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

Abstract

The electronic device obtains the user's target weight loss percentage and the user's current weight, the target weight loss percentage is the weight loss percentage expected by the user, the weight loss percentage is the percentage of weight loss in a first unit time period relative to the current weight, the amount of fat lost corresponding to the target weight loss percentage is determined, the amount of fat lost is the percentage of the weight lost relative to the weight lost, and the calorie deficit of the user in a second unit time period is determined based on the amount of fat lost corresponding to the target weight loss percentage, the target weight loss percentage, the user's current weight, the amount of fat calories per unit body weight, and the amount of lean body calories per unit body weight.

Description

Technical Field

[0001] This application claims the priority of Chinese Patent Application No. 202311168990.5 entitled "Health plan formulation method, health plan formulation apparatus, and electronic device", filed with the China National Intellectual Property Administration on September 11, 2023, the entire contents of which are incorporated herein by reference in their entirety.

[0002] Embodiments of this application relate to the field of electronic devices, and more specifically, to a health plan formulation method, a health plan formulation apparatus, and an electronic device.

Background Art

[0003] Electronic devices may obtain relevant information about a user to improve the user's physical fitness, and formulate a health plan for the user based on the relevant information for the user's reference.

[0004] However, health plans formulated by electronic devices currently lack sufficient accuracy, which affects the speed at which the user's physical fitness is improved.

Summary of the Invention

[0005] Embodiments of this application provide a health plan formulation method, a health plan formulation apparatus, and an electronic device, so as to provide an accurate health plan for a user.

Means for Solving the Problems

[0006] According to the first embodiment, a method for formulating a health plan is provided. The method is applied to an electronic device and includes the steps of: obtaining the user's target weight loss rate and the user's current weight, wherein the target weight loss rate is the weight loss rate expected by the user, and the weight loss rate is the percentage of weight loss in a first unit time period relative to the current weight; determining the amount of fat lost corresponding to the target weight loss rate, wherein the amount of fat lost is the percentage of fat in the weight lost during the weight loss; and determining the user's calorie deficit in a second unit time period based on the amount of fat lost corresponding to the target weight loss rate, the target weight loss rate, the user's current weight, fat calories per unit body weight, and lean body calories per unit body weight.

[0007] In this method, the corresponding amount of fat lost is determined based on the user's target weight loss percentage, and the calorie deficit is determined based on the amount of fat lost. Therefore, a more accurate calorie deficit can be obtained. This can help improve the accuracy of the healthy fat loss plan formulated by the user based on the calorie deficit.

[0008] In some possible embodiments, the step of obtaining the user's target weight loss rate includes the steps of obtaining the user's target weight loss rate and the user's current weight, wherein the target weight loss rate is the weight loss rate expected by the user and the weight loss rate is the weight loss in a first unit of time; and the step of determining the target weight loss rate rate based on the user's target weight loss rate and the user's current weight.

[0009] In some possible embodiments, the step of determining the amount of fat lost corresponding to the target weight loss rate includes the steps of determining the group category to which the user belongs, determining a first mapping relationship from a plurality of mapping relationships based on the group category to which the user belongs, wherein the first mapping relationship is a mapping relationship among the plurality of mapping relationships that corresponds to the group category to which the user belongs, the plurality of mapping relationships have a one-to-one correspondence with the plurality of group categories, and each mapping relationship in the plurality of mapping relationships shows a mapping relationship between the fat percentage in the weight loss of users in the corresponding group category and the weight loss rate of users in the corresponding group category over a first unit time length, and determining the amount of fat lost corresponding to the target weight loss rate based on the first mapping relationship.

[0010] In some possible embodiments, the step of determining the group category to which a user belongs includes the steps of obtaining user information, wherein the user information includes at least one of the following information about the user: maximum oxygen uptake, body fat percentage, age, sex, current weight, and body mass index; and determining the group category to which the user belongs based on the user information.

[0011] In several possible embodiments, the fat content corresponding to the target weight loss percentage, the target weight loss percentage, the user's current weight, the calories from fat per unit body weight, the calories from lean body weight per unit body weight, and the user's calorie deficit at a second unit time length satisfy the following relationship: g = (w*v*p*k1 + w*v*(1-p)*k2) / t.

[0012] g represents the calorie deficit, w represents the user's current weight, v represents the target weight loss percentage, p represents the amount of fat lost corresponding to the target weight loss percentage, k1 represents the fat calories per unit body weight, k2 represents the lean body calories per unit body weight, and t represents the ratio of the first unit time length to the second unit time length.

[0013] In some possible embodiments, the method includes the step of determining the user's meal plan and exercise plan for a second unit of time based on the calorie deficit and the user's basal metabolic calorie intake during the second unit of time.

[0014] According to the second embodiment, an electronic device or cloud server is provided. The method is a step of acquiring a first basal metabolic state, a first fat loss time, and a first exercise capacity, wherein the first basal metabolic state is the basal metabolic state 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 loss time is the fat loss time expected by the user for whom a health plan is to be formulated; and a step of determining a first target exercise plan based on the first basal metabolic state, the first fat loss time, and the first exercise capacity, wherein the first target exercise plan comprises a plurality of target stages, a plurality of target time durations, a plurality of target exercise items. The system includes a set, and a step which includes multiple exercise time ratios, where multiple target time lengths have a one-to-one correspondence with multiple target stages, where each target time length in the multiple target time lengths is the time length included in the first fat reduction time length in the corresponding target stage, where multiple target exercise item sets have a one-to-one correspondence with multiple target stages, where each target exercise item set in the multiple target exercise item sets includes the exercise item in the corresponding target stage, where multiple exercise time ratios have a one-to-one correspondence with multiple target exercise item sets, where each exercise time ratio in the multiple exercise time ratios is the exercise time ratio between exercise items in the corresponding target exercise item set.

[0015] In this method, an individualized fat-loss exercise plan is specified based on basic information, exercise capacity, and the user's fat-loss goals, and this individualized fat-loss exercise plan is flexible and accurate to the weight-loss training requirements in various scenarios.

[0016] In several possible embodiments, the step of determining a first target exercise plan based on a first basal metabolic state, a first fat loss duration, and a first exercise capacity includes the steps of determining a plurality of target stages, a plurality of target durations, a plurality of target exercise type sets, and a plurality of exercise duration ratios based on the first basal metabolic state and the first fat loss duration, wherein the plurality of target exercise type sets have a one-to-one correspondence with the plurality of target stages, and each target exercise type set in the plurality of target exercise type sets includes the exercise type in the corresponding target stage; and the step of determining a set of target exercise items for the corresponding target stage based on the first exercise capacity and each target exercise type set.

[0017] In some possible embodiments, the step of determining a plurality of target stages, a plurality of target durations, a plurality of target exercise type sets, and a plurality of exercise duration ratios based on a first basal metabolic state and a first fat loss duration includes: determining a plurality of target stages and a plurality of target durations based on a first basal metabolic state and a first fat loss duration; determining a target exercise type set for each of the plurality of target stages and obtaining a plurality of target exercise type sets that correspond one-to-one with the plurality of target stages; and determining the exercise duration ratios of a plurality of exercise types in each of the plurality of target exercise type sets in order to obtain a plurality of target duration ratios that correspond one-to-one with the plurality of target exercise type sets.

[0018] In several possible embodiments, the step of determining a set of target motor items for a corresponding target stage based on a first motor ability and each set of target motor types includes: a step of obtaining a first score based on the first motor ability, wherein the first score is the score of the first motor ability; a step of determining a first motor difficulty based on a mapping relationship between the motor ability score and the motor difficulty, wherein the first motor difficulty is the motor difficulty associated with the first score; and a step of determining a set of target motor items for a target stage corresponding to each set of target motor types, wherein the set of target motor items for a target stage corresponding to each set of target motor types includes motor items that constitute each motor type in each set of target motor types, and whose motor difficulty is the first motor difficulty.

[0019] In some possible embodiments, the method includes the steps of obtaining the degree of completion of a first target exercise plan and / or user feedback on the first target exercise plan, and determining a second target exercise plan.

[0020] In some possible embodiments, the step of obtaining the degree of completion of a first target exercise plan includes: obtaining the actual completion time of each exercise item in each of a set of multiple target exercise items; determining the planned time of each exercise item in each set of target exercise items based on a set of target time lengths and a set of exercise time ratios; determining the degree of completion of exercise items of the same type in each set of target exercise items based on the actual completion time and planned time of exercise items of the same type in each set of target exercise items; and determining the degree of exercise completion for the target stage corresponding to each set of target exercise items based on the degree of completion of exercise items of the same type in each set of target exercise items.

[0021] According to a third aspect, this application provides an apparatus. The apparatus may include modules that correspond one-to-one with the methods / operations / steps / work described in the first or second aspect. The modules may be implemented by hardware circuits, software, or a combination of hardware circuits and software.

[0022] In the design, the apparatus may include a processing module and a communication module. The communication module is configured to perform information acquisition operations in the manner described in the second embodiment, and the processing module is configured to perform processing operations in the manner described in the first or second embodiment.

[0023] In the design, the device may be an electronic device, or a device, module, circuit, chip, etc., that is configured in an electronic device, or a device that can be used together with an electronic device.

[0024] According to a fourth aspect, an apparatus is provided. The apparatus includes a processor and a storage medium. The storage medium stores instructions. When an instruction is executed by the processor, a method according to the first aspect or any one of the possible embodiments of the first aspect is performed.

[0025] According to a fifth aspect, an apparatus is provided. The apparatus includes a processor. The processor is configured to process data and / or information and to carry out a method relating to the first aspect or any one of possible embodiments of the first aspect, or to carry out a method relating to the second aspect or any one of possible embodiments of the second aspect.

[0026] In the design, the device may be an electronic device, or a device, module, circuit, chip, etc., that is configured in an electronic device, or a device that can be used together with an electronic device.

[0027] Optionally, the apparatus may further comprise a memory. The memory is configured to store a program or instructions. The processor is configured to execute the program or the instructions to implement the method according to any one of the first aspect or the possible implementations of the first aspect, or to implement the method according to any one of the second aspect or the possible implementations of the second aspect.

[0028] Optionally, the apparatus may further comprise a transceiver circuit or an input / output interface.

[0029] According to a sixth aspect, a chip is provided. The chip comprises a processor. The processor is configured to execute a program or instructions to implement the method according to any one of the first aspect or the possible implementations of the first aspect, or to implement the method according to any one of the second aspect or the possible implementations of the second aspect.

[0030] Optionally, the chip may further comprise a memory, and the memory is configured to store a program or instructions. Optionally, the chip may further comprise a transceiver circuit or an input / output interface.

[0031] According to a seventh aspect, a computer-readable storage medium is provided. The computer-readable storage medium comprises instructions. When the instructions are executed by a processor, the method according to any one of the first aspect or the possible implementations of the first aspect is implemented, or the method according to any one of the second aspect or the possible implementations of the second aspect is implemented.

[0032] According to an eighth aspect, a computer program product is provided. The computer program product comprises computer program code or instructions. When the computer program code or the instructions are executed, the method of the first aspect or any possible implementation of the first aspect is implemented, or the method of the second aspect or any possible implementation of the second aspect is implemented. [Brief Description of the Drawings]

[0033] [Figure 1] This is a diagram of the structure of an electronic device. [Figure 2] This is a block diagram of the software structure of an electronic device according to one embodiment of this application. [Figure 3] This is a schematic flowchart of a health plan formulation method according to one embodiment of this application. [Figure 4] This figure shows how to determine a fat percentage model based on the group category to which the user belongs, according to one embodiment of this application. [Figure 5] This is an illustrative diagram of a user interface according to one embodiment of this application. [Figure 6] This is a schematic flowchart of a health plan formulation method according to another embodiment of this application. [Figure 7] This is an illustrative diagram illustrating the determination of a user's metabolic state according to one embodiment of this application. [Figure 8] This is a diagram showing the structure of an apparatus according to one embodiment of this application. [Figure 9] This is a diagram showing the structure of an apparatus according to another embodiment of this application. [Modes for carrying out the invention]

[0034] The following describes the technical solutions of the embodiments in this application with reference to the attached drawings.

[0035] The terms used in the following embodiments are intended to describe specific embodiments only and are not intended to limit this application. The singular terms “one,” “a,” “the foregoing,” “this,” and “the one” as used herein and in the claims appended to this application are intended to also include expressions such as “one or more,” unless explicitly specified in the context. In the following embodiments of this application, it should be further understood that “at least one” and “one or more” mean one, two, or more. The terms “and / or” are used to describe a relational relationship between related subjects and indicate that three relationships may exist. For example, A and / or B may represent the cases of: A only; A and B both; and B only, where A and B may be singular or plural. The letter “ / ” generally indicates an “or” relationship between related subjects.

[0036] References to “one embodiment,” “several embodiments,” etc., described in this specification mean that certain features, structures, or characteristics described by reference to an embodiment are included in one or more embodiments of this application. Accordingly, phrases such as “in one embodiment,” “in several embodiments,” “in several other embodiments,” and “in other embodiments,” appearing in different parts of this specification, do not necessarily mean that they refer to the same embodiment. Instead, these phrases mean “one or more embodiments, but not all,” unless otherwise specifically emphasized. The terms “include,” “contain,” “have,” and variations thereof all mean “include, but not limited to,” unless otherwise specifically emphasized.

[0037] The electronic device in the embodiments of this application may be a mobile phone, a tablet computer, a wearable electronic device with wireless communication capabilities (e.g., a smartwatch), a laptop computer, etc. It should be further understood that in some embodiments, the electronic device may not be a portable electronic device as described above, but may be a desktop computer.

[0038] For example, Figure 1 shows the configuration of an electronic device 100. The electronic device 100 may include a processor 110, an external memory interface 120, internal memory 121, a universal serial bus (USB) interface 130, a charge 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, a headset jack 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display 194, a subscriber identification module (SIM) card interface 195, and the like. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, a barometric pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a light proximity sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, and the like.

[0039] It can be understood that the structures shown in the embodiments of this application do not constitute any particular limitation on the electronic device 100. In some other embodiments of this application, the electronic device 100 may include more or fewer components than those shown in the figures, or some components may be combined, or some components may be separated, or different component arrangements may be used. The components shown in the figures may be implemented by hardware, software, or a combination of software and hardware.

[0040] 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, memory, a video codec, a digital signal processor (DSP), a baseband processor, a neural network processing unit (NPU), and the like. Different processing units may be independent components or may be integrated into one or more processors.

[0041] The controller may be the neural center and command center of the electronic device 100. The controller can generate operation control signals based on instruction operation codes and time-series signals to complete the control of instruction reading and instruction execution.

[0042] Memory may be further located within the processor 110 and configured to store instructions and data. In some embodiments, the memory within the processor 110 is cache memory. The memory may store instructions or data that were most recently used or periodically used by the processor 110. The processor 110 may directly retrieve the instructions or data from memory when it needs to use them again. This avoids repeated access, reduces latency in the processor 110, and improves system efficiency.

[0043] In some embodiments, the processor 110 may include one or more interfaces. These 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, a universal serial bus (USB) interface, and the like.

[0044] The wireless communication function of the electronic device 100 can be implemented via antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor, baseband processor, etc.

[0045] Antennas 1 and 2 are configured to transmit and receive electromagnetic wave signals. Each antenna of the electronic device 100 may be configured to cover one or more communication frequency bands. Different antennas may be reused to improve antenna utilization. For example, antenna 1 may be reused as a diversity antenna in a wireless local area network. In some other embodiments, the antennas may be used in combination with tuning switches.

[0046] The mobile communication module 150 is applied to the electronic device 100 and can provide wireless communication solutions including 2G / 3G / 4G / 5G, etc. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), etc. The mobile communication module 150 may receive electromagnetic waves via antenna 1, process the received electromagnetic waves such as filtering and amplification, and transmit the electromagnetic waves to the modem processor for demodulation. The mobile communication module 150 may further amplify the signal modulated by the modem processor and convert the signal into electromagnetic waves for radiation via antenna 1. In some embodiments, at least some of the functional modules in the mobile communication module 150 may be located in the processor 110. In some embodiments, at least some of the functional modules in the mobile communication module 150 may be located in the same device as at least some of the modules in the processor 110.

[0047] The modem processor may include a modulator and a demodulator. The modulator is configured to modulate a low-frequency baseband signal to be transmitted into a medium-to-high frequency signal. The demodulator is configured to demodulate the received electromagnetic signal into a low-frequency baseband signal. The demodulator then transmits the low-frequency baseband signal obtained through demodulation to a baseband processor for processing. The low-frequency baseband signal is processed by the baseband processor and then transmitted to an application processor. The application processor outputs an acoustic signal through an audio device (not limited to speaker 170A, receiver 170B, etc.) or displays an image or video through a display 194. In some embodiments, the modem processor may be a separate component. In some other embodiments, the modem processor may be independent of the processor 110 and be located in the same device as the mobile communication module 150 or another functional module.

[0048] The wireless communication module 160 is applied to the electronic device 100 and can provide wireless communication solutions including wireless local area networks (WLAN) (e.g., wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite systems (GNSS), frequency modulation (FM), near-field communication (NFC) technology, and infrared (IR) technology. The wireless communication module 160 may be one or more components integrating at least one communication processor module. The wireless communication module 160 receives electromagnetic waves with the antenna 2, performs frequency modulation and filtering on the electromagnetic wave signal, and sends the processed signal to the processor 110. The wireless communication module 160 may further receive a signal transmitted from the processor 110, perform frequency modulation and amplification on this signal, and convert this signal into an electromagnetic wave for radiation via the antenna 2.

[0049] In some embodiments, antenna 1 and mobile communication module 150 are coupled in the electronic device 100, and antenna 2 and wireless communication module 160 are coupled in the electronic device 100, so that the electronic device 100 can communicate with a network and other devices using wireless communication technology. Wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-SCDMA), long-term evolution (LTE), BT, GNSS, WLAN, NFC, FM, IR technology, etc. GNSS may include the Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), Beidou Navigation Satellite System (BDS), Quasi-Zenith Satellite System (QZSS), and / or Satellite-Based Augmentation Systems (SBAS).

[0050] The electronic device 100 may implement display functions via a GPU, a display 194, an application processor, and the like. The GPU is a microprocessor for image processing and is connected to the display 194 and the application processor. The GPU is configured to perform mathematical and geometric calculations and to render images. The processor 110 may include one or more GPUs that execute program instructions for generating or modifying display information.

[0051] The display 194 is configured to display images, videos, etc. The display 194 includes a display panel. The display panel may be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a mini-LED, a micro-LED, a micro-OLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the electronic device 100 may include one or N displays 194, where N is a positive integer greater than 1.

[0052] The electronic device 100 may implement the shooting function via a camera 193, ISP, video codec, GPU, display 194, application processor, etc.

[0053] The ISP is configured to process data fed back by the camera 193. For example, during shooting, the shutter is pressed and light is transmitted through the lens to the camera's photosensitive element. The light signal is converted into an electrical signal, and the camera's photosensitive element sends the electrical signal to the ISP for processing in order to convert the electrical signal into a visible image. The ISP may further perform algorithmic optimization for image noise, brightness, and skin tone. The ISP may further optimize parameters such as exposure and color temperature of the shooting scenario. In some embodiments, the ISP may be located within the camera 193.

[0054] The camera 193 is configured to capture still images or video. An optical image of the subject is generated through a lens and projected onto a photosensitive element. The photosensitive element may be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal and then transmits the electrical signal to an ISP to convert the electrical signal into a digital image signal. The ISP outputs the digital image signal to a DSP for processing. The DSP converts the digital image signal into an image signal in a standard format such as RGB or YUV. In some embodiments, the electronic device 100 may include one or N cameras 193, where N is a positive integer greater than 1.

[0055] A digital signal processor is configured to process digital signals and may process other digital signals in addition to digital image signals. For example, when electronic device 100 selects a frequency, the digital signal processor is configured to perform a Fourier transform on the frequency energy.

[0056] A video codec is configured to compress or decompress digital video. The electronic device 100 may support one or more video codecs. In this way, the electronic device 100 can play or record video in multiple coding formats, such as moving picture experts group (MPEG) 1, MPEG 2, MPEG 3, and MPEG 4.

[0057] An NPU (Neural Network Processing Unit) is a neural network (NN) computing processor that simulates biological neural network structures, such as the communication modes between neurons in the human brain, to rapidly process input information and further enable continuous self-learning. Intelligent cognition applications of electronic devices 100, such as image recognition, face recognition, speech recognition, and text comprehension, can be realized via an NPU.

[0058] The external memory interface 120 may be used to connect to an external storage card, such as a Micro SD card, in order to extend 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 are stored on the external storage card.

[0059] The internal memory 121 may be configured to store computer executable program code. Executable program code includes instructions. The processor 110 executes instructions stored in the internal memory 121 to perform various functional applications and data processing of the electronic device 100. The internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system, applications required by at least one function (e.g., audio playback function or image playback function), etc. The data storage area may store data created during use of the electronic device 100 (e.g., audio data or address book). In addition, the internal memory 121 may include high-speed random access memory and non-volatile memory, such as at least one magnetic disk storage device, flash memory, or universal flash storage (UFS).

[0060] The electronic device 100 can implement audio functions, such as music playback and recording, through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, a headset jack 170D, an application processor, and the like.

[0061] The audio module 170 is configured to convert digital audio information into an analog audio signal for output, and also to convert an analog audio input into a digital audio signal. The audio module 170 may be further configured to encode and decode audio signals. In some embodiments, the audio module 170 may be located within the processor 110, or some functional modules within the audio module 170 may be located within the processor 110.

[0062] Speaker 170A, also known as a "loudspeaker," is configured to convert audio electrical signals into acoustic signals. Electronic device 100 can be used to listen to music or answer phone calls in hands-free mode via speaker 170A.

[0063] The receiver 170B, also referred to as an "earphone," is configured to convert audio electrical signals into sound signals. When answering a phone call or receiving speech information via the electronic device 100, the receiver 170B can be brought close to a person's ear to hear the sound.

[0064] The microphone 170C, also referred to as "mike" or "mic," is configured to convert an acoustic signal into an electrical signal. When making a phone call or sending a voice message, the user may input an acoustic signal to the microphone 170C by making a sound near the microphone 170C through the user's mouth. At least one microphone 170C may be located within the electronic device 100. In some other embodiments, two microphones 170C may be located within the electronic device 100 to capture acoustic signals and implement noise reduction functions. In some other embodiments, three, four, or more microphones 170C may be located within the electronic device 100 to capture acoustic signals, perform noise reduction, identify sound sources, and thereby implement directional recording functions, etc.

[0065] The pressure sensor 180A is configured to sense a pressure signal and can convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A may be located on the display 194. There are several types of pressure sensors 180A, including resistive pressure sensors, inductive pressure sensors, and capacitive pressure sensors. A capacitive pressure sensor may include at least two parallel plates made of a conductive material. When force is applied to the pressure sensor 180A, the capacitance between the electrodes changes. The electronic device 100 determines the pressure intensity based on the change in capacitance. When a touch operation is performed on the display 194, the electronic device 100 detects the intensity of the touch operation via the pressure sensor 180A. The electronic device 100 can also calculate the touch position based on the detection signal from the pressure sensor 180A. In some embodiments, touch operations performed at the same touch position but with different touch operation intensities may correspond to different operation commands. For example, when a touch operation exceeding a first pressure threshold acts on the alarm clock app icon, the command to create the alarm clock is executed.

[0066] The fingerprint sensor 180H is configured to collect fingerprints. The electronic device 100 may use the characteristics of the collected fingerprints to perform fingerprint-based unlocking, application lock access, fingerprint-based photography, fingerprint-based phone answering, and so on. For example, when the mobile phone detects a user touch operation on the lock screen interface, the mobile phone may collect the user's fingerprint information via the fingerprint sensor 180H and compare the collected fingerprint information with fingerprint information pre-configured on the mobile phone. If the match is successful, the mobile phone may move from the lock screen interface to the unlocked screen interface.

[0067] The touch sensor 180K is also referred to as a touch panel. The touch sensor 180K may be located within the display 194, and the touch sensor 180K and the display 194 together form a touchscreen, also referred to as a “touchscreen”. The touch sensor 180K is configured to detect touch operations performed on or near the touch sensor. The touch sensor may transmit the detected touch operations to an application processor to determine the type of touch event. Visual output related to the touch operations may be provided via the display 194. In some other embodiments, the touch sensor 180K may also be located on the surface of the electronic device 100 at a location different from the location of the display 194.

[0068] Figure 2 is a block diagram of the software structure of an electronic device 100 according to one embodiment of this application. In a layered architecture, the software is divided into multiple layers, each with a distinct role and task. The layers communicate with each other through a software interface. In some embodiments, the software system of an electronic device is divided into four layers, from top to bottom: the application layer, the application framework layer, the runtime and system libraries, and the kernel layer. The application layer may include a series of application packages.

[0069] As shown in Figure 2, the application layer may include the camera, settings, skin modules, user interface (UI), and third-party applications. Third-party applications may include the gallery, calendar, phone, maps, navigation, WLAN, Bluetooth, music, video, messaging, etc.

[0070] The application framework layer provides an application programming interface (API) and a programming framework for applications within the application layer. The application framework layer may include some predefined functionalities.

[0071] As shown in Figure 2, the application framework layer may include a window manager, content provider, view system, phone manager, resource manager, notification manager, and so on.

[0072] The window manager is configured to manage window programs. It can retrieve the display size, determine if there is a status bar, perform screen lock, take screenshots, and so on. The content provider is configured to store and retrieve data and allow applications to access it. This data may include videos, images, audio, outgoing and incoming calls, browsing history and bookmarks, address books, and more.

[0073] The view system includes visual controls such as controls for displaying text or pictures, for example, controls for displaying instructional information prompting a virtual shutter button in this embodiment of the application. The view system may be configured to build an application. The display interface may include one or more views. For example, a display interface including an SMS message notification icon may include a text display view and an image display view.

[0074] The telephone manager is configured to provide management of the communication functions of the electronic device 100, such as call status (including answering, rejecting, etc.).

[0075] The resource manager provides applications with various resources, such as localized text, icons, images, layout files, and video files.

[0076] A notification manager can be configured to allow applications to display notification information in the status bar and to convey notification messages. A notification manager can automatically disappear after a short pause without requiring user interaction. For example, a notification manager can be configured to provide download completion notifications, message notifications, etc. Alternatively, a notification manager may appear in the system's top status bar in the form of graphs or scrollbar text, such as notifications from applications running in the background, or it may appear on the screen in the form of dialog windows. For example, text information may be displayed in the status bar, an announcement may be made, an electronic device may vibrate, or an indicator light may flash.

[0077] The runtime includes core libraries and virtual machines. The runtime is responsible for scheduling and managing the software system.

[0078] The core library consists of two parts: the functions that need to be called by the programming language, and the system core library.

[0079] The application layer and application framework layer are launched on a virtual machine. The virtual machine executes the Java files of the application layer and application framework layer as binary files. The virtual machine is configured to implement features such as object lifecycle management, stack management, thread management, security and exception management, and garbage collection.

[0080] A system library may include multiple functional modules, such as a surface manager, a media library, a 3D graphics processing library (e.g., OpenGL ES), and a 2D graphics engine (e.g., SGL).

[0081] The Surface Manager manages the display subsystem and is configured to provide fusion of 2D and 3D layers for multiple applications.

[0082] The media library supports playback and recording of multiple commonly used audio and video formats, as well as still image files. The media library may support multiple audio and video coding formats, such as MPEG-4, H.264, MP3, AAC, AMR, JPG, and PNG.

[0083] The 3D graphics processing library is configured to perform 3D graphics drawing, image rendering, compositing, layer processing, and other similar operations.

[0084] A 2D graphics engine is a rendering engine used for 2D drawing.

[0085] In addition, the system library may further include a state monitoring service module configured to analyze and identify user gestures, such as a physical state identification module, and a sensor service module configured to monitor sensor data uploaded by various sensors at the hardware layer to determine the physical state of the electronic device 100.

[0086] The kernel layer is the layer between hardware and software. The kernel layer includes at least a display driver, camera driver, audio driver, and sensor driver.

[0087] The hardware layer may include various types of sensors, such as the various types of sensors shown in Figure 1, and accelerometers, gyroscopes, touch sensors, etc., in embodiments of this application.

[0088] Figure 3 is a schematic flowchart of a health plan formulation method according to one embodiment of this application. As shown in Figure 3, the method includes S310, S320, and S330. The method may be carried out by an electronic device. The electronic device may be a terminal device, such as a mobile phone or tablet computer, a wearable device, or a cloud server. An example of the structure of the electronic device is shown in Figure 1 and / or Figure 2.

[0089] S310: Obtain the user's target weight loss percentage and the user's current weight. The target weight loss percentage is the weight loss percentage expected by the user, and the weight loss percentage is the percentage of weight loss in a first unit of time relative to the current weight.

[0090] For example, the first unit of time may be a day, a week, a month, a year, or the like.

[0091] For example, the weight loss rate is the percentage of weight loss in a first unit of time relative to the current weight. For example, the weight loss rate may be 1% per week.

[0092] For example, if a user expects to lose 1% of their current weight in one week, the first unit of time is one week, and the user's target weight loss rate is 1%.

[0093] S320: Determine the amount of fat lost that corresponds to the target weight loss rate. The amount of fat lost is the percentage of fat in the body weight lost.

[0094] For example, weight loss fat content is the percentage of fat lost during weight loss. For instance, if the weight loss is 1 kilogram (kg) and the fat content loss is 0.5 kg, then the weight loss fat content is the percentage of 0.5 kg per 1 kg, or 50%.

[0095] Generally, there is a mapping relationship between the percentage of weight loss and the amount of fat lost. For example, a larger percentage of weight loss indicates a smaller percentage of fat lost; in other words, the percentage of fat lost is inversely proportional to the percentage of weight loss.

[0096] In this step, for example, the amount of fat lost corresponding to the target weight loss percentage can be determined based on the mapping relationship between the weight loss percentage and the amount of fat lost.

[0097] S330: The user's calorie deficit during the second unit time is determined based on the fat content corresponding to the target weight loss rate, the target weight loss rate, the user's current weight, the fat calories per unit body weight, and the lean body calories per unit body weight.

[0098] In this step, lean body mass may be understood as the collective term for the set of non-fat components in the human body.

[0099] For example, the second unit of time length may be a day, a week, a month, a year, or the like.

[0100] For example, the unit weight may be grams (g), kilograms, half a kilogram, kilograms, etc.

[0101] For example, the amount of fat lost corresponding to the target weight loss percentage, the target weight loss percentage, the user's current weight, the calories from fat per unit body weight, the calories from lean body weight per unit body weight, and the user's calorie deficit at the second unit time length satisfy the following relationship. g = (w*v*p*k1 + w*v*(1-p)*k2) / t.

[0102] g represents the calorie deficit in the second unit time length, w represents the user's current body weight, v represents the target weight loss percentage, p represents the amount of fat lost corresponding to the target weight loss percentage, k1 represents the fat calories per unit body weight, k2 represents the lean body calories per unit body weight, and t represents the ratio of the first unit time length to the second unit time length.

[0103] It should be understood that the aforementioned relationships are merely illustrative for calculating the calorie deficit based on the fat content corresponding to the target weight loss percentage, the target weight loss percentage, the user's current weight, fat calories per unit body weight, and lean body calories per unit body weight. Any relationships obtained by transforming the aforementioned relationships should fall within the scope of this step.

[0104] The principle of this step can be understood as follows: The target weight loss may be learned based on the current weight and the target weight loss percentage in a first unit time length, where the target weight loss is the weight the user expects to lose in the first unit time length. Based on the target weight loss and the weight loss fat content corresponding to the target weight loss percentage, the fat mass in the target weight loss, i.e., the fat mass included in the weight the user expects to lose in the first unit time length, may be learned. The fat calories that need to be lost in the first unit time length may be learned based on the fat mass in the target weight loss and the fat calories per unit weight. Based on the weight loss fat content corresponding to the target weight loss percentage, the weight loss lean body mass corresponding to the target weight loss percentage may be learned, where the weight loss lean body mass is the percentage of lean body mass lost in the weight during the first unit time length of weight loss. The lean body mass in the target weight loss, i.e., the lean body mass included in the weight the user expects to lose in the first unit time length, may be learned based on the target weight loss and the weight loss lean body mass corresponding to the target weight loss percentage. The lean calories that need to be lost in the first unit time may be learned based on lean body mass and lean calories per unit body weight in the target weight loss. The total calories that need to be lost in the first unit time may be learned based on the lean calories that need to be lost in the first unit time and the lean calories that need to be lost in the first unit time. The calories that need to be lost in the second unit time, i.e., the calorie deficit in the second unit time, may be learned 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.

[0105] It can be understood that any method for determining a calorie deficit based on the fat content corresponding to the target weight loss percentage, the target weight loss percentage, the user's current weight, fat calories per unit body weight, and lean body calories per unit body weight is included within the scope of this step, by using the aforementioned principles or related principles that can be clearly derived from the aforementioned principles.

[0106] In this embodiment, for example, the first unit time length may be the default time length. For example, the default time length may be one week or one month.

[0107] For example, the first unit time length may be entered by the user, for example, through a user interface.

[0108] For example, the weight loss time may be calculated based on the user's expected target weight, current weight, and weight loss rate. For instance, the weight loss time may be calculated by dividing the difference between the target weight and current weight by the weight loss rate. Optionally, the weight loss rate may also be calculated based on the weight loss rate percentage.

[0109] For example, the user's target weight may be obtained through user input. For example, the target weight may be obtained by user input via a user interface.

[0110] For example, the user interface may include a text input control, in which the user may enter a target weight.

[0111] For example, the user interface may include a selection control, which may offer the user multiple weight options. The user may then select a target weight through the selection control.

[0112] In this embodiment, in one example, the second unit time length may be the default time length. For example, the default time length may be one week or one month.

[0113] For example, the second unit time length may be entered by the user, for example, through a user interface.

[0114] In this embodiment, for example, the step of obtaining the user's target weight loss percentage may include the steps of obtaining the user's target weight loss rate and the user's current weight, and determining the target weight loss percentage based on the user's target weight loss rate and the user's current weight.

[0115] For example, the step of determining the target weight loss percentage based on the user's target weight loss percentage and the user's current weight may include the step of obtaining the ratio of the user's target weight loss percentage to the user's current weight in order to obtain the target weight loss percentage.

[0116] For example, the step of obtaining the user's target weight loss rate may include the step of obtaining the target weight loss rate entered by the user. For example, the target weight loss rate entered by the user is obtained through controls in the user interface.

[0117] For example, the user interface may include a text input control, in which the user may input a target weight loss rate.

[0118] For example, the user interface may include a selection control, which may offer the user multiple weight loss rate options. The user may select a weight loss rate through the selection control, and the weight loss rate selected by the user may be used as the target weight loss rate entered by the user.

[0119] For example, the step of obtaining a user's target weight loss rate may include the step of obtaining the weight loss mode expected by the user, and the step of determining the user's target weight loss rate based on the mapping relationship between the user's weight loss mode and the weight loss rate. Different weight loss modes correspond to different weight loss rates. The weight loss mode expected by the user may be referred to as the target weight loss mode.

[0120] The weight loss mode may include at least one of the following modes: recommended mode, fast mode, or radical mode. Three weight loss rates corresponding to the three modes may increase sequentially.

[0121] For example, the weight loss rate corresponding to the high-speed mode could be between 1.1% and 1.5%.

[0122] For example, the step of obtaining the user's weight loss mode may include the step of obtaining a target weight loss mode entered by the user through controls in the user interface.

[0123] For example, the user interface may include a text input control, in which the user may input a target weight loss mode.

[0124] For example, the user interface may include selection controls, which may provide the user with multiple weight loss mode options. The user may select a weight loss mode through the selection controls, and the weight loss mode selected by the user may be used as the target weight loss mode entered by the user.

[0125] In scenarios where the user interface optionally includes selection controls used to select a weight loss mode, the user interface may further include weight loss percentages corresponding to each selectable weight loss mode to provide the user with criteria for selecting a weight loss mode.

[0126] For example, the step of obtaining the user's target weight loss percentage may include the step of obtaining the target weight loss percentage entered by the user. For example, the target weight loss percentage entered by the user is obtained via the user interface.

[0127] For example, the user interface may include a text input control, in which the user may input a target weight loss percentage.

[0128] For example, the user interface may include selection controls, which may provide the user with options for multiple weight loss percentages. The user may select a weight loss percentage through the selection controls, and the weight loss mode selected by the user may be used as the target weight loss percentage entered by the user.

[0129] In a scenario that optionally includes selection controls used by the user interface to select a weight loss rate, the user interface may further include weight loss rates and / or weight loss modes corresponding to each selectable weight loss rate to provide the user with criteria for selecting a weight loss rate.

[0130] For example, the step of obtaining the user's current weight may include the step of obtaining the current weight entered by the user through controls in the user interface.

[0131] For example, the user interface may include a text input control, in which the user may enter their current weight.

[0132] For example, the user interface may include a selection control, which may provide the user with multiple weight options. The user may select a weight via the selection control, and the weight selected by the user may be used as the current weight entered by the user.

[0133] For example, the step of obtaining the user's current weight may include the step of receiving the weight obtained by measuring the user with a weight detection device. An example of a weight detection device is a body fat scale.

[0134] For example, after establishing a connection to a weight detection device, the electronic device receives the user's weight, currently measured in real time by the weight detection device, or the weight previously measured by the user using the weight detection device, and uses the received weight value as the user's current weight.

[0135] For example, the step of determining the amount of fat lost corresponding to the target weight loss rate includes the steps of determining the group category to which the user belongs, determining a first mapping relationship from a plurality of mapping relationships based on the group category to which the user belongs, wherein the first mapping relationship is a mapping relationship among the plurality of mapping relationships that corresponds to the group category to which the user belongs, the plurality of mapping relationships have a one-to-one correspondence with the plurality of group categories, and each mapping relationship in the plurality of mapping relationships shows a mapping relationship between the fat percentage in the weight loss of users in the corresponding group category and the weight loss rate of users in the corresponding group category over a first unit time length, and determining the amount of fat lost corresponding to the target weight loss rate based on the first mapping relationship.

[0136] In this embodiment, the mapping relationship between the fat percentage in weight loss for users in a corresponding group category and the weight loss percentage for users in a corresponding group category over a first unit time length may be called the weight loss fat percentage model.

[0137] For example, a group category may include at least one of the following categories: obese group, fitness group, and lean group.

[0138] In this step, users in different group categories differ in at least one of the following pieces of information: maximum oxygen uptake, body fat percentage, age, sex, current weight, or body mass index (BMI).

[0139] For example, group categories may be represented by the names of the group categories. For example, the names of the group categories may include "Obese Group," "Fitness Group," or "Lean Group."

[0140] For example, group categories may be represented by the characteristics of users within those categories. For instance, high body fat percentage, high BMI, and male might correspond to the obese group. In another example, low body fat percentage, high BMI, and male might correspond to the fitness group.

[0141] For example, a group category may be represented by the range of characteristic information values ​​to which users within that group category belong. For instance, a body fat percentage of a1% to b1%, a BMI of c1% to d1%, and males may correspond to the obese group. In another example, a body fat percentage of a2% to b2%, a BMI of c2% to d2%, and males may correspond to the fitness group.

[0142] For example, the step of determining the group category to which a user belongs may include the step of obtaining information that is entered by the user and can represent the group category, and the step of determining the group category to which the user belongs based on the information.

[0143] For example, the user interface may include a text input control, in which the user may input information representing a group category.

[0144] For example, the user interface may include selection controls. These selection controls may provide the user with informational options representing different group categories. The user may select information representing different group categories through these selection controls. The information selected by the user may be entered by the user and used to represent different group categories.

[0145] For example, if the name of the group category to which the user belongs is obtained, and the mapping relationship between the weight loss rate and the amount of fat lost is associated with the name of the group category, the first mapping relationship may be determined based on the name of the group category to which the user belongs.

[0146] For example, if user characteristic information is acquired and a mapping relationship between weight loss percentage and weight loss fat content is associated with the name of a group category, then the name of the group category to which the user belongs must first be determined based on the mapping relationship between the user characteristic information and the group category. Subsequently, the first mapping relationship is determined based on the name of the group category to which the user belongs.

[0147] For example, if user characteristic information is obtained and a mapping relationship between the weight loss rate and the amount of fat lost is associated with the user's characteristics, the first mapping relationship may be determined based on the user's characteristic information.

[0148] For example, if user characteristic information is obtained and the mapping relationship between the weight loss rate and the amount of fat lost is associated with the range to which the characteristic value belongs, the range to which the user's characteristic value belongs may be determined first based on the mapping relationship between the user's characteristic information and the range to which the characteristic value belongs. Subsequently, a first mapping relationship is determined based on the range to which the user's characteristic value belongs.

[0149] For example, if user characteristic information is acquired and a mapping relationship between weight loss percentage and weight loss fat content is associated with the name of a group category, the range to which the user's characteristic value belongs may be determined first based on the mapping relationship between the user's characteristic information and the range to which that characteristic value belongs. Then, the name of the group category to which the user belongs is determined based on the mapping relationship between the range to which the user's characteristic value belongs and the group category. Finally, the first mapping relationship is determined based on the name of the group category to which the user belongs.

[0150] Figure 4 is a diagram for determining a body fat percentage model based on the group category to which the user belongs. As shown in Figure 4, body fat percentage may be divided into several ranges, such as a1% to b1% and a2% to b2%. BMI may be divided into several ranges, such as c1 to d1 and c2 to d2. Age may be divided into several ranges, such as e1 to f1 and e2 to f2. Gender is divided into male and female.

[0151] Body fat percentage a1% to b1%, BMI c1 to d1, age e1 to f1, and male gender are associated with a fat percentage model. Body fat percentage a2% to b2%, BMI c2 to d2, age e2 to f2, and male gender are associated with a different weight loss fat percentage model.

[0152] In Figure 4, it can be understood that the information representing the group category, "body fat percentage a1%~b1%, BMI c1~d1, age e1~f1, male gender," may be replaced with the name of the corresponding group category, "obesity group." Similarly, the information representing the group category, "body fat percentage a2%~b2%, BMI c2~d2, age e2~f2, male gender," may be replaced with the name of the corresponding group category, "fitness group."

[0153] In Figure 4, it can be understood that the group category information "body fat percentage a1%~b1%, BMI c1~d1, age e1~f1, male gender" may be replaced with the group category information "high body fat percentage, high BMI, elderly, male." The group category information "body fat percentage a2%~b2%, BMI c1~d1, age e2~f2, male gender" may be replaced with the group category information "low body fat percentage, high BMI, young age, and male."

[0154] As shown in Figure 4, if 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 may be determined based on the user information as the weight loss fat percentage model located at the top of the two weight loss fat percentage models shown in Figure 4.

[0155] In this embodiment, the target weight loss rate may optionally be a weight loss rate range, and this weight loss rate range is also called the weight loss rate interval.

[0156] In this scenario, the calorie deficit corresponding to each endpoint may be obtained based on the endpoints at two endpoints within the weight loss percentage range, according to the method described above. The calorie range, where two calorie deficits corresponding one-to-one with the two endpoints are used as the upper and lower limits of the interval, is used as the calorie deficit corresponding to the target weight loss rate. The calorie deficit is a range. The larger of the two calorie deficits is the upper limit of the interval, and the smaller value is the lower limit of the interval.

[0157] In this embodiment, after the user's calorie deficit in a second unit time length is obtained, the calorie deficit may be output. For example, the calorie deficit may be output via the user interface.

[0158] If a calorie deficit is optionally output via the user interface, all or part of the information for obtaining the calorie deficit may be further output.

[0159] Optionally, in this embodiment, the method may further include the following steps: determining the user's meal plan and exercise plan for a second unit of time based on the calorie deficit and the user's basal metabolic calorie intake during the second unit of time.

[0160] For example, the user's basal metabolic calorie intake in a second unit of time may be entered directly by the user or calculated based on other information about the user.

[0161] For example, a user's meal plan for a second unit of time may include the following: the total calories that can be consumed during the second unit of time, indicated as the first calories, and the total calories that should be consumed during the second unit of time, indicated as the second calories. The difference between the first calories and the second calories is equal to a calorie deficit.

[0162] If a calorie deficit is within a certain range, it can be understood that the first and second calories in a meal plan may also be within that range.

[0163] For example, a user's meal plan in a second unit of time may further include the following: the amount of food consumed each day, and the calories that may be consumed in each meal. It can be understood that if there is a calorie deficit, the calories that may be consumed in each meal may also be within a range.

[0164] For example, an exercise plan may include exercise types, further include exercise items included in each exercise type, and further include duration information for the exercise items of each exercise type. The duration information may be an absolute duration, for example, one hour, or a relative duration, for example, the duration ratio of exercise items of different exercise types.

[0165] Figure 5 is an illustrative diagram of a user interface according to one embodiment of this application. As shown to the left of the dashed line in Figure 5, the user information input user interface may output a plurality of height values ​​for the user to select, output a plurality of weight values ​​for the user to select, provide a plurality of weight loss rates for the user to select, provide a plurality of weight loss percentages for the user to select, provide a plurality of weight loss modes for the user to select, and provide a plurality of target weights for the user to select.

[0166] As shown to the right of the dashed line in Figure 5, the calorie deficit user interface may include the following three parts: weight loss goals, meal plans, and exercise plans.

[0167] The weight loss goal section may include the following: daily calorie deficit, weekly weight loss rate, weight loss duration, and target weight.

[0168] The meal plan section may include the following: total calories that can be consumed per day, calories that can be consumed for breakfast, calories that can be consumed for lunch, calories that can be consumed for dinner, and calories that can be consumed for snacks.

[0169] The exercise plan section may include the following: the calories that can be burned by the recommended activities, and the recommended type of exercise determined based on the calories that can be burned by the recommended activities. For example, if the calories that can be burned by the recommended activities are 550 kcal, the recommended type of exercise is 70% aerobic exercise such as walking, running, and cycling, and / or 30% strength training such as core strengthening and upper limb strength training.

[0170] In some other embodiments of this application, when the method shown in Figure 3 is performed by a cloud server, a terminal device, such as a mobile phone, may acquire relevant user information and send the relevant user information to the cloud server. After the cloud server acquires the calorie deficit or any other information that may be output to the user by performing the method in the embodiment shown in Figure 3, the cloud server sends the calorie deficit and related information to the terminal device. The terminal device outputs the calorie deficit and related information via a user interface.

[0171] Optionally, the terminal device may further send calorie deficit and related information to a wearable device and display the calorie deficit and related information to the user via the wearable device, thereby further improving the convenience of the user in viewing calorie deficit and related information.

[0172] Figure 6 is a schematic flowchart of a health planning method according to another embodiment of this application. As shown in Figure 6, the method may include S610 and S620.

[0173] S610: The first basal metabolic state, the first fat loss time, and the first exercise capacity are obtained, the first basal metabolic state being the basal metabolic state of the user for whom a health plan is being formulated, the first exercise capacity being the exercise capacity of the user for whom a health plan is being formulated, and the first fat loss time being the fat loss time expected by the user for whom a health plan is being formulated.

[0174] For example, basal metabolic state is used to indicate basal metabolic rate, and different basal metabolic states indicate different basal metabolic rates.

[0175] For example, the basal metabolic state may include high metabolism, normal metabolism, and low metabolism, and the basal metabolic rates corresponding to the three basal metabolic states are in descending order.

[0176] For example, the step of obtaining a first basal metabolic state may include the step of obtaining a first basal metabolic state entered by the user. For example, the first basal metabolic state may be entered by the user through controls in the user interface.

[0177] For example, the user interface may include a text input control, in which the user may input a first basal metabolic state.

[0178] For example, the user interface may include selection controls, which may provide the user with multiple basal metabolic state options. The user may select a basal metabolic state through the selection controls. The basal metabolic state selected by the user may be used as the first basal metabolic state entered by the user.

[0179] For example, the user interface may display a range of basal metabolic values ​​corresponding to each basal metabolic state, thereby allowing the user to determine the basal metabolic value range in which they are located based on their own basal metabolic value, and as a result, the user can accurately select their own basal metabolic state.

[0180] For example, the step of obtaining the first basal metabolic state may include the steps of obtaining the basal metabolic rate entered by the user and determining the user's first basal metabolic state based on the basal metabolic rate. For example, the basal metabolic rate range to which the basal metabolic rate entered by the user belongs is determined, and the basal metabolic state corresponding to that basal metabolic rate range is determined as the first basal metabolic state. For simplicity of explanation, the basal metabolic rate entered by the user is called the first basal metabolic rate.

[0181] For example, the step of obtaining a first basal metabolic rate entered by the user may include the step of obtaining a first basal metabolic rate entered by the user through control in the user interface.

[0182] For example, the user interface may include a text input control, in which the user may input a first basal metabolic rate.

[0183] For example, the user interface may include selection controls, which may provide the user with multiple basal metabolic rate (BMR) options. The user may select a BMR through the selection controls. The BMR selected by the user may be used as the first BMR entered by the user.

[0184] For example, the step of obtaining a first basal metabolic state entered by the user may include the steps of obtaining at least one piece of information from the user's BMI, gender, and age, along with body fat percentage, and determining the first basal metabolic state based on at least one piece of information and body fat percentage.

[0185] For details on how the user's BMI, gender, and age are obtained, please refer to the relevant information in the embodiment shown in Figure 3. Details will not be repeated here.

[0186] For example, the step of determining a first basal metabolic state based on body fat percentage and at least one piece of information from BMI, sex, and age includes the steps of obtaining the user's body fat percentage and at least one piece of information from the user's BMI, sex, and age; determining a normal body fat percentage range associated with at least one piece of information based on the correspondence between at least one piece of information and a normal body fat percentage; and determining the relationship between the user's body fat percentage and the normal body fat percentage range. If the user's body fat percentage is higher than the normal body fat percentage range, the first basal metabolic state may be considered high metabolism. If the user's body fat percentage is within the normal body fat percentage range, the first basal metabolic state may be considered standard basal metabolism. If the user's body fat percentage is lower than the normal body fat percentage range, the first basal metabolic state may be considered low metabolism.

[0187] Figure 7 is a flowchart for determining the first basal metabolic state based on body fat percentage and at least one of the following pieces of information: BMI, sex, and age. The method shown in Figure 7 includes steps S701 to S707.

[0188] S701: Retrieves the user's BMI, gender, age, and body fat percentage.

[0189] S702: Determine a normal body fat percentage range associated with at least one piece of information, based on the correspondence between the user's BMI, gender, and age and a normal body fat percentage.

[0190] S703: Determine whether the user's body fat percentage is higher than the maximum value of the normal body fat percentage range. If the user's body fat percentage is higher than the maximum value of the normal body fat percentage range, S704 may be performed. If the user's body fat percentage is not higher than the maximum value of the normal body fat percentage range, S705 may be performed.

[0191] S704: The first basal metabolic state is determined to be high metabolism.

[0192] S705: Determine whether the user's body fat percentage is lower than the minimum value of the normal body fat percentage range. If the user's body fat percentage is lower than the minimum value of the normal body fat percentage range, S706 is performed. If the user's body fat percentage is not lower than the minimum value of the normal body fat percentage range, S707 is performed.

[0193] S706: The first basal metabolic state is determined to be low metabolism.

[0194] S707: Determine that the first basal metabolic state is the standard metabolic state.

[0195] Alternatively, the first step is to determine whether the user's body fat percentage is lower than the minimum value of the normal body fat percentage range. If the user's body fat percentage is lower than the minimum value of the normal body fat percentage range, S706 is performed. If the user's body fat percentage is not lower than the minimum value of the normal body fat percentage range, it is determined whether the user's body fat percentage is greater than the maximum value of the normal body fat percentage range. If the user's body fat percentage is greater than the maximum value of the normal body fat percentage range, S705 is performed. If the user's body fat percentage is not greater than the maximum value of the normal body fat percentage range, S707 is performed.

[0196] The following describes an embodiment in which a first athletic ability and a first fat reduction time are obtained in S610.

[0197] For example, regarding the method for obtaining the first weight loss time in this embodiment, please refer to the relevant information on obtaining the weight loss time in the embodiment shown in Figure 3. Details will not be repeated here.

[0198] For example, a user's motor skills may be represented by a score. Therefore, the step of obtaining the first motor skills of the first user can also be understood as the step of determining the user's motor skills score. The motor skills score may be called the first motor skills score.

[0199] For example, the step of obtaining a user's first motor skills score may include the step of obtaining a first motor skills score entered by the user.

[0200] For example, the step of obtaining a first motor skill score entered by the user may include the step of obtaining a first motor skill score entered by the user through control in the user interface.

[0201] For example, the user interface may include a text input control, in which the user may input a first motor skills score.

[0202] For example, the user interface may include a selection control, which may provide the user with multiple motor skill scoring options. The user may select a motor skill score through the selection control. The motor skill score selected by the user may be used as a first motor skill score entered by the user.

[0203] For example, the step of obtaining a user's first motor skills score may include the steps of obtaining the user's motor skills scores for multiple motor skills items and / or for each of at least one body part, and the step of determining the first motor skills score based on the motor skills scores.

[0204] For example, the exercise scores for exercise items of multiple exercise types may include aerobic exercise capacity scores and strength exercise capacity scores.

[0205] For example, the user's upper limb motor ability score is w, the weight of the upper limb motor ability score is a, the lower limb motor ability score is x, the weight of the lower limb motor ability score is b, the core motor ability score is y, the weight of the core motor ability score is c, the aerobic motor ability score is z, and the weight of the aerobic motor ability score is d. In this case, the first motor ability score may satisfy the following relationship, namely, s = a*w + b*x + c*y + d*z, where s represents the first motor ability score, and a, b, c, and d may be predetermined parameter values.

[0206] In one example, the step of obtaining the exercise ability score for each exercise item of each exercise type may include the step of obtaining the exercise ability score for each exercise item of each exercise type entered by the user.

[0207] For an embodiment of obtaining the exercise ability score for each exercise item of each exercise type entered by the user, please refer to the relevant section above regarding obtaining the first exercise ability score. Details will not be repeated here.

[0208] For example, the step of obtaining an exercise capacity score for each exercise item of each exercise type may include the step of obtaining at least one of the following information about the user, namely, the number of times the exercise item is performed within a given time period, the time period required by the user to complete the exercise item, or the user's physical characteristic parameter values ​​within that time period, such as heart rate, blood pressure, blood sample, or maximum oxygen uptake, and the step of calculating an exercise capacity score based on at least one type of information.

[0209] For example, the number of times an exercise item is performed within a specific time period, the time required by the user to complete an exercise item, or one or more of the user's physical characteristic parameter values ​​within that time period may be values ​​directly entered by the user, such as values ​​entered by the user based on historical records, or may be obtained by an electronic device by measuring the user in real time.

[0210] S620: A first target exercise plan is determined based on a first basal metabolic state, a first fat loss duration, and a first exercise capacity. The first target exercise plan includes multiple target stages, multiple target durations, multiple target exercise item sets, and multiple exercise duration ratios. Each of the multiple target durations has a one-to-one correspondence with each of the multiple target stages, and each target duration in the multiple target durations is the duration included in the first fat loss duration with respect to the corresponding target stage. Each of the multiple target exercise item sets has a one-to-one correspondence with each of the multiple target exercise item sets, and each exercise duration ratio in the multiple exercise duration ratios is the exercise duration ratio between exercise items in the corresponding target exercise item set.

[0211] For example, the multiple target stages included in the first target exercise plan may include at least one of the following stages: a fat loss adaptation period, a metabolic improvement period, a high-efficiency fat burning period, and a results retention period. It can be understood that at least one of the following aspects of these stages may differ: duration, type of exercise within the stage, different exercise items of the same type, different durations of exercise of the same type, or different durations of exercise of the same item.

[0212] For example, the fat loss adaptation period is designed to gradually adapt the body to the exercise-based fat loss rhythm, and the intensity is low. The metabolic improvement period mainly consists of strength training and is primarily used to improve metabolism; there may not be a significant change in weight, but the body becomes firmer and slimmer. The high-efficiency fat burning period mainly consists of aerobic training and high-intensity interval training (HIIT), and as the training frequency increases, total calorie expenditure increases, and fat decreases rapidly. The results retention period is a balanced period of aerobic and strength training that maintains muscle mass, maintains metabolism, reduces body fat percentage, and solidifies the results of the rapid fat loss period.

[0213] For example, the step of determining a first target exercise plan based on a first basal metabolic state, a first fat loss duration, and a first exercise capacity may include the steps of determining a plurality of target stages, a plurality of target durations, a plurality of target exercise type sets, and a plurality of exercise duration ratios based on the first basal metabolic state and the first fat loss duration, wherein the plurality of target exercise type sets have a one-to-one correspondence with the plurality of target stages, and each target exercise type set in the plurality of target exercise type sets includes the exercise type in the corresponding target stage; and the step of determining a set of target exercise items for the corresponding target stage based on the first exercise capacity and each target exercise type set.

[0214] For example, the step of determining multiple target stages, multiple target durations, multiple target exercise type sets, and multiple exercise duration ratios based on a first basal metabolic state and a first fat loss duration includes the steps of determining multiple target stages and multiple target durations based on a first basal metabolic state and a first fat loss duration; determining target exercise type sets for each target stage in the multiple target stages and obtaining multiple target exercise type sets that have a one-to-one correspondence with the multiple target stages; and determining exercise duration ratios for multiple exercise types in each target exercise type set in the multiple target exercise type sets in order to obtain multiple target duration ratios that have a one-to-one correspondence with the multiple target exercise type sets.

[0215] For example, multiple target stages may be specifically divided based on a first fat loss duration and a first basal metabolic state.

[0216] For example, if the first fat loss duration planned by the user is X weeks and the first basal metabolic state is low metabolism, the first fat loss duration may be divided into a fat loss adaptation period, A weeks; a metabolic improvement period, B weeks; a high-efficiency fat burning period, C weeks; and a results retention period, D weeks.

[0217] As another example, if the first fat loss duration planned by the user is Y weeks and the first basal metabolic state is high metabolism, the first fat loss duration may be divided into a fat loss adaptation period, A weeks; a high-efficiency fat burning period, E weeks; and a results retention period, F weeks.

[0218] It can be understood that the multiple target stages in the first target exercise plan correspond to multiple target durations, and the sum of these multiple target durations represents the first fat loss duration.

[0219] For example, based on the first athletic ability and the first basal metabolic state, the type of exercise corresponding to each target stage is determined.

[0220] For example, each of the multiple goal stages corresponds to a corresponding set of target exercise items. Table 1 shows the sets of target exercise items corresponding to the fat loss adaptation period, the metabolic improvement period, the high-efficiency fat burning period, and the results retention period.

[0221] [Table 1]

[0222] For example, the duration of each target exercise type in the target exercise items corresponding to each of the multiple target stages may be determined based on the weekly training frequency.

[0223] Each target exercise set may include multiple exercise types, such as aerobic, strength endurance, and HIIT. Each exercise type corresponds to a different exercise duration. The exercise duration is determined based on the weekly training frequency.

[0224] For example, if a user is in a metabolic improvement phase and their weekly training frequency is K, then at this stage, M aerobic training courses, N strength training courses, and P HIIT training courses would be provided.

[0225] For example, the step of determining a set of target exercise items corresponding to a target stage based on a first motor ability and each set of target exercise types may include a step of determining a first exercise difficulty based on a mapping relationship between a first motor ability score and exercise difficulty, wherein the first exercise difficulty is the exercise difficulty associated with the first motor ability score, and a step of determining a set of target exercise items for a target stage corresponding to each set of target exercise types based on each set of target exercise types and the first exercise difficulty, wherein the set of target exercise items for a target stage corresponding to each set of target exercise types includes exercise items that constitute each exercise type in each set of target exercise types, and whose exercise difficulty is the first exercise difficulty.

[0226] For example, the first exercise difficulty level includes strength course difficulty and aerobic course difficulty, which may be determined by the user's strength score, aerobic score, gender, and weight. Tables 2 and 3 show the strength course difficulty levels corresponding to the strength score and aerobic score, respectively.

[0227] [Table 2]

[0228] [Table 3]

[0229] For example, if the user's strength test score is 'a' and the corresponding course difficulty is Y1, then strength training with difficulty Y1 will be randomly selected and placed in the target exercise type based on the aforementioned course type and course proportion. The same applies to aerobic training.

[0230] In this embodiment, if the electronic device is a terminal device such as a mobile phone, tablet, or wearable device, it can be understood that the step of acquiring various information entered by the user may be performed by the electronic device or received from another terminal device that establishes a communication connection to the electronic device.

[0231] In this embodiment, if the electronic device is a cloud server, the step of acquiring various information entered by the user may be performed using a terminal device, and it can be understood that the terminal device receives the information.

[0232] In this embodiment, after the first target exercise plan is obtained, the first target exercise plan may be displayed to the user.

[0233] 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 via the user interface of the electronic device.

[0234] In a scenario in which the electronic device optionally displays the first target exercise plan to the user, the electronic device may further send the first target exercise plan to a wearable device and display the first target exercise plan to the wearable device user.

[0235] In another example, if the electronic device is a cloud server, the electronic device may send the first target exercise plan to various terminal devices such as mobile phones, tablet computers, and wearable devices, and display the first target exercise plan to the user via the electronic device's user interface.

[0236] For example, the method in this embodiment may further include the step of obtaining the degree of completion of a first target movement plan and / or user feedback on the first target movement plan, wherein the degree of completion of the first target movement plan and / or user feedback on the first target movement plan determines a second target movement plan.

[0237] In the steps of this embodiment, the second target exercise plan may be adjusted after the first target exercise plan is completed and may be a plan based on the degree of training completion and / or user feedback on the first target exercise plan.

[0238] For example, the degree of completion of the first target exercise plan may be calculated based on the actual exercise conditions and the planned conditions after the completion of training for multiple target stages.

[0239] For example, user feedback on the first target exercise plan may be at the user's subjective level of perception after each training session is completed.

[0240] For example, the level of recognition may be classified into four levels: easy, just right, intense, and difficult.

[0241] For example, feedback on the first target exercise plan may be obtained through the user interface.

[0242] For example, the step of obtaining the degree of completion of the first target exercise plan includes the steps of obtaining the actual completion time for each exercise item in each of the multiple target exercise item sets, determining the planned time for each exercise item in each target exercise item set based on multiple target time lengths and multiple exercise time ratios, determining the degree of completion for the same type of exercise item in each target exercise item set based on the actual completion time and planned time for the same type of exercise item in each target exercise item set, and determining the degree of exercise completion for the target stage corresponding to each target exercise item set based on the degree of completion for the same type of exercise item in each target exercise item set.

[0243] For example, the actual exercise status may be determined by collecting statistics on the actual number of completed groups and the actual number of completed sessions for different exercise types. The planned conditions are determined using the planned number of groups and the planned number of sessions. The degree of completion of the first target exercise plan may be calculated using weighted values ​​for the completion of different types of exercise.

[0244] For example, the completion rate of strength training in the first target exercise plan is calculated by multiplying the ratio of the actual number of strength training groups to the planned number of strength training groups by the ratio of the actual number of repetitions to the planned number of repetitions. The completion rate of aerobic training in the first target exercise plan is calculated by multiplying the ratio of the actual number of aerobic training groups to the planned number of aerobic training groups by the ratio of the actual number of repetitions to the planned number of repetitions. The completion rate of HIIT training in the first target exercise plan is calculated by multiplying the ratio of the actual number of HIIT training groups to the planned number of HIIT training groups by the ratio of the actual number of repetitions to the planned number of repetitions.

[0245] In this embodiment, it may be understood that the following steps may be repeated: namely, obtaining the degree of completion and / or subjective feedback of the second target exercise plan, and adjusting the second target exercise plan based on the information to obtain a new second target exercise plan.

[0246] Figure 8 is a diagram showing the structure of an apparatus according to one embodiment of this application. As shown in Figure 8, the apparatus 800 may include a processing module 801 and a communication module 802.

[0247] In the first example, the apparatus 800 may be configured to perform a method implemented in any one of the embodiments shown in Figures 3 to 7. For example, the processing module 801 is configured to perform the relevant steps of the processing operation in the method described in any one of the embodiments shown in Figures 3 to 7, and the communication module 802 is configured to perform the relevant steps of the information acquisition operation in the method described in any one of the embodiments shown in Figures 3 to 7.

[0248] Figure 9 is a diagram illustrating the structure of an apparatus according to another embodiment of this application. As shown in Figure 9, the apparatus 900 includes a processor 901 and a communication circuit 902. The processor 901 and the communication circuit 902 are coupled to each other. It can be understood that the communication circuit 902 may be a transceiver or an input / output interface. Optionally, the apparatus 900 may further include a memory 903 configured to store instructions executed by the processor 901, or input data required by the processor 901 to execute instructions, or data generated after the processor 901 has executed instructions. It can be understood that the memory 903 may be located outside the processor 901 or inside the processor 901.

[0249] In one example, the processor 901 is configured to implement the functions of the processing module 801, and the communication circuit 902 is configured to implement the functions of the communication module 802.

[0250] The device 900 may be an electronic device, or a device, module, circuit, chip, etc., placed on an electronic device, or a device that can be used together with an electronic device.

[0251] One embodiment of this application provides a computer program product. When the computer program product is launched on an electronic device, the electronic device becomes capable of performing the technical solutions described in the above-described embodiment. The implementation principles and technical effects of the computer program product are the same as those of the method-related embodiments described above. Details will not be repeated here.

[0252] One embodiment of this application provides a readable storage medium, which contains instructions. When the instructions are executed on an electronic device, the electronic device becomes capable of performing the technical solutions of the embodiments described above. The implementation principles and technical effects of the readable storage medium are similar and will not be repeated in detail here.

[0253] One embodiment of this application provides a chip configured to execute instructions. When the chip is activated, the technical solution of the above-described embodiment is performed. The implementation principle and technical effects of the readable storage medium are the same. Details will not be repeated here.

[0254] As those skilled in the art will notice, the units and algorithmic steps may be implemented by electronic hardware, or a combination of computer software and electronic hardware, in combination with the examples described in the embodiments disclosed in this specification. Whether the functionality is performed by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functionality for specific applications, but the embodiments should not be considered to exceed the scope of the embodiments of this application.

[0255] For the sake of convenience and simplicity, and so that those skilled in the art can clearly understand, please refer to the corresponding procedures in the aforementioned method embodiments for detailed operating processes of the aforementioned systems, apparatus, and units. Details will not be repeated here.

[0256] In some embodiments provided in this application, it should be understood that the disclosed systems, apparatus, and methods may be implemented in other ways. For example, the embodiments of the apparatus described are merely examples. For example, the division into units is merely a logical functional division. Other divisional configurations may exist in actual implementation. For example, multiple units or components may be combined or incorporated into another system, or some features may be ignored or omitted. Furthermore, the mutual coupling, direct coupling, or communication connection indicated or discussed may be implemented by using some interfaces. Indirect coupling or communication connection between apparatus or units may be implemented electrically, mechanically, or in other forms.

[0257] Units described as separate parts may or may not be physically separate, and parts shown as units may or may not be physical units, may be located in one place, or may be distributed across multiple network units. Some or all of the units may be selected based on actual requirements to achieve the objectives of the solution of the embodiment.

[0258] In addition, the functional units in the embodiments of this application may be incorporated into a single processing unit, or they may exist physically separately, or two or more units may be incorporated into a single unit.

[0259] When a function is implemented in the form of a software function unit and sold or used as an independent product, the function may be stored on a computer-readable storage medium. Based on such understanding, the technical solution of the embodiments of this application may be implemented in the form of a software product, which may be essentially, or contribute to the prior art, or be a part of the technical solution. The computer software product may be stored on a storage medium and include several instructions for instructing a computer device (which may be a personal computer, server, network device, etc.) to perform all or part of the steps of the method described in the embodiments of this application. The aforementioned storage medium includes any medium capable of storing program code, such as a USB flash drive, removable hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0260] The foregoing description represents only specific embodiments of the embodiments of this application. However, the scope of protection of the embodiments of this application is not limited to these. Any modification or substitution that is readily conceivable by a person skilled in the art within the technical scope disclosed in the embodiments of this application shall fall within the scope of protection of the embodiments of this application. Accordingly, the scope of protection of the embodiments of this application shall be subject to the scope of protection of the claims. [Explanation of symbols]

[0261] 100 Electronic Devices 110 processors 120 Interface for external memory 121 Internal Memory 130 USB Interfaces 140 Charging Management Module 141 Power Management Module 142 batteries 150 Mobile Communication Module 2G / 3G / 4G / 5G 160 Wireless Communication Modules BT / WLAN / GNSS / NFC / IR / FM 170 Audio Modules 170A speaker 170B receiver 170C Microphone 170D headset jack 180 Sensor Modules 180A pressure sensor 180B Gyroscope Sensor 180°C Barometric Pressure Sensor 180D Magnetic Sensor 180E Accelerometer 180F Distance Sensor 180G Optical Proximity Sensor 180H Fingerprint Sensor 180J Temperature Sensor 180K touch sensor 180L Ambient Light Sensor 180M Bone Conduction Sensor 190 buttons 191 Motor 192 Indicators 193 Camera 1~N 194 Display 1~N 195 SIM card interface 800 equipment 801 Processing Module 802 Communication Module 900 equipment 901 Processor 902 Communication Circuit 903 memory

Claims

1. In a method for formulating a health plan, the method is applied to an electronic device. A step of obtaining the user's target weight loss rate and the user's current weight, wherein the target weight loss rate is the weight loss rate expected by the user, and the weight loss rate is the percentage of weight loss in a first unit time period relative to the current weight; A step of determining the amount of fat lost corresponding to the target weight loss rate, wherein the amount of fat lost is the ratio of the amount of fat to the weight lost in the weight loss. A step of determining the user's calorie deficit at a second unit time length based on the amount of fat lost corresponding to the target weight loss rate, the target weight loss rate, the user's current weight, the amount of fat calories per unit body weight, and the amount of lean body calories per unit body weight. A method for formulating a health plan, including the following.

2. The step of obtaining the target weight loss percentage for the user is: A step of obtaining the user's target weight loss rate and the user's current weight, wherein the target weight loss rate is the weight loss rate expected by the user, and the weight loss rate is the weight loss over the first unit time period, A step of determining the target weight loss rate based on the user's target weight loss rate and the user's current weight. The method according to claim 1, including the method described in claim 1.

3. The step of determining the amount of fat lost that corresponds to the target weight loss rate is: The steps include determining the group category to which the user belongs, A step of determining a first mapping relationship from a plurality of mapping relationships based on the group category to which the user belongs, wherein the first mapping relationship is a mapping relationship among the plurality of mapping relationships that corresponds to the group category to which the user belongs, the plurality of mapping relationships have a one-to-one correspondence with the plurality of group categories, and each mapping relationship in the plurality of mapping relationships shows a mapping relationship between the fat percentage in the weight loss of a user in the corresponding group category and the weight loss percentage of the user in the corresponding group category over the first unit time length. A step of determining the amount of fat lost corresponding to the target weight loss percentage based on the first mapping relationship described above. The method according to claim 1 or 2, including the method described in claim 1 or 2.

4. The step of determining the group category to which the user belongs is: A step of obtaining user information, wherein the user information includes at least one of the following information of the user: maximum oxygen uptake, body fat percentage, age, sex, current weight, and body mass index. The steps include determining the group category to which the user belongs based on the user information, and The method according to claim 3, including the method described in claim 3.

5. The following relationship is satisfied when the amount of fat lost, the target weight loss percentage, the user's current weight, the calories from fat per unit body weight, the calories from lean body weight per unit body weight, and the user's calorie deficit at the second unit time length, corresponding to the target weight loss percentage: g = (w * v * p * k1 + w * v * (1 - p) * k2) / t, in the equation, g represents the calorie deficit, w represents the user's current weight, v represents the target weight loss percentage, p represents the weight loss fat content corresponding to the target weight loss percentage, k1 represents the fat calories per unit body weight, k2 represents the lean body calories per unit body weight, and t represents the ratio of the first unit time length to the second unit time length. The method according to any one of claims 1 to 4.

6. The step of determining the user's meal plan and exercise plan for the second unit of time based on the calorie deficit and the user's basal metabolic calorie intake during the second unit of time. The method according to any one of claims 1 to 5, further comprising:

7. In a method for formulating health plans applicable to electronic devices or cloud servers, A step of obtaining a first basal metabolic state, a first fat loss time, and a first exercise capacity, wherein the first basal metabolic state is the basal metabolic state of the user for whom a health plan is being formulated, the first exercise capacity is the exercise capacity of the user for whom the health plan is being formulated, and the first fat loss time is the fat loss time expected by the user for whom the health plan is being formulated. A step of determining a first target exercise plan based on the first basal metabolic state, the first fat loss duration, and the first exercise capacity, wherein the first target exercise plan includes a plurality of target stages, a plurality of target durations, a plurality of target exercise item sets, and a plurality of exercise duration ratios, wherein the plurality of target durations have a one-to-one correspondence with the plurality of target stages, each target duration in the plurality of target durations is the duration included in the first fat loss duration in the corresponding target stage, the plurality of target exercise item sets have a one-to-one correspondence with the plurality of target stages, each target exercise item set in the plurality of target exercise item sets includes the exercise item in the corresponding target stage, the plurality of exercise duration ratios have a one-to-one correspondence with the plurality of target exercise item sets, and each exercise duration ratio in the plurality of exercise duration ratios is the exercise duration ratio between exercise items in the corresponding target exercise item set. A method for formulating a health plan, including the following.

8. The step of determining the first target exercise plan based on the first basal metabolic state, the first fat loss duration, and the first exercise capacity is: A step of determining the plurality of target stages, the plurality of target durations, the plurality of target exercise type sets, and the plurality of exercise duration ratios based on the first basal metabolic state and the first fat loss duration, wherein the plurality of target exercise type sets have a one-to-one correspondence with the plurality of target stages, and each target exercise type set in the plurality of target exercise type sets includes the exercise type in the corresponding target stage. The steps include determining the set of target exercise items for the corresponding target stage based on the first exercise ability and each set of target exercise types, and The method according to claim 7, including the method described in claim 7.

9. The step of determining the plurality of target stages, the plurality of target durations, the plurality of target exercise type sets, and the plurality of exercise duration ratios based on the first basal metabolic state and the first fat loss duration is: A step of determining the plurality of target stages and the plurality of target time lengths based on the first basal metabolic state and the first fat reduction time length, The steps include determining the target exercise type set for each of the multiple target stages and obtaining the multiple target exercise type sets that correspond one-to-one with the multiple target stages, In order to obtain a plurality of target time length ratios that correspond one-to-one with the plurality of target exercise type sets, the steps include determining the exercise time length ratios of the plurality of exercise types in each of the plurality of target exercise type sets. The method according to claim 8, including the method described in claim 8.

10. The step of determining the set of target exercise items for the corresponding target stage based on the first exercise ability and each set of target exercise types is: A step of obtaining a first score based on the first motor ability, wherein the first score is the score of the first motor ability, A step of determining a first motor difficulty level based on a mapping relationship between a motor ability score and a motor difficulty level, wherein the first motor difficulty level is the motor difficulty level associated with the first score, A step of determining a set of target exercise items for a target stage corresponding to each set of target exercise types, based on each set of target exercise types and the first set of exercise difficulty, wherein the set of target exercise items for the target stage corresponding to each set of target exercise types includes exercise items that constitute each exercise type in each set of target exercise types, and whose exercise difficulty is the first set of exercise difficulty. The method according to claim 8 or 9, including the method described in claim 8 or 9.

11. A step of determining a second target exercise plan by obtaining the degree of completion of the first target exercise plan and / or the user's feedback regarding the first target exercise plan. The method according to any one of claims 9 to 10, further comprising:

12. The step of obtaining the completion rate of the first target exercise plan is: The steps include obtaining the actual completion time for each of the aforementioned sets of multiple target exercise items, The steps include determining the planned duration of each exercise item in each target exercise item set based on the plurality of target durations and the plurality of exercise duration ratios, A step of determining the degree of completion of the same type of exercise item in each target set of exercise items based on the actual completion time and planned time for the same type of exercise item in each target set of exercise items, A step of determining the degree of completion of the target stage corresponding to each target set of target exercise items, based on the degree of completion of the same type of exercise item in each set of target exercise items. The method according to claim 11, including the method described in claim 11.

13. It is an electronic device, One or more processors, One or more memory devices, Equipped with, The one or more memory stores one or more computer programs, and the one or more computer programs include instructions, and when the instructions are executed by the one or more processors, the electronic device is enabled to perform the method according to any one of claims 1 to 12. Electronic devices.

14. A computer-readable storage medium wherein the computer-readable storage medium includes a computer program or instructions, and when the computer program or instructions are executed on a computer, the method according to any one of claims 1 to 12 is performed.

15. A computer program product comprising a computer program or instruction, wherein when the computer program or instruction is executed on a computer, the method described in any one of claims 1 to 12 is performed.

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