Health plan formulation method, health plan formulation apparatus, and electronic device

Abstract

The present application provides a health plan formulation method, a health plan formulation apparatus, and an electronic device, applicable to the field of electronic devices. In the technical solution provided by the present application, an electronic device acquires a target weight loss rate proportion of a user and the current weight of the user, wherein the target weight loss rate proportion is the desired weight loss rate proportion of the user, and the weight loss rate proportion is the proportion of the weight decreased in a first unit duration in the current weight; weight loss fat content corresponding to the target weight loss rate proportion is determined, wherein the weight loss fat content is the proportion of the decreased fat in the decreased weight; and on the basis of the weight loss fat content corresponding to the target weight loss rate proportion, the target weight loss rate proportion, the current weight of the user, the calories per unit weight of fat, and calories per unit weight of lean body mass, a calorie deficit of the user in a second unit duration is determined, thereby providing a matched fat loss workout plan for the user.

Description

Health plan formulation method, health plan formulation device and electronic device

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on September 11, 2023, with application number 202311168990.5 and application name “Health Plan Formulation Method, Health Plan Formulation Device and Electronic Device”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The embodiments of the present application relate to the field of electronic devices, and more specifically, to a health plan formulation method, a health plan formulation device, and an electronic device. Background Art

[0003] The electronic device can obtain relevant information of the user and specify a health plan for the user based on the relevant information for the user's reference, so as to improve the user's physical fitness.

[0004] However, the current health plans specified by electronic devices are not accurate enough, which affects the rate at which users improve their physical fitness.

[0005] Summary of the Invention

[0006] The embodiments of the present application provide a health plan formulation method, a health plan formulation device, and an electronic device, which can provide users with accurate health plans.

[0007] In a first aspect, a health plan formulation method is provided, which is applied to an electronic device, comprising: obtaining a user's target weight loss rate ratio and the user's current weight, wherein the target weight loss rate ratio is the user's expected weight loss rate ratio, and the weight loss rate ratio is the ratio of the weight lost in a first unit time period to the current weight; determining a weight loss fat content corresponding to the target weight loss rate ratio, wherein the weight loss fat content is the ratio of the amount of fat in the reduced weight to the reduced weight; and determining the user's calorie gap in a second unit time period based on the weight loss fat content corresponding to the target weight loss rate ratio, the target weight loss rate ratio, the user's current weight, fat calories per unit weight, and lean body calories per unit weight.

[0008] In this method, the corresponding weight loss fat content is determined according to the user's target weight loss rate ratio, and the calorie gap is determined based on the weight loss fat content. A more accurate calorie gap can be obtained, which can help improve the accuracy of the healthy fat loss plan formulated by the user based on the calorie gap.

[0009] In some possible implementations, obtaining the target weight loss rate ratio of the user includes: obtaining the target weight loss rate of the user and the current weight of the user, the target weight loss rate being the weight loss rate expected by the user, and the weight loss rate being the weight lost within the first unit time period; determining the target weight loss rate ratio based on the target weight loss rate of the user and the current weight of the user.

[0010] In some possible implementations, determining the weight loss fat content corresponding to the target weight loss rate ratio includes: determining the population category to which the user belongs; and determining a first mapping relationship from a plurality of mapping relationships based on the population category to which the user belongs, wherein the first mapping relationship is a mapping relationship among the plurality of mapping relationships corresponding to the population category to which the user belongs, the plurality of mapping relationships corresponding one-to-one to the plurality of population categories, and each mapping relationship in the plurality of mapping relationships is used to indicate a mapping relationship between the fat content of the weight loss of users in the corresponding population category and the weight loss content of users in the corresponding population category within the first unit time period. The weight loss fat content corresponding to the target weight loss rate ratio is determined based on the first mapping relationship.

[0011] In some possible implementations, determining the population category to which the user belongs includes: obtaining user information, where the user information includes at least one of the following information about the user: maximum oxygen uptake, body fat percentage, age, gender, current weight, and body mass index; and determining the population category to which the user belongs based on the user information.

[0012] In some possible implementations, the fat content corresponding to the target weight loss rate ratio, the target weight loss rate ratio, the user's current weight, fat calories per unit weight, lean body calories per unit weight, and the user's calorie deficit in the second unit time satisfy the following relationship: g = (w*v*p*k1+w*v*(1-p)*k2) / t

[0013] Among them, g represents the calorie gap, w represents the current weight of the user, v represents the target weight loss rate ratio, p represents the weight loss fat content corresponding to the target weight loss rate ratio, k1 represents the fat calories per unit weight, k2 represents the lean body calories per unit weight, and t represents the ratio of the first unit time to the second unit time.

[0014] In some possible implementations, the diet plan and exercise plan of the user in the second unit time are determined based on the calorie deficit and the basal metabolic calories of the user in the second unit time.

[0015] In a second aspect, an electronic device or a cloud server is provided, the method including: obtaining a first basal metabolic condition, a first fat reduction duration, and a first exercise capacity, wherein the first basal metabolic condition is the basal metabolic condition of a user for whom a health plan is to be formulated, the first exercise capacity is the exercise capacity of the user for whom a health plan is to be formulated, and the first fat reduction duration is the fat reduction duration expected by the user for whom a health plan is to be formulated; determining a first target exercise plan based on the first basal metabolic condition, the first fat reduction duration, and the first exercise capacity, wherein the first target exercise plan includes multiple target stages, multiple target durations, multiple target exercise item sets, and multiple exercise duration ratios, the multiple target durations corresponding one-to-one to the multiple target stages, each target duration in the multiple target durations being the duration of the corresponding target stage included in the first fat reduction duration, the multiple target exercise item sets corresponding one-to-one to the multiple target stages, each target exercise item set in the multiple target exercise item sets including exercise items within the corresponding target stage, the multiple exercise duration ratios corresponding one-to-one to the multiple target exercise item sets, and each exercise duration ratio in the multiple exercise duration ratios being an exercise duration ratio between exercise items within the corresponding target exercise item set.

[0016] In this method, a personalized fat-loss exercise plan is specified based on the user's basic information, exercise ability, and fat-loss goals, which flexibly and accurately adapts to the weight-loss training requirements in various scenarios.

[0017] In some possible implementations, a first target exercise plan is determined based on the first basal metabolic condition, the first fat loss duration, and the first exercise capacity, including: determining the multiple target stages, the multiple target durations, the multiple target exercise type sets, and the multiple exercise duration ratios based on the first basal metabolic condition and the first fat loss duration, the multiple target exercise type sets corresponding to the multiple target stages one-to-one, and each target exercise type set in the multiple target exercise type sets contains the exercise type of the corresponding target stage; determining the target exercise item set of the corresponding target stage based on the first exercise capacity and each target exercise type set.

[0018] In some possible implementations, the multiple target stages, the multiple target durations, the multiple target exercise type sets and the multiple exercise duration ratios are determined according to the first basal metabolic condition and the first fat loss duration, including: determining the multiple target stages and the multiple target durations according to the first basal metabolic condition and the first fat loss duration; determining the target exercise type set for each target stage in the multiple target stages, and obtaining multiple target exercise type sets that correspond one-to-one to the multiple target stages; determining the exercise duration ratios of the multiple exercise types in each target exercise type set in the multiple target exercise type sets, and obtaining the multiple target duration ratios that correspond one-to-one to the multiple target exercise type sets.

[0019] In some possible implementations, determining the target sports item set corresponding to the target stage based on the first sports ability and each target sports type set includes: obtaining a first score based on the first sports ability, the first score being the score of the first sports ability; determining a first sports difficulty based on a mapping relationship between the sports ability score and the sports difficulty, the first sports difficulty being the sports difficulty associated with the first score; determining the target sports item set corresponding to the target stage for each target sports type set based on each target sports type set and the first sports difficulty, the target sports item set corresponding to the target stage for each target sports type set including sports items of each sports type in each target sports type set and having a sports difficulty of the first sports difficulty.

[0020] In some possible implementations, the second target motion plan is determined by obtaining the degree of completion of the first target motion plan and / or user feedback on the first target motion plan.

[0021] In some possible implementations, obtaining the completion degree of the first target exercise plan includes: obtaining the actual completion time of each exercise item in each target exercise item set in the multiple target exercise item sets; determining the planned duration of each exercise item in each target exercise item set based on the ratio of the multiple target durations to the multiple exercise durations; determining the completion degree of the same type of exercise items in each target exercise item set based on the actual completion time and the planned duration of the same type of exercise items in each target exercise item set; and determining the exercise completion degree of the target stage corresponding to each target exercise item set based on the completion degree of the same type of exercise items in each target exercise item set.

[0022] In a third aspect, the present application provides an apparatus. The apparatus may include a module corresponding to each of the methods / operations / steps / actions described in the first or second aspects, and the module may be implemented as a hardware circuit, software, or a combination of hardware circuit and software.

[0023] In one design, the apparatus may include a processing module and a communication module. The communication module is configured to perform the information acquisition actions described in the second aspect of the method, and the processing module is configured to perform the processing actions described in the first or second aspect of the method.

[0024] In one design, the device may be an electronic device, or a device, module, circuit or chip configured in an electronic device, or a device that can be used in conjunction with an electronic device.

[0025] In a fourth aspect, a device is provided, comprising a processor and a storage medium, wherein the storage medium stores instructions, and when the instructions are executed by the processor, the method in the first aspect or any possible implementation manner of the first aspect is implemented.

[0026] In a fifth aspect, a device is provided, comprising a processor, wherein the processor is used to process data and / or information so that the method in the first aspect or any possible implementation of the first aspect is implemented, or the method in the second aspect or any possible implementation of the second aspect is implemented.

[0027] In one design, the device may be an electronic device, or a device, module, circuit or chip configured in an electronic device, or a device that can be used in conjunction with an electronic device.

[0028] Optionally, the device may also include a memory for storing programs or instructions, and the processor is used to run the programs or instructions so that the method in the first aspect or any possible implementation of the first aspect is implemented, or the method in the second aspect or any possible implementation of the second aspect is implemented.

[0029] Optionally, the device may further include the transceiver circuit, or an input / output interface.

[0030] In a sixth aspect, a chip is provided, comprising a processor, wherein the processor is used to run a program or instruction so that the method in the first aspect or any possible implementation of the first aspect is implemented, or the method in the second aspect or any possible implementation of the second aspect is implemented.

[0031] Optionally, the chip may further include a memory for storing programs or instructions. Optionally, the chip may further include the transceiver circuit, or an input / output interface.

[0032] In the seventh aspect, a computer-readable storage medium is provided, which includes instructions. When the instructions are executed by a processor, the method in the first aspect or any possible implementation of the first aspect is implemented, or the method in the second aspect or any possible implementation of the second aspect is implemented.

[0033] In an eighth aspect, a computer program product is provided, comprising computer program code or instructions, which, when executed, enables the method according to the first aspect or any possible implementation of the first aspect to be implemented, or enables the method according to the second aspect or any possible implementation of the second aspect to be implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] FIG1 is a schematic structural diagram of an electronic device;

[0035] FIG2 is a block diagram of the software structure of the electronic device provided in an embodiment of the present application;

[0036] FIG3 is a schematic flow chart of a health plan formulation method according to an embodiment of the present application;

[0037] FIG4 is a schematic diagram of a fat percentage model determined based on the user's demographic category according to an embodiment of the present application;

[0038] FIG5 is an example diagram of a user interface according to an embodiment of the present application;

[0039] FIG6 is a schematic flow chart of a health plan formulation method according to another embodiment of the present application;

[0040] FIG7 is an example diagram of determining a user's metabolic status according to an embodiment of the present application;

[0041] FIG8 is a schematic diagram of the structure of a device provided by an embodiment of the present application;

[0042] FIG9 is a schematic diagram of the device structure provided in yet another embodiment of the present application. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.

[0044] The terms used in the following embodiments are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of this application and the appended claims, the singular expressions "a", "an", "said", "above", "the" and "this" are intended to also include expressions such as "one or more", unless there is a clear contrary indication in the context. It should also be understood that in the following embodiments of the present application, "at least one", "one or more" refer to one, two or more. The term "and / or" is used to describe the association relationship of associated objects, indicating that three relationships can exist; for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship.

[0045] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in yet other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0046] The electronic devices in the embodiments of the present application may be mobile phones, tablet computers, wearable electronic devices with wireless communication functions (such as smart watches), laptop computers, etc. It should also be understood that in some embodiments, the electronic device may not be the aforementioned portable electronic device, but a desktop computer.

[0047] 1 shows a schematic structural diagram of an electronic device 100. 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 194, and a subscriber identification module (SIM) card interface 195. 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.

[0048] It should be understood that the structures illustrated in the embodiments of the present application do 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.

[0049] 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 processing unit (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 processing unit (NPU). The different processing units may be independent devices or integrated into one or more processors.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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.

[0054] 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.

[0055] 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.

[0056] 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.

[0057] 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 (IR), etc., which are applied to the electronic device 100. The wireless communication module 160 can be one or more devices that integrate 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.

[0058] 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 a network and other devices through wireless communication technologies. The wireless communication technologies may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR 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).

[0059] 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.

[0060] Display screen 194 is used to display images, videos, and the like. Display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a MiniLED, a MicroLED, a Micro-oLed, or a quantum dot light-emitting diode (QLED). In some embodiments, electronic device 100 may include one or N display screens 194, where N is a positive integer greater than one.

[0061] The electronic device 100 can implement a shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, and an application processor.

[0062] 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. 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.

[0063] 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 light signal into an electrical signal, and then passes the electrical signal to the ISP for conversion into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image 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.

[0064] The digital signal processor is used to process digital signals. In addition to processing digital image 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.

[0065] 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.

[0066] The NPU is a neural network (NN) computing processor. Drawing on the structure of biological neural networks, such as the transmission patterns between neurons in the human brain, it rapidly processes input information and can continuously self-learn. The NPU can enable intelligent cognitive applications in electronic device 100, such as image recognition, face recognition, speech recognition, and text comprehension.

[0067] 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.

[0068] 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 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 storage (UFS), etc.

[0069] 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.

[0070] 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.

[0071] 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.

[0072] 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.

[0073] 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 collect 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 collect sound signals, reduce noise, identify the source of sound, realize directional recording function, etc.

[0074] The pressure sensor 180A is used to sense pressure signals and convert them into electrical signals. In some embodiments, the pressure sensor 180A can be set on the display screen 194. There are many types of pressure sensors 180A, such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, etc. A capacitive pressure sensor can be a device comprising at least two parallel plates with conductive materials. When a force acts on the pressure sensor 180A, the capacitance between the electrodes changes. The electronic device 100 determines the intensity of the pressure based on the change in capacitance. When a touch operation acts on the display screen 194, the electronic device 100 detects the intensity of the touch operation based on the pressure sensor 180A. The electronic device 100 can also calculate the position of the touch based on the detection signal of the pressure sensor 180A. In some embodiments, touch operations acting on the same touch position but with different touch operation intensities can correspond to different operation instructions. For example, when a touch operation with a touch operation intensity greater than or equal to the first pressure threshold acts on the alarm application icon, the instruction to create a new alarm is executed.

[0075] Fingerprint sensor 180H is used to collect fingerprints. Electronic device 100 can use the collected fingerprint characteristics to implement fingerprint unlocking, accessing application locks, taking photos with fingerprints, answering calls with fingerprints, and so on. For example, when the phone detects a user's touch operation on the lock screen, the phone can collect the user's fingerprint information through fingerprint sensor 180H and match the collected fingerprint information with the fingerprint information pre-set in the phone. If the match is successful, the phone can enter the non-lock screen interface from the lock screen interface.

[0076] 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.

[0077] Figure 2 is a block diagram of the software structure of the electronic device 100 according to an embodiment of the present application. The layered architecture divides the software into several layers, each with clear roles and division of labor. The layers communicate with each other through software interfaces. In some embodiments, the software system of the electronic device is divided into four layers: the application layer, the application framework layer, the runtime and system library, and the kernel layer. The application layer may include a series of application packages.

[0078] As shown in Figure 2, the application layer may include camera, settings, skin modules, user interface (UI), third-party applications, etc. Among them, third-party applications may include gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, short message, etc.

[0079] The application framework layer provides an application programming interface (API) and a programming framework for applications in the application layer. The application framework layer may include some predefined functions.

[0080] As shown in FIG2 , the application framework layer may include a window manager, a content provider, a view system, a telephony manager, a resource manager, a notification manager, and the like.

[0081] The window manager manages windowed applications. It can determine the display size, determine whether a status bar is present, lock the screen, and take screenshots. Content providers store and retrieve data and make it accessible to applications. This data can include video, images, audio, incoming and outgoing calls, browsing history and bookmarks, and phone books.

[0082] The view system includes visual controls, such as controls for displaying text and images, such as the instructions for prompting a virtual shutter button in the embodiments of this application. The view system can be used to build applications. A display interface can be composed of one or more views. For example, a display interface including a text notification icon can include a view for displaying text and a view for displaying images.

[0083] 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.).

[0084] The resource manager provides various resources for applications, such as localized strings, icons, images, layout files, video files, and so on.

[0085] The Notification Manager allows applications to display notifications in the status bar. These messages can be displayed briefly and then disappear automatically without user interaction. For example, the Notification Manager is used to notify users of completed downloads and message reminders. 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 windows on the screen. Examples include text messages in the status bar, beeps, vibrations on electronic devices, and flashing indicator lights.

[0086] The runtime includes the core library and the virtual machine. The runtime is responsible for the scheduling and management of the software system.

[0087] The core library consists of two parts: one is the functional functions that the programming language needs to call, and the other is the system core library.

[0088] The application layer and application framework layer run in a virtual machine. The virtual machine executes Java files in the application layer and application framework layer as binary files. The virtual machine manages object lifecycles, stack management, thread management, security and exception management, and garbage collection.

[0089] The system library can include multiple functional modules, such as a surface manager, media libraries, a 3D graphics processing library (such as OpenGL ES), and a 2D graphics engine (such as SGL).

[0090] The surface manager is used to manage the display subsystem and provide fusion of 2D and 3D layers for multiple applications.

[0091] 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.

[0092] The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.

[0093] A 2D graphics engine is a drawing engine for 2D drawings.

[0094] In addition, the system library can also include status monitoring service modules, such as a physical status recognition module for analyzing and identifying user gestures; a sensor service module for monitoring sensor data uploaded by various sensors at the hardware layer to determine the physical status of the electronic device 100.

[0095] The kernel layer is the layer between hardware and software. The kernel layer includes at least display driver, camera driver, audio driver, and sensor driver.

[0096] The hardware layer may include various sensors, such as the various sensors introduced in FIG. 1 , the acceleration sensor, gyroscope sensor, touch sensor, etc. involved in the embodiments of the present application.

[0097] FIG3 is a schematic flow chart of a health plan formulation method according to an embodiment of the present application. As shown in FIG3 , the method includes S310, S320, and S330. The method can be performed by an electronic device. The electronic device can be a terminal device, such as a mobile phone, tablet computer, or other terminal device, or a wearable device, or a cloud server. An exemplary structure of the electronic device is shown in FIG1 and / or FIG2 .

[0098] S310, obtaining the user's target weight loss rate ratio and the user's current weight, where the target weight loss rate ratio is the user's expected weight loss rate ratio, and the weight loss rate ratio is the ratio of the weight lost in the first unit time to the current weight.

[0099] As an example, the first unit duration may be a day, a week, a month, or a year.

[0100] As an example, the weight loss rate ratio is the percentage of the weight lost in the first unit time period to the current weight. For example, the weight loss rate may be 1% per week.

[0101] For example, when a user desires to lose 1% of the current weight in a week, the first unit time is one week, and the user's target weight loss rate is 1%.

[0102] S320, determining the weight loss fat content corresponding to the target weight loss rate ratio, where the weight loss fat content is the ratio of the amount of fat in the reduced weight to the reduced weight.

[0103] For example, the fat content of weight loss is the percentage of fat in the weight loss. For example, if the weight loss is 1 kilogram (kg) and the fat content loss is 0.5 kg, the fat content of weight loss is the percentage of 0.5 kg to 1 kg, which is 50%.

[0104] Generally speaking, there is a mapping relationship between the weight loss rate and the fat content of the weight loss. For example, the greater the weight loss rate, the smaller the fat content of the weight loss, that is, the fat content of the weight loss is inversely proportional to the weight loss rate.

[0105] In this step, as an example, the weight loss fat content corresponding to the target weight loss rate ratio can be determined based on the mapping relationship between the weight loss rate ratio and the weight loss fat content.

[0106] S330, determining the user's calorie deficit within the second unit time based on the weight loss fat content corresponding to the target weight loss rate ratio, the target weight loss rate ratio, the user's current weight, fat calories per unit weight, and lean body calories per unit weight.

[0107] In this step, lean body can be understood as a general term for the collection of other components in the human body except fat.

[0108] As an example, the second unit of time may be a day, a week, a month, or a year.

[0109] As an example, the unit weight may be gram (g), kg, jin or kilogram, etc.

[0110] As an example, the following relationship is satisfied between the target weight loss rate percentage corresponding to the fat content, the target weight loss rate percentage, the user's current weight, fat calories per unit weight, lean body calories per unit weight, and the user's calorie deficit in the second unit time: g = (w*v*p*k1+w*v*(1-p)*k2) / t

[0111] Among them, g represents the calorie gap of the second unit time, w represents the user's current weight, v represents the target weight loss rate ratio, p represents the fat content corresponding to the target weight loss rate ratio, k1 represents the fat calories per unit weight, k2 represents the lean body calories per unit weight, and t represents the ratio of the first unit time to the second unit time.

[0112] It can be understood that the above relationship is only an exemplary relationship for calculating the calorie gap based on the weight loss fat content corresponding to the target weight loss rate ratio, the target weight loss rate ratio, the user's current weight, fat calories per unit weight and lean body calories per unit weight. Any relationship obtained by deforming the above relationship should be included in the scope of this step.

[0113] It can be understood that one principle of this step is as follows: based on the current weight and the target weight loss rate ratio within the first unit time, the target weight loss can be obtained, and the target weight loss is the weight the user expects to lose in the first unit time; based on the target weight loss and the target weight loss rate ratio corresponding to the weight loss fat content, the fat weight in the target weight loss can be obtained, that is, the fat weight contained in the weight the user expects to lose in the first unit time; based on the fat weight in the target weight loss and the fat calories per unit weight, the fat calories that need to be lost in the first unit time can be obtained; based on the target weight loss rate ratio corresponding to the weight loss fat content, the target weight loss rate ratio corresponding to the weight loss lean body content can be obtained, and the weight loss lean body content is the weight lost in the first unit time. The proportion of lean body in the weight lost; the lean body content of weight loss corresponding to the target weight loss and the target weight loss rate can be used to know the lean body weight in the target weight loss, that is, the lean body weight included in the weight that the user expects to lose in the first unit time; the lean body calories that need to be lost in the first unit time can be known based on the lean body weight in the target weight loss and the lean body calories per unit weight; the total calories that need to be lost in the first unit time can be known based on the lean body calories that need to be lost in the first unit time and the lean body calories that need to be lost in the first unit time; the calories that need to be lost in the second unit time can be known based on the total calories that need to be lost in the first unit time and the ratio of the first unit time to the second unit time, that is, the calorie gap in the second unit time.

[0114] It can be understood that any method that uses the above principles or related principles that can be undoubtedly derived from the above principles and determines the calorie deficit based on the weight loss fat content corresponding to the target weight loss rate ratio, the target weight loss rate ratio, the user's current weight, fat calories per unit weight, and lean body calories per unit weight should be included in the scope of this step.

[0115] In this embodiment, as an example, the first unit duration may be a default, such as a default of one week or one month.

[0116] As an example, the first unit duration may be input by a user, such as input through a user interface.

[0117] As an example, the weight loss duration can be calculated based on the user's desired target weight, current weight, and weight loss rate. For example, the difference between the target weight and the current weight divided by the weight loss rate can be used as the weight loss duration. Alternatively, the weight loss rate can also be calculated based on the weight loss rate percentage.

[0118] As an example, the user's target weight may be obtained through user input, for example, the target weight input by the user through a user interface may be obtained.

[0119] As an example, the user interface may include a text input control in which the user may enter a target weight.

[0120] As an example, the user interface may include a selection control, which may provide a plurality of weight options for the user, and the user may select a target weight through the selection control.

[0121] In this embodiment, as an example, the second unit duration may be a default, such as a default of one week or one month.

[0122] As an example, the second unit duration may be input by a user, such as through a user interface.

[0123] In this embodiment, as an example, obtaining the user's target weight loss rate ratio may include: obtaining the user's target weight loss rate and the user's current weight; and determining the target weight loss rate ratio based on the user's target weight loss rate and the user's current weight.

[0124] As an example, determining the target weight loss rate ratio based on the user's target weight loss rate and the user's current weight may include: obtaining the ratio of the user's target weight loss rate and the user's current weight to obtain the target weight loss rate ratio.

[0125] As an example, obtaining the user's target weight loss rate may include: obtaining the target weight loss rate input by the user, for example, obtaining the target weight loss rate input by the user through a control in a user interface.

[0126] As an example, the user interface may include a text input control in which the user may enter a target weight loss rate.

[0127] As an example, the user interface may include a selection control that provides the user with multiple weight loss rate options, through which the user can select a weight loss rate, wherein the weight loss rate selected by the user can be used as the target weight loss rate input by the user.

[0128] For example, obtaining a user's target weight loss rate may include obtaining a user's desired weight loss mode, and determining the user's target weight loss rate based on a mapping relationship between the user's weight loss mode and weight loss rates, where different weight loss modes correspond to different weight loss rates. The user's desired weight loss mode may be referred to as the target weight loss mode.

[0129] The weight loss mode may include at least one of the following modes: a recommended mode, a fast mode, or an aggressive mode, and the three weight loss rates corresponding to the three modes may increase in sequence.

[0130] As an example, the weight reduction rate corresponding to the fast mode may be between 1.1% and 1.5%.

[0131] As an example, obtaining the user's weight loss mode may include: obtaining a target weight loss mode input by the user through a control in a user interface.

[0132] As an example, the user interface may include a text input control in which the user may enter a target weight loss mode.

[0133] As an example, the user interface may include a selection control that provides the user with a variety of weight loss mode options. The user may select a weight loss mode through the selection control, wherein the weight loss mode selected by the user may serve as the target weight loss mode input by the user.

[0134] Optionally, in a scenario where the user interface includes a selection control for selecting a weight loss mode, the user interface may also include a weight loss rate corresponding to each selectable weight loss mode for the user to use as a reference when selecting a weight loss mode.

[0135] As an example, obtaining the user's target weight loss rate percentage may include: obtaining the target weight loss rate percentage input by the user. For example, obtaining the target weight loss rate percentage input by the user through a user interface.

[0136] As an example, the user interface may include a text input control in which the user may enter a target weight loss rate percentage.

[0137] As an example, the user interface may include a selection control that provides the user with a variety of weight loss rate ratio options, through which the user can select the weight loss rate ratio, wherein the weight loss mode selected by the user can be used as the target weight loss rate ratio input by the user.

[0138] Optionally, in a scenario where the user interface includes a selection control for selecting a weight loss rate, the user interface may also include a weight loss rate and / or weight loss mode corresponding to each selectable weight loss rate ratio for the user to select the weight loss rate ratio as a reference.

[0139] As an example, obtaining the current weight of the user may include: obtaining the current weight input by the user through a control in the user interface.

[0140] As an example, the user interface may include a text input control in which the user can enter their current weight.

[0141] As an example, the user interface may include a selection control that provides the user with multiple weight options. The user may select a weight through the selection control, wherein the weight selected by the user may be used as the current weight input by the user.

[0142] As an example, obtaining the current weight of the user may include: receiving the weight of the user measured by a weight detection device, an example of which is a body fat scale.

[0143] For example, an electronic device establishes a connection with a weight detection device, and then receives the user's weight currently measured in real time by the weight detection device from the weight detection device, or receives the user's weight most recently measured using the weight detection device from the weight detection device, and uses the received weight value as the user's current weight.

[0144] As an example, determining the weight loss fat content corresponding to the target weight loss rate ratio includes: determining the population category to which the user belongs; determining a first mapping relationship from multiple mapping relationships based on the population category to which the user belongs, the first mapping relationship being a mapping relationship among the multiple mapping relationships corresponding to the population category to which the user belongs, the multiple mapping relationships corresponding one-to-one to the multiple population categories, each mapping relationship in the multiple mapping relationships being used to indicate a mapping relationship between the fat ratio in the weight loss of users of the corresponding population category and the weight loss ratio of users of the corresponding population category within a first unit time period; determining the weight loss fat content corresponding to the target weight loss rate ratio based on the first mapping relationship.

[0145] In this embodiment, the mapping relationship between the fat percentage in the weight loss of users of the corresponding population category and the weight loss percentage of users of the corresponding population category within the first unit time period can be called a weight loss fat percentage model.

[0146] As an example, the population category may include at least one of the following categories: obese people, fitness people, and thin people.

[0147] In this step, users of different population categories may have different at least one of the following information: maximum oxygen uptake, body fat percentage, age, gender, current weight, or body mass index (BMI).

[0148] As an example, the crowd category may be characterized by a name of the crowd category, such as "obese crowd", "fitness crowd" or "thin crowd".

[0149] As an example, a crowd category can be characterized by the characteristic information of users in the crowd category. For example, a high body fat percentage, a high BMI, and being male can be characterized as an obese crowd; another example is a low body fat percentage, a high BMI, and being male can be characterized as a fitness crowd.

[0150] For example, a demographic category can be characterized by the range of characteristic information values ​​of users within that demographic category. For example, a body fat percentage of a1%-b1%, a BMI of c1%-d1%, and male gender can represent an obese population; another example is a body fat percentage of a2%-b2%, a BMI of c2%-d2%, and male gender can represent a fitness group.

[0151] As an example, determining the crowd category to which the user belongs may include: obtaining information input by the user that can represent the crowd category, and determining the crowd category to which the user belongs based on the information.

[0152] As an example, the user interface may include a text input control in which the user may specify information about a population category.

[0153] As an example, the user interface may include a selection control that provides the user with information options representing different categories of people. The user may select information representing different categories of people through the selection control, wherein the information selected by the user may serve as the information representing different categories of people input by the user.

[0154] As an example, when the name of the population category to which the user belongs is obtained and the mapping relationship between the fat weight loss rate ratio and the weight loss fat content is associated with the name of the population category, the first mapping relationship can be determined based on the name of the population category to which the user belongs.

[0155] As an example, when the user's characteristic information is obtained and the mapping relationship between the fat weight loss rate ratio and the weight loss fat content is associated with the name of a population category, it is necessary to first determine the name of the population category to which the user belongs based on the mapping relationship between the user's characteristic information and the population category, and then determine the first mapping relationship based on the name of the population category to which the user belongs.

[0156] As an example, when characteristic information of the user is obtained and the mapping relationship between the fat weight loss rate ratio and the weight loss fat content is associated with the user characteristics, the first mapping relationship can be determined based on the characteristic information of the user.

[0157] As an example, when the user's characteristic information is obtained and the mapping relationship between the fat weight loss rate ratio and the weight loss fat content is associated with the range of the characteristic value, the range of the user's characteristic value can be determined based on the mapping relationship between the user's characteristic information and the range of the characteristic value, and then the first mapping relationship can be determined based on the range of the user's characteristic value.

[0158] As an example, when the user's characteristic information is obtained and the mapping relationship between the fat weight loss rate ratio and the weight loss fat content is associated with the name of a population category, the range of the user's characteristic value can be determined based on the mapping relationship between the user's characteristic information and the range of the characteristic value, and then the name of the population category to which the user belongs can be determined based on the mapping relationship between the range of the user's characteristic value and the population category, and finally the first mapping relationship is determined based on the name of the population category to which the user belongs.

[0159] Figure 4 is a schematic diagram of a model for determining body fat percentage based on the user's demographic category. As shown in Figure 4, body fat percentage can be categorized into several ranges, such as a1%-b1% and a2%-b2%, BMI can be categorized into several ranges, such as c1-d1 and c2-d2, age can be categorized into several ranges, such as e1-f1 and e2-f2, and gender can be categorized into male and female.

[0160] Among them, body fat percentage a1%-b1%, BMI c1-d1, age e1-f1 and male gender are associated with one fat percentage model, and body fat percentage a2%-b2%, BMI c2-d2, age e2-f2 and male gender are associated with another weight loss fat percentage model.

[0161] It can be understood that in Figure 4, the information representing the population category "body fat rate a1%-b1%, BMI c1-d1, age e1-f1 and gender male" can be replaced by the name of the corresponding population category "obese people", and the information representing the population category "body fat rate a2%-b2%, BMI c2-d2, age e2-f2 and gender male" can be replaced by the name of the corresponding population category "fitness people".

[0162] It can be understood that in Figure 4, the information representing the population category "body fat percentage a1%-b1%, BMI c1-d1, age e1-f1 and gender male" can be replaced by the information representing the population category "high body fat percentage, high BMI, old age and male", and the information representing the population category "body fat percentage a2%-b2%, BMI c1-d1, age e2-f2 and gender male" can be replaced by the information representing the population category "low body fat percentage, high BMI, young and male".

[0163] As shown in Figure 4, when the acquired user information is "body fat percentage a, BMI c, age e and gender male" and a is between a1 and b1, c is between c1 and d1, and e is between e1 and f1, then the first mapping relationship can be determined based on the user information as the weight loss fat percentage model located above the two weight loss fat percentage models shown in Figure 4.

[0164] In this embodiment, optionally, the target weight loss rate ratio may be a weight loss rate ratio range, which is also referred to as a weight loss rate ratio interval.

[0165] In this scenario, the calorie gap corresponding to each of the two endpoint values ​​in the weight loss rate ratio range can be obtained according to the aforementioned method. The calorie gap corresponding to the target weight loss rate is a range with the two calorie gaps corresponding to the two endpoint values ​​as the upper and lower limits of the interval. The larger of the two calorie gaps is the upper limit of the interval, and the smaller is the lower limit of the interval.

[0166] In this embodiment, after obtaining the calorie gap of the user within the second unit time, the calorie gap can be output. For example, the calorie gap can be output through a user interface.

[0167] Optionally, when the calorie gap is output through the user interface, all or part of the information for obtaining the calorie gap may also be output.

[0168] In this embodiment, optionally, the following step may be further included: determining the diet plan and exercise plan of the user in the second unit time according to the calorie gap and the basal metabolic calories of the user in the second unit time.

[0169] As an example, the basal metabolic heat of the user in the second unit time period may be directly input by the user, or may be calculated based on other information of the user.

[0170] As an example, the user's diet plan for the second unit time may include the following: the total calories that can be consumed in the second unit time is recorded as the first calories; the total calories that should be consumed in the second unit time is recorded as the second calories; wherein, the difference between the first calories and the second calories is equal to the calorie gap.

[0171] It can be understood that if the calorie gap is a range, the first calorie and the second calorie in the diet plan can also be a range respectively.

[0172] As an example, the user's diet plan within the second unit time may also include the following: the number of meals per day and the calorie intake per meal. It is understood that if the calorie gap is a range, the calorie intake per meal may also be a range.

[0173] For example, an exercise plan may include exercise types, the exercise events included in each exercise type, and the duration of each exercise event. The duration information can be an absolute duration, such as one hour, or a relative duration, such as the ratio of the duration of exercise events in different exercise types.

[0174] Figure 5 is an example diagram of a user interface according to an embodiment of the present application. As shown to the left of the dashed line in Figure 5, the user information input user interface can output multiple height values ​​for the user to select, can output multiple weight values ​​for the user to select, can provide multiple weight loss rates for the user to select, can provide multiple weight loss rate percentages for the user to select, can provide multiple weight loss modes for the user to select, and can provide multiple target weights for the user to select.

[0175] As shown in the content to the right of the dotted line in Figure 5, the calorie gap user interface can include the following three parts: weight loss goal, diet plan and exercise plan.

[0176] The weight loss goal section can include the following: daily calorie deficit, weekly weight loss rate, weight loss duration, and target weight.

[0177] The diet plan section may include the following: total daily calorie intake, calories intake for breakfast, calories intake for lunch, calories intake for dinner, and calories intake for snacks.

[0178] The exercise plan section may include the following: the recommended calorie burn for the recommended activity and the recommended exercise type based on the recommended calorie burn. For example, if the recommended activity burns 550 kcal, the recommended exercise type may be: 70% aerobic exercise, such as walking, running, cycling, etc., and / or 30% strength training, such as core strengthening and upper limb strength training.

[0179] In other embodiments of the present application, if the method shown in Figure 3 is executed by a cloud server, it can be a terminal device, such as a mobile phone, that obtains relevant user information and sends the relevant user information to the cloud server. After the cloud server executes the method in the embodiment shown in Figure 3 to obtain the calorie gap or even other information that can be output to the user, the cloud server sends the calorie gap and related information to the terminal device, and the terminal device then outputs the calorie gap and related information through the user interface.

[0180] Optionally, the terminal device can also send the calorie gap and related information to the wearable device, and display the calorie gap and related information to the user through the wearable device, thereby further improving the convenience of the user in browsing the calorie gap and related information.

[0181] Figure 6 is a schematic flow chart of a health plan formulation method according to another embodiment of the present application. As shown in Figure 6 , the method may include S610 and S620.

[0182] S610, obtaining a first basal metabolic condition, a first fat reduction time, and a first exercise capacity, wherein the first basal metabolic condition is the basal metabolic condition of the user for whom a health plan is to be formulated, the first exercise capacity is the exercise capacity of the user for whom a health plan is to be formulated, and the first fat reduction time is the fat reduction time expected by the user for whom a health plan is to be formulated.

[0183] As an example, the basal metabolic status is used to indicate the speed of the basal metabolic rate, and different basal metabolic statuses indicate different degrees of basal metabolic rate.

[0184] As an example, the basal metabolic conditions may include: high metabolism, standard metabolism and low metabolism, and the basal metabolic rates corresponding to these three basal metabolic conditions decrease in sequence.

[0185] As an example, obtaining the first basal metabolic condition may include: obtaining the first basal metabolic condition input by a user, for example, obtaining the first basal metabolic condition input by the user through a control in a user interface.

[0186] As an example, the user interface may include a text input control, and the user may input the first basal metabolic condition in the text input control.

[0187] As an example, the user interface may include a selection control that provides the user with multiple basal metabolic status options. The user may select a basal metabolic status through the selection control, wherein the basal metabolic status selected by the user may be used as the first basal metabolic status input by the user.

[0188] As an example, the user interface may display the basal metabolic value range corresponding to each basal metabolic condition, so that the user can determine which basal metabolic value range the user is in based on his or her basal metabolic value, thereby accurately selecting his or her basal metabolic condition.

[0189] As an example, obtaining the first basal metabolic profile may include obtaining a basal metabolic value input by a user, and determining the user's first basal metabolic profile based on the basal metabolic value. For example, determining to which basal metabolic value range the basal metabolic value input by the user belongs, and determining the basal metabolic profile corresponding to the basal metabolic value range as the first basal metabolic profile. For ease of description, the basal metabolic value input by the user is referred to as the first basal metabolic value.

[0190] As an example, obtaining the first basal metabolic value input by the user may include: obtaining the first basal metabolic value input by the user through a control in a user interface.

[0191] As an example, the user interface may include a text input control, and the user may enter the first basal metabolic value in the text input control.

[0192] As an example, the user interface may include a selection control that provides the user with multiple basal metabolic value options. The user may select a basal metabolic value through the selection control, wherein the basal metabolic value selected by the user may be used as the first basal metabolic value input by the user.

[0193] As an example, obtaining the first basal metabolic condition input by the user may include: obtaining at least one piece of information among the user's BMI, gender, and age and body fat percentage, and determining the first basal metabolic condition based on the at least one piece of information and the body fat percentage.

[0194] The method for obtaining the user's BMI, gender and age can refer to the relevant content in the embodiment shown in Figure 3, which will not be repeated here.

[0195] As an example, determining the first basal metabolic condition based on at least one of BMI, gender, and age and body fat percentage may include: obtaining at least one of the user's BMI, gender, and age and the user's body fat percentage; determining the normal body fat percentage range associated with the at least one of the information based on the correspondence between the at least one of the information and the normal body fat percentage; judging the relationship between the user's body fat percentage and the normal body fat percentage range; if it is higher than the normal body fat percentage range, the first basal metabolic condition may be considered as high metabolism; if it is within the normal body fat percentage range, the first basal metabolic condition may be considered as standard basal metabolism; if it is lower than the normal body fat percentage range, the first basal metabolic condition may be considered as low metabolism.

[0196] Figure 7 is a flow chart of determining a first basal metabolic condition based on at least one of BMI, gender, and age and body fat percentage. The method shown in Figure 7 includes S701 to S707.

[0197] S701, obtaining the user's BMI, gender, age, and body fat percentage.

[0198] S702: Determine a normal body fat percentage range associated with the at least one piece of information based on the corresponding relationship between the user's BMI, gender, and age and the normal body fat percentage.

[0199] S703: Determine whether the user's body fat percentage is greater than the maximum value of the normal body fat percentage range. If so, proceed to S704; otherwise, proceed to S705.

[0200] S704: Determine that the first basal metabolic condition is high metabolism.

[0201] S705: Determine whether the user's body fat percentage is lower than the minimum value of the normal body fat percentage range. If so, execute S706; otherwise, execute S707.

[0202] S706: Determine that the first basal metabolic condition is low metabolism.

[0203] S707, determining the first basal metabolic condition as standard metabolism.

[0204] Alternatively, conversely, the user's body fat percentage is first determined to be lower than the minimum value of the normal body fat percentage range. If so, the process proceeds to S706. Otherwise, the process proceeds to S705. Otherwise, the process proceeds to S707.

[0205] The following describes a method for obtaining the first exercise capacity and the first fat-reduction duration in S610.

[0206] As an example, the method of obtaining the first weight loss duration in this embodiment can refer to the relevant content of obtaining the weight loss duration in the embodiment shown in Figure 3, which will not be repeated here.

[0207] As an example, the level of a user's athletic ability can be characterized by a score. Therefore, obtaining the first athletic ability of the first user can also be understood as determining the user's athletic ability score. This athletic ability score can be referred to as the first athletic ability score.

[0208] As an example, obtaining the first athletic ability score of the user may include: obtaining the first athletic ability score input by the user.

[0209] As an example, obtaining the first athletic ability score input by the user may include: obtaining the first athletic ability score input by the user through a control in a user interface.

[0210] As an example, the user interface may include a text input control in which the user may enter the first athletic ability score.

[0211] As an example, the user interface may include a selection control that provides the user with multiple athletic ability score options, through which the user can select an athletic ability score, wherein the athletic ability score selected by the user can be used as the first athletic ability score input by the user.

[0212] As an example, obtaining the user's first athletic ability score may include: obtaining the user's athletic scores for sports of multiple sports types and / or the athletic scores for each of at least one body part, and determining the first athletic ability score based on these athletic scores.

[0213] As an example, the sports scores for sports items of multiple sports types may include: an aerobic sports capacity score and a strength sports capacity score.

[0214] For example, the user's upper limb motor ability score is w, and its weight is a; the lower limb motor ability score is x, and its weight is b; the core motor ability score is y, and its weight is c; the aerobic motor ability score is z, and its weight is d, then the first motor ability score can satisfy the following relationship: s=a*w+b*x+c*y+d*z, where s represents the first motor ability score, and a, b, c and d can be preset parameter values.

[0215] As an example, obtaining the athletic ability score for each sport type of sport may include: obtaining the athletic ability score for each sport type of sport input by the user.

[0216] The time slot method for obtaining the athletic ability score of each sport type input by the user can refer to the relevant content of obtaining the first athletic ability score in the aforementioned content, which will not be repeated here.

[0217] As an example, obtaining the athletic ability score for each type of sports event may include: obtaining at least one of the following information of the user: the number of times the sports event is performed within a certain period of time, obtaining the time required for the user to complete the sports event once, or obtaining the user's physical characteristic parameter values ​​within the period of time, such as heart rate, blood pressure, blood sample or maximum oxygen uptake; and calculating the athletic ability score based on the at least one information.

[0218] As an example, the number of times the exercise is performed within a certain period of time, the time required for the user to complete the exercise is obtained, or one or more of the user's physical characteristic parameter values ​​within the period of time are obtained. These can be values ​​directly entered by the user, such as values ​​entered by the user based on historical records; they can be values ​​obtained by the electronic device measuring the user in real time.

[0219] S620, determine a first target exercise plan based on the first basal metabolic condition, the first fat loss duration and the first exercise capacity, the first target exercise plan including multiple target stages, multiple target durations, multiple target exercise item sets and multiple exercise duration ratios, the multiple target durations corresponding one-to-one to the multiple target stages, each of the multiple target durations is the duration of the corresponding target stage included in the first fat loss duration, the multiple target exercise item sets corresponding one-to-one to the multiple target stages, each of the multiple target exercise item sets contains exercise items within the corresponding target stage, the multiple exercise duration ratios corresponding one-to-one to the multiple target exercise item sets, and each of the multiple exercise duration ratios is the exercise duration ratio between exercise items within the corresponding target exercise item set.

[0220] For example, the multiple target phases included in the first target exercise plan may include at least one of the following phases: a fat loss adaptation phase, a metabolism boost phase, a high-efficiency fat burning phase, and a results consolidation phase. It is understood that these phases may differ in at least one of the following: duration, the type of exercise within the phase, different exercise types within the same exercise type, different exercise durations within the same exercise type, or different exercise durations within the same exercise.

[0221] As an example, the fat loss adaptation period is to allow the body to gradually adapt to the rhythm of exercise for fat loss, with a lower intensity; the metabolism enhancement period is mainly strength training, mainly to improve metabolism. The weight may not change significantly, but the body will become firmer and the body shape will become thinner; the efficient fat burning period is mainly aerobic training and high-intensity interval training (HIIT) training. The frequency of training increases, the overall calorie consumption increases, and fat can be lost quickly; the result consolidation period is a balanced aerobic and strength training to maintain muscle mass and stabilize metabolism, while reducing body fat percentage and consolidating the results of the rapid fat loss period.

[0222] As an example, determining the first target exercise plan based on the first basal metabolic condition, the first fat loss duration and the first exercise capacity may include: determining multiple target stages, multiple target durations, multiple target exercise type sets and multiple exercise duration ratios based on the first basal metabolic condition and the first fat loss duration, the multiple target exercise type sets corresponding one-to-one to the multiple target stages, and each target exercise type set in the multiple target exercise type sets containing the exercise type of the corresponding target stage; determining the target exercise item set corresponding to the target stage based on the first exercise capacity and each target exercise type set.

[0223] As an example, multiple target stages, multiple target durations, multiple target exercise type sets, and multiple exercise duration ratios are determined based on the first basal metabolic condition and the first fat loss duration, including: determining multiple target stages and multiple target durations based on the first basal metabolic condition and the first fat loss duration; determining a target exercise type set for each target stage in the multiple target stages, and obtaining multiple target exercise type sets that correspond one-to-one to the multiple target stages; determining the exercise duration ratios of multiple exercise types in each target exercise type set in the multiple target exercise type sets, and obtaining multiple target duration ratios that correspond one-to-one to the multiple target exercise type sets.

[0224] As an example, the multiple target stages can be specifically divided according to a first fat loss duration and a first basal metabolic condition.

[0225] For example, if the user's first fat loss plan duration is X weeks and the first basal metabolic condition is low metabolism, then the first fat loss period can be divided into: fat loss adaptation period, week A; metabolism improvement period, week B; efficient fat burning period, week C; and result consolidation period, week D.

[0226] For example, if the user's first fat loss plan duration is Y weeks and the first basal metabolic state is high metabolism, then the first fat loss period can be divided into: fat loss adaptation period, week A; efficient fat burning period, week E; and result consolidation period, week F.

[0227] It can be understood that the multiple target stages in the first target exercise plan correspond to multiple target durations, wherein the sum of the multiple target durations is the first fat-reduction duration.

[0228] As an example, the exercise type corresponding to each target stage is determined based on the first exercise capacity and the first basal metabolic condition.

[0229] As an example, each of the multiple target stages corresponds to a corresponding set of target exercise items, as shown in Table 1, which are the target exercise item sets corresponding to the fat loss adaptation period, metabolism enhancement period, efficient fat burning period and result consolidation period, respectively.

[0230] Table 1

[0231] As an example, the exercise duration of each target exercise type in the target exercise event corresponding to each target stage in the multiple target stages can be determined according to the weekly training frequency.

[0232] It can be understood that each target exercise set includes multiple exercise types, such as aerobics, strength endurance, and HIIT. Each exercise type corresponds to a different exercise duration, which is determined by the weekly training frequency.

[0233] For example, if the user is in the metabolic enhancement period and the weekly training frequency is K, then in this stage, M aerobic training classes, N strength training classes, and P HIIT training classes are arranged.

[0234] As an example, determining a target sports item set corresponding to a target stage based on the first sports ability and each target sports type set may include: determining the first sports difficulty based on a mapping relationship between the first sports ability score and the sports difficulty, the first sports difficulty being the sports difficulty associated with the first sports ability score; determining a target sports item set corresponding to a target stage for each target sports type set based on each target sports type set and the first sports difficulty, the target sports item set corresponding to the target stage for each target sports type set including sports items of each sports type in each target sports type set and having a sports difficulty of the first sports difficulty.

[0235] For example, the first exercise difficulty level includes a strength class difficulty level and an aerobic class difficulty level. The strength class difficulty level and the aerobic class difficulty level can be determined by the user's strength score, aerobic score, gender, and weight. Tables 2 and 3 show the strength class difficulty levels corresponding to the strength score and aerobic score, respectively.

[0236] Table 2

[0237] Table 3

[0238] As an example, if the user's strength test score is a, and the course difficulty corresponding to this athletic ability score is Y1, then according to the aforementioned course type and course ratio, strength training with a difficulty of Y1 is randomly selected and arranged into the target exercise type. The same applies to aerobic training.

[0239] In this embodiment, it can be understood that if the electronic device is a terminal device such as a mobile phone, tablet or wearable device, the step of obtaining various information input by the user can be implemented by the electronic device itself, or can be received from other terminal devices that establish a communication connection with the electronic device.

[0240] In this embodiment, it can be understood that if the electronic device is a cloud server, the step of obtaining various information input by the user can be implemented by the terminal device and received from the terminal device.

[0241] In this embodiment, after the first target motion plan is obtained, the first target motion plan may be displayed to the user.

[0242] For example, if the electronic device is a mobile phone or a tablet computer, the first target exercise plan may be displayed to the user through the user interface of the electronic device.

[0243] Optionally, in a scenario where the electronic device presents the first target exercise plan to the user, the electronic device may also send the first target exercise plan to the wearable device, so that the first target exercise plan is presented to the user through the wearable device.

[0244] For another example, if the electronic device is a cloud server, the electronic device can send the first target exercise plan to various terminal devices such as mobile phones, tablet computers, wearable devices, etc., and display the first target exercise plan to the user through the user interface of the electronic device.

[0245] As an example, the method of this embodiment may also include: obtaining the completion degree of the first target motion plan and / or the user's feedback on the first target motion plan, and determining the second target motion plan based on the completion degree of the first target motion plan and / or the user's feedback on the first target motion plan.

[0246] In the steps of this embodiment, the second target exercise plan may be a plan adjusted after the first target exercise plan is completed, taking into account the training completion degree and / or the user's feedback on the first target exercise plan.

[0247] As an example, the degree of completion of the first target exercise program may be calculated based on actual exercise conditions and planned conditions after multiple target stage trainings are completed.

[0248] As an example, the user's feedback on the first target exercise program may be the user's subjective perception level after each training session.

[0249] As an example, the perception level can be divided into four levels: easy, just right, strenuous, and challenging.

[0250] As an example, feedback on the first target motion plan may be obtained on a user interface.

[0251] As an example, obtaining the completion degree of the first target exercise plan includes: obtaining the actual completion time of each exercise item in each target exercise item set in the multiple target exercise item sets; determining the planned duration of each exercise item in each target exercise item set based on the ratio of the multiple target durations to the multiple exercise durations; determining the completion degree of the same type of exercise items in each target exercise item set based on the actual completion time and the planned duration of the same type of exercise items in each target exercise item set; determining the exercise completion degree of the target stage corresponding to each target exercise item set based on the completion degree of the same type of exercise items in each target exercise item set.

[0252] As an example, the actual exercise situation can be determined by counting the actual number of completed sets and actual number of completed times of different types of exercise, the planned situation can be determined by the planned number of sets and planned number of times, and the completion degree of the first target exercise plan can be calculated by the weighted value of the completion degree of different types of exercise.

[0253] As an example, the value obtained by multiplying the ratio of the actual number of strength training sets to the planned number of sets by the ratio of the actual number of times to the planned number of times is the completion degree of strength training in the first target exercise plan; the value obtained by multiplying the ratio of the actual number of aerobic training sets to the planned number of sets by the ratio of the actual number of times to the planned number of times is the completion degree of aerobic training in the first target exercise plan; the value obtained by multiplying the ratio of the actual number of HIIT training sets to the planned number of sets by the ratio of the actual number of times to the planned number of times is the completion degree of HIIT training in the first target exercise plan.

[0254] It is understandable that in this embodiment, the following steps may be repeatedly performed: obtaining the degree of completion of the second target motion plan and / or the user's subjective feedback, and adjusting the second target motion plan based on this information to obtain a new second target motion plan.

[0255] FIG8 is a schematic diagram of the structure of an apparatus provided in an embodiment of the present application. As shown in FIG8 , the apparatus 800 may include a processing module 801 and a communication module 802 .

[0256] As a first example, the apparatus 800 can be used to implement the method implemented in any one of the embodiments shown in Figures 3 to 7. For example, the processing module 801 is used to implement the relevant steps involving processing actions in the method described in any one of the embodiments shown in Figures 3 to 7, and the communication module 802 is used to implement the relevant steps involving information acquisition actions in the method described in any one of the embodiments shown in Figures 3 to 7.

[0257] Figure 9 is a schematic diagram of the device structure provided by another embodiment of the present application. As shown in Figure 9, the device 900 includes a processor 901 and a communication circuit 902. The processor 901 and the communication circuit 902 are coupled to each other. It is understood that the communication circuit 902 can be a transceiver or an input / output interface. Optionally, the device 900 may also include a memory 903 for storing instructions executed by the processor 901 or storing input data required by the processor 901 to run the instructions or storing data generated after the processor 901 runs the instructions. It is understood that the memory 903 can be located outside the processor 901, or inside the processor 901.

[0258] As an example, the processor 901 is used to implement the functions of the above-mentioned processing module 801, and the communication circuit 902 is used to implement the functions of the above-mentioned communication module 802.

[0259] The device 900 may be an electronic device, or a device, module, circuit, chip, etc. configured and arranged in an electronic device, or a device that can be used in conjunction with an electronic device.

[0260] The present application provides a computer program product that, when executed on an electronic device, enables the electronic device to execute the technical solution in the above embodiment. The implementation principle and technical effects are similar to those of the above method-related embodiments and will not be described in detail here.

[0261] The embodiment of the present application provides a readable storage medium, which contains instructions. When the instructions are executed on an electronic device, the electronic device executes the technical solution of the above embodiment. The implementation principle and technical effect are similar and will not be repeated here.

[0262] The present application provides a chip for executing instructions. When the chip is running, the technical solution of the above embodiment is executed. The implementation principle and technical effect are similar and will not be described here.

[0263] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of this application.

[0264] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0265] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0266] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0267] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0268] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0269] The above description is merely a specific implementation of the embodiments of the present application, but the scope of protection of the embodiments of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the embodiments of the present application should be included in the scope of protection of the embodiments of the present application. Therefore, the scope of protection of the embodiments of the present application should be based on the scope of protection of the claims.

Claims

1. A method for formulating a health plan, characterized in that: The method is applied to an electronic device, comprising: Obtaining a target weight loss rate ratio of a user and a current weight of the user, wherein the target weight loss rate ratio is a weight loss rate ratio expected by the user, and the weight loss rate ratio is a ratio of the weight lost within a first unit time period to the current weight; Determine the weight loss fat content corresponding to the target weight loss rate ratio, wherein the weight loss fat content is the ratio of fat in the reduced body weight to the reduced body weight; The calorie deficit of the user in the second unit time period is determined based on the weight loss fat content corresponding to the target weight loss rate ratio, the target weight loss rate ratio, the user's current weight, fat calories per unit weight, and lean body calories per unit weight.

2. The method according to claim 1, characterized in that The obtaining of the user's target weight loss rate ratio includes: Obtaining a target weight loss rate of the user and a current weight of the user, wherein the target weight loss rate is a weight loss rate expected by the user, and the weight loss rate is a weight loss within the first unit time period; The target weight loss rate ratio is determined according to the target weight loss rate of the user and the current weight of the user.

3. The method according to claim 1 or 2, characterized in that: Determining the weight loss fat content corresponding to the target weight loss rate ratio includes: Determining the population category to which the user belongs; Determining a first mapping relationship from a plurality of mapping relationships according to the population category to which the user belongs, the first mapping relationship being a mapping relationship corresponding to the population category to which the user belongs among the plurality of mapping relationships, the plurality of mapping relationships corresponding one-to-one to the plurality of population categories, and each mapping relationship among the plurality of mapping relationships being used to indicate a mapping relationship between a fat percentage in a weight loss of a user of a corresponding population category and a weight loss percentage of the user of the corresponding population category within the first unit time period; The weight loss fat content corresponding to the target weight loss rate ratio is determined according to the first mapping relationship.

4. The method according to claim 3, characterized in that The determining the group category to which the user belongs includes: Acquire user information, wherein the user information includes at least one of the following information of the user: maximum oxygen uptake, body fat percentage, age, gender, current weight, and body mass index; The group category to which the user belongs is determined according to the user information.

5. The method according to any one of claims 1 to 4, characterized in that The fat content corresponding to the target weight loss rate ratio, the target weight loss rate ratio, the user's current weight, fat calories per unit weight, lean body calories per unit weight and the user's calorie deficit in the second unit time satisfy the following relationship: g = (w*v*p*k1+w*v*(1-p)*k2) / t Among them, g represents the calorie gap, w represents the current weight of the user, v represents the target weight loss rate ratio, p represents the weight loss fat content corresponding to the target weight loss rate ratio, k1 represents the fat calories per unit weight, k2 represents the lean body calories per unit weight, and t represents the ratio of the first unit time to the second unit time.

6. The method according to any one of claims 1 to 5, characterized in that The method further comprises: A diet plan and an exercise plan for the user in the second unit time are determined according to the calorie deficit and the basal metabolic calories of the user in the second unit time.

7. A method for formulating a health plan, characterized in that: Applied to an electronic device or a cloud server, the method comprises: Acquire a first basal metabolic condition, a first fat reduction duration, and a first exercise capacity, wherein the first basal metabolic condition is the basal metabolic condition of the user for whom a health plan is to be formulated, the first exercise capacity is the exercise capacity of the user for whom a health plan is to be formulated, and the first fat reduction duration is the fat reduction duration expected by the user for whom a health plan is to be formulated; A first target exercise plan is determined according to the first basal metabolic condition, the first fat loss duration and the first exercise capacity, wherein the first target exercise plan includes multiple target stages, multiple target durations, multiple target exercise item sets and multiple exercise duration ratios, the multiple target durations correspond one-to-one to the multiple target stages, each of the multiple target durations is the duration of the corresponding target stage included in the first fat loss duration, the multiple target exercise item sets correspond one-to-one to the multiple target stages, each of the multiple target exercise item sets includes exercise items within the corresponding target stage, the multiple exercise duration ratios correspond one-to-one to the multiple target exercise item sets, and each of the multiple exercise duration ratios is the exercise duration ratio between exercise items within the corresponding target exercise item set.

8. The method according to claim 7, characterized in that The determining of the first target exercise program according to the first basal metabolic condition, the first fat reduction duration, and the first exercise capacity includes: Determine the multiple target stages, the multiple target durations, the multiple target exercise type sets, and the multiple exercise duration ratios according to the first basal metabolic condition and the first fat loss duration, wherein the multiple target exercise type sets correspond to the multiple target stages one by one, and each target exercise type set in the multiple target exercise type sets includes an exercise type corresponding to the target stage; A target sports item set corresponding to the target stage is determined according to the first sports ability and each target sports type set.

9. The method according to claim 8, characterized in that The determining, according to the first basal metabolic condition and the first fat loss duration, the multiple target stages, the multiple target durations, the multiple target exercise type sets, and the multiple exercise duration ratios includes: Determining the multiple target stages and the multiple target durations according to the first basal metabolic condition and the first fat loss duration; Determine a target motion type set for each target stage in the multiple target stages to obtain multiple target motion type sets corresponding to the multiple target stages one by one; The motion duration ratios of the multiple motion types in each target motion type set in the multiple target motion type sets are determined to obtain a plurality of target duration ratios of the multiple target motion type sets in one-to-one correspondence.

10. The method according to claim 8 or 9, characterized in that: The step of determining a target sports item set corresponding to a target stage according to the first sports ability and each target sports type set includes: Obtaining a first score according to the first athletic ability, where the first score is a score of the first athletic ability; Determine a first exercise difficulty according to a mapping relationship between the exercise ability score and the exercise difficulty, wherein the first exercise difficulty is the exercise difficulty associated with the first score; Determine a target sports item set corresponding to a target stage for each target sports type set according to each target sports type set and the first sports difficulty level, wherein the target sports item set corresponding to the target stage for each target sports type set includes sports items of each sports type in each target sports type set and whose sports difficulty level is the first sports difficulty level.

11. The method according to any one of claims 9 to 10, characterized in that The method further comprises: The second target exercise plan is determined by obtaining the degree of completion of the first target exercise plan and / or the user's feedback on the first target exercise plan.

12. The method according to claim 11, characterized in that The obtaining the degree of completion of the first target motion scheme includes: Obtaining the actual completion time of each sports item in each target sports item set in the plurality of target sports item sets; Determine the planned duration of each sport item in each target sport item set according to the ratios of the multiple target durations to the multiple sport durations; Determine the degree of completion of the same type of sports items in each target sports item set according to the actual completion time and the planned time of the same type of sports items in each target sports item set; The exercise completion degree of the target stage corresponding to each target sports item set is determined according to the completion degree of the sports items of the same type in each target sports item set.

13. An electronic device, characterized in that: include: one or more processors; one or more memories; The one or more memories store one or more computer programs, and the one or more computer programs include instructions, which, when executed by the one or more processors, enable the electronic device to perform the method as claimed in any one of claims 1 to 12.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium comprises a computer program or instructions, and when the computer program or instructions are run on a computer, the method according to any one of claims 1 to 12 is executed.

15. A computer program product, characterized in that The computer program product comprises a computer program or instructions, and when the computer program or instructions are run on a computer, the method as described in any one of 1 to 12 is executed.

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