait symmetry and gait variability of p effective gaits.

[0495] S2703, The wearable device collects second motion data, which is the motion data of the user standing on one leg with eyes closed.

[0496] In one possible implementation, before the wearable device collects the second motion data, the method further includes: if the wearable device determines that a finger on the wrist of the user not wearing the wearable device is touching the screen of the wearable device, the wearable device outputs a second audio signal to prompt the user to close their eyes and stand on one leg and measure static balance; the wearable device collects the second motion data, specifically including: in response to the second audio signal, the wearable device collects the second motion data.

[0497] Here, the touch of the fingers on the wrist of the user not wearing the wearable device to the wearable device screen can serve as a trigger condition for starting the static balance measurement. If the wearable device detects that the fingers on the wrist of the user not wearing the wearable device are not touching the wearable device screen, the wearable device can prompt the user via voice to place both hands in front of their chest and touch the fingers on the wearable device screen. If the fingers on the wrist of the user not wearing the wearable device are touching the wearable device screen, the wearable device can prompt the user via voice to begin measuring static balance by closing their eyes and standing on one leg.

[0498] S2704, The wearable device obtains a static balance score when standing on one leg with eyes closed based on the second motion data.

[0499] In one possible implementation, before the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data, the method further includes: the wearable device obtaining real-time swing amplitude and real-time swing frequency based on the second motion data; and if the real-time swing amplitude and real-time swing frequency meet preset values, the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data.

[0500] Real-time swing amplitude and real-time swing frequency can be the user's real-time swing amplitude and real-time swing frequency.

[0501] This allows for the determination of whether a user's posture while standing on one leg with their eyes closed is stable based on real-time swing amplitude and frequency. If the real-time swing amplitude and frequency do not meet preset values, it indicates that the user's body is swaying significantly and they are not yet stable. In this case, static balance cannot be measured. Once the user's posture while standing on one leg with their eyes closed is stable, i.e., after the real-time swing amplitude and frequency meet the preset values, a static balance score can be obtained based on the collected motion data. This improves the accuracy of static balance measurements.

[0502] In one possible implementation, after the wearable device collects the second motion data, the method further includes: the wearable device stopping the collection of motion data.

[0503] After both static and dynamic balance measurements are completed, the wearable device can stop collecting motion data to reduce power consumption.

[0504] In some embodiments, after the dynamic balance measurement is completed, such as after obtaining a dynamic balance score, or after the wearable device acquires the first motion data, the wearable device can send a message to the foot motion sensor, instructing the foot motion sensor to stop collecting motion data, in order to reduce the power consumption of the foot motion sensor.

[0505] In one possible implementation, the wearable device stops collecting motion data, specifically including: during the period when the wearable device is collecting second motion data, if it detects that the fingers of the wrist not wearing the wearable device are constantly touching the screen of the wearable device, and the duration of the second motion data is longer than the first duration, the wearable device stops collecting motion data.

[0506] In other words, when measuring static balance, if the fingers of the wrist not wearing the wearable device remain on the screen of the wearable device, and the data collection time for motion data while standing on one leg exceeds a preset duration (the first duration), then the second data can confirm static balance. In other words, the fact that the fingers of the wrist not wearing the wearable device remain on the screen and the duration of the second motion data exceeds the first duration can serve as a trigger condition for ending the static balance measurement. The wearable device can then automatically stop collecting motion data to reduce its power consumption.

[0507] In other possible implementations, the wearable device could stop collecting motion data after obtaining a static balance score, in order to reduce the power consumption of the wearable device.

[0508] In one possible implementation, the wearable device stops collecting motion data, specifically including: after the wearable device collects second motion data, the fingers of the wrist not wearing the wearable device stop touching the screen of the wearable device, and the duration of the second motion data is greater than the second duration but less than the first duration, and the wearable device stops collecting motion data.

[0509] The termination of static balance measurement can also be triggered when the fingers on the wrist not wearing the wearable device stop touching the screen of the wearable device and the duration of the second motion data is greater than the second duration but less than the first duration.

[0510] S2705. Wearable devices obtain a comprehensive score of the user's balance ability based on dynamic balance scoring and static balance scoring.

[0511] In this application, dynamic balance can be measured first, followed by static balance. Alternatively, static balance can be measured first, followed by dynamic balance; this application does not limit the choice.

[0512] In one possible implementation, the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data, specifically including: the wearable device obtains the average swing amplitude and average swing frequency based on the second motion data; the wearable device obtains a static balance score for standing on one leg with eyes closed based on the duration, average swing amplitude and average swing frequency of the second motion data.

[0513] The average swing amplitude and average swing frequency can be the average swing amplitude and average swing frequency of the user's body.

[0514] In this way, a static balance score can be obtained when the user stands on one leg with their eyes closed, based on the average swing amplitude and average swing frequency when the user stands on one leg, and the duration of the second motion data.

[0515] In one possible implementation, the method further includes: the wearable device receiving third motion data sent by the foot motion sensor; the wearable device obtaining the motion trajectory of the user's two feet based on the third motion data; and, if the motion trajectory meets a first condition, the wearable device determining that the user is in a single-leg standing state.

[0516] The first condition can be the movement trajectory from standing on both feet to slowly raising the other foot to standing on one foot.

[0517] In this way, during the static balance measurement process, the wearable device can determine whether the user is in a single-leg standing posture based on the motion data collected by the foot motion sensor.

[0518] In one possible implementation, the method further includes: the wearable device receiving multiple image frames sent by a first electronic device, the multiple image frames being image frames captured by the camera of the first electronic device when facing the user; the wearable device obtaining the movement trajectory of the user's two feet based on the multiple image frames; and, if the movement trajectory satisfies a second condition, the wearable device determining that the user is in a single-leg standing state.

[0519] The second condition can be the movement trajectory from standing on both feet to slowly lifting the other foot back to standing on one foot. The second condition can be the same as or different from the first condition.

[0520] The first electronic device can be a mobile phone, tablet, or other electronic device.

[0521] In this way, other electronic devices can determine whether a user is standing on one leg.

[0522] In one possible implementation, the method further includes: the wearable device obtaining the real-time swaying frequency of the user's torso during the acquisition of the second motion data based on the second motion data; and determining that the user is in a closed-eye state when the real-time swaying frequency is greater than a preset frequency.

[0523] In this way, wearable devices can determine whether a user is in a closed-eye state based on the second motion data.

[0524] In one possible implementation, the method further includes: the wearable device receiving multiple image frames sent by the first electronic device, the multiple image frames being image frames captured by the camera of the first electronic device when facing the user; the wearable device determining, based on the multiple image frames, that both of the user's eyes are closed, and the wearable device being able to determine that the user is in a closed-eye state.

[0525] For example, the first electronic device may be electronic device 200.

[0526] In other embodiments, Figure 27 The methods and steps performed by the wearable device can also be performed by the electronic device 200, or the wearable device and the electronic device 200 can cooperate and perform them separately. Figure 27 The method steps are shown.

[0527] In other embodiments, dynamic balance detection can be achieved using electronic device 200 and foot motion sensor, and static balance detection can be achieved using electronic device 200 and wearable device, or using wearable device alone.

[0528] This application enables wearable devices to obtain a comprehensive score of a user's balance ability by combining static and dynamic balance detection, thereby improving the accuracy of user balance ability detection.

[0529] This application provides a balance ability detection system, which includes a wearable device and a foot motion sensor. The wearable device and the foot motion sensor establish a communication connection. The wearable device is worn on the user's wrist. The foot motion sensor includes a first foot motion sensor and a second foot motion sensor. The first foot motion sensor is worn on the user's left ankle, and the second foot motion sensor is worn on the user's right ankle. The foot motion sensor includes one or more motion sensors.

[0530] Among them, the foot motion sensor is used to collect the first motion data and send the first motion data to the wearable device. The first motion data is the motion data when the user walks naturally.

[0531] Wearable devices are used to receive initial motion data from foot motion sensors.

[0532] Wearable devices are also used to obtain dynamic balance scores during natural walking based on the first motion data.

[0533] Wearable devices are also used to collect second motion data, which is the motion data of a user standing on one leg with their eyes closed.

[0534] Wearable devices are also used to obtain static balance scores when standing on one leg with eyes closed, based on second motion data.

[0535] Wearable devices are also used to obtain a user's overall balance score based on dynamic and static balance scores.

[0536] Wearable devices can be devices such as smartwatches / smart bracelets.

[0537] The communication connection can be a Bluetooth connection or other communication connection.

[0538] In this application, dynamic balance can be measured first, followed by static balance. Alternatively, static balance can be measured first, followed by dynamic balance; this application does not limit the choice.

[0539] In one possible implementation, the foot motion sensor is also used to: collect third motion data and send the third motion data to the wearable device, wherein the third motion data is motion data of the user walking.

[0540] The wearable device is also used to output a first audio signal when gait parameters are determined based on third motion data. The first audio signal is used to prompt the user to start walking naturally and to measure dynamic balance.

[0541] A wearable device, specifically used to receive first motion data sent by a foot motion sensor in response to a first audio signal.

[0542] In one possible implementation, gait parameters include one or more of the following: stride length, swing time, ground contact time, ground contact angle, ground lift angle, cadence, gait speed, foot force, knee force, and foot roll angle.

[0543] In one possible implementation, a motion data set includes motion data for M gaits, of which p are valid gaits and q are invalid gaits, where p is greater than or equal to a preset number of steps.

[0544] Wearable devices are specifically used for:

[0545] Discard the motion data of q invalid gaits.

[0546] Gait parameters for p effective gait states are obtained based on the motion data of p effective gait states.

[0547] The dynamic balance score during natural walking is obtained based on the gait parameters of p effective gaits.

[0548] In conjunction with the second aspect, in one possible implementation, the wearable device is specifically used for:

[0549] Based on the gait parameters of p effective gaits, we obtain the gait symmetry and gait variability of p effective gaits.

[0550] The dynamic balance score during natural walking is obtained based on the gait symmetry and gait variability of p effective gaits.

[0551] In one possible implementation, the wearable device is also used to output a second audio signal when it is determined that a finger on the wrist of the user not wearing the wearable device is touching the screen of the wearable device. The second audio signal is used to prompt the user to begin closing their eyes and standing on one leg and measuring static balance.

[0552] Wearable devices, specifically used to collect second motion data in response to a second audio signal.

[0553] In one possible implementation, the wearable device is also used for:

[0554] The real-time swing amplitude and real-time swing frequency are obtained based on the second motion data.

[0555] When the real-time swing amplitude and real-time swing frequency meet the preset values, the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data.

[0556] In one possible implementation, the wearable device is also used to: stop collecting motion data.

[0557] In one possible implementation, the wearable device is specifically configured to stop collecting motion data if, during the period when the wearable device is collecting second motion data, it detects that the fingers of the wrist not wearing the wearable device are constantly touching the screen of the wearable device, and the duration of the second motion data is longer than the first duration.

[0558] Another possible implementation is to stop collecting motion data after obtaining a static balance score, in order to reduce the power consumption of the wearable device.

[0559] In one possible implementation, the wearable device is specifically configured to, after collecting second motion data, stop the fingers of the wrist not wearing the wearable device from touching the screen of the wearable device, and stop collecting motion data if the duration of the second motion data is greater than a second duration but less than a first duration.

[0560] In one possible implementation, the wearable device is specifically used for:

[0561] The average swing amplitude and average swing frequency are obtained based on the second motion data.

[0562] The static balance score for standing on one leg with eyes closed is obtained based on the duration, average swing amplitude, and average swing frequency of the second motion data.

[0563] This application provides a wearable device, which includes one or more displays, a processor, and a memory; the memory is coupled to the processor, and the one or more displays are used to store computer program code, which includes computer instructions. The processor invokes the computer instructions to execute the aforementioned code in the wearable device. Figure 27 A method for testing balance ability is provided.

[0564] This application provides a computer-readable storage medium for storing computer instructions, which, when executed on a wearable device, cause the wearable device to perform the aforementioned actions. Figure 27 A method for testing balance ability is provided.

[0565] This application provides a computer program product that, when run on a wearable device, causes the wearable device to perform the aforementioned actions. Figure 27 A method for testing balance ability is provided.

[0566] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if..." or "after..." or "in response to determining..." or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is detected" can be interpreted as meaning "if determining..." or "in response to determining..." or "when (the stated condition or event) is detected" or "in response to detecting (the stated condition or event)".

[0567] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The 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 processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0568] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.< / canvas> < / video> < / videoview> < / imgview> < / textview>

Claims

1. A method for detecting balance ability, characterized in that, The method is applied to a wearable device and a foot motion sensor, wherein the wearable device and the foot motion sensor establish a communication connection. The wearable device is worn on the user's wrist, and the foot motion sensor includes a first foot motion sensor and a second foot motion sensor, wherein the first foot motion sensor is worn on the user's left ankle, and the second foot motion sensor is worn on the user's right ankle; the method includes: The wearable device receives first motion data sent by the foot motion sensor, the first motion data being motion data of the user walking naturally; The wearable device obtains a dynamic balance score during natural walking based on the first motion data; If the wearable device determines that the fingers of the wrist not wearing the wearable device are not touching the screen of the wearable device, the wearable device outputs a second audio signal to prompt the user to place both hands in front of their chest and touch the screen of the wearable device with the fingers of the wrist not wearing the wearable device. After outputting the second audio, if the wearable device determines that a finger on the wrist of the user who is not wearing the wearable device is touching the screen of the wearable device, the wearable device collects second motion data, which is the motion data of the user standing on one leg with eyes closed. The wearable device obtains a static balance score when standing on one leg with eyes closed based on the second motion data; The wearable device obtains a comprehensive score of the user's balance ability based on the dynamic balance score and the static balance score.

2. The method according to claim 1, characterized in that, Before the wearable device receives the first motion data sent by the foot motion sensor, the method further includes: The wearable device receives third motion data sent by the foot motion sensor, the third motion data being motion data of the user walking. When the wearable device determines that there are gait parameters based on the third motion data, the wearable device outputs a first audio signal, which is used to prompt the user to start walking naturally and measure dynamic balance. The wearable device receives the first motion data sent by the foot motion sensor, specifically including: In response to the first audio, the wearable device receives the first motion data sent by the foot motion sensor.

3. The method according to claim 2, characterized in that, The gait parameters include one or more of the following: stride length, swing time, ground contact time, ground contact angle, ground lift angle, cadence, gait speed, foot force, knee joint force, and foot roll angle.

4. The method according to any one of claims 1-3, characterized in that, The first motion data includes motion data of M gaits, of which p are valid gaits and q are invalid gaits, and p is greater than or equal to a preset number of steps; The wearable device obtains a dynamic balance score during natural walking based on the first motion data, specifically including: The wearable device discards the motion data of the q invalid gaits; The wearable device obtains the gait parameters of the p effective gait based on the motion data of the p effective gait. The wearable device obtains the dynamic balance score during natural walking based on the gait parameters of the p effective gait states.

5. The method according to claim 4, characterized in that, The wearable device obtains the dynamic balance score during natural walking based on the gait parameters of the p effective gait states, specifically including: The wearable device obtains the gait symmetry and gait variability of the p effective gaits based on the gait parameters of the p effective gaits; The wearable device obtains the dynamic balance score during natural walking based on the gait symmetry and gait variability of the p effective gaits.

6. The method according to any one of claims 1-3, characterized in that, Before the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data, the method further includes: The wearable device obtains the real-time swing amplitude and real-time swing frequency based on the second motion data; If the real-time swing amplitude and real-time swing frequency meet the preset values, the wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data.

7. The method according to claim 6, characterized in that, After the wearable device collects the second motion data, the method further includes: The wearable device stopped collecting motion data.

8. The method according to claim 7, characterized in that, The wearable device stops collecting motion data, specifically including: If, during the period when the wearable device is collecting the second motion data, a finger on the wrist not wearing the wearable device is constantly touching the screen of the wearable device, and the duration of the second motion data is greater than the first duration, the wearable device will stop collecting motion data.

9. The method according to claim 7, characterized in that, The wearable device stops collecting motion data, specifically including: After the wearable device collects the second motion data, the fingers on the wrist that are not wearing the wearable device stop touching the screen of the wearable device, and the duration of the second motion data is greater than the second duration but less than the first duration, at which point the wearable device stops collecting motion data.

10. The method according to any one of claims 1-3 or 7-9, characterized in that, The wearable device obtains a static balance score for standing on one leg with eyes closed based on the second motion data, specifically including: The wearable device obtains the average swing amplitude and average swing frequency based on the second motion data; The wearable device obtains a static balance score for standing on one leg with eyes closed based on the duration of the second motion data, the average swing amplitude, and the average swing frequency.

11. The method according to any one of claims 1-3 or 7-9, characterized in that, The method further includes: The wearable device receives third motion data sent by the foot motion sensor; The wearable device obtains the movement trajectory of the user's two feet based on the third motion data; If the movement trajectory meets the first condition, the wearable device determines that the user is in a single-leg standing state.

12. The method according to any one of claims 1-3 or 7-9, characterized in that, The method further includes: The wearable device receives multiple image frames sent by the first electronic device, wherein the multiple image frames are image frames captured by the camera of the first electronic device when it is facing the user. The wearable device obtains the movement trajectory of the user's feet based on the multiple image frames; If the movement trajectory meets the second condition, the wearable device determines that the user is in a single-leg standing position.

13. The method according to any one of claims 1-3 or 7-9, characterized in that, The method further includes: The wearable device obtains the real-time swaying frequency of the user's torso based on the second motion data during the period when the second motion data is collected; When the real-time oscillation frequency is greater than a preset frequency, the wearable device determines that the user is in a closed-eye state.

14. A wearable device, characterized in that, The wearable device includes one or more displays, a processor, and a memory; the memory is coupled to the processor, the one or more displays, and the memory is used to store computer program code, the computer program code including computer instructions, and the processor invokes the computer instructions to perform the method of any one of claims 1-13.

15. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed on a wearable device, cause the wearable device to perform the method described in any one of claims 1-13.

16. A computer program product, characterized in that, When the computer program product is run on a wearable device, the wearable device performs the method according to any one of claims 1-13.

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