A method, apparatus, and system for detecting the tightness of wearable devices.

Abstract

This application discloses a method, apparatus, and system for detecting the tightness of a wearable device. The method includes collecting a user's motion data when the wearable device is detected to be in a wearing state; identifying motion data of a first action in the user's motion data; and determining the tightness of the wearable device corresponding to the motion data of the first action. Thus, embodiments of this application can determine the tightness of the wearable device based on the user's motion data, thereby avoiding the problem of inaccurate motion data collection, making the collection of motion data more reliable, and laying the foundation for providing users with more professional guidance.

Description

Technical Field

[0001] The present invention relates to the field of electronic device technology, and in particular to a method, apparatus and system for detecting the tightness of wearable devices. Background Technology

[0002] With the development of technology, wearable devices are widely used in people's lives, work, and studies. For example, wearable devices can detect a user's health status and exercise activity. When a wearable device is worn too loosely, the data collected is inaccurate, leading to inaccurate assessments of the user's health status or exercise activity, thus affecting the device's detection performance. Therefore, how to detect the tightness of a wearable device is a technical problem that needs to be solved in this field. Summary of the Invention

[0003] This application provides a method, apparatus, and system for detecting the tightness of wearable devices, which is used to detect the tightness of wearable devices and ensure the detection performance of wearable devices.

[0004] Firstly, this application provides a method for detecting the tightness of a wearable device. The method can be executed by an electronic device (such as a wearable device) or by a component within the electronic device (e.g., a chip, chip system, or processor). The following description uses an electronic device as the executing entity. The method includes: when the wearable device is detected to be in a wearing state, collecting the user's motion data; identifying motion data of a first action within the user's motion data; and determining the tightness of the wearable device corresponding to the motion data of the first action.

[0005] The user's motion data may include acceleration and / or angular velocity. The tightness of the wearable device can be understood as the degree of tightness (e.g., the wearable device is worn normally, the wearable device is loose, and the wearable device is tight), or it can be understood as a specific numerical value.

[0006] The first action is a movement performed by the user during exercise. This first action corresponds to the position where the wearable device is worn. When the wearable device is worn on the user's arm or wrist, the first action may include arm swinging movements, etc. When the wearable device is worn on the user's ankle or running shoes, the first action may include jumping movements, leg kicking movements, etc.

[0007] In this way, the embodiments of this application can determine the tightness of the wearable device based on the user's exercise data, thereby avoiding the problem of inaccurate exercise data collection, making the collection of exercise data more reliable, and laying the foundation for providing users with more professional guidance.

[0008] In one possible implementation, the tightness of the wearable device corresponding to the motion data of the first action can be determined by: determining the tightness of the wearable device based on the motion data of the first action and the preset correspondence between motion data and tightness.

[0009] The preset correspondence between motion data and wearing tightness can be understood as follows: First, a one-to-one correspondence between motion data and wearing tightness, meaning that the value of the motion data corresponds one-to-one with the wearing tightness. For example, taking acceleration as the motion data, the acceleration value is 30 m / s². 2 The first type corresponds to the tightness of the fit, indicating proper wearing. The second type is a correlation between a set of motion data and the tightness of the fit; that is, the numerical range of the motion data corresponds to the tightness of the fit. For example, taking acceleration as the motion data, the numerical range of acceleration is 30-50 m / s². 2 Its tightness corresponds to the normal wearing tightness.

[0010] In this embodiment, the wearable device can determine the tightness of the wearable device based on the user's motion data. No additional hardware device is needed to drive the wearable device to move. The tightness of the wearable device can be detected, which can effectively avoid the problem of inaccurate motion data collection, making the collection of motion data more reliable and laying the foundation for providing users with more professional guidance.

[0011] In one possible implementation, the wearing tightness of the wearable device is determined based on the motion data of the first action and a preset correspondence between motion data and wearing tightness. Specifically, this can be achieved by: identifying the motion data of a first action node in the motion data of the first action; determining the first feature data corresponding to the first action node based on the motion data of the first action node; and determining the wearing tightness of the wearable device based on the first feature data and the preset correspondence between motion data and wearing tightness.

[0012] In one possible implementation, the first feature data includes at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of troughs of the acceleration waveform, the number of troughs of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of the acceleration, the mean value of the angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform.

[0013] The mean acceleration can be understood as the average acceleration over a preset time period. The mean angular velocity can be understood as the average angular velocity over a preset time period. The gradient of the acceleration waveform can be understood as the slope of the tangent line at a preset position in the acceleration waveform. The gradient of the angular velocity waveform can be understood as the slope of the tangent line at a preset position in the angular velocity waveform.

[0014] In one possible implementation, determining the wear tightness of the wearable device corresponding to the motion data of the first action can be achieved by: determining the wear tightness of the wearable device corresponding to the motion data of the first action and a wear tightness model. Here, the motion data of the first action serves as the input to the wear tightness model, and the wear tightness of the wearable device serves as the output of the wear tightness model.

[0015] In one possible implementation, after determining the tightness of the wearable device corresponding to the action data of the first action, the method for detecting the tightness of the wearable device provided in this application embodiment may further include: generating a prompt message based on the tightness of the wearable device, and presenting the detection result of the tightness of the wearable device in a preset presentation format. The preset presentation format includes one or more of the following combinations: sound presentation, text presentation, vibration presentation, and light presentation.

[0016] In this embodiment of the application, by using different forms to prompt the detection results to the user, it is possible to effectively avoid the phenomenon that the user's wearable device is easy to fall off or be lost during the user's exercise. At the same time, it can avoid the risk of the user being bumped or accidentally bumping into something during the exercise.

[0017] In one possible implementation, the tightness of the wearable device includes: normal wear, loose wear, and tight wear.

[0018] In some embodiments, a method for detecting the tightness of a wearable device provided in this application further includes: determining the tightness of the wearable device at each moment within a first duration; determining a second duration for which the wearable device is loose based on the tightness of the wearable device at each moment within the first duration; and calculating a second kinetic energy of the user within the first duration based on the first duration, the second duration, and a first kinetic energy calculated by the wearable device. The first kinetic energy is calculated under the condition that the wearable device is worn normally or tightly within the first duration.

[0019] Here, both the first and second kinetic energy can be understood as the user's energy consumption during exercise. For example, the calories burned during exercise.

[0020] The second duration can refer to a continuous duration or the sum of multiple non-continuous durations. In other words, the second duration can be a continuous period of time during which the wearable device is loosened, or it can be the sum of multiple non-continuous durations during which the wearable device is loosened.

[0021] Therefore, in this embodiment, the wearable device can assess the user's exercise energy during a second duration. If the wearable device is loosely fitted, it can determine the user's actual exercise energy during the second duration based on the proportion of time the device is loose and the assessed exercise energy, making the user's exercise data more reliable and reminding the user to adjust the tightness of the wearable device during the next run.

[0022] In one possible implementation, the first action includes a take-off action, and the first action node includes the feet leaving the ground and / or the feet touching the ground; or, the first action includes an arm swing action, and the first action node includes the arms swinging to a designated position in front of the body and / or the arms swinging to a designated position behind the body.

[0023] In one possible implementation, the wearable device is worn on the user's foot or shoe.

[0024] Secondly, this application provides a device for detecting the tightness of a wearable device. The device includes: a data acquisition unit for acquiring user motion data when the wearable device is detected to be in a wearing state; an identification unit for identifying motion data of a first action within the user's motion data; and a first determination unit for determining the tightness of the wearable device corresponding to the motion data of the first action. Thus, this application embodiment can determine the tightness of the wearable device based on the user's motion data, thereby avoiding the problem of inaccurate motion data acquisition, making the acquisition of motion data more reliable, and laying the foundation for providing users with more professional guidance.

[0025] In one possible implementation, the first determining unit is further configured to: determine the wearing tightness of the wearable device based on the motion data of the first action and the preset correspondence between motion data and wearing tightness.

[0026] In one possible implementation, the first determining unit is further configured to: identify the motion data of a first motion node in the motion data of the first motion; determine the first feature data corresponding to the first motion node based on the motion data of the first motion node; and determine the wearing tightness of the wearable device based on the first feature data and a preset correspondence between motion data and wearing tightness.

[0027] In one possible implementation, the first feature data includes at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of troughs of the acceleration waveform, the number of troughs of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of the angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform.

[0028] In one possible implementation, the first determining unit is further configured to: determine the wearing tightness of the wearable device corresponding to the motion data of the first action, based on the motion data of the first action and the wearing tightness model. The motion data of the first action serves as the input to the wearing tightness model, and the wearing tightness of the wearable device serves as the output of the wearing tightness model.

[0029] In some embodiments, the apparatus for detecting the tightness of a wearable device provided in this application further includes: a generation unit, configured to generate a prompt message based on the tightness of the wearable device, wherein the prompt message presents the detection result of the tightness of the wearable device in a preset presentation format. The preset presentation format includes one or more of the following combinations: sound presentation, text presentation, vibration presentation, and light presentation.

[0030] In this embodiment of the application, by using different forms to prompt the detection results to the user, it is possible to effectively avoid the phenomenon that the user's wearable device is easy to fall off or be lost during the user's exercise. At the same time, it can avoid the risk of the user being bumped or accidentally bumping into something during the exercise.

[0031] In one possible implementation, the tightness of the wearable device includes: normal wear, loose wear, and tight wear.

[0032] In some embodiments, the apparatus for detecting the tightness of a wearable device provided in this application further includes: a second determining unit, configured to determine the tightness of the wearable device at each moment within a first duration; a third determining unit, configured to determine a second duration of loose wear based on the tightness of the wearable device at each moment within the first duration; and a calculation unit, configured to calculate the user's second kinetic energy within the first duration based on the first duration, the second duration, and a first kinetic energy calculated by the wearable device. The first kinetic energy is calculated under the condition that the wearable device is worn normally or tightly within the first duration.

[0033] Therefore, in this embodiment, the wearable device can assess the user's exercise energy during a second duration. If the wearable device is loosely fitted, it can determine the user's actual exercise energy during the second duration based on the proportion of time the device is loose and the assessed exercise energy, making the user's exercise data more reliable and reminding the user to adjust the tightness of the wearable device during the next run.

[0034] In one possible implementation, the first action includes a take-off action, and the first action node includes the feet leaving the ground and / or the feet touching the ground; or, the first action includes an arm swing action, and the first action node includes the arms swinging to a designated position in front of the body and / or the arms swinging to a designated position behind the body.

[0035] In one possible implementation, the wearable device is worn on the user's foot or shoe.

[0036] It is understood that the device has the function of implementing any of the above aspects and possible implementation methods. This function can be implemented by hardware or by hardware executing corresponding software. The hardware or software includes at least one module or unit corresponding to the above function.

[0037] Thirdly, this application provides a system for detecting the tightness of a wearable device. The system includes: a wearable device, configured to: collect user motion data when the wearable device is detected to be in a wearing state; identify motion data of a first action within the user's motion data; determine the tightness of the wearable device corresponding to the motion data of the first action; and send the tightness of the wearable device to a non-wearable device. The non-wearable device is configured to: receive the tightness of the wearable device and generate a prompt message based on the tightness of the wearable device, the prompt message being used to inform the user of the detection result of the tightness of the wearable device.

[0038] In this embodiment, the function of detecting the tightness of wearable devices is extended to multiple devices. Through the coordinated operation of multiple devices, the problem of tightness of wear for users is solved, and the user's experience of multiple devices working together is enhanced.

[0039] Fourthly, this application provides a system for detecting the tightness of a wearable device. The system includes: a wearable device, configured to: collect user motion data when the wearable device is detected to be in a wearing state; and send the collected motion data to a non-wearable device. The non-wearable device is configured to: receive the motion data sent by the wearable device, identify motion data of a first action within the motion data, and determine the tightness of the wearable device corresponding to the motion data of the first action.

[0040] In one possible implementation, the non-wearable device is also used to: generate prompt information based on the tightness of the wearable device, the prompt information being used to inform the user of the detection result of the tightness of the wearable device.

[0041] In this embodiment, the detection and prompting function of the wearable device's tightness is extended to multiple devices. Through the coordinated operation of multiple devices, the problem of tightness of the wearer is solved, and the user's experience of multiple devices working together is enhanced.

[0042] Fifthly, a computer-readable storage medium is provided, including computer instructions that, when executed on a terminal, cause the terminal to perform the methods described in the foregoing aspects and any possible implementation thereof.

[0043] Sixthly, a computer program product is provided that, when run on a computer, causes the computer to perform the methods described in the foregoing aspects and any of their possible implementations.

[0044] A seventh aspect provides a chip system including a processor, which, when executing instructions, performs the methods described in the foregoing aspects and any possible implementation thereof.

[0045] For the specific implementation methods and corresponding technical effects of the embodiments in the second to seventh aspects mentioned above, please refer to the specific implementation methods and technical effects of the first aspect mentioned above. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 This is a schematic diagram of the structure of a wearable device provided in an embodiment of this application;

[0048] Figure 2 A flowchart illustrating a method for detecting the tightness of a wearable device, provided in an embodiment of this application;

[0049] Figure 3 This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application.

[0050] Figure 4 This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application.

[0051] Figure 5 This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application.

[0052] Figure 6a This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application.

[0053] Figure 6b This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application.

[0054] Figure 7 A flowchart illustrating a method for detecting the tightness of wearable devices in an application scenario, provided in an embodiment of this application;

[0055] Figure 8 A flowchart illustrating a method for detecting the tightness of wearable devices in an application scenario, provided in an embodiment of this application;

[0056] Figure 9 A flowchart illustrating a method for detecting the tightness of wearable devices in an application scenario, provided in an embodiment of this application;

[0057] Figure 10 A flowchart illustrating a method for detecting the tightness of a wearable device, provided in an embodiment of this application;

[0058] Figure 11 A flowchart illustrating a method for detecting the tightness of a wearable device, provided in an embodiment of this application;

[0059] Figure 12 This is a schematic diagram of a device for detecting the tightness of a wearable device, provided in an embodiment of this application. Detailed Implementation

[0060] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. "And / or" in this document is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone.

[0061] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of embodiments of this application, unless otherwise stated, "a plurality of" means two or more.

[0062] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0063] With the development of technology, wearable devices are widely used in people's lives, work, and studies. For example, wearable devices can detect a user's health status and exercise activity. When a wearable device is worn loosely, the data collected is inaccurate, leading to inaccurate assessments of the user's health status or exercise activity, thus affecting the device's detection performance.

[0064] To ensure the detection performance of wearable devices, the following method can be used to detect the tightness of the wearable device: a pressure sensor installed on the bottom shell of the wearable device detects the pressure value on the bottom shell of the wearable device, and the tightness of the wearable device is determined based on the detected pressure value. This solves the problem of detecting the tightness of the wearable device, improves user comfort, and increases the accuracy of the wearable device detection performance.

[0065] This application provides another method for detecting the tightness of a wearable device: when the wearable device is detected to be in a wearing state, the user's motion data is collected. The motion data of the first action in the user's motion data is identified. The tightness of the wearable device corresponding to the motion data of the first action is determined. In this way, this application embodiment can determine the tightness of the wearable device based on the user's motion data, thereby avoiding the problem of inaccurate motion data collection, making the collection of motion data more reliable, and laying the foundation for providing users with more professional guidance.

[0066] Furthermore, determining the wearability tightness of the wearable device corresponding to the motion data of the first action can be achieved in the following ways: Method 1: Determine the wearability tightness of the wearable device based on the motion data of the first action and the correspondence between motion data and wearability tightness. For example, based on the motion data of the first action, determine the first feature data corresponding to the first action node of the user's first action. Determine the wearability tightness of the wearable device based on the correspondence between feature data and wearability tightness, and the first feature data corresponding to the first action node. Method 2: Determine the wearability tightness of the wearable device corresponding to the motion data of the first action based on the motion data of the first action and a wearability tightness model. Here, the motion data of the first action serves as the input to the wearability tightness model, and the wearability tightness of the wearable device serves as the output of the wearability tightness model, which is trained based on motion data and wearability tightness of the wearable device.

[0067] Furthermore, the method for detecting the tightness of a wearable device provided in this application embodiment further includes: generating a prompt message based on the tightness of the wearable device, and presenting the detection result of the tightness of the wearable device to the user in a preset presentation format. The preset presentation format includes one or more combinations of the following: sound presentation, text presentation, vibration presentation, and light presentation. This effectively and intuitively displays the detection result to the user, achieving a timely reminder.

[0068] The method for adjusting the tightness of wearable devices provided in this application can be implemented by one or more entities.

[0069] When there is only one entity executing the method for detecting the tightness of a wearable device, the entity executing the method for detecting the tightness of a wearable device can be the wearable device itself.

[0070] When the method for detecting the tightness of a wearable device involves at least two entities, these entities can include both the wearable device and a non-wearable device. The non-wearable device can be a mobile phone, computer, headphones, watch, bracelet, or similar device. The interaction between the wearable device and the non-wearable device can be implemented in various ways. For example, it can be described as follows:

[0071] Method 1: When the wearable device detects that it is being worn, it collects the user's motion data, identifies the first action data within the motion data, determines the tightness of the wearable device corresponding to the first action data, and sends the tightness information to a non-wearable device. Specifically: When the wearable device detects that it is being worn, it collects the user's motion data. The wearable device identifies the first action data within the collected motion data, which includes at least one action node. The wearable device determines the first feature data corresponding to the first action node of the user's first action. Based on the correspondence between motion data stored in a standard database (e.g., the first standard data of the first action node) and the tightness information, and the first feature data corresponding to the first action node, the wearable device determines the tightness of the wearable device. The wearable device sends the tightness information to the non-wearable device. The non-wearable device receives the tightness information and generates a prompt message to inform the user of the tightness detection result.

[0072] Method 2: When the wearable device detects that it is being worn, it collects the user's motion data. The wearable device sends the collected motion data to a non-wearable device. The non-wearable device receives the motion data sent by the wearable device and identifies the motion data of the first action within the motion data to determine the tightness of the wearable device corresponding to the motion data of the first action. Specifically, the non-wearable device identifies the motion data of the first action in the motion data, and the first action includes at least one motion node. The non-wearable device determines the first feature data corresponding to the first motion node of the user's first action. The non-wearable device determines the tightness of the wearable device based on the correspondence between motion data stored in a standard database (e.g., the first standard data of the first motion node) and the tightness of the wearable device, and the first feature data corresponding to the first motion node. Furthermore, the non-wearable device generates a prompt message based on the tightness of the wearable device to inform the user of the detection result of the tightness of the wearable device. Other methods can also be used for the cooperation between the wearable device and the non-wearable device.

[0073] The structure of wearable devices or non-wearable devices is described below. Wearable devices and non-wearable devices can have the same structure. This application uses the example of wearable devices and non-wearable devices having the same structure for illustration. Figure 1 A schematic diagram of the structure of the wearable device 100 is shown.

[0074] Wearable device 100 may include a processor 110, a memory 120, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, a sensor module 150, a display screen 160, an antenna 1, a wireless communication module 170, and an audio module 180, etc. The sensor module 150 may include an accelerometer 150A, a gyroscope 150B, etc. The audio module 180 may include a speaker 180A, a receiver 180B, a microphone 180C, etc.

[0075] It is understood that the structures illustrated in the embodiments of the present invention 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.

[0076] Processor 110 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.

[0077] The controller can generate operation control signals based on the instruction opcode and timing signals to complete the control of instruction fetching and execution.

[0078] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 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 110, and thus improves the efficiency of the system.

[0079] In some embodiments, the processor 110 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, and / or a universal serial bus (USB) interface, etc.

[0080] It is understood that the interface connection relationships between the modules illustrated in the embodiments of the present invention are merely illustrative and do not constitute a structural limitation on the wearable device 100. In other embodiments of this application, the wearable device 100 may also employ different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0081] The memory 120 can be used to store computer executable program code, which includes instructions. The memory 120 may include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback, image playback, etc.), etc. The data storage area may store data created during the use of the wearable device 100 (such as audio data, phonebook, etc.). Furthermore, the memory 120 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc. The processor 110 executes various functional applications and data processing of the wearable device 100 by running instructions stored in the memory 120 and / or instructions stored in memory disposed within the processor.

[0082] 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 wearable device 100. While charging the battery 142, the charging management module 140 can also supply power to the wearable device via the power management module 141.

[0083] The power management module 141 connects the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, providing power to the processor 110, internal memory 121, display screen 160, and wireless communication module 170, 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 110. In other embodiments, the power management module 141 and the charging management module 140 may be located in the same device.

[0084] The accelerometer 150A can detect the magnitude of acceleration of the wearable device 100 in various directions (typically three axes). When the wearable device 100 is stationary, it can detect the magnitude and direction of gravity. It can also be used to identify the posture of the wearable device, and can be applied to applications such as screen orientation switching and pedometers.

[0085] The gyroscope sensor 150B can be used to determine the motion posture of the wearable device 100. In some embodiments, the gyroscope sensor 150B can determine the angular velocity of the wearable device 100 about three axes (i.e., the x, y, and z axes). The gyroscope sensor 150B can be used for image stabilization. For example, when the shutter is pressed, the gyroscope sensor 150B detects the angle of the wearable device 100's shake, calculates the distance that the lens module needs to compensate based on the angle, and allows the lens to counteract the shake of the wearable device 100 through reverse movement, thus achieving image stabilization. The gyroscope sensor 150B can also be used in navigation and motion-sensing gaming scenarios.

[0086] The wireless communication function of the wearable device 100 can be implemented through the antenna 1, the wireless communication module 170, the modem processor, and the baseband processor.

[0087] Antenna 1 is used to transmit and receive electromagnetic wave signals. Each antenna in wearable device 100 can be used to cover one or more communication frequency bands. Different antennas can also be reused to improve antenna utilization. In some other embodiments, the antenna can be used in conjunction with a tuning switch.

[0088] Wearable device 100 implements display functions through a GPU, display screen 160, and application processor. The GPU is a microprocessor for image processing, connected to the display screen 160 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs, which execute program instructions to generate or modify display information.

[0089] The display screen 160 is used to display images, videos, etc. The display screen 160 includes a display panel. The display panel may be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a miniature LED, a microLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the wearable device 100 may include one or N displays 160, where N is a positive integer greater than 1.

[0090] The wireless communication module 170 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 170 can be one or more devices integrating at least one communication processing module. The wireless communication module 170 receives electromagnetic waves via antenna 1, performs frequency modulation and filtering of the electromagnetic wave signals, and sends the processed signal to processor 110. The wireless communication module 170 can also receive signals to be transmitted from processor 110, perform frequency modulation and amplification, and convert them into electromagnetic waves for radiation via antenna 1.

[0091] The audio module 180 is used to convert digital audio information into analog audio signals for output, and also to convert analog audio input into digital audio signals. The audio module 180 can also be used for encoding and decoding audio signals. In some embodiments, the audio module 180 may be located in the processor 110, or some functional modules of the audio module 180 may be located in the processor 110.

[0092] The speaker 180A, also known as a "loudspeaker," is used to convert audio electrical signals into sound signals. The wearable device 100 can listen to music or make hands-free calls through the speaker 180A.

[0093] The receiver 180B, also known as the "earpiece," is used to convert audio electrical signals into sound signals. When the wearable device 100 answers a phone call or voice message, it can do so by bringing the receiver 180B close to the wearer's ear.

[0094] Microphone 180C, 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 180C, inputting the sound signal into microphone 180C. Electronic device 300 may have at least one microphone 180C. In some embodiments, wearable device 100 may have two microphones 180C, which, in addition to collecting sound signals, can also perform noise reduction. In other embodiments, wearable device 100 may also have three, four, or more microphones 180C, enabling sound signal collection, noise reduction, sound source identification, and directional recording, among other functions.

[0095] Of course, the wearable device 100 may also include other functional units, which are not limited in this application embodiment.

[0096] The following is based on Figure 1 Taking the illustrated architecture as an example, the method for detecting the tightness of a wearable device provided in this application embodiment will be described. Each unit in the following embodiments may possess... Figure 1 The components shown are not described in detail. It should be noted that the message names or parameter names in the messages between the various devices in the embodiments of this application are just examples, and other names may be used in the specific implementation. The term "generate" in the embodiments of this application can also be understood as "create" or "determine", and the term "including" in the embodiments of this application can also be understood as "carry". This is a unified explanation, and the embodiments of this application do not make specific limitations in this regard.

[0097] As described above, the method for adjusting the tightness of a wearable device provided in this application embodiment can be implemented by one or more entities. Detailed descriptions are provided below for different entities:

[0098] The first type is when there is only one entity executing the method for detecting the tightness of a wearable device, which can be the wearable device itself.

[0099] Figure 2 This application provides a flowchart illustrating a method for detecting the tightness of a wearable device, as illustrated in the embodiments below. Figure 2 As shown, the subject executing this method can be the wearable device, and the method can include:

[0100] S201. When the wearable device is detected to be in a wearing state, the wearable device collects the user's motion data.

[0101] For example, the wearable device being in a wearing state can mean that the wearable device can be worn on the user's arm or wrist, or it can be worn on the user's ankle or running shoes. Specifically, the wearable device is worn on the user's running shoes. Specifically, the wearable device can be connected to the running shoes via a buckle, or other fitting connection methods are also possible; this application embodiment does not specifically limit this. The wearable device can be worn on the upper, collar, or laces of the running shoes; specifically, it is worn on the user's shoelaces. Therefore, the method for detecting the tightness of a wearable device provided in this application embodiment adds a tightness detection solution in running shoe wearing scenarios.

[0102] For example, wearable devices can collect user motion data in the following ways: Method 1: An accelerometer on the wearable device collects the acceleration of a first body part. Method 2: A gyroscope on the wearable device collects the angular velocity of the first body part. Method 3: An accelerometer on the wearable device collects the acceleration of the first body part, and a gyroscope on the wearable device collects the angular velocity of the first body part. In the above implementations, the first body part is related to the user's motion.

[0103] Example 1, Figure 3 This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application. Figure 3 As shown, taking the user's movement as jumping as an example, the first body part can be the feet. During the jumping process, the accelerometer on the wearable device collects the acceleration of the user's feet, and / or the gyroscope sensor on the wearable device collects the angular velocity of the user's feet.

[0104] Example 2, taking the user's movement as an arm swing as an example, the first body part can be the arm. During the arm swing, the accelerometer on the wearable device collects the acceleration of the user's arm, and / or the gyroscope on the wearable device collects the angular velocity of the user's arm.

[0105] S202, The wearable device identifies the motion data of the first action in the user's motion data.

[0106] The first action is a movement performed by the user during exercise. This first action corresponds to the position where the wearable device is worn. When the wearable device is worn on the user's arm or wrist, the first action may include arm swinging, etc. When the wearable device is worn on the user's ankle or running shoes, the first action may include jumping, kicking, etc. Of course, the first action can include any movement that the human body can perform; this application does not impose specific limitations.

[0107] The first action may include at least one action node. An action node can be understood as a point in time where a part of the user's body changes during an action. For example, if the first action is a jump, the action nodes may include two points: foot leaving the ground and foot touching the ground. If the first action is an arm swing, the action nodes may include points such as the arm swinging to a specified position in front of the body and the arm swinging to a specified position behind the body.

[0108] Specifically, the wearable device identifies the action data of the first action within the user's motion data. This can be achieved as follows: the wearable device determines the action data of the first action based on the real-time motion data collected during the user's movement, pre-stored data for each action and its corresponding standard data. In other words, the wearable device compares the collected motion data with the standard data for each action, identifying the first motion data that is similar to the standard data for the first action. The wearable device then identifies the action corresponding to the first motion data as the first action, and determines the first motion data as the action data of the first action. Alternatively, the wearable device compares the collected motion data with the standard data for each action, identifies the standard data for the first action that is closest to the first motion data, and determines the first action as the action corresponding to the first motion data; the first motion data is thus the action data of the first action.

[0109] S203. The wearable device determines the tightness of the wearable device corresponding to the motion data of the first action.

[0110] For example, S203 can be implemented in the following ways:

[0111] Method 1: The wearable device determines the tightness of its fit based on the motion data of the first action and the pre-defined correspondence between motion data and fit tightness. Alternatively, the wearable device determines the tightness of its fit based on the motion data of the first action and the correspondence between standard data of the first action stored in a standard database and fit tightness.

[0112] The preset correspondence between motion data and wearing tightness can be understood as follows: First, a one-to-one correspondence between motion data and wearing tightness, meaning that the value of the motion data corresponds one-to-one with the wearing tightness. For example, taking acceleration as the motion data, the acceleration value is 30 m / s². 2 The first type corresponds to the tightness of the fit, indicating proper wearing. The second type is a correlation between a set of motion data and the tightness of the fit; that is, the numerical range of the motion data corresponds to the tightness of the fit. For example, taking acceleration as the motion data, the numerical range of acceleration is 30-50 m / s². 2 Its tightness corresponds to the normal wearing tightness.

[0113] Furthermore, since the first action can include at least one action node, in order to accurately determine the tightness of the wearable device, the wearable device can determine the action data of each action node based on the action data of the first action. For example:

[0114] S2031, The wearable device identifies the action data of the first action node in the action data of the first action.

[0115] The first action node can be determined based on abrupt changes in motion data, at least one of the acceleration direction and angular velocity direction.

[0116] Specifically, this can be achieved as follows: the wearable device determines the motion waveform formed by the motion data of the first body part during the user's first action. Based on the motion waveform, the wearable device determines the motion data of the first action node.

[0117] To more accurately determine the tightness of the wearable device, the wearable device determines the feature data corresponding to the first action node based on the action data of each action node. Specifically, this can be achieved as follows:

[0118] S2032. The wearable device determines the first feature data corresponding to the first action node based on the action data of the first action node.

[0119] The first characteristic data may include, but is not limited to, at least one of the following: the number of peaks, the number of troughs, the peak value, the mean value, and the gradient of the acceleration or angular velocity waveform. Of course, the first characteristic data may also include other characteristic data, which are not specifically limited in this embodiment.

[0120] For example, S2032 can be specifically implemented as follows: the wearable device determines the motion waveform formed by the motion data of the first body part during the user's first action. Based on the motion waveform, the wearable device determines the trigger time of the first action node and the first feature data corresponding to the first preset time within the trigger time.

[0121] The first preset time can refer to a period of time, the length of which is set according to the actual situation, and this application embodiment does not make a specific limitation.

[0122] Continuing with Example 1 above, taking the first action as a jump as an example, the first action node of the first action can be either the user's foot leaving the ground or the user's foot touching the ground. Let's illustrate this using the user's foot acceleration as the motion data and the first action node as the user's foot leaving the ground:

[0123] A. Wearable devices determine the acceleration waveform formed by the acceleration data of the user's feet during the take-off action.

[0124] B. The wearable device determines the moment when the acceleration exceeds a preset acceleration based on the acceleration waveform as the first moment the foot leaves the ground, and determines the acceleration data corresponding to the first preset time interval within that first moment. Based on the acceleration data corresponding to the first preset time interval within that first moment, the wearable device calculates first feature data within the first preset time interval.

[0125] S2033. The wearable device determines the wearing tightness based on the first feature data corresponding to the first action node and the preset relationship between motion data and wearing tightness.

[0126] In other words, the wearable device determines the tightness of the wearable device based on the correspondence between motion data (such as standard data of the first motion node) stored in the standard database and the tightness of the wear, as well as the first feature data corresponding to the first motion node.

[0127] In the above implementation, the standard data in the standard database can be pushed by a cloud server, downloaded by the wearable device, or pre-stored in the wearable device. This standard data can be action data corresponding to a normal person performing the first action, or historical data of the wearable device user. Specifically, the standard data can be filtered based on parameters such as the user's gender, height, and weight. Specifically, the standard data in the standard database can be: standard data of the first action node during the user's first action under different wearing tightness conditions of the wearable device. The types of this standard data can include, but are not limited to, at least one of the following: the number of peaks in the acceleration waveform, the number of peaks in the angular velocity waveform, the number of troughs in the acceleration waveform, the number of troughs in the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of acceleration, the mean value of angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform.

[0128] Continuing with Example 1 above, taking the first action as a jump as an example, the first action node of the first action can be either the user's foot leaving the ground or the user's foot touching the ground. Using the user's foot acceleration as the motion data, the first action node being the user's foot leaving the ground, and the standard data being the number of peaks, this will be explained as follows:

[0129] S2033 can be specifically implemented as follows: the wearable device determines the wearing tightness of the wearable device based on the number of peaks corresponding to the first preset time period at the trigger time, and the pre-stored standard number of peaks when the user's feet leave the ground during the jumping action under different wearing tightness conditions of the wearable device.

[0130] In this embodiment, the wearable device can determine the tightness of the wearable device based on the user's motion data. No additional hardware device is needed to drive the wearable device to move. The tightness of the wearable device can be detected, which can effectively avoid the problem of inaccurate motion data collection, making the collection of motion data more reliable and laying the foundation for providing users with more professional guidance.

[0131] Method 2: The wearable device determines the wear tightness corresponding to the motion data of the first action based on the motion data of the first action and the wear tightness model. The motion data of the first action serves as the input to the wear tightness model, and the wear tightness of the wearable device serves as the output of the wear tightness model. This wear tightness model is trained based on the motion data and the wear tightness, and the specific implementation method of training this model is not specifically limited in this application.

[0132] Furthermore, the method for detecting the tightness of a wearable device provided in this application embodiment may further include: S204, the wearable device generates a prompt message based on the tightness to inform the user of the detection result of the tightness of the wearable device. Here, the tightness of the wearable device can be understood as the degree of tightness of the wearable device, or it can be understood as a specific numerical value. When the tightness of the wearable device is understood as the degree of tightness of the wearable device, the tightness can include the wearable device being worn normally, the wearable device being loose, and the wearable device being tight. When the tightness of the wearable device is understood as a specific numerical value, S204 can specifically be implemented as follows: when the tightness of the wearable device is greater than a threshold, the wearable device determines that the wearable device is worn tightly and informs the user of the detection result of the tightness through a first prompt message. When the tightness of the wearable device is equal to or close to the threshold, the wearable device determines that the wearable device is worn normally and informs the user of the detection result of the normal wearing through a second prompt message. When the tightness of the wearable device is less than the threshold, the wearable device determines that the wearable device is worn loose and informs the user of the detection result of the looseness through a third prompt message.

[0133] The first, second, and third prompts can all be presented to the user in different ways. For example, they can be displayed to the user through a user interface (UI), or by emitting different colors of light from LEDs, or by different vibration intensities and / or frequencies, or by sound. Of course, different combinations of presentation methods can also be used; this embodiment does not impose specific limitations.

[0134] For example, presentation format one: prompts can be made on the user interface (UI) through text and vibration. For instance, Figure 4 This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application. Figure 4As shown, when the wearable device is detected to be worn correctly, the wearable device will display a second prompt message through the user interface (e.g., "Wearing Correctly" on the UI), and the wearable device will vibrate once to indicate to the user that the wearable device is worn correctly. When the wearable device is detected to be loose, the wearable device will display a third prompt message through the user interface (e.g., "Loosely Worn" on the UI), and the wearable device will vibrate twice to indicate to the user that the wearable device is loosely worn. Of course, the number of vibrations of the wearable device can be arbitrarily set, and this embodiment does not impose a specific limitation.

[0135] Presentation Method Two: The user interface (UI) can use a combination of text, vibration, and sound to provide prompts. For example, when the wearable device is detected to be worn correctly, the device will generate a second prompt message and display it on the user interface (e.g., "Wearing Correctly" on the UI), while simultaneously vibrating once and emitting the first prompt sound to indicate to the user that the device is worn correctly. Figure 5 This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application. Figure 5 As shown, when the wearable device is detected to be loosely worn, the wearable device will generate a third prompt message and display it through the user interface (e.g., display "Loose Wearing" on the UI). The wearable device will also vibrate twice and emit a second prompt sound to alert the user that the device is loosely worn. Of course, the number of vibrations and the selection of prompt sounds under different detection results can be arbitrarily set; this embodiment does not impose specific limitations.

[0136] Presentation Format 3: Prompts can be displayed on the user interface (UI) using a combination of text and LED lights. For example, Figure 6a This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application. Figure 6a As shown, when the wearable device is detected to be worn normally, the wearable device will generate a second prompt message and display it through the user interface (such as "Wearing normally" displayed on the user interface UI), and the LED light set on the wearable device will emit the first prompt light to prompt the user that the wearable device is worn normally. Figure 6b This is a schematic diagram illustrating an application scenario of a method for detecting the tightness of a wearable device, as provided in an embodiment of this application. Figure 6bAs shown, when the wearable device is detected to be loosely worn, the device will generate a third prompt message displayed through the user interface (e.g., "Loose Wearing" on the UI), and the LEDs on the wearable device will emit a second prompt light to alert the user that the device is loose. The first prompt light can be green, and the second prompt light can be red. It's worth noting that the LEDs on the wearable device can be arranged, but are not limited to, the perimeter of the screen. This way, even in dark environments, the user wearing the wearable device can alert other users, effectively preventing the risk of accidental bumping.

[0137] Of course, the sound can be presented in the form of voice broadcast. In other words, the detection results of the tightness of the wearable device can also be displayed through voice broadcast.

[0138] In this embodiment of the application, by using different forms to prompt the detection results to the user, it is possible to effectively avoid the phenomenon that the user's wearable device is easy to fall off or be lost during the user's exercise. At the same time, it can avoid the risk of the user being bumped or accidentally bumping into something during the exercise.

[0139] In some embodiments, wearable devices can assess the user's kinetic energy based on their exercise data. For example, during running, the wearable device can assess the user's kinetic energy based on data such as running distance, speed, and duration. When the wearable device is loosely worn, the collected data on running distance, speed, and duration may be inaccurate, affecting the accuracy of the device's assessment of the user's kinetic energy. To ensure high accuracy in the kinetic energy assessment output by the wearable device regardless of its condition, [further measures are needed]. Figure 2 As shown in the embodiments of this application, a method for detecting the tightness of a wearable device further includes:

[0140] S205. The wearable device determines the tightness of the wearable device at each moment within the first time period.

[0141] In other words, during the second preset time of exercise, the wearable device determines the tightness of the wearable device at each moment within the second preset time (that is, the first duration).

[0142] S206. The wearable device determines the second duration of loosening based on the tightness of the wearable device at each moment within the first duration.

[0143] The second duration can refer to a continuous duration or the sum of multiple non-continuous durations.

[0144] In addition, the wearable device records the time when the wearable device becomes loose based on the tightness of the wearable device at each moment within the second preset time period and issues a reminder alarm.

[0145] This alert is used to remind the user that the wearable device is loose. The alert may include a bell or warning light, etc. Of course, other forms of alerts may also be included; this application embodiment does not specifically limit the scope.

[0146] S207. The wearable device calculates the user's second motion energy within the first duration based on the first duration and the second duration, and the first motion energy calculated by the wearable device.

[0147] The first kinetic energy is calculated under the condition that the wearable device is worn normally or tightly within the first duration.

[0148] Specifically, S207 can be implemented as follows: The wearable device calculates the second duration of loosening based on the time the wearable device has been loosened, and then determines the proportion of loosening time based on the ratio of the second duration to the first duration. The wearable device determines the user's second kinetic energy within a second preset time based on the proportion of loosening time and the first kinetic energy calculated by the wearable device.

[0149] For example, assuming the user's exercise is running, during the second preset time (i.e., the aforementioned first duration), the wearable device can determine the tightness of the wearable device in real time. The wearable device assesses the exercise energy based on the user's exercise data collected during the second preset time. Based on the proportion of time the wearable device is loose, and the exercise energy assessed by the user during the second preset time (i.e., the aforementioned first exercise energy), the wearable device calculates compensating exercise energy. This compensating exercise energy can be the proportion of time the wearable device is loose multiplied by the assessed exercise energy. In this way, the wearable device can determine the user's actual exercise energy during the second preset time (i.e., the aforementioned second exercise energy), which can be the difference between the assessed exercise energy and the compensating exercise energy.

[0150] Therefore, in this embodiment, the wearable device can assess the user's exercise energy during a second preset time. If the wearable device is loosely fitted, it can determine the user's actual exercise energy during the second preset time based on the proportion of time the device is loose and the assessed exercise energy, making the user's exercise data more reliable and reminding the user to adjust the tightness of the wearable device during the next run.

[0151] The following provides a detailed description of the method for detecting the tightness of wearable devices provided in this application embodiment, using an application scenario as an example:

[0152] Before running, Figure 7 This is a flowchart illustrating a method for detecting the tightness of a wearable device in an application scenario, as provided in an embodiment of this application. Figure 7 As shown, the method includes: S701, the user wears the wearable device on the shoelaces of their running shoes. S702, the user checks the tightness of the wearable device by performing a pre-run warm-up exercise (such as a standing jump). S703, when the user performs the jump, the wearable device collects the user's motion data through an accelerometer and / or a gyroscope sensor. S704, the wearable device identifies the motion data of the jump from the collected motion data and determines the characteristic data of the foot leaving the ground and the foot contacting the ground during the jump. The jump is the first action mentioned above, and the foot leaving the ground and the foot contacting the ground are the aforementioned action nodes. Specifically, S704 can be that the wearable device determines the acceleration waveform formed by the acceleration data of the foot during the user's jump. The wearable device determines the moment when the acceleration is greater than a preset acceleration as the first moment when the foot leaves the ground, and determines the acceleration data corresponding to the first preset time within that first moment. The wearable device calculates characteristic data within the first preset time period based on the acceleration data corresponding to the first moment. This characteristic data may include, but is not limited to, at least one of the following: number of peaks, number of troughs, peak value, mean acceleration, gradient of the acceleration waveform, etc. S705: The wearable device determines the wearing tightness based on the correspondence between standard data of the first action node (such as foot leaving the ground and foot contacting the ground) and wearing tightness stored in the standard database, as well as the characteristic data corresponding to foot leaving the ground and foot contacting the ground. S706: The wearable device determines whether the wearable device is loose based on the relationship between wearing tightness and a threshold. Specifically, when the wearing tightness of the wearable device is less than the threshold, the wearable device determines that the wearable device is loose. When the wearing tightness of the wearable device is equal to or close to the threshold, the wearable device determines that the wearable device is properly worn. When the wearing tightness of the wearable device is greater than the threshold, the wearable device determines that the wearable device is tight. If the wearable device determines that the wearable device is not loose, the process ends; if the wearable device determines that the wearable device is loose, S707 is executed. S707, Wearable devices generate prompts to alert users to make adjustments.

[0153] During the run, Figure 8 This is a flowchart illustrating a method for detecting the tightness of a wearable device in an application scenario, as provided in an embodiment of this application. Figure 8As shown, the method includes: S801, the wearable device collects motion data of the user running for a second preset time (i.e., the first duration mentioned above). S802, the wearable device determines the tightness of the fit at each moment within the second preset time based on the collected motion data of the user running for the second preset time. S803, the wearable device determines whether the wearable device is loose based on the relationship between the tightness of the fit and a threshold. If not, the process ends. If yes, S804 is executed. S804, the wearable device generates a prompt message to remind the user that the wearable device is loose, and records the time when the wearable device became loose.

[0154] After running, Figure 9 This is a flowchart illustrating a method for detecting the tightness of a wearable device in an application scenario, as provided in an embodiment of this application. Figure 9 As shown, the method includes: S901, the wearable device assesses the exercise energy based on the collected exercise data during the user's running process. S902, the wearable device determines whether the wearable device is loose during the user's running period. If the wearable device determines that the wearable device is loose during the user's running period, then proceed to S903; if the wearable device determines that the wearable device is not loose during the user's running period, then proceed to S904. S903, the wearable device determines the loosening time within a second preset time period, and determines the proportion of loosening time based on the ratio of the loosening time to the second preset time period. The wearable device calculates compensating exercise energy based on the proportion of loosening time and the exercise energy assessed by the user during the running process in the second preset time period (i.e., the first exercise energy mentioned above), which can be the proportion of loosening time multiplied by the assessed exercise energy. The wearable device determines the actual running energy of the user during the running process in the second preset time period (i.e., the second exercise energy mentioned above), which can be the difference between the assessed running energy and the compensating running energy. S904, the wearable device determines that the exercise energy assessed by the wearable device is the actual exercise energy.

[0155] The second type, when the method for detecting the tightness of a wearable device is performed by at least two entities, may include both the wearable device and a non-wearable device.

[0156] The collaborative operation between wearable and non-wearable devices can be achieved in several ways. Specifically, it can be described as follows:

[0157] Method 1: Figure 10 This application provides a flowchart illustrating a method for detecting the tightness of a wearable device, as illustrated in the embodiments below. Figure 10As shown, the method may include: ① When the wearable device is detected to be in a wearing state, the wearable device collects the user's motion data. ② The wearable device identifies the motion data of a first action in the collected motion data and determines the first feature data corresponding to the first action node of the user's first action. Specifically, the wearable device identifies the motion data of the first action in the collected user motion data and determines the motion waveform formed by the motion data of the first body part during the user's first action. Based on the motion waveform, the wearable device determines the trigger time of the first action node and the first feature data corresponding to the first preset time within that trigger time. Based on the correspondence between the standard data of the first action node and the wearing tightness stored in the standard database and the first feature data corresponding to the first action node, the wearable device determines the wearing tightness of the wearable device. ③ The wearable device sends the detection result corresponding to the wearing tightness to a non-wearable device. Specifically, the wearable device can send the detection result corresponding to the wearing tightness to the non-wearable device via Bluetooth. Of course, other transmission methods can also be used, and this application embodiment does not specifically limit them.

[0158] Specifically, depending on the specific type of non-wearable device, the way the non-wearable device receives the detection result of the wearability of the wearable device and displays this result to the user varies. Details are as follows:

[0159] For example, ④ if the non-wearable device can be a watch or a bracelet, the watch or bracelet receives the detection result of the tightness of the wearable device sent by the wearable device, and generates a prompt message based on the detection result. The prompt message can be presented on the user interface (UI) in the form of text, and / or in the form of vibration.

[0160] For example, such as Figure 4 As shown, when the wearable device is detected to be worn correctly, the watch or bracelet will display a prompt message through the user interface (e.g., "Wearing Correctly" on the UI), and the watch or bracelet will vibrate once to indicate to the user that the wearable device is worn correctly. When the wearable device is detected to be loose, the watch or bracelet will display a prompt message through the user interface (e.g., "Loosely Worn" on the UI), and the wearable device will vibrate twice to indicate to the user that the wearable device is loosely worn. Of course, the number of vibrations of the wearable device can be arbitrarily set, and this embodiment does not impose a specific limitation.

[0161] ⑤ If the non-wearable device can be an earphone, the earphone receives the detection result of the tightness of the wearable device sent by the wearable device, and generates a prompt message based on the detection result. The prompt message can be presented in the form of voice.

[0162] ⑥ If the non-wearable device can be a mobile phone, the mobile phone receives the detection result of the tightness of the wearable device sent by the wearable device, and generates a prompt message based on the detection result. The prompt message can be presented on the user interface (UI) in the form of text, and / or in the form of vibration / LED light.

[0163] For example, such as Figure 6a As shown, when the wearable device is detected to be worn correctly, the phone will display a notification message through the user interface (e.g., "Wearing Correctly" on the UI), and the LED light on the phone will emit a first type of notification light to indicate to the user that the wearable device is being worn correctly. Figure 6b As shown, when the wearable device is detected to be loosely worn, the phone will generate a prompt message displayed through the user interface (such as "Loose Wearing" on the UI), and the LED light on the phone will emit a second prompt light to remind the user that the wearable device is loosely worn. The first prompt light can be green, and the second prompt light can be red. It should be noted that the phone can also provide a notification by illuminating the screen.

[0164] Of course, the sound can be presented in the form of voice broadcast. In other words, the mobile phone can display the detection results of the tightness of the wearable device through voice broadcast.

[0165] The specific implementation of each step can be found in the relevant content of the above embodiments, and will not be repeated in the embodiments of this application.

[0166] Method 2:

[0167] Figure 11 This application provides a flowchart illustrating a method for detecting the tightness of a wearable device, as illustrated in the embodiments below. Figure 11As shown, the method may include: ① When the wearable device is detected to be in a wearing state, the wearable device collects the user's motion data. ② The wearable device sends the motion data to a non-wearable device. Specifically, the wearable device can send the motion data to the non-wearable device via Bluetooth. Of course, other transmission methods can also be used, and this application embodiment does not specifically limit them. ③ The non-wearable device receives the user's motion data sent by the wearable device, identifies the motion data of a first action in the motion data, and determines the first feature data corresponding to the first action node of the user's first action. Specifically, the non-wearable device determines the motion waveform formed by the motion data of the first body part during the user's first action based on the user's motion data. The non-wearable device determines the trigger time of the first action node and the first feature data corresponding to the first preset time within the trigger time based on the motion waveform. The non-wearable device determines the wearing tightness of the wearable device based on the correspondence between the standard data of the first action node and the wearing tightness stored in the standard database, and the first feature data corresponding to the first action node.

[0168] Specifically, depending on the specific type of non-wearable device, the way it displays the detection results of the wearable device's tightness to the user varies. Details are as follows:

[0169] For example, ④ if the non-wearable device can be a watch or a bracelet, the watch or bracelet can generate a prompt message based on the tightness of the wearable device. This prompt message can be presented on the user interface (UI) through text and / or through vibration.

[0170] For example, such as Figure 4 As shown, when the wearable device is detected to be worn correctly, the watch or bracelet will display a prompt message through the user interface (e.g., "Wearing Correctly" on the UI), and the watch or bracelet will vibrate once to indicate to the user that the wearable device is worn correctly. When the wearable device is detected to be loose, the watch or bracelet will display a prompt message through the user interface (e.g., "Loosely Worn" on the UI), and the wearable device will vibrate twice to indicate to the user that the wearable device is loosely worn. Of course, the number of vibrations of the wearable device can be arbitrarily set, and this embodiment does not impose a specific limitation.

[0171] ⑤ If the non-wearable device can be an earphone, the earphone generates a prompt message based on the tightness of the wearable device, and the prompt message can be presented in the form of voice.

[0172] ⑥ If the non-wearable device can be a mobile phone, the mobile phone generates a prompt message based on the tightness of the wearable device. This prompt message can be presented on the user interface (UI) through text and / or through vibration / LED light.

[0173] For example, such as Figure 6a As shown, when the wearable device is detected to be worn correctly, the phone will display a notification message through the user interface (e.g., "Wearing Correctly" on the UI), and the LED light on the phone will emit a first type of notification light to indicate to the user that the wearable device is being worn correctly. Figure 6b As shown, when the wearable device is detected to be loosely worn, the phone will generate a prompt message displayed through the user interface (such as "Loose Wearing" on the UI), and the LED light on the phone will emit a second prompt light to remind the user that the wearable device is loosely worn. The first prompt light can be green, and the second prompt light can be red. It should be noted that the phone can also provide a notification by illuminating the screen.

[0174] Of course, the sound can be presented in the form of voice broadcast. In other words, the mobile phone can display the detection results of the tightness of the wearable device through voice broadcast.

[0175] The specific implementation of each step can be found in the relevant content of the above embodiments, and will not be repeated in the embodiments of this application.

[0176] In this embodiment, the detection and prompting function of the wearable device's tightness is extended to multiple devices. Through the coordinated operation of multiple devices, the problem of tightness of the wearer is solved, and the user's experience of multiple devices working together is enhanced.

[0177] Figure 12 A device for detecting the tightness of a wearable device provided in this application embodiment may include:

[0178] The acquisition unit 1201 is used to acquire the user's motion data when the wearable device is detected to be in a wearing state;

[0179] The recognition unit 1202 is used to recognize the motion data of the first action in the user's motion data;

[0180] The first determining unit 1203 is used to determine the tightness of the wearable device corresponding to the action data of the first action.

[0181] In one possible implementation, the first determining unit 1203 is further configured to:

[0182] The tightness of the wearable device is determined based on the motion data of the first action and the corresponding relationship between the preset motion data and the wearing tightness.

[0183] In one possible implementation, the first determining unit 1203 is further configured to:

[0184] Identify the action data of the first action node in the action data of the first action;

[0185] Based on the action data of the first action node, determine the first feature data corresponding to the first action node;

[0186] The wearing tightness of the wearable device is determined based on the first feature data and the preset relationship between motion data and wearing tightness.

[0187] In one possible implementation, the first feature data includes at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of troughs of the acceleration waveform, the number of troughs of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of the acceleration, the mean value of the angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform.

[0188] In one possible implementation, the first determining unit 1203 is further configured to:

[0189] Based on the motion data of the first action and the wearing tightness model, determine the wearing tightness of the wearable device corresponding to the motion data of the first action;

[0190] Among them, the motion data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is used as the output of the wearing tightness model.

[0191] In some embodiments, the device for detecting the tightness of a wearable device provided in this application may further include:

[0192] The generation unit 1204 is used to generate prompt information based on the tightness of the wearable device. The prompt information presents the detection result of the tightness of the wearable device in a preset presentation format.

[0193] The preset presentation formats include one or more of the following combinations: sound presentation, text presentation, vibration presentation, and light presentation.

[0194] In one possible implementation, the tightness of the wearable device includes: normal wear, loose wear, and tight wear.

[0195] In some embodiments, the device for detecting the tightness of a wearable device provided in this application may further include:

[0196] The second determining unit 1205 is used to determine the tightness of the wearable device at each moment within the first time period;

[0197] The third determining unit 1206 is used to determine the second duration of loose wear of the wearable device based on the tightness of the wearable device at each moment within the first duration;

[0198] The calculation unit 1207 is used to calculate the user's second motion energy within the first duration based on the first duration and the second duration, and the first motion energy calculated by the wearable device; wherein the first motion energy is calculated under the condition that the wearable device is worn normally or tightly within the first duration.

[0199] In one possible implementation, the first action includes a take-off action, and the first action node includes the foot leaving the ground and / or the foot contacting the ground; or...

[0200] The first movement includes an arm swing, and the first movement node includes the arm swinging to a designated position in front of the body and / or the arm swinging to a designated position behind the body.

[0201] In one possible implementation, the wearable device is worn on the user's feet or shoes.

[0202] Optionally, the aforementioned device 1200 can be implemented by code or by circuitry; specifically, the device can be the entire terminal device. For example, the acquisition unit 1201 can be an acquisition circuit or a sensor (such as...) Figure 1 The accelerometer sensor 150A and / or gyroscope sensor 150B shown are used for implementation. The identification unit 1202, the first determination unit 1203, the generation unit 1204, the second determination unit 1205, the third determination unit 1206, and the calculation unit 1207 can be processors (such as...). Figure 1 The processor 110 shown.

[0203] Optionally, in this possible design, the above Figures 1 to 11 All relevant details regarding the steps involving the electronic device in the illustrated method embodiment can be found in the functional descriptions of the corresponding functional modules, and will not be repeated here. The electronic device described in this possible design is used to perform... Figures 1 to 11 The electronic device in the method for detecting the tightness of a wearable device can achieve the same effect as the method described above for detecting the tightness of a wearable device.

[0204] This application also provides a chip system including at least one processor and at least one interface circuit. The processor and the interface circuit are interconnected via lines. For example, the interface circuit can be used to receive signals from other devices (e.g., memory). Or, for example, the interface circuit can be used to send signals to other devices (e.g., the processor). Exemplarily, the interface circuit can read instructions stored in memory and send those instructions to the processor. When the instructions are executed by the processor, the electronic device can perform the various steps executed by the wearable device in the above embodiments. Of course, the chip system may also include other discrete components, and this application does not specifically limit this.

[0205] This application also provides an apparatus included in an electronic device, which has the function of implementing the behavior of the electronic device in any of the methods described above. This function can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes at least one module or unit corresponding to the above function. For example, a detection module or unit, and a determination module or unit, etc.

[0206] This application also provides a computer-readable storage medium including computer instructions that, when executed on an electronic device, cause the electronic device to perform any of the methods described in the above embodiments.

[0207] This application also provides a computer program product that, when run on a computer, causes the computer to perform any of the methods described in the above embodiments.

[0208] It is understood that, in order to achieve the aforementioned functions, the aforementioned terminals and other devices include hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this invention.

[0209] This application embodiment can divide the aforementioned terminal, etc., into functional modules according to the above method examples. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods.

[0210] Through the above description of the embodiments, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0211] In the embodiments of this application, the functional units can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0212] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially, or the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as flash memory, portable hard disk, read-only memory, random access memory, magnetic disk, or optical disk.

[0213] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for detecting the tightness of a wearable device, characterized in that, The method includes: When the wearable device is detected to be in a wearing state, motion data of the user's first body part is collected, and the motion data includes acceleration and / or angular velocity; Identify the motion data of the first action in the motion data of the first body part of the user; Determine the wearing tightness of the wearable device corresponding to the action data of the first action, wherein the wearing tightness of the wearable device is the wearing tightness when the wearable device is in the wearing state, including: Based on the motion waveform formed by the motion data of the first body part during the user's first action, the motion data of the first action node is determined; the first action node is the node where the body part changes during the user's first action. Based on the action data of the first action node, determine the first feature data corresponding to the first action node. The first feature data includes at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of troughs of the acceleration waveform, the number of troughs of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of acceleration, the mean value of angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform. Based on the first feature data and the preset correspondence between motion data and wearing tightness, the wearing tightness of the wearable device is determined.

2. The method according to claim 1, characterized in that, Determining the tightness of the wearable device corresponding to the action data of the first action includes: Based on the motion data of the first action and the wearing tightness model, determine the wearing tightness of the wearable device corresponding to the motion data of the first action; The action data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is used as the output of the wearing tightness model.

3. The method according to claim 1 or 2, characterized in that, After determining the wearability tightness of the wearable device corresponding to the motion data of the first action, the process also includes: Based on the tightness of the wearable device, a prompt message is generated, and the prompt message presents the detection result of the tightness of the wearable device in a preset presentation format; The preset presentation format includes one or more of the following combinations: sound presentation format, text presentation format, vibration presentation format, and light presentation format.

4. The method according to any one of claims 1-3, characterized in that, The tightness of the wearable device includes: normal wear, loose wear, and tight wear.

5. The method according to any one of claims 1-4, characterized in that, Also includes: Determine the tightness of the wearable device at each moment within the first time period; Based on the tightness of the wearable device at each moment within the first time period, a second time period for loose wear of the wearable device is determined; Based on the first duration and the second duration, and the first kinetic energy calculated by the wearable device, the second kinetic energy of the user within the first duration is calculated; wherein, the first kinetic energy is calculated under the condition that the wearable device is worn normally or tightly within the first duration.

6. The method according to claim 1, characterized in that, The first action includes a take-off action, and the first action node includes the foot leaving the ground and / or the foot contacting the ground; or, The first action includes an arm swinging motion, and the first action node includes the arm swinging to a designated position in front of the body and / or the arm swinging to a designated position behind the body.

7. The method according to any one of claims 1-6, characterized in that, The wearable device is for wearing on the user's feet or shoes.

8. A device for detecting the tightness of a wearable device, characterized in that, The device includes: The acquisition unit is used to acquire motion data of a user's first body part when the wearable device is detected to be in a wearing state. The motion data includes acceleration and / or angular velocity. The identification unit is used to identify the motion data of the first action in the motion data of the first body part of the user; The first determining unit is configured to determine the wearing tightness of the wearable device corresponding to the action data of the first action, wherein the wearing tightness of the wearable device is the wearing tightness when the wearable device is in the wearing state, including: Based on the motion waveform formed by the motion data of the first body part during the user's first action, the motion data of the first action node is determined; the first action node is the node where the body part changes during the user's first action. Based on the action data of the first action node, determine the first feature data corresponding to the first action node. The first feature data includes at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of troughs of the acceleration waveform, the number of troughs of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of acceleration, the mean value of angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform. Based on the first feature data and the preset correspondence between motion data and wearing tightness, the wearing tightness of the wearable device is determined.

9. The apparatus according to claim 8, characterized in that, The first determining unit is further configured to: Based on the motion data of the first action and the wearing tightness model, determine the wearing tightness of the wearable device corresponding to the motion data of the first action; The action data of the first action is used as the input of the wearing tightness model, and the wearing tightness of the wearable device is used as the output of the wearing tightness model.

10. The apparatus according to any one of claims 8 or 9, characterized in that, Also includes: The generation unit is used to generate prompt information based on the tightness of the wearable device. The prompt information presents the detection result of the tightness of the wearable device in a preset presentation format. The preset presentation format includes one or more of the following combinations: sound presentation format, text presentation format, vibration presentation format, and light presentation format.

11. The apparatus according to any one of claims 8-10, characterized in that, The tightness of the wearable device includes: normal wear, loose wear, and tight wear.

12. The apparatus according to any one of claims 8-11, characterized in that, Also includes: The second determining unit is used to determine the tightness of the wearable device at each moment within the first time period; The third determining unit is used to determine the second duration of loose wear of the wearable device based on the tightness of the wearable device at each moment within the first duration; The calculation unit is configured to calculate the user's second motion energy within the first duration based on the first duration, the second duration, and the first motion energy calculated by the wearable device; wherein the first motion energy is calculated under the condition that the wearable device is worn normally or tightly within the first duration.

13. The apparatus according to claim 8, characterized in that, The first action includes a take-off action, and the first action node includes the foot leaving the ground and / or the foot contacting the ground; or, The first action includes an arm swinging motion, and the first action node includes the arm swinging to a designated position in front of the body and / or the arm swinging to a designated position behind the body.

14. The apparatus according to any one of claims 8-13, characterized in that, The wearable device is for wearing on the user's feet or shoes.

15. A system for detecting the tightness of a wearable device, characterized in that, The system includes: A wearable device is configured to: when the wearable device is detected to be in a wearing state, collect motion data of a user's first body part, the motion data including acceleration and / or angular velocity; identify motion data of a first action in the motion data of the user's first body part; and determine the wearing tightness of the wearable device corresponding to the motion data of the first action, including: Based on the motion waveform formed by the motion data of the first body part during the user's first action, the motion data of the first action node is determined; the first action node is the node where the body part changes during the user's first action. Based on the action data of the first action node, determine the first feature data corresponding to the first action node. The first feature data includes at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of troughs of the acceleration waveform, the number of troughs of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of acceleration, the mean value of angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform. Based on the first feature data and the preset correspondence between motion data and wearing tightness, the wearing tightness of the wearable device is determined; The wearability of the wearable device is sent to the non-wearable device, where the wearability of the wearable device is the wearability when the wearable device is in the wearing state. The non-wearable device is configured to: receive the tightness of the wearable device, and generate a prompt message based on the tightness of the wearable device, the prompt message being used to inform the user of the detection result of the tightness of the wearable device.

16. A system for detecting the tightness of a wearable device, characterized in that, The system includes: A wearable device is configured to: when the wearable device is detected to be in a wearing state, collect motion data of a first body part of the user, the motion data including acceleration and / or angular velocity; and send the collected motion data to a non-wearable device; The non-wearable device is configured to: receive motion data of the first body part sent by the wearable device, and identify motion data of a first action in the motion data of the first body part; determine the wearing tightness of the wearable device corresponding to the motion data of the first action, wherein the wearing tightness of the wearable device is the wearing tightness when the wearable device is in the wearing state, including: Based on the motion waveform formed by the motion data of the first body part during the user's first action, the motion data of the first action node is determined; the first action node is the node where the body part changes during the user's first action. Based on the action data of the first action node, determine the first feature data corresponding to the first action node. The first feature data includes at least one of the following: the number of peaks of the acceleration waveform, the number of peaks of the angular velocity waveform, the number of troughs of the acceleration waveform, the number of troughs of the angular velocity waveform, the peak value of the acceleration waveform, the peak value of the angular velocity waveform, the mean value of acceleration, the mean value of angular velocity, the gradient of the acceleration waveform, and the gradient of the angular velocity waveform. Based on the first feature data and the preset correspondence between motion data and wearing tightness, the wearing tightness of the wearable device is determined.

17. The system according to claim 16, characterized in that, The non-wearable device is also used to: generate prompt information based on the tightness of the wearable device, the prompt information being used to inform the user of the detection result of the tightness of the wearable device.

18. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes computer instructions that, when executed on an electronic device, cause the electronic device to perform the method for detecting the tightness of a wearable device as described in any one of claims 1-7.

19. A computer program product, characterized in that, When the program is invoked by the processor, the method for detecting the tightness of a wearable device as described in any one of claims 1-7 is executed.

20. A chip system, characterized in that, It includes one or more processors, which, when executing instructions, perform a method for detecting the tightness of a wearable device as described in any one of claims 1-7.

Images