A method for evaluating user's motion status and related equipment

Abstract

The embodiment of the present application provides a method and related equipment for evaluating the user's motion state. The method includes: obtaining and processing the user's current motion data, determining the speed interval to which the user's motion speed belongs and the cadence interval to which the step frequency corresponding to the motion speed belongs; determining the high-frequency cadence interval, that is, determining the cadence interval with the largest distribution of cadence corresponding to the motion speed in the speed interval; determining the high-frequency cadence based on the high-frequency cadence interval; determining the user's cadence variation value based on the user's historical motion data and the high-frequency cadence; and determining the user's motion state based on the cadence variation value. This method can evaluate the user's motion state during the entire motion process, and divides the speed and cadence into intervals for evaluation, thereby avoiding the difficulty of comparison caused by excessive motion data and improving the accuracy of the evaluation.

Description

Technical Field

[0001] The present application relates to the field of sports health management, and in particular to a method for evaluating a user's sports status and related equipment. Background Art

[0002] As one of the most economical forms of exercise, running has become the preferred sport for most people. Running data, such as speed, stride length, cadence, and heart rate, can reflect the runner's performance. Accurately identifying a runner's performance could alert them to stop exercising and take a break when their performance is poor, thus preventing overexertion.

[0003] Existing technology can evaluate a runner's exercise status by comparing the cadence data before and after a single exercise, but this method lacks holistic consideration and can easily overlook the runner's overall state during the running process.

[0004] Therefore, how to reasonably evaluate the overall status of users during sports such as running is an urgent problem that needs to be solved. Summary of the Invention

[0005] The present application provides a method and related equipment for evaluating a user's exercise status, which can use historical data to analyze the user's habitual cadence at different speeds, and compare the cadence at different speeds during the current running process with the habitual cadence, thereby evaluating the runner's current physical condition. The user can also adjust the exercise schedule in time according to the physical condition obtained from the evaluation, which can prevent injuries caused by excessive exercise. This evaluation method does not require heart rate data, that is, the user does not need to wear a heart rate detection device. In addition, the combination of historical data and multiple parameters for evaluation improves the accuracy of the evaluation.

[0006] In a first aspect, the present application provides a method for evaluating a user's motion state, the method may include: obtaining the user's current motion data, the motion data including the user's motion speed and the step frequency corresponding to the motion speed; processing the user's current motion data to determine the speed interval to which the user's motion speed belongs and the step frequency interval to which the step frequency corresponding to the motion speed belongs; determining a high-frequency step frequency interval, the high-frequency step frequency interval being the step frequency interval with the largest distribution of step frequencies corresponding to the motion speed in the speed interval; determining a high-frequency step frequency based on the high-frequency step frequency interval; determining a step frequency variation value of the user based on the user's historical motion data and the high-frequency step frequency, the step frequency variation value being used to describe the magnitude of the change in the user's step frequency, wherein the historical motion data includes the user's historical motion speed and the step frequency corresponding to the historical motion speed; determining the user's motion state according to the step frequency variation value.

[0007] In the solution provided in this application, a new evaluation method is adopted. There is no need to collect heart rate data. Instead, speed and cadence are combined. The user's exercise status of this exercise is evaluated by comparing historical exercise data and current exercise data. Specifically, the habitual cadence corresponding to each speed interval of the user during the running process is determined based on the user's historical exercise data, and then the high-frequency cadence corresponding to each speed interval of the user during the current running process is determined. The cadence variation value is calculated by using the habitual cadence and the high-frequency cadence to evaluate the user's running status. This evaluation method combines historical exercise data and can evaluate the user's exercise status during the entire exercise process, allowing the user to understand their own status in a timely manner and make adjustments to prevent injuries caused by excessive exercise. In addition, by combining speed and cadence and dividing the intervals to compare historical exercise data and current exercise data, evaluation is performed, which avoids the difficulty of comparison caused by too much exercise data and also improves the accuracy of the evaluation.

[0008] In combination with the first aspect, in a possible implementation of the first aspect, before obtaining the user's current motion data, the method also includes: analyzing the user's historical motion data, determining the speed range to which the user's historical motion speed belongs and the cadence range to which the step frequency corresponding to the historical motion speed belongs; determining the habitual cadence range, the habitual cadence range being the cadence range with the most cadence distribution corresponding to the historical motion speed in the speed range; and determining the habitual cadence based on the habitual cadence range.

[0009] In the solution provided in this application, the user's exercise status during the entire exercise process can be evaluated by combining historical exercise data. In addition, the speed and step frequency are combined and divided into intervals for evaluation, avoiding the difficulties caused by excessive historical exercise data.

[0010] In combination with the first aspect, in a possible implementation of the first aspect, determining the user's cadence variation value based on the user's historical exercise data and the high-frequency cadence includes: determining the user's cadence variation value based on the habitual cadence and the high-frequency cadence; the cadence variation value is: Among them, a i is the high frequency step frequency, b i is the habitual cadence, and N is the number of speed intervals to which the user's exercise speed belongs.

[0011] In the solution provided in the present application, the cadence variation value is determined based on historical motion data and current motion data, that is, the change in cadence corresponding to each speed is determined, so as to evaluate whether the user's motion state is good. By making the speed and cadence correspond, the difficulty of data processing during the evaluation is reduced, and the comparison of historical motion data and current motion data is facilitated. In addition, the evaluation is performed through multiple parameters, which improves the accuracy of the evaluation.

[0012] In combination with the first aspect, in a possible implementation of the first aspect, determining the user's exercise state based on the cadence variation value includes: if the cadence variation value is not greater than a preset threshold, determining that the user's current state is poor; or, if the cadence variation value is greater than a preset threshold, determining that the user's current state is good.

[0013] In the solution provided in this application, the cadence variation value is obtained by comparing historical exercise data with current exercise data. The user's exercise status is determined by comparing the cadence variation value with a preset threshold. The user's exercise status during the entire exercise process can be evaluated, allowing the user to understand their own status in a timely manner and make adjustments to prevent injuries caused by excessive exercise.

[0014] In combination with the first aspect, in a possible implementation of the first aspect, after determining the user's exercise status based on the cadence variation value, the method further includes: if it is determined that the user's exercise status is poor, prompting the user to stop exercising and deleting the user's exercise data.

[0015] In the solution provided in the present application, when the user's exercise state is poor, the user is prompted to stop exercising to avoid sports injuries that may be caused by the user continuing to exercise. In addition, the exercise data when the user's exercise state is poor is deleted and is not used as historical exercise data for subsequent exercise, so as to avoid the exercise data when the user's exercise state is poor affecting the classification of habitual cadence, thereby ensuring the accuracy of the evaluation.

[0016] In a second aspect, the present application provides an electronic device, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors are used to call the computer instructions to enable the electronic device to execute: obtaining the user's current motion data, the motion data including the user's motion speed and the step frequency corresponding to the motion speed; processing the user's current motion data to determine the speed interval to which the user's motion speed belongs and the step frequency interval to which the step frequency corresponding to the motion speed belongs; determining a high-frequency step frequency interval, the high-frequency step frequency interval being the step frequency interval with the most step frequency distribution corresponding to the motion speed in the speed interval; determining a high-frequency step frequency based on the high-frequency step frequency interval; determining a step frequency variation value of the user based on the user's historical motion data and the high-frequency step frequency, the step frequency variation value being used to describe the magnitude of the change in the user's step frequency, wherein the historical motion data includes the user's historical motion speed and the step frequency corresponding to the historical motion speed; and determining the user's motion state based on the step frequency variation value.

[0017] In combination with the second aspect, in a possible implementation of the second aspect, the one or more processors, before being used to call the computer instructions to enable the electronic device to execute the acquisition of the user's current motion data, are also used to call the computer instructions to enable the electronic device to execute: analyzing the user's historical motion data, determining the speed range to which the user's historical motion speed belongs and the cadence range to which the step frequency corresponding to the historical motion speed belongs; determining the habitual cadence range, the habitual cadence range being the cadence range with the most cadence distribution corresponding to the historical motion speed in the speed range; and determining the habitual cadence based on the habitual cadence range.

[0018] In conjunction with the second aspect, in a possible implementation of the second aspect, the one or more processors, when used to call the computer instructions to cause the electronic device to execute the step of determining the user's cadence variation value based on the user's historical motion data and the high-frequency cadence, are specifically used to call the computer instructions to cause the electronic device to execute: determining the user's cadence variation value based on the habitual cadence and the high-frequency cadence; the cadence variation value is: Among them, a i is the high frequency step frequency, b i is the habitual cadence, and N is the number of speed intervals to which the user's exercise speed belongs.

[0019] In combination with the second aspect, in a possible implementation of the second aspect, the one or more processors, when used to call the computer instructions so that the electronic device executes the determination of the user's motion state based on the cadence variation value, are specifically used to call the computer instructions so that the electronic device executes: if the cadence variation value is not greater than a preset threshold, determine that the user's motion state is poor; or, if the cadence variation value is greater than a preset threshold, determine that the user's motion state is good.

[0020] In combination with the second aspect, in a possible implementation of the second aspect, the one or more processors, after being used to call the computer instructions to enable the electronic device to execute the determination of the user's exercise status based on the cadence variation value, are also used to call the computer instructions to enable the electronic device to execute: if it is determined that the user's exercise status is poor, prompt the user to stop exercising and delete the user's exercise data.

[0021] In a third aspect, a computer program product comprising instructions is provided. When the computer program product is run on an electronic device, the electronic device can execute the method for evaluating the user's motion status described in the first aspect and any one of the implementation methods of the first aspect.

[0022] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program. When the computer program runs on an electronic device, the electronic device executes the method for evaluating the user's motion status described in the first aspect and any one of the implementation methods of the first aspect.

[0023] In a fifth aspect, an embodiment of the present application provides a chip, which is applied to an electronic device, and the chip includes one or more processors, and the processors are used to call computer instructions to enable the electronic device to execute the method for evaluating the user's motion state described in the first aspect and any one of the implementation methods of the first aspect.

[0024] In a sixth aspect, the present application provides a chip system, which is applied to an electronic device to support the electronic device in implementing the functions involved in the first aspect, for example, generating or processing the information involved in the method for evaluating the user's motion state in the first aspect. In one possible design, the chip system also includes a memory, which is used to store program instructions and data necessary for the data sending device. The chip system can be composed of a chip, or it can include a chip and other discrete devices.

[0025] It is understandable that the electronic device provided in the second aspect, the computer program product comprising instructions provided in the third aspect, the computer-readable storage medium provided in the fourth aspect, the chip provided in the fifth aspect, and the chip system provided in the sixth aspect are all used to execute the method for assessing the user's motion state provided in the first aspect. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the method for assessing the user's motion state provided in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of the hardware structure of an electronic device 100 provided in an embodiment of the present application;

[0027] Figure 2 A software structure block diagram of an electronic device 100 provided in an embodiment of the present application;

[0028] Figure 3 A schematic diagram of a sports scene provided in an embodiment of the present application;

[0029] Figure 4 A flowchart of a method for evaluating a user's motion status provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of a user interface provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of another user interface provided in an embodiment of the present application;

[0032] Figure 7 A schematic diagram of another user interface provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0034] First, some of the terms and related technologies involved in this application are explained to facilitate understanding by those skilled in the art.

[0035] Cadence, or the frequency of your steps, is the number of times your legs alternate in a unit of time when walking or running. It is a key factor in determining walking or running speed. Cadence is usually measured in steps per second, but can also be expressed in steps per minute.

[0036] Your stride is the distance between the centers of your feet after one step.

[0037] Many parameters during the user's exercise (for example, speed, stride, cadence, heart rate, etc.) can be used to judge the user's exercise habits and exercise status. If the user's exercise status can be obtained in time and the user is reminded when the status is not ideal, the user can get a rest and prevent sports injuries.

[0038] The heart rate data during exercise can most intuitively reflect the user's exercise status. However, when the electronic device 100 cannot measure the user's heart rate, the user's exercise status can also be determined through other parameters.

[0039] For example, the user's exercise status is evaluated by the changes in the user's cadence before and after a single exercise. However, this method can only evaluate the user's exercise status in the later stage by comparing the cadence data before and after a single exercise, and cannot evaluate the user's overall state of this exercise.

[0040] Based on the above content, the present application provides a method and related equipment for evaluating the user's exercise status. By comparing the differences between the cadence of the user at various speeds during the current exercise and the cadence at various speeds in the historical data, the overall status of the user during the current exercise can be analyzed, and the user's exercise status can be evaluated more comprehensively.

[0041] The following describes the device involved in the embodiments of the present application.

[0042] Figure 1 1 is a schematic diagram of the hardware structure of an electronic device 100 provided by an embodiment of the present invention.

[0043] The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a Universal Serial Bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a Subscriber Identification Module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0044] It should be understood that the structure illustrated in the embodiments of the present invention does not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown, or may combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0045] The processor 110 may include one or more processing units, for example: the processor 110 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processor (NPU), etc. Among them, different processing units can be independent devices or integrated into one or more processors. In this embodiment, the electronic device 100 can process historical motion data and current motion data through the processor 110. For example, the electronic device 100 can determine the speed range to which the user's motion speed belongs and the step frequency range to which the step frequency corresponding to the motion speed belongs through the processor 110.

[0046] The controller may be the nerve center and command center of the electronic device 100. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

[0047] In this embodiment provided in the present application, the electronic device 100 may execute the method for evaluating the user's motion state through the processor 110 .

[0048] Processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in processor 110 is a cache memory. This memory can store instructions or data that have just been used or are being recycled by processor 110. If processor 110 needs to use the same instruction or data again, it can directly access the memory. This avoids duplicate accesses, reduces processor 110 latency, and thus improves system efficiency.

[0049] In some embodiments, the processor 110 may include one or more interfaces. The 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.

[0050] The I2C interface is a bidirectional synchronous serial bus that includes a serial data line (SDA) and a serial clock line (SCL). In some embodiments, the processor 110 may include multiple I2C bus lines. The processor 110 may be coupled to the touch sensor 180K, the charger, the flash, the camera 193, and the like via different I2C bus interfaces. For example, the processor 110 may be coupled to the touch sensor 180K via the I2C interface, enabling communication between the processor 110 and the touch sensor 180K via the I2C bus interface, thereby implementing the touch function of the electronic device 100.

[0051] The I2S interface can be used for audio communication. In some embodiments, the processor 110 can include multiple I2S buses. The processor 110 can be coupled to the audio module 170 via the I2S bus to enable communication between the processor 110 and the audio module 170. In some embodiments, the audio module 170 can transmit audio signals to the wireless communication module 160 via the I2S interface, enabling the function of answering calls through a Bluetooth headset.

[0052] The PCM interface can also be used for audio communication, sampling, quantizing, and encoding analog signals. In some embodiments, the audio module 170 and the wireless communication module 160 can be coupled via a PCM bus interface. In some embodiments, the audio module 170 can also transmit audio signals to the wireless communication module 160 via the PCM interface, enabling the function of answering calls via a Bluetooth headset. Both the I2S interface and the PCM interface can be used for audio communication.

[0053] The UART interface is a universal serial data bus used for asynchronous communication. This bus can be a bidirectional communication bus. It converts the data to be transmitted between serial communication and parallel communication. In some embodiments, the UART interface is typically used to connect the processor 110 and the wireless communication module 160. For example, the processor 110 communicates with the Bluetooth module in the wireless communication module 160 via the UART interface to implement Bluetooth functionality. In some embodiments, the audio module 170 can transmit audio signals to the wireless communication module 160 via the UART interface, enabling the function of playing music through Bluetooth headphones.

[0054] The MIPI interface can be used to connect the processor 110 to peripheral devices such as the display 194 and the camera 193. MIPI interfaces include the Camera Serial Interface (CSI) and the Display Serial Interface (DSI). In some embodiments, the processor 110 and the camera 193 communicate via the CSI interface to implement the camera function of the electronic device 100. The processor 110 and the display 194 communicate via the DSI interface to implement the display function of the electronic device 100.

[0055] The GPIO interface can be configured via software. The GPIO interface can be configured as either a control signal or a data signal. In some embodiments, the GPIO interface can be used to connect the processor 110 to the camera 193, display 194, wireless communication module 160, audio module 170, sensor module 180, etc. The GPIO interface can also be configured as an I2C interface, an I2S interface, a UART interface, a MIPI interface, etc.

[0056] The USB interface 130 is an interface that complies with USB standards and may be a Mini USB interface, a Micro USB interface, a USB Type-C interface, or the like. The USB interface 130 can be used to connect a charger to charge the electronic device 100, or to transfer data between the electronic device 100 and peripheral devices. It can also be used to connect headphones to play audio. This interface can also be used to connect other electronic devices 100, such as AR devices.

[0057] It is understood that the interface connection relationship between the modules illustrated in the embodiment of the present invention is merely an illustrative illustration and does not constitute a structural limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection methods from the above embodiments, or a combination of multiple interface connection methods.

[0058] The charging management module 140 is configured to receive charging input from a charger. The charger can be either a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 can receive charging input from the wired charger via the USB interface 130. In some wireless charging embodiments, the charging management module 140 can receive wireless charging input via the wireless charging coil of the electronic device 100. While charging the battery 142, the charging management module 140 can also provide power to the electronic device 100 via the power management module 141.

[0059] The power management module 141 is used to connect 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, and provides power to the processor 110, the internal memory 121, the external memory, the display 194, the camera 193, and the wireless communication module 160. The power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle count, and battery health status (leakage, impedance). In some other embodiments, the power management module 141 can also be set in the processor 110. In other embodiments, the power management module 141 and the charging management module 140 can also be set in the same device.

[0060] The wireless communication function of the electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

[0061] Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In other embodiments, the antennas can be used in conjunction with a tuning switch.

[0062] The mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the same device as at least some of the modules of the processor 110.

[0063] The modem processor may include a modulator and a demodulator. The modulator is used to modulate the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After being processed by the baseband processor, the low-frequency baseband signal is passed to the application processor. The application processor outputs a sound signal through an audio device (not limited to the speaker 170A, the receiver 170B, etc.) or displays an image or video through the display screen 194. In some embodiments, the modem processor may be an independent device. In other embodiments, the modem processor may be independent of the processor 110 and be set in the same device as the mobile communication module 150 or other functional modules.

[0064] The wireless communication module 160 can provide wireless communication solutions 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), infrared technology (IR), etc. applied to the electronic device 100. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110. The wireless communication module 160 can also receive the signal to be sent from the processor 110, frequency modulate it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2. In this embodiment, the wireless communication module 160 is used to realize the interaction between the first device and the second device. For example, the first device has a wireless communication module, and the first device sends a verification request to the second device through the module and receives the verification data sent by the second device.

[0065] In some embodiments, the antenna 1 of the electronic device 100 is coupled to the mobile communication module 150, and the antenna 2 is coupled to the wireless communication module 160, so that the electronic device 100 can communicate with the network and other devices through wireless communication technology. The wireless communication technology may include Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Time-Division Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology. The GNSS may include a Global Positioning System (GPS), a Global Navigation Satellite System (GLONASS), a Beidou Navigation Satellite System (BDS), a Quasi-Zenith Satellite System (QZSS) and / or a Satellite Based Augmentation System (SBAS).

[0066] Electronic device 100 implements display functionality through a GPU, display screen 194, and an application processor. A GPU is a microprocessor for image processing that connects display screen 194 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 that execute program instructions to generate or modify display information.

[0067] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), organic light-emitting diode (OLED), active-matrix organic light-emitting diode or active-matrix organic light-emitting diode (AMOLED), flexible light-emitting diode (FLED), MiniLED, MicroLED, Micro-OLED, quantum dot light-emitting diode (QLED), etc. In some embodiments, electronic device 100 may include one or N display screens 194, where N is a positive integer greater than 1.

[0068] The electronic device 100 can implement the acquisition function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, and an application processor.

[0069] The ISP processes data fed back by camera 193. For example, when taking a photo, the shutter is opened, and light is transmitted through the lens to the camera's photosensitive element. The light signal is converted into an electrical signal, which is then passed to the ISP for processing and converted into a visible image or video. The ISP can also perform algorithmic optimization on image noise, brightness, and skin tone. It can also optimize parameters such as exposure and color temperature of the captured scene. In some embodiments, the ISP can be located within camera 193.

[0070] The camera 193 is used to capture still images or videos. The object generates an optical image through the lens and projects it onto the photosensitive element. The photosensitive element can be a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, and then transmits the electrical signal to the ISP for conversion into a digital image or video signal. The ISP outputs the digital image or video signal to the DSP for processing. The DSP converts the digital image or video signal into an image or video signal in a standard RGB, YUV or other format. In some embodiments, the electronic device 100 may include 1 or N cameras 193, where N is a positive integer greater than 1. For example, in some embodiments, the electronic device 100 can use N cameras 193 to obtain images with multiple exposure coefficients. Then, in video post-processing, the electronic device 100 can synthesize an HDR image based on the images with multiple exposure coefficients using HDR technology.

[0071] The digital signal processor is used to process digital signals. In addition to processing digital images or video signals, it can also process other digital signals. For example, when the electronic device 100 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy.

[0072] Video codecs are used to compress or decompress digital video. Electronic device 100 may support one or more video codecs. This allows electronic device 100 to play or record videos in various encoding formats, such as Moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, and MPEG4.

[0073] The NPU is a neural network (NN) computing processor that rapidly processes input information and continuously self-learns by drawing on the structure of biological neural networks, such as the transmission patterns between neurons in the human brain. The NPU enables intelligent cognitive applications in electronic device 100, such as image recognition, face recognition, speech recognition, and text comprehension.

[0074] The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 110 via the external memory interface 120 to implement data storage functions. For example, files such as music and videos can be stored on the external memory card.

[0075] The internal memory 121 can be used to store computer executable program codes, which include instructions. The processor 110 executes various functional applications and data processing of the electronic device 100 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image and video playback function, etc.), etc. The data storage area can store data created during the use of the electronic device 100 (such as audio data, a phone book, etc.), etc. In addition, the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash memory (UFS), etc.

[0076] The electronic device 100 can implement audio functions such as music playback and recording through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone jack 170D, and the application processor.

[0077] The audio module 170 is used to convert digital audio information into analog audio signal output, and is also used to convert analog audio input into digital audio signals. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 can be provided in the processor 110, or some functional modules of the audio module 170 can be provided in the processor 110.

[0078] The speaker 170A, also called a "speaker", is used to convert audio electrical signals into sound signals. The electronic device 100 can listen to music or listen to hands-free calls through the speaker 170A.

[0079] The receiver 170B, also called a "handset", is used to convert audio electrical signals into sound signals. When the electronic device 100 receives a call or a voice message, the user can place the receiver 170B close to the ear to hear the voice.

[0080] Microphone 170C, also known as "microphone" or "microphone", is used to convert sound signals into electrical signals. When making a call or sending a voice message, the user can speak by putting their mouth close to the microphone 170C to input the sound signal into the microphone 170C. The electronic device 100 can be provided with at least one microphone 170C. In other embodiments, the electronic device 100 can be provided with two microphones 170C, which can not only obtain sound signals but also realize noise reduction function. In other embodiments, the electronic device 100 can also be provided with three, four or more microphones 170C to obtain sound signals, reduce noise, identify the source of sound, realize directional recording function, etc.

[0081] The headphone jack 170D is used to connect a wired headphone and can be a USB interface 130 or a 3.5mm Open Mobile Terminal Platform (OMTP) standard interface or a Cellular Telecommunications Industry Association of the USA (CTIA) standard interface.

[0082] The sensor module 180 may include one or more sensors, which may be of the same type or different types. In the embodiment of the present application, the sensor module 180 may obtain the user's motion data, including but not limited to the user's cadence, stride length, and speed. After the sensor module 180 obtains the data, the processor 110 may process the motion data. It is understandable that Figure 1 The sensor module 180 shown is only an exemplary division method. There may be other division methods, which are not limited in this application.

[0083] Pressure sensor 180A is used to sense pressure signals and convert them into electrical signals. In some embodiments, pressure sensor 180A can be located on display screen 194. There are many types of pressure sensors 180A, such as resistive, inductive, and capacitive. A capacitive pressure sensor can include at least two parallel plates made of conductive material. When force acts on pressure sensor 180A, the capacitance between the electrodes changes. Electronic device 100 determines the intensity of the pressure based on this change in capacitance. When a touch operation is applied to display screen 194, electronic device 100 detects the touch intensity based on pressure sensor 180A. Electronic device 100 can also calculate the touch location based on the detection signal from pressure sensor 180A. In some embodiments, touch operations applied to the same touch location but with different touch intensities can correspond to different operation instructions. For example, when a touch operation with an intensity less than a first pressure threshold is applied to a short message application icon, a command to view short messages is executed. When a touch operation with an intensity greater than or equal to the first pressure threshold is applied to a short message application icon, a command to create a new short message is executed.

[0084] The gyroscope sensor 180B can be used to determine the motion posture of the electronic device 100. In some embodiments, the angular velocity of the electronic device 100 around three axes (i.e., x, y, and z axes) can be determined by the gyroscope sensor 180B. The gyroscope sensor 180B can be used for anti-shake shooting. For example, when the shutter is pressed, the gyroscope sensor 180B detects the angle of the electronic device 100 shaking, calculates the distance that the lens module needs to compensate based on the angle, and allows the lens to offset the shaking of the electronic device 100 through reverse movement to achieve anti-shake. The gyroscope sensor 180B can also be used for navigation and somatosensory game scenes.

[0085] The air pressure sensor 180C is used to measure air pressure. In some embodiments, the electronic device 100 calculates the altitude using the air pressure value measured by the air pressure sensor 180C to assist in positioning and navigation.

[0086] The magnetic sensor 180D includes a Hall sensor. The electronic device 100 can use the magnetic sensor 180D to detect the opening and closing of the flip case. In some embodiments, when the electronic device 100 is a flip phone, the electronic device 100 can detect the opening and closing of the flip cover based on the magnetic sensor 180D. Based on the detected opening and closing status of the case or flip cover, features such as automatic unlocking of the flip cover can be configured.

[0087] Accelerometer 180E can detect the magnitude of acceleration of electronic device 100 in all directions (generally three axes). When electronic device 100 is stationary, it can detect the magnitude and direction of gravity. It can also be used to identify the posture of electronic device 100, enabling applications such as switching between landscape and portrait modes and pedometers.

[0088] The distance sensor 180F is used to measure distance. The electronic device 100 can measure distance using infrared or laser. In some embodiments, when shooting a scene, the electronic device 100 can use the distance sensor 180F to measure distance to achieve fast focusing.

[0089] The proximity light sensor 180G may include, for example, a light emitting diode (LED) and a light detector, such as a photodiode. The light emitting diode may be an infrared light emitting diode. The electronic device 100 emits infrared light outward through the light emitting diode. The electronic device 100 uses a photodiode to detect infrared reflected light from nearby objects. When sufficient reflected light is detected, it can be determined that there is an object near the electronic device 100. When insufficient reflected light is detected, the electronic device 100 can determine that there is no object near the electronic device 100. The electronic device 100 can use the proximity light sensor 180G to detect that the user is holding the electronic device 100 close to the ear to talk, so as to automatically turn off the screen to save power. The proximity light sensor 180G can also be used in leather case mode and pocket mode to automatically unlock and lock the screen.

[0090] Ambient light sensor 180L is used to sense ambient light brightness. Electronic device 100 can adaptively adjust the brightness of display screen 194 based on the perceived ambient light. Ambient light sensor 180L can also be used to automatically adjust white balance when taking photos. Ambient light sensor 180L can also work with proximity light sensor 180G to detect whether electronic device 100 is in a pocket to prevent accidental touches.

[0091] The fingerprint sensor 180H is used to obtain fingerprints. The electronic device 100 can use the obtained fingerprint characteristics to implement fingerprint unlocking, access application locks, fingerprint photography, fingerprint call answering, etc.

[0092] The temperature sensor 180J is used to detect temperature. In some embodiments, the electronic device 100 uses the temperature detected by the temperature sensor 180J to execute a temperature processing strategy. For example, when the temperature reported by the temperature sensor 180J exceeds a threshold, the electronic device 100 reduces the performance of the processor located near the temperature sensor 180J to reduce power consumption and implement thermal protection. In other embodiments, when the temperature is lower than another threshold, the electronic device 100 heats the battery 142 to prevent the electronic device 100 from shutting down abnormally due to low temperature. In other embodiments, when the temperature is lower than another threshold, the electronic device 100 boosts the output voltage of the battery 142 to prevent abnormal shutdown due to low temperature.

[0093] The touch sensor 180K is also called a "touch panel." The touch sensor 180K can be disposed on the display screen 194. The touch sensor 180K and the display screen 194 form a touch screen, also called a "touch screen." The touch sensor 180K is used to detect touch operations applied thereto or in the vicinity thereof. The touch sensor can transmit the detected touch operations to the application processor to determine the type of touch event. Visual output related to the touch operations can be provided via the display screen 194. In other embodiments, the touch sensor 180K can also be disposed on the surface of the electronic device 100, in a location different from that of the display screen 194.

[0094] The bone conduction sensor 180M can obtain vibration signals. In some embodiments, the bone conduction sensor 180M can obtain vibration signals from the vibrating bones of the human body. The bone conduction sensor 180M can also contact the human pulse to receive blood pressure pulse signals. In some embodiments, the bone conduction sensor 180M can also be set in headphones to form bone conduction headphones. The audio module 170 can parse out voice signals based on the vibration signals of the vibrating bones of the human body obtained by the bone conduction sensor 180M to implement voice functions. The application processor can parse heart rate information based on the blood pressure pulse signals obtained by the bone conduction sensor 180M to implement heart rate detection functions.

[0095] The buttons 190 include a power button, a volume button, and the like. The buttons 190 may be mechanical buttons or touch buttons. The electronic device 100 may receive key inputs and generate key signal inputs related to user settings and function control of the electronic device 100.

[0096] Motor 191 can generate vibration prompts. Motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. For example, touch operations acting on different applications (such as taking pictures, audio playback, etc.) can correspond to different vibration feedback effects. For touch operations acting on different areas of the display screen 194, motor 191 can also correspond to different vibration feedback effects. Different application scenarios (for example: time reminders, receiving messages, alarm clocks, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also support customization.

[0097] The indicator 192 may be an indicator light, which may be used to indicate the charging status, power level changes, messages, missed calls, notifications, etc.

[0098] The SIM card interface 195 is used to connect a SIM card. The SIM card can be connected to or disconnected from the electronic device 100 by inserting it into or removing it from the SIM card interface 195. The electronic device 100 can support 1 or N SIM card interfaces, where N is a positive integer greater than 1. The SIM card interface 195 can support Nano SIM cards, Micro SIM cards, SIM cards, and the like. Multiple cards can be inserted into the same SIM card interface 195 at the same time. The types of the multiple cards can be the same or different. The SIM card interface 195 can also be compatible with different types of SIM cards. The SIM card interface 195 can also be compatible with external memory cards. The electronic device 100 interacts with the network through the SIM card to implement functions such as calls and data communications. In some embodiments, the electronic device 100 uses an eSIM, i.e., an embedded SIM card. The eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100.

[0099] Figure 2 A software structure block diagram of an electronic device 100 provided in an embodiment of the present application.

[0100] A layered architecture divides software into several layers, each with distinct roles and responsibilities. Layers communicate with each other via software interfaces. In some embodiments, the system is divided into four layers: application layer, application framework layer, runtime and system libraries, and kernel layer.

[0101] The application layer can include a series of application packages.

[0102] like Figure 2As shown, the application package may include camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, short message and other applications (also referred to as applications).

[0103] It should be noted that the application layer can also include another application, which the user can open while exercising to record exercise data in real time and generate an exercise report after the exercise. The exercise report may include a user's status assessment report. It is understandable that the name of the application can be "Health", "Exercise", etc., and this application does not impose any restrictions on this.

[0104] The application framework layer provides an application programming interface (API) and a programming framework for the applications in the application layer. The application framework layer includes some predefined functions.

[0105] like Figure 2 As shown, the application framework layer may include a window manager, a content provider, a view system, a phone manager, a resource manager, a notification manager, and the like.

[0106] The window manager is used to manage window programs. The window manager can obtain the display size, determine whether there is a status bar, lock the screen, take screenshots, etc.

[0107] Content providers are used to store and retrieve data and make it accessible to applications. The data may include videos, images, audio, calls made and received, browsing history and bookmarks, phone books, etc.

[0108] The view system includes visual controls, such as those for displaying text and images. The view system is used to build applications. A display interface can consist of one or more views. For example, a display interface containing a text notification icon might include a view for displaying text and a view for displaying images.

[0109] The phone manager is used to provide communication functions of the electronic device 100, such as management of call status (including answering, hanging up, etc.).

[0110] The resource manager provides various resources for applications, such as localized strings, icons, images, layout files, video files, and so on.

[0111] The Notification Manager allows applications to display notifications in the status bar. These messages can be displayed briefly and then disappear automatically, without requiring user interaction. For example, the Notification Manager can be used to notify users of completed downloads, message reminders, and so on. The Notification Manager can also display notifications in the top status bar of the system as icons or scrolling text, such as notifications from background applications, or as dialog interfaces on the screen. Examples include text messages in the status bar, beeps, vibrations on electronic devices, and flashing indicator lights.

[0112] The runtime includes the core library and the virtual machine. The runtime is responsible for system scheduling and management.

[0113] The core library consists of two parts: one part is the functional functions that need to be called by the programming language (for example, Java language), and the other part is the core library of the system.

[0114] The application layer and application framework layer run in a virtual machine. The virtual machine executes application layer and application framework layer programming files (for example, Java files) as binary files. The virtual machine performs functions such as object lifecycle management, stack management, thread management, security and exception management, and garbage collection.

[0115] The system library can include multiple functional modules, such as the surface manager, media libraries, 3D graphics processing library (such as OpenGL ES), and 2D graphics engine (such as SGL).

[0116] The surface manager is used to manage the display subsystem and provide the fusion of two-dimensional (2D) and three-dimensional (3D) layers for multiple applications.

[0117] The media library supports playback and recording of a variety of common audio and video formats, as well as static image files. The media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.

[0118] The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.

[0119] A 2D graphics engine is a drawing engine for 2D drawings.

[0120] The kernel layer is the layer between hardware and software. The kernel layer contains at least display driver, camera driver, audio driver, sensor driver, and virtual card driver.

[0121] The following describes the workflow of the software and hardware of the electronic device 100 in conjunction with capturing a photo scene.

[0122] When the touch sensor 180K receives a touch operation, the corresponding hardware interrupt is sent to the kernel layer. The kernel layer processes the touch operation into a raw input event (including touch coordinates, touch operation timestamp, and other information). The raw input event is stored in the kernel layer. The application framework layer obtains the raw input event from the kernel layer and identifies the control corresponding to the input event. For example, if the touch operation is a touch single-click operation and the control corresponding to the single-click operation is the control of the camera application icon, the camera application calls the interface of the application framework layer to start the camera application, and then starts the camera driver by calling the kernel layer to capture a still image or video through the camera 193.

[0123] The following describes a motion scenario based on an embodiment of the present application.

[0124] See also Figure 3 , Figure 3 1 is a schematic diagram of a sports scene provided by an embodiment of the present application, in which a user carries an electronic device 100 for running. Figure 3 As shown, when a user carries the electronic device 100 for running, the electronic device 100 records the user's speed and cadence. After the running is completed, the cadence at different speeds of the running process is analyzed, and then compared with the cadence at different speeds in the historical data, and the cadence variation value is calculated to determine the user's exercise status, so as to judge whether the user is suitable for continuing exercise, thereby avoiding sports injuries caused by poor exercise status of the user.

[0125] It can be understood that the ways of carrying the electronic device 100 include but are not limited to holding the electronic device 100 in hand, tying the electronic device 100 to a part of the body, etc., and this application does not impose any restrictions on this; the electronic device 100 includes but is not limited to mobile phones, smart watches and other terminal devices, and this application does not impose any restrictions on this; the running includes but is not limited to indoor running and outdoor running, and this application does not impose any restrictions on this.

[0126] based on Figure 3 The present application provides a method for evaluating the user's motion state, such as Figure 4 As shown, Figure 4 A flowchart of a method for evaluating a user's motion status provided in an embodiment of the present application is provided. The method includes but is not limited to the following steps:

[0127] S410: Obtain and process the user's current exercise data.

[0128] Specifically, the electronic device 100 obtains the user's current motion data, which includes the user's motion speed and the step frequency corresponding to the motion speed, and then processes the user's current motion data to determine the speed range to which the user's motion speed belongs and the step frequency range to which the step frequency corresponding to the motion speed belongs.

[0129] It is understood that the user's movement speed may include one or more instantaneous speeds of the user during this exercise, and may also include the average speed within one or more time periods. The user's movement speed may also include one or more speeds calculated in other ways, and this application does not limit this. Similarly, the cadence corresponding to the movement speed may include the cadence corresponding to the one or more instantaneous speeds of the user during this exercise, and may also include the average cadence within one or more time periods. The cadence corresponding to the movement speed may also include the cadence corresponding to the user's movement speed calculated in other ways, and this application does not limit this.

[0130] In one embodiment provided in the present application, the electronic device 100 obtains user data once at a certain interval. Optionally, the user data may include the instantaneous speed of the user when the electronic device 100 obtains the user data and the step frequency corresponding to the instantaneous speed, and may also include the average speed and average step frequency of the user in the previous interval. It can be understood that the user's current exercise data obtained by the electronic device 100 is a collection of several user data obtained by the electronic device 100 during this exercise.

[0131] It should be noted that during one exercise, the interval time for obtaining the user data is the same, while during different exercise processes, the interval time may be different. For example, during a certain exercise process, the interval time for obtaining user data is 1 minute, and during another exercise process, the interval time for obtaining user data is 30 seconds. This application does not impose any restrictions on this.

[0132] For ease of understanding, the user data acquired by the electronic device 100 each time will be represented in the form of an array below, and the user's current exercise data can be represented as several arrays.

[0133] For example, during a user's running process, part of the user's exercise data obtained by the electronic device 100 is: (7.5 km / h, 125 steps / min), (7.8 km / h, 130 steps / min), (8 km / h, 133 steps / min), (8.1 km / h, 135 steps / min), and (8.3 km / h, 138 steps / min). These five arrays are generated within five minutes of this exercise process, and the generation time of each of the above arrays is 1 minute apart.

[0134] It should be noted that the speed interval and the cadence interval can be pre-set / divided, or divided by the electronic device 100, and can be selected according to actual needs. This application does not impose any restrictions on this.

[0135] The following introduces the rules for dividing speed intervals and cadence intervals.

[0136] 1. Generally speaking, the interval lengths of different speed intervals are the same, and the interval lengths of different synchronous frequency intervals are also the same.

[0137] For example, each speed unit (km / h) is divided into a speed interval, and each ten cadence units (steps / minute) are divided into a cadence interval. The embodiment of the present application provides a preferred method of dividing each five or ten cadence units (steps / minute) into a cadence interval.

[0138] It can be understood that the human body has its own speed limit. When dividing the interval, the influence of this factor can be considered. Therefore, a limit speed can be set. When dividing the speed interval, speeds greater than or not less than the limit speed are discarded, or the speed range greater than or not less than the limit speed is directly divided into a speed interval. At this time, there is a speed interval with a different interval length from other speed intervals. For example, if a limit speed is set to 20km / h, the speeds within the interval of (20,∞) (in kilometers / hour) or [20,∞) (in kilometers / hour) can be discarded, or the speeds within the interval of (20,∞) (in kilometers / hour) or [20,∞) (in kilometers / hour) can be retained, and (20,∞) (in kilometers / hour) or [20,∞) (in kilometers / hour) can be used as a speed interval.

[0139] In addition, an initial speed can also be set, and the speed intervals can be divided starting from the initial speed, that is, speeds less than or not greater than the initial speed are discarded. For example, if the initial speed is set to 0 km / h, the limit speed is set to 20 km / h, and the interval length is 2, then the speed intervals can be divided starting from 0 km / h. The speed (in kilometers per hour) intervals can be divided into: [0,2), [2,4), [4,6), [6,8), [8,10), [10,12), [12,14), [14,16), [16,18), [18,20), [20,∞), or (0,2), [2,4), [4,6), [6,8), [8,10), [10,12), [12,14), [14,16), [16,18), [18,20), [20,∞); 6km / h, set the limit speed to 20km / h, and the interval length to 1, then the speed interval is divided from 6km / h, and the speed (unit is km / h) interval can be divided into: [6,7), [7,8), [8,9), [9,10), [10,11), [11,12), [12,13), [13,14), [14,15), [15,16), [16,17), [ ,17,18), [18,19), [19,20), [20,∞), or, (6,7), [7,8), [8,9), [9,10), [10,11), [11,12), [12,13), [13,14), [14,15), [15,16), [16,17), [17,18), [18,19), [19,20), [20,∞).

[0140] Accordingly, a limit step frequency can be set. When dividing the step frequency interval, the step frequency greater than or not less than the limit step frequency is discarded, or the step frequency range greater than or not less than the limit step frequency is directly divided into a step frequency interval. At this time, there is a step frequency interval with a length different from that of other step frequency intervals. For example, a limit step frequency is set to 200 steps / minute. The step frequencies within the interval range of (200,∞) (in steps / minute) or [200,∞) (in steps / minute) can be discarded, or the step frequencies within the interval range of (200,∞) (in steps / minute) or [200,∞) (in steps / minute) can be retained, and (200,∞) (in steps / minute) or [200,∞) (in steps / minute) can be used as a step frequency interval.

[0141] In addition, you can also set an initial stride frequency and start dividing the stride frequency intervals from the initial stride frequency, that is, discard the stride frequencies that are less than or not greater than the initial stride frequency. For example, set the initial stride frequency to 100 steps / minute, set the limit stride frequency to 200 steps / minute, and the interval length to 10. Then, start dividing the stride frequency intervals from 100 steps / minute, and the stride frequency (unit is steps / minute) intervals can be divided into: [100,110), [110,120), [120,130), [130,140), [140,150), [150,160), [160,170), [170,180), [180,190), [190,200), [200,∞).

[0142] 2. Generally speaking, a finite number of speed intervals and a finite number of step frequency intervals are obtained after division.

[0143] For example, the speed (in kilometers per hour) interval can be divided into: [6,7), [7,8), [8,9), [9,10), [10,11), [11,12), [12,13), [13,14), [14,15), [15,16), [16,17), [17,18), [18,19), [19,20), [20,∞), and the number of speed intervals obtained by division is The cadence (in steps / minute) interval can be divided into: [100,110), [110,120), [120,130), [130,140), [140,150), [150,160), [160,170), [170,180), [180,190), [190,200), [200,∞), and the number of cadence intervals obtained by division is finite.

[0144] 3. Generally speaking, the speed intervals obtained by division can be open intervals or closed intervals, or open first and then closed intervals, or closed first and then open intervals. Similarly, the cadence intervals obtained by division can be open intervals or closed intervals, or open first and then closed intervals, or closed first and then open intervals.

[0145] In one embodiment of the present application, the speed intervals obtained by division are all closed-at-front-and-open-at-back intervals, which can be referred to the above examples and will not be described in detail here.

[0146] In one embodiment of the present application, the divided cadence intervals are all closed at the front and open at the back, as can be seen from the above examples, which will not be described in detail here.

[0147] In one embodiment of the present application, the speed intervals obtained by division include a front-open and rear-closed interval and an open interval. For example, the speed (in kilometers per hour) interval can be divided into: (6,7], (7,8], (8,9], (9,10], (10,11], (11,12], (12,13], (13,14], (14,15], (15,16], (16,17], (17,18], (18,19], (19,20], (20,∞).

[0148] In one embodiment of the present application, the cadence interval obtained by division includes a front-open and rear-closed interval and an open interval. For example, the cadence (in steps / minute) interval can be divided into: (100, 110], (110, 120], (120, 130], (130, 140], (140, 150], (150, 160], (160, 170], (170, 180], (180, 190], (190, 200], (200, ∞).

[0149] 4. Generally speaking, there is no overlap between the speed intervals obtained by division, and there is no overlap between the cadence intervals obtained by division.

[0150] For example, if there are two speed intervals - (9, 10.5] and (10, 11.5], it can be seen that these two speed intervals have overlapping parts and cannot be the cadence intervals obtained by the same division; if there are two cadence intervals - (170, 185] and (180, 195], it can be seen that the ranges of these two cadence intervals have overlapping parts and cannot be the cadence intervals obtained by the same division.

[0151] It should be noted that, when the initial speed and the limit speed have been set, the speed intervals can be divided by limiting the number of speed intervals, or by setting the interval length; and when only the initial speed or the limit speed is set, the speed intervals can be divided by setting the interval length and the number of speed intervals. It can be understood that by setting the limit speed, the interval length and the number of intervals to divide the speed intervals, there may be speed intervals containing negative numbers in the speed intervals obtained by the division. In this case, the speed intervals containing negative numbers can be discarded, or only the non-negative numbers in the speed intervals containing negative numbers can be retained as the final speed intervals.

[0152] For example, the limit speed is set to 20km / h, the interval length is 3, the number of intervals is 8, and the speed range not less than the limit speed is directly divided into a speed interval. The divided speed (in kilometers per hour) intervals are: [-1,2), [2,5), [5,8), [8,11), [11,14), [14,17), [17,20), [20,∞). Among these speed intervals, there is an interval [-1,2) containing negative numbers. The non-negative numbers in this interval are retained as the final speed interval, that is, [0,2) is retained as the final speed interval. Therefore, the speed (in kilometers per hour) intervals finally obtained by division are: [0,2), [2,5), [5,8), [8,11), [11,14), [14,17), [17,20), [20,∞).

[0153] Similarly, when the initial cadence and the maximum cadence have been set, the division can be carried out by limiting the number of cadence intervals, or by setting the interval length; and when only the initial cadence or the maximum cadence is set, the division can be carried out by setting the interval length and the number of cadence intervals. It can be understood that by setting the maximum cadence, the interval length and the number of intervals to divide the cadence intervals, there may be cadence intervals containing negative numbers in the cadence intervals obtained by the division. In this case, the cadence intervals containing negative numbers can be discarded, or only the non-negative numbers in the cadence intervals containing negative numbers can be retained as the final cadence intervals. Please refer to the above examples and will not repeat them here.

[0154] It should also be noted that after the speed intervals and cadence intervals are divided, they will generally not be divided again. This is because the speed intervals and cadence intervals remain unchanged, so that the changes in the user's speed and cadence during multiple exercises can be reasonably evaluated, thereby evaluating the user's exercise status. If the speed intervals and cadence intervals based on the comparison of the user's multiple exercise processes are not exactly the same, then the conclusions drawn from the comparison may not be accurate.

[0155] However, in one embodiment of the present application, the lowest speed, highest speed, lowest cadence and highest cadence during the user's exercise can be obtained by acquiring several times of the user's exercise data, and then, according to the lowest speed, the highest speed, the lowest cadence and the highest cadence, the initial speed, the limit speed, the initial cadence and the limit cadence are set, and the speed interval and the cadence interval are divided according to the initial speed, the limit speed, the initial cadence and the limit cadence.

[0156] It is understandable that a default speed interval and a default cadence interval can also be set. When the user has no specific requirements, the default speed interval and the default cadence interval can be directly used. If the user has specific requirements, the electronic device 100 can be triggered to re-divide the speed interval and cadence interval according to the user's own motion data.

[0157] It should be noted that based on the user's current exercise data obtained by the electronic device 100 (including the user's exercise speed and the step frequency corresponding to the exercise speed), as well as the speed intervals and step frequency intervals obtained through division, the speed interval in which the user's exercise speed is located and the step frequency interval to which the step frequency corresponding to the exercise speed belongs can be determined.

[0158] For example, if part of the user's current motion data obtained by the electronic device 100 is: (7.5 km / h, 125 steps / min), (7.8 km / h, 130 steps / min), (8 km / h, 133 steps / min), (8.1 km / h, 135 steps / min), (8.3 km / h, 138 steps / min), the speed interval (in km / h) obtained by division is: [6,7 ), [7,8), [8,9), [9,10), [10,11), [11,12), [12,13), [13,14), [14,15), [15,16), [16,17), [17,18), [18,19), [19,20), [20,∞), the step frequency (in steps / minute) intervals obtained by division are: [100,110), [11 ,120), [120,130), [130,140), [140,150), [150,160), [160,170), [170,180), [180,190), [190,200), [200,∞), then, when the user's movement speed is 7.5 km / h, the speed falls in the speed interval [7,8), the corresponding step frequency is 125 steps / minute, and the step frequency falls in the step frequency interval [120,130), when the user's movement speed is 7.8 km / h, the speed falls in the speed interval [7,8), the corresponding step frequency is 130 steps / minute, and the step frequency falls in the step frequency interval [130,140), similarly, the method of determining the speed intervals of the user's other movement speeds and the step frequency intervals corresponding to these speeds can refer to the above content.

[0159] It should be noted that before obtaining the user's current exercise data, the electronic device 100 will also analyze the historical exercise data to determine the speed range to which the user's historical exercise speed belongs and the cadence range to which the step frequency corresponding to the historical exercise speed belongs. The electronic device 100 will also determine the habitual cadence range and habitual cadence.

[0160] It can be understood that the historical motion data includes the user's historical motion speed and the step frequency corresponding to the historical motion speed. The historical motion data can also be understood as a collection of several historical user data. The historical motion data can be historical user data of any time period before this exercise, and the historical user data is user data acquired and stored in the electronic device 100 before this exercise. For ease of understanding, the historical user data can also be represented in the form of an array, and the historical user data can also be represented as several arrays.

[0161] It can be understood that the process of determining the speed range to which the user's historical movement speed belongs and the cadence range to which the step frequency corresponding to the historical movement speed belongs can refer to the above-mentioned process of determining the speed range to which the user's movement speed belongs and the cadence range to which the step frequency corresponding to the movement speed belongs, and will not be repeated here.

[0162] Specifically, after determining the speed interval to which the user's historical movement speed belongs and the cadence interval to which the cadence corresponding to the historical movement speed belongs, the electronic device 100 determines the habitual cadence interval and habitual cadence corresponding to these speed intervals. Taking a speed interval as an example, the electronic device 100 first determines the historical movement speed within this speed interval, then determines the cadence interval to which the cadence corresponding to the historical movement speed belongs. This means that the cadence distribution within this speed interval is calculated, and the cadence interval with the most cadence distribution is then determined as the habitual cadence interval. The habitual cadence can be calculated by taking the average of the left and right endpoints of this interval as the habitual cadence.

[0163] It can be understood that each speed interval has its corresponding habitual cadence interval and habitual cadence. The habitual cadence interval and habitual cadence corresponding to a certain exercise speed of the user are the habitual cadence interval and habitual cadence corresponding to the speed interval to which this exercise speed belongs.

[0164] In one embodiment of the present application, there are several cadence intervals that meet the above conditions for being a habitual cadence interval, and a cadence interval with a larger cadence can be selected as the habitual cadence interval.

[0165] For example, the speed (in kilometers per hour) intervals include: [6,7), [7,8), [8,9), [9,10), [10,11), [11,12), [12,13), [13,14), [14,15), [15,16), [16,17), [17,18), [18,19), [19,20), [20,∞), and the cadence (in steps per minute) intervals include: [100 ,110),[110,120),[120,130),[130,140),[140,150),[150,160),[160,170),[170,180),[180,190),[190,200),[200,∞), the historical movement speeds (in kilometers per hour) included in the speed interval [8,9) are: 8, 8.1, 8.3, 8.4, 8.8, 8 .6, the cadences (in steps / minute) corresponding to these historical movement speeds are: 133, 135, 138, 140, 146, and 143, and the cadence intervals corresponding to these cadences are: [130, 140), [130, 140), [130, 140), [140, 150), [140, 150), [140, 150). According to the cadence distribution of the speed interval [8, 9), [130, 140) and [140, 150) both meet the conditions for being the habitual cadence interval of the speed interval [8, 9). In this case, the cadence interval [140, 150) with a larger cadence can be selected as the habitual cadence interval of the speed interval [8, 9). Alternatively, the average of the left and right endpoints of the cadence interval [140, 150) can be selected as the habitual cadence, that is, the average of 140 and 150 (in steps / minute) can be selected as the habitual cadence.

[0166] S420: Determine the high-frequency cadence interval and the high-frequency cadence.

[0167] Specifically, after processing the user's current exercise data, the cadence interval with the largest distribution of cadences corresponding to the exercise speed in the speed interval is taken as the high-frequency cadence interval corresponding to the speed interval, and the average of the left endpoint and the right endpoint of the high-cadence interval can be selected as the high-frequency cadence corresponding to the speed interval.

[0168] It can be understood that the process of determining the high-frequency cadence interval and the high-frequency cadence may refer to the process of determining the habitual cadence interval and the habitual cadence in S410 .

[0169] For example, the speed (in kilometers per hour) intervals include: [6,7), [7,8), [8,9), [9,10), [10,11), [11,12), [12,13), [13,14), [14,15), [15,16), [16,17), [17,18), [18,19), [19,20), [20,∞), and the cadence (in steps per minute) intervals include: [100,110), [110,12 0), [120,130), [130,140), [140,150), [150,160), [160,170), [170,180), [180,190), [190,200), [200,∞), the user's current exercise data obtained by the electronic device 100 includes: (7.5 km / h, 125 steps / min), (7.8 km / h, 130 steps / min), (8 km / h, 133 steps / min), (8.1 km / h, 1 m / h, 135 steps / min), (8.3 km / h, 138 steps / min), (8.4 km / h, 140 steps / min), (8.8 km / h, 146 steps / min), (9 km / h, 150 steps / min), (9.3 km / h, 155 steps / min), (9.6 km / h, 160 steps / min), (10.2 km / h, 170 steps / min), (9.5 km / h, 158 steps / min), (8.9 km / h, 148 steps / min), (8 .8 km / h, 146 steps / min), (8.6 km / h, 143 steps / min), (8.1 km / h, 135 steps / min), (7.9 km / h, 132 steps / min), (7.3 km / h, 122 steps / min), (6.9 km / h, 115 steps / min), (6.5 km / h, 108 steps / min), the speed ranges of these motion data include: [6,7), [7,8), [8,9), [9,10), [10,11). The speed interval [6,7) includes the following speeds (in km / h): 6.9 and 6.5, and their corresponding cadences (in steps / min): 115 and 108, respectively. The corresponding cadence intervals for these two cadences are: [110,120) and [100,110), respectively. From the above content, we can see that the cadence interval [110,120) with a larger cadence can be selected as the high-frequency cadence interval corresponding to the speed interval [6,7). We can also select the average of the left and right endpoints of the cadence interval [110,120) as the high-frequency cadence, that is, the average of 110 and 120 (in steps / min) is selected as the high-frequency cadence. The speed interval [7,8) includes the following speeds (in km / h): 7.5, 7.8, 7.9, 7.3. The step frequencies (in steps / minute) corresponding to these movement speeds are: 125, 130, 132, 122, and the step frequency intervals corresponding to these step frequencies are: [120, 130), [130, 140), [130, 140), [120, 130). It can be seen that [120, 130) and [130, 140) both meet the conditions of being the high-frequency step frequency interval of the speed interval [7, 8). At this time, the step frequency interval [130, 140) with a larger step frequency can be selected as the high-frequency step frequency interval corresponding to the speed interval [7, 8). The average of the left and right endpoints of the step frequency interval [130, 140) can also be selected as the high-frequency step frequency, that is, the average of 130 and 140 (135) can be selected. The unit is steps / minute) as the high-frequency step frequency; the movement speeds (in kilometers / hour) included in the speed interval [8,9) are: 8, 8.1, 8.3, 8.4, 8.8, 8.9, 8.8, 8.6, 8.1, and the step frequencies (in steps / minute) corresponding to these movement speeds are: 133, 135, 138, 140, 146, 148, 146, 143, 135, and the step frequency intervals corresponding to these step frequencies are: [130,140), [130,140), [130,140), [130,140), [140,150), [140,150), [140,150), [140,150), [130,140), It can be seen that the step frequency The most distributed step frequency interval is [140,150), so the step frequency interval [140,150) is selected as the high-frequency step frequency interval corresponding to the speed interval [8,9), and the average of the left and right endpoints of the step frequency interval [140,150) can also be selected as the high-frequency step frequency, that is, the average of 140 and 150, 145 (in steps / minute), is selected as the high-frequency step frequency; the speed interval [9,10) includes the following movement speeds (in kilometers / hour): 9, 9.3, 9.6, 9.5, and the step frequencies (in steps / minute) corresponding to these movement speeds are: 150, 155, 160, 158, and the step frequency intervals corresponding to these step frequencies are: [150,160), [150,160), [ 160,170), [150,160). It can be seen that the cadence interval with the largest cadence distribution is [150,160). Therefore, the cadence interval [150,160) is selected as the high-frequency cadence interval corresponding to the speed interval [9,10). The average of the left and right endpoints of the cadence interval [150,160) can also be selected as the high-frequency cadence, that is, the average of 150 and 160 (155 steps / minute) is selected as the high-frequency cadence. Similarly, the cadence interval [170,180) can be selected as the high-frequency cadence interval corresponding to the speed interval [10,11). The average of the left and right endpoints of the cadence interval [170,180) (175) can also be selected as the high-frequency cadence for the speed interval [10,11).

[0170] S430: Determine the user's cadence variation value.

[0171] Specifically, based on the high-frequency cadence and the habitual cadence, the cadence variation value of the user's current exercise is determined, and the habitual cadence is obtained based on the user's historical exercise data.

[0172] In one embodiment of the present application, the cadence variation value is: Among them, a i is the high frequency step frequency, b i is the habitual cadence, and N is the number of speed intervals to which the user's exercise speed belongs.

[0173] For example, the speed intervals to which the user's movement speed belongs during this running process are: [6,7), [7,8), [8,9), [9,10), [10,11), wherein the high-frequency step frequency interval corresponding to the speed interval [6,7) is [100,110), the high-frequency step frequency interval corresponding to the speed interval [7,8) is [130,140), the high-frequency step frequency interval corresponding to the speed interval [8,9) is [140,150), the high-frequency step frequency interval corresponding to the speed interval [9,10) is [140,150), and the high-frequency step frequency interval corresponding to the speed interval [10,11) is [160,170). Based on the above content, 105, 135, 145, 145 and 165 (in steps / minute) can be respectively used as the speed intervals [6,7), [7,8), [8 ,9), [9,10) and [10,11) corresponding to the high-frequency cadence, and from the user's historical motion data, the habitual cadence interval corresponding to the speed interval [6,7) is [110,120), the high-frequency cadence interval corresponding to the speed interval [7,8) is [130,140), the high-frequency cadence interval corresponding to the speed interval [8,9) is [140,150), the high-frequency cadence interval corresponding to the speed interval [9,10) is [150,160), and the high-frequency cadence interval corresponding to the speed interval [10,11) is [170,180), which means that 115, 135, 145, 155 and 175 (in steps / minute) can be used as the high-frequency cadence corresponding to the speed intervals [6,7), [7,8), [8,9), [9,10) and [10,11) respectively, then The "5" in the formula means that the number of speed intervals that the user's running speed belongs to is 5, namely [6,7), [7,8), [8,9), [9,10), [10,11). The a in the formula is i Specifically a i =[105, 135, 145, 145, 165], where b i Specifically b i=[115, 135, 145, 155, 175], therefore,

[0174] S440: Determine the user's exercise status.

[0175] Specifically, after determining the cadence variation value of the user's current exercise, the user's exercise state is determined based on the cadence variation value.

[0176] In one embodiment of the present application, if the cadence variation value is not greater than a preset threshold, it is determined that the user's current state is poor; or, if the cadence variation value is greater than a preset threshold, it is determined that the user's current state is good.

[0177] In one embodiment of the present application, a preset threshold and a first threshold can be set. If the cadence variation value is not greater than the preset threshold, it is determined that the overall change of the user's current exercise is large, the cadence has decreased, and the current state is poor; if the cadence variation value is greater than the preset threshold and less than the first threshold, it is determined that the overall change of the user's current exercise is small, and the current state is good; if the cadence variation value is not less than the first threshold, it is determined that the overall change of the user's current exercise is large, the cadence has increased, and the current state is good.

[0178] It can be understood that the preset threshold and the first threshold are used to evaluate the overall status of the user's exercise, and can be set according to actual needs and experimental data. This application does not impose any restrictions on this.

[0179] For example, the preset threshold is -10, and when the first threshold is 10, if the cadence variation value is not greater than -10, the overall change of the user's current exercise is large, and the cadence has decreased, and the user's current state is poor; if the cadence variation value is greater than -10 and less than 10, the overall change of the user's current exercise is small, and the user's current state is good; if the cadence variation value is not less than 10, the overall change of the user's current exercise is large, and the cadence has increased, and the user's current state is good.

[0180] It should be noted that after the electronic device 100 determines the user's exercise status, it can generate a status analysis report. The status analysis report may include the user's cadence variation value for the current exercise, suggestions for the user's subsequent exercise, and other specific content related to the current exercise, such as more detailed data during the current exercise. In addition, the status analysis report can be provided on the same interface as the report of other parameters of the current exercise, or it can be a separate interface.

[0181] In one embodiment of the present application, the electronic device 100 is a smart phone, such as Figure 5 As shown, Figure 5The user interface 50 may include a status bar 501, a return control 502, a sharing control 503, a menu control 504, a first display area 505 and a second display area 506, wherein the menu control 504 may include a pace menu 5041, a chart menu 5042 and a details menu 5043, and the content displayed in the first display area 505 and the second display area 506 is the content under the details menu. The first display area 505 may include the start and / or end time, distance and various parameters of the run (such as exercise time, calories, average pace, average speed, average cadence, average stride, number of steps and average heart rate, etc.), and the content displayed in the second display area 506 is a status assessment report. The second display area 506 may include a first sub-area 5061, a second sub-area 5062 and a third sub-area 5063, wherein the content displayed in the first sub-area 5061 may be the cadence variation value, the content displayed in the second sub-area 5062 may be the user's exercise status, and the content displayed in the third sub-area 5063 may be exercise analysis and suggestions for this exercise.

[0182] In one embodiment of the present application, the electronic device 100 is a smart phone, such as Figure 6 As shown, Figure 6 The user interface 60 may include a status bar, a return control, a sharing control, a menu control, etc., and may also include a display area 601. The display area 601 may include the start and / or end time, distance, and various parameters of the current run. The control 6011 is used to respond to the user's touch operation, so that the electronic device 100 displays the status evaluation report corresponding to the control 6011, such as Figure 7 As shown, Figure 7 The user interface 70 is an interface displayed by the control 6011 in response to the user's touch operation. The user interface 70 may include a status bar, a return control, a sharing control, a menu control, etc., and may also include a display area 701. The display area 701 may include the start and / or end time, distance, etc. of the current run, and may also include relevant specific content of the current run process (such as the speed-cadence correspondence diagram 7011), cadence variation value, user's exercise status, and analysis and suggestions of the current run process, etc., which can be referred to Figure 5 The second display area 506 shown is not described again here.

[0183] It should also be noted that if it is determined that the user's current state is not good, the electronic device 100 can prompt the user to stop exercising (for example, Figure 5 、 Figure 6 and, Figure 7 The user's current exercise data will be deleted, that is, the user's exercise data when the condition is not good will not be used as historical exercise data for subsequent exercise.

[0184] It is understandable that the method shown in steps S410-S440 can also be used in combination with other methods for evaluating the user's exercise status, for example, combining the user's heart rate changes for evaluation, etc., and this application does not limit this.

Claims

1. A method for evaluating a user's motion status, characterized in that: The method comprises: Obtaining the user's current exercise data, the exercise data including the user's exercise speed and the cadence corresponding to the exercise speed; Processing the current exercise data of the user to determine the speed interval to which the user's exercise speed belongs and the cadence interval to which the cadence corresponding to the exercise speed belongs; Determine a high-frequency cadence interval, where the high-frequency cadence interval is the cadence interval with the largest cadence distribution corresponding to the movement speed in the speed interval; determining a high-frequency cadence based on the high-frequency cadence interval; Determining a habitual cadence based on historical exercise data of the user, wherein the historical exercise data includes a historical exercise speed of the user and a cadence corresponding to the historical exercise speed; Based on the habitual cadence and the high frequency cadence, a cadence variation value of the user is determined. The cadence variation value is used to describe the magnitude of the change in the user's cadence. The cadence variation value is: Among them, a i is the high frequency step frequency, b i is the habitual cadence, and N is the number of speed intervals to which the user's exercise speed belongs; The user's exercise state is determined according to the cadence variation value.

2. The method according to claim 1, wherein Before obtaining the current exercise data of the user, determining the habitual cadence based on the user's historical exercise data includes: Analyze the user's historical exercise data to determine the speed interval to which the user's historical exercise speed belongs and the cadence interval to which the cadence corresponding to the historical exercise speed belongs; Determine a habitual cadence interval, where the habitual cadence interval is the cadence interval with the largest cadence distribution corresponding to the historical movement speed in the speed interval; A habitual cadence is determined based on the habitual cadence interval.

3. The method according to claim 1 or 2, wherein: Determining the user's exercise state based on the cadence variation value includes: If the cadence variation value is not greater than a preset threshold, it is determined that the user's exercise state is poor; Alternatively, if the cadence variation value is greater than a preset threshold, it is determined that the user's exercise state is good.

4. The method according to claim 3, wherein After determining the user's exercise state based on the cadence variation value, the method further includes: If it is determined that the user's exercise state is not good, the user is prompted to stop exercising and the user's exercise data is deleted.

5. An electronic device, characterized in that: The electronic device includes: one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program code, where the computer program code includes computer instructions, and the one or more processors are used to call the computer instructions to enable the electronic device to execute: Obtaining the user's current exercise data, the exercise data including the user's exercise speed and the cadence corresponding to the exercise speed; Processing the current exercise data of the user to determine the speed interval to which the user's exercise speed belongs and the cadence interval to which the cadence corresponding to the exercise speed belongs; Determine a high-frequency cadence interval, where the high-frequency cadence interval is the cadence interval with the largest cadence distribution corresponding to the movement speed in the speed interval; determining a high-frequency cadence based on the high-frequency cadence interval; Determining a habitual cadence based on historical exercise data of the user, wherein the historical exercise data includes a historical exercise speed of the user and a cadence corresponding to the historical exercise speed; Based on the habitual cadence and the high frequency cadence, a cadence variation value of the user is determined. The cadence variation value is used to describe the magnitude of the change in the user's cadence. The cadence variation value is: Among them, a i is the high frequency step frequency, b i is the habitual cadence, and N is the number of speed intervals to which the user's exercise speed belongs; The user's exercise state is determined according to the cadence variation value.

6. The electronic device according to claim 5, wherein: The one or more processors, when determining the habitual cadence based on the user's historical motion data before calling the computer instructions to cause the electronic device to execute the acquisition of the user's current motion data, are specifically configured to call the computer instructions to cause the electronic device to execute: Analyze the user's historical exercise data to determine the speed interval to which the user's historical exercise speed belongs and the cadence interval to which the cadence corresponding to the historical exercise speed belongs; Determine a habitual cadence interval, where the habitual cadence interval is the cadence interval with the largest cadence distribution corresponding to the historical movement speed in the speed interval; A habitual cadence is determined based on the habitual cadence interval.

7. The electronic device according to claim 5 or 6, wherein: The one or more processors, when used to call the computer instructions to enable the electronic device to determine the user's exercise state based on the cadence variation value, are specifically used to call the computer instructions to enable the electronic device to execute: If the cadence variation value is not greater than a preset threshold, it is determined that the user's exercise state is poor; Alternatively, if the cadence variation value is greater than a preset threshold, it is determined that the user's exercise state is good.

8. The electronic device according to claim 7, wherein: The one or more processors, after being configured to call the computer instructions to cause the electronic device to execute determining the user's exercise state based on the cadence variation value, are further configured to call the computer instructions to cause the electronic device to execute: If it is determined that the user's exercise state is not good, the user is prompted to stop exercising and the user's exercise data is deleted.

9. A computer program product comprising instructions, characterized in that When the computer program product is run on an electronic device, the electronic device is caused to execute the method according to any one of claims 1 to 4.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on an electronic device, the electronic device is caused to execute the method according to any one of claims 1 to 4.

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