CN113823377A

CN113823377A - Motion guiding method and electronic equipment

Info

Publication number: CN113823377A
Application number: CN202010561190.XA
Authority: CN
Inventors: 董晓杰
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2020-06-18
Filing date: 2020-06-18
Publication date: 2021-12-21

Abstract

The application provides a motion guidance method and electronic equipment. According to the embodiment of the application, prompt information can be given to the user based on the recovery percentage, so that the user can timely adjust the exercise amount and the exercise ending time of the exercise based on the prompt information to help the user to obtain the excessive recovery, the beneficial effect of the excessive recovery is effectively utilized, and the problem that the user cannot know the exercise income of the exercise and can blindly exercise is solved.

Description

Motion guiding method and electronic equipment

Technical Field

The present application relates to terminal device technologies, and in particular, to a motion guidance method and an electronic device.

Background

As society develops and concerns about health, people improve their physical fitness and cardiopulmonary ability through exercise, such as running, swimming, etc. An application program (for example, sports health) on the terminal equipment can record and analyze data in the sports process of the user, and rich and professional sports health services are provided for the user.

For running, an Application (APP) of the terminal device may acquire data of a user during running through a sensor of the terminal device, and calculate information such as a movement distance, time, calories consumed and the like based on the data, and the APP of the terminal device displays the information such as the movement distance, time, calories consumed and the like on a user interface so that the user can know the amount of exercise of the user in time. After the running is finished, the application program of the terminal device can also calculate the recovery time according to the amount of exercise of the running, and display the recovery time on the user interface, so that the user can know that the next exercise is performed when the recovery time is up.

However, although the above process application provides the user with a recovery time during which the user can gradually recover the energy substances of the exercise body consumed during exercise by taking a rest, the user cannot accurately improve the exercise yield based on the information provided by the application. Recovery studies have shown that muscle glycogen consumed during exercise can be gradually recovered after exercise, and in some cases, it can be recovered to an amount exceeding the original amount, so-called over-recovery. The principle of excessive recovery can provide theoretical basis for explaining that the exercise can effectively improve the functions and the abilities of the body. The application program in the process is not based on the principle of excessive recovery, and effective guidance is provided for the movement of the user, so that the user cannot accurately improve the movement income based on the information provided by the application program.

Disclosure of Invention

The application provides a motion guidance method and electronic equipment, which can provide effective guidance for the motion of a user to help the user to obtain excessive recovery, and further effectively utilize the beneficial effect of the excessive recovery.

In a first aspect, an embodiment of the present application provides a motion guidance method, which may include: in response to a first operation, a training effect for a first period of time is acquired, the training effect being indicative of an amount of motion for the first period of time. And determining the recovery percentage corresponding to the training effect according to the training effect of the first time period. And generating prompt information according to the recovery percentage, wherein the prompt information is used for guiding the user to move.

According to the implementation mode, the recovery percentage corresponding to the training effect is determined through the training effect of the user in the first time period, and the user is guided to move based on the recovery percentage. Therefore, prompt information is given to the user based on the recovery percentage, so that the user can timely adjust the exercise amount and the exercise ending time of the exercise based on the prompt information to help the user to obtain the excessive recovery, the beneficial effect of the excessive recovery is effectively utilized, and the problem that the user cannot know the exercise income after the exercise is ended and the exercise is performed blindly is solved.

For example, the first time period may be a time period of the current exercise in the following embodiment, and different ending times of the current exercise correspond to different training effects, that is, training effects of different first time periods. The recovery percentages corresponding to the training effects in different first time periods can be determined in the exercise process of the user, and prompt information is given to the user based on the recovery percentages, so that the user can timely adjust the exercise amount and the exercise ending time of the exercise based on the prompt information.

In one possible design, the recovery percentage corresponding to the training effect includes recovery percentages at a plurality of time points after the first time period, and when a maximum value of the recovery percentages at the plurality of time points is equal to 1, the prompt message includes a first prompt message for prompting a user to increase exercise intensity; or when the maximum value of the recovery percentages at the plurality of time points is less than 1, the prompt message comprises a second prompt message which is used for prompting the user to stop the movement.

The plurality of time points after the first period of time may be a plurality of time points within a recovery time in the following embodiments. The first prompt message may be a fourth prompt message in the following detailed description, and the first prompt message may be a second prompt message in the following detailed description.

This implementation, through increasing exercise intensity to the suggestion of user for the user can in time adjust the motion, thereby acquires the excess and resumes. By prompting the user to stop the movement, the user can stop the movement in time, and the damage to the body caused by excessive movement is avoided.

In a possible design, the recovery percentage corresponding to the training effect includes recovery percentages at a plurality of time points after the first time period, and when a maximum value of the recovery percentages at the plurality of time points is greater than 1, the prompt message includes a third prompt message, where the third prompt message is used for prompting that there is excessive recovery.

The third prompt message may be the first prompt message in the following detailed description.

This implementation mode, through to the user suggestion there is the excess to resume for the user can in time learn can acquire the excess and resume, and then rationally finish the motion.

In one possible design, the third prompting message is also used for prompting the time of the over-recovery.

In one possible design, the method may further include: and generating fourth prompt information according to the excessive recovery time, wherein the fourth prompt information is used for prompting the user to do exercise at the excessive recovery time.

The fourth prompting message may be the third prompting message in the following specific embodiment.

This implementation through to the user suggestion user at the time of excessive recovery carry out the motion for the user can rationally arrange the motion, and then effectively utilize the beneficial effect that the excessive was resumeed.

In one possible design, determining the recovery percentage corresponding to the training effect according to the training effect of the first time period may include: and respectively determining the fused training effect of each time point according to the training effect of the first time period, a plurality of time points after the first time period, the training effects of the N second time periods and the end time of the N second time periods. And determining the recovery percentage of each time point according to the fused training effect of each time point.

The N second time periods may be time periods corresponding to the historical N movements in the embodiments described below.

This implementation, through the training effect that combines N second time quantum, confirm the recovery percentage, can promote the degree of accuracy of recovery percentage, and then promote the accuracy of motion guidance.

In one possible design, determining the fused training effect of each time point according to the training effect of the first time period, a plurality of time points after the first time period, the training effects of the N second time periods, and the end times of the N second time periods respectively includes:

according to the formula respectively

DeterminingWeight a of the nth training effect for each time point_n。

According to the formula respectively

Determining a fused training effect TE for each time point_new。

Wherein, t₀Is a point in time, TE, after the first period of time₀Is the training effect of this first time period, t₁To t_NIs the end time of the N second time periods, c is a predetermined constant, TE₁To TE_NIs the training effect for the N second time periods.

In one possible design, the determining the recovery percentage for each time point according to the fused training effect for each time point may include: according to the formula respectively

The percent recovery for each of the time points is determined. Wherein, P (t)₀) Is t₀Percent recovery of b₀、b₁、b₂Is a preset constant.

In one possible design, obtaining the training effect for the first time period includes: and acquiring the motion data of the self sensor. And determining the training effect of the first time period according to the motion data in the first time period. Or receiving the motion data sent by other electronic equipment, and determining the training effect of the first time period according to the motion data of the first time period. Or receiving the training effect of the first time period sent by other electronic equipment.

In one possible design, the method may further include at least one of: displaying the recovery percentage; alternatively, the recovery percentage is sent; or, the prompt message is sent.

In a second aspect, the present application provides an electronic apparatus, which may be an electronic device or a chip or a system on a chip in an electronic device, and may also be a functional module in an electronic device for implementing the method of the first aspect or any possible design of the first aspect. The electronic device may implement the functions of the first aspect or each possible design of the first aspect, and the functions may be implemented by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions. For example, in one possible implementation, the electronic device may include: the device comprises an acquisition module and a processing module. The acquisition module is used for responding to the first operation and acquiring a training effect of a first time period, wherein the training effect is used for expressing the quantity of motion of the first time period. The processing module is used for determining the recovery percentage corresponding to the training effect according to the training effect of the first time period. The processing module is further used for generating prompt information according to the recovery percentage, and the prompt information is used for guiding the user to move.

In one possible design, the recovery percentage corresponding to the training effect includes recovery percentages at a plurality of time points after the first time period, and when a maximum value of the recovery percentages at the plurality of time points is equal to 1, the prompt message includes a first prompt message for prompting a user to increase exercise intensity; or,

when the maximum value of the recovery percentages at the plurality of time points is less than 1, the prompt message comprises a second prompt message, and the second prompt message is used for prompting the user to stop the movement.

In one possible design, the processing module is further configured to: and generating fourth prompt information according to the excessive recovery time, wherein the fourth prompt information is used for prompting the user to do exercise at the excessive recovery time.

In one possible design, the processing module is configured to: respectively determining the fused training effect of each time point according to the training effect of the first time period, a plurality of time points after the first time period, the training effects of the N second time periods and the end time of the N second time periods; and determining the recovery percentage of each time point according to the fused training effect of each time point.

In one possible design, the processing module is configured to: according to the formula respectively

Determining a weight a of an nth training effect for each time point_n(ii) a According to the formula respectively

Determining a fused training effect TE for each time point_new。

Wherein, t₀Is a point in time, TE, after said first period of time₀Is the training effect of this first time period, t₁To t_NIs the end time of the N second time periods, c is a predetermined constant, TE₁To TE_NIs the training effect for the N second time periods.

Determining the percent recovery for each of the time points.

Wherein, P (t)₀) Is t₀Percent recovery of b₀、b₁、b₂Is a preset constant.

In one possible design, the obtaining module is configured to: acquiring motion data; and determining the training effect of the first time period according to the motion data in the first time period.

In one possible design, the processing module is further configured to: displaying the recovery percentage; alternatively, the recovery percentage is sent; or, the prompt message is sent.

In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; a memory for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement the method of any one of the first aspects as described above.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, comprising a computer program, which when executed on a computer, causes the computer to perform the method according to any one of the above first aspects.

In a fifth aspect, an embodiment of the present application provides a chip, including a processor and a memory, where the memory is used to store a computer program, and the processor is used to call and execute the computer program stored in the memory to perform the method according to any one of the above first aspects.

In a sixth aspect, embodiments of the present application provide a computer program product comprising computer program instructions which, when executed on a computer, cause the computer to perform the method according to any one of the above first aspects.

According to the exercise guidance method and the electronic equipment, the exercise data of the exercise of the user is used for determining the training effect of the exercise, and then the recovery percentage is determined according to the training effect of the exercise so as to guide the user to exercise based on the recovery percentage. Therefore, the electronic equipment can determine the recovery percentages corresponding to the training effects in different time periods in the user movement process, and give prompt information to the user based on the recovery percentages, so that the user can timely adjust the movement amount and the movement ending time of the movement based on the prompt information to help the user to obtain excessive recovery, further effectively utilize the beneficial effect of the excessive recovery, and solve the problem that the user cannot know the movement benefits of the movement and blindly moves.

Drawings

Fig. 1 is a schematic time diagram of the current exercise according to the embodiment of the present application;

fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present application;

fig. 3A is a schematic diagram of an application scenario according to an embodiment of the present application;

FIG. 3B is a diagram illustrating another application scenario according to an embodiment of the present application;

FIG. 4 is a flow chart of a method of motion guidance according to an embodiment of the present application;

FIG. 5A is a schematic diagram of a recovery curve provided in an embodiment of the present application;

FIG. 5B is a graph illustrating a percent recovery provided by an embodiment of the present application;

fig. 6 is a schematic diagram of a prompt message provided in an embodiment of the present application;

FIG. 7 is a flow chart of a method of determining a percentage of recovery according to an embodiment of the present application;

FIG. 8 is a flow chart of another method of motion guidance according to an embodiment of the present application;

FIG. 9 is a schematic view of a user interface of an embodiment of the present application;

FIG. 10 is a schematic view of a user interface of an embodiment of the present application;

FIG. 11 is a flow chart of another method of motion guidance according to an embodiment of the present application;

FIG. 12 is a schematic view of a user interface of an embodiment of the present application;

FIG. 13 is a schematic view of a user interface of an embodiment of the present application;

fig. 14 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The terms "first," "second," and the like, as referred to in the embodiments of the present application, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance, nor order. Furthermore, the terms "comprises" and "comprising," as well as any variations thereof, are intended to cover a non-exclusive inclusion, such as a list of steps or elements. A method, system, article, or apparatus is not necessarily limited to those steps or elements explicitly listed, but may include other steps or elements not explicitly listed or inherent to such process, system, article, or apparatus.

It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.

In the scheme provided by the embodiment of the application, the electronic device can determine the recovery percentage corresponding to a time period according to the motion data of the user in the time period, and the recovery percentage reflects the change of the motion body substance or the motion function in the recovery time along with the time. In this way, the electronic device may generate a prompt for directing the user to move, e.g., directing the intensity of the user's movement, based on the percentage of recovery. Therefore, the electronic equipment can provide effective guidance for the movement of the user by the method so as to accurately acquire the excessive recovery, thereby improving the use experience of the user. The recovery percentage may include a recovery percentage assumed to be after ending the motion at the ending time of the time period, e.g., the recovery percentage may include recovery percentages at a plurality of time points after ending the motion at the current time, assuming the ending time of the time period is the current time.

First, some terms in the embodiments of the present application are explained to facilitate understanding of the movement guidance method of the embodiments of the present application.

Sports profit, which is a representation of the profit of sports organism material or function that a user can obtain in one sport. The exercise yield may be a difference between exercise body substances or functions within the recovery time after the exercise and exercise body substances or functions before the exercise. In some embodiments, the exercise body substance or function during the recovery time may be the exercise body substance or function at a time during the recovery time. For example, the exercise profit is 0, which indicates that the exercise body material or function at a time point in the recovery time after the current exercise is 0 different from the exercise body material or function before the current exercise, that is, no profit is obtained at the time point. The exercise profit is a negative number, which indicates that the difference between the exercise body material or function at a time within the recovery time after the exercise and the exercise body material or function before the exercise is a negative number, that is, the negative profit at the time. The exercise yield is a positive number, which indicates the exercise body material or function at a time within the recovery time after the exercise, and the difference between the exercise body material or function before the exercise is a positive number, that is, the positive yield at the time. In other words, the athletic benefits are related to the user's exercise and recovery time. As the recovery time varies, the athletic return also varies.

In some embodiments, the exercise body substance can be an amount of exercise body substance. For the existence of a moment positive income, the recovery time means that the sports organism substance or function can be recovered to exceed the original sports organism substance or function, so that the function and capacity of the sports organism can be improved. It is understood that the exercise body substance may be protein, myoglycogen, phosphate, glycogen, etc. The embodiment of the present application does not limit the specific contents of the sports organism substance. Wherein the function may be cardiopulmonary function, maximal strength, etc.

In another expression of the exercise benefit, the exercise benefit may be a ratio of exercise body substances or functions at a time within the recovery time after the exercise to exercise body substances or functions before the exercise. For example, the exercise profit is 1, which indicates that the ratio of the exercise body material or function at a time within the recovery time after the current exercise to the exercise body material or function before the current exercise is 1, that is, there is no profit at the time; the exercise income is less than 1, which represents that the ratio of the exercise organism substance or function at a moment in the recovery time after the exercise to the exercise organism substance or function before the exercise is less than 1, namely the moment is negative income; the exercise profit is larger than 1, which means that the ratio of the exercise body material or function at a moment in the recovery time after the exercise to the exercise body material or function before the exercise is larger than 1, namely the moment is positive profit. The following examples are illustrated in the representation of ratios.

For example, the exercise profit may be a ratio of exercise body substances or functions at a time within a recovery time after the exercise is finished at the current time to exercise body substances or functions before the exercise, that is, assuming that the finishing time of the exercise is the current time. For example, the exercise yield may be a ratio of the number of myoglycogen in the recovery time after the current exercise is finished to the number of myoglycogen before the current exercise. It is understood that it is not possible to measure moving body substances or functions in the body of a user in real time in daily life. The exercise yield in the embodiment of the present application is an estimation value determined by the training effect calculation, and the estimation value may be referred to as a recovery percentage, that is, the exercise yield is expressed by using the calculated recovery percentage. For example, as shown in fig. 5A, assuming that the user ends the exercise at point B, the exercise yield varies with the recovery time. Illustratively, the change in the athletic benefit may be represented by a recovery curve, as shown by curve C2 at point B in FIG. 5A, with the athletic benefit changing with the recovery time. Note that the coordinate system of the restoration curve is not shown in fig. 5A, that is, the horizontal axis of the coordinate system of the restoration curve is different from the horizontal axis of the coordinate system of fig. 5A. The vertical axis of the coordinate system of fig. 5A is the percentage axis and the vertical axis of a point on the curve C2 may be in the form of the percentage of recovery of the user at a time, the percentage of recovery representing the percentage of the ratio of the user's moving body mass or function to the user's original moving body mass or function. The ordinate of the origin of the coordinate system of fig. 5A is 100%. The original exercise body substance or function may refer to the exercise body substance or function before the present exercise.

Of course, it can be understood that the ending time of the exercise may be any other time. For example, the exercise may be one exercise in the training plan, and the ending time of the exercise may be the ending time of the exercise in the training plan, which is a time in the future. The embodiment of the present application does not specifically limit the ending time of the current exercise.

Training Effect (TE), a manifestation of the amount of motion in a single exercise. For example, the training effect may be represented in a specific numerical value. Illustratively, the training effect can be represented by a value in a value range of [0-5], and the larger the value is, the larger the amount of exercise of the exercise is. In one implementation, the training effect may be calculated by first calculating an excess-oxygen consumption after Exercise (EPOC) through machine learning or deep learning using a heart rate, and then mapping the EPOC to a training effect in accordance with the daily activity of the individual. In other words, the heart rate of the user may be determined by the sensor, and the EPOC is calculated from the heart rate data acquired. And determining the training effect of the user in the exercise according to the EPOC and the historical data. In another implementation, the calculation method of the training effect may also be determined based on other parameters. The other parameters may include, but are not limited to, a number of steps, a speed, or other motion data parameters, for example, which are not specifically limited in this embodiment. Excess-oxygen consumption (EPOC) after exercise, oxygen depletion during recovery after exercise to replace the exercise, and oxygen consumption to restore the body at a high level of metabolism to a resting level after exercise.

Reference to an exercise in accordance with embodiments of the present application is explained, where an exercise refers to a period of time, and the exercise may be any one form of exercise or any combination of forms of exercise, such as, for example, running outdoors, running indoors, riding outdoors, running off-road, or cycling indoors, among others. The length of the time period of one exercise may be any time period such as 30 minutes (min), 45 minutes (min), or 1 hour (h). The time interval between different motions may be greater than or equal to a preset threshold, where the preset threshold may be flexibly set according to requirements, and the preset threshold is used for the terminal device to determine whether motions of the user in multiple time periods belong to different motions based on the threshold, for example, the preset threshold may be 3 hours, 8 hours, 12 hours, or 1 day, and the like. Taking the preset threshold as 3 hours as an example for illustration, when the starting time of the current exercise of the user is 4 hours apart from the ending time of the previous exercise of the user, the current exercise and the previous exercise of the user belong to different exercises. Referring to fig. 1, the vertical stripe regions indicate motion, one vertical stripe region may indicate one motion, and the blank region indicates no motion, and there is no motion between different motions, in other words, there is a time interval between different motions. This exercise may also be referred to as current exercise, and the like, and the embodiment of the present application is not necessarily illustrated. The other motions before the current motion may be referred to as the past N motions or the historical N motions, for example, the historical 1 motion, which may be a motion before the current motion that is closest to the current motion time, and may be specifically shown in fig. 1. The historical 2 movements, which may be the movement next closest to the current movement time before the current movement, may be specifically shown in fig. 1. And N is any positive integer greater than 1.

It is understood that this movement and other movements before this movement may be considered as movements in different time periods, for example, a movement in a first time period, a movement in a second time period, … …, and a movement in an nth time period.

Excessive recovery (excessive recovery) refers to the situation that after one training, the motor function of the human body gradually rises to exceed the original physical ability level. At this stage, the body's consumption of the exercise body's substances and functions during the exercise can not only be restored, but even exceed the original levels. After a certain period of time, the water level returns to the original level. For example, as shown in fig. 5A, it is assumed that the user starts the exercise at the origin of the coordinate system, and as the exercise progresses this time, the exercise body material is consumed or the function is reduced, that is, as shown by the solid line in fig. 5A, this stage is the exercise body material or function reduction stage. Assuming that the user stops the exercise at the time corresponding to the point B and does not continue the exercise within the recovery time, the exercise yield varies with the recovery time as shown in a curve C2. With the increase of the recovery time, the exercise yield is gradually increased, and after the highest point is reached, the exercise yield is gradually recovered to the level before the exercise. Illustratively, point P1 is where the athletic yield is just zero, i.e., the body material in the user's body that is consumed by exercise returns to the level just prior to exercise. The point P2 is when the sports profit is highest, and the point P3 is when the sports profit returns to zero. The excess recovery stage is defined as between P1 and P2, and the regression stage is defined as between P2 and P3. If the user makes the next exercise between the points P1 and P2, i.e., the body material or function is moving for a period of time exceeding the original level, the user can keep the body material or function recovered excessively from fading away and can gradually accumulate the training effect. If the user exercises with the physical function and the body material not recovered, the function and the body material are degraded.

The training according to the embodiment of the present application is synonymous with exercise, and for example, one training may be referred to as one exercise. Different forms of exercise may also be referred to as different forms of training, such as strength training, running training, and the like.

The meaning of the excessive recovery is that the user can be helped to make scientific exercises, so as to more effectively improve the functions and the capabilities of the exercise body of the user, for example, improve one or more items of strength, speed or endurance of the exercise body. The exercise guidance method provided by the embodiment of the application can calculate the recovery percentage through the exercise data, and further helps the exercise to make scientific exercise based on the recovery percentage, so that the user can obtain excessive recovery, and the function and the capability of the exercise body of the user can be effectively improved.

It is understood that the excess recovery is related to the type of exercise and body material. For example, if the user is performing strength training, since strength training primarily encourages the over-recovery of protein in muscle, the time of over-recovery of protein may occur on day 3. So that the user's excessive recovery of this exercise may occur on day 3.

The application provides a motion guidance mode, and the relation between the predicted recovery percentage and the recovery time of the current motion is determined through historical data and the training effect of the current motion. The terminal device may prompt the user for the determined relationship, such as curve C1, C2, or C3 shown in fig. 5A. Therefore, the user can determine the time of the next movement according to the curve, and the beneficial effect of the excess recovery is more effectively utilized.

The electronic equipment in the embodiment of the application is portable intelligent equipment. The electronic device has sensors embedded therein, or the electronic device can establish a connection with other electronic devices having sensors. Some examples of electronic devices are: smart mobile phone, smart watch, intelligent bracelet, smart glasses and other motion accessories or wearable equipment etc. do not do the restriction here in this application embodiment.

A scenario in which the embodiment of the present application can be applied is described below, and fig. 2 shows a structure diagram of a possible electronic device in which the embodiment of the present application can be applied. Referring to fig. 2, the electronic device 100 includes: communication unit 101, processor 102, memory 103, display unit 104, input unit 105, audio circuitry 106, sensor 107, camera 108, and positioning module 109. The respective components of the electronic apparatus 100 will be specifically described below with reference to fig. 2.

The communication unit 101 is used to implement data communication between the electronic apparatus 100 and other electronic apparatuses. Optionally, the communication unit 101 may include a wireless fidelity (WiFi) module 1011 and/or a bluetooth (bluetooth) module 1012.

Both the bluetooth wireless technology and the WiFi technology belong to short-distance wireless transmission technologies, and the electronic device 100 can be connected to an Access Point (AP) through the WiFi module 1011, thereby implementing access to a data network, and communicating with other electronic devices or accessories (such as a far-end camera) connected to the AP through the AP. The electronic device 100 establishes a connection directly with other electronic devices or accessories through the bluetooth module 1012. For example, in this embodiment of the application, the electronic device 100 may receive, through the communication unit 101, motion data or a training effect of the user's motion, provided by another device, where the other device is a device that can acquire the motion data of the user, such as a wearable device: sports watches, etc.

Radio Frequency (RF) circuitry may also be included in the communication unit 101. For example, when the electronic device 100 is a smart phone, the electronic device 100 can establish a wireless connection with a base station through the RF circuit 210, and implement a call or access to a data network through a mobile communication system.

The terminal device 100 may also include a communication interface for physically interfacing with other devices. The communication interface may be connected to the communication interface of the other device through a cable, so as to implement data transmission between the electronic device 100 and the other device. For another example, in this embodiment of the application, the terminal device 100 may receive, through the communication interface, the motion data or the training effect of the user's motion, which is provided by another device, where the another device is a device that can acquire the motion data of the user, such as a wearable device: smart watches, and the like.

The memory 103 may be used to store software programs as well as data. The processor 102 executes various functional applications and data processing of the electronic device 100 by executing software programs and data stored in the memory 103. In the embodiment of the present application, the software program may be an exercise health program, an exercise recording program, etc., and the data may be recovery percentages at different time points.

The memory 103 may mainly include a program storage area and a data storage area. Wherein, the storage program area can store an operating system, various application programs and the like; the storage data area may store user input or data created during the execution of the software program by the electronic device 100, and the like. In addition, the memory 103 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. For example, in the present embodiment, an exercise health program, an exercise recording program, and the like may be stored in the storage program area, and the recovery percentages of the user at different time points may be stored in the storage data area.

The input unit 105 may be used to receive character information and signals input by a user. Alternatively, the input unit 105 may include a touch panel 1051 and other input devices (e.g., function keys). The touch panel 1051, also referred to as a touch screen, can collect touch operations of a user thereon or nearby, generate corresponding touch information, and send the touch information to the processor 102, so that the processor 102 executes a command corresponding to the touch information. The touch panel 1051 may be implemented by various types such as resistive, capacitive, infrared, and surface acoustic wave. For example, in the embodiment of the present application, the user may start an exercise health program of the electronic device through the touch panel 1051.

The display unit 104 is used for presenting a user interface and realizing human-computer interaction. For example, the display unit 104 may display information input by the user, or information provided to the user, and contents of various menus, interfaces of the respective APPs, and the like of the electronic apparatus 100. In the embodiment of the present application, after the processor 102 calculates the recovery percentage, the recovery percentage can be displayed in the display unit 104 to provide the user with motion guidance, so as to accurately obtain the excessive recovery.

The display unit 104 may include a display panel 1041, and the display panel 1041 may be configured in the form of a Liquid Crystal Display (LCD), an organic light-emitting diode (OLED), or the like.

It should be noted that the touch panel 1051 can cover the display panel 1041, and although in fig. 2, the touch panel 1051 and the display panel 1041 are implemented as two independent components to implement the input and output functions of the terminal device 100, in the embodiment of the present application, the touch panel 1051 and the display panel 1041 can be integrated (i.e., touch the display screen) to implement the input and output functions of the electronic device 100.

The processor 102 is a control center of the electronic device 100, connects various components by using various interfaces and lines, executes various functions of the electronic device 100 and processes data by running or executing software programs and/or modules stored in the memory 103 and calling data stored in the memory 103, thereby implementing various services based on the electronic device 100. For example, the processor 102 is connected to the sensor 107 through an internal interface and a wire, or is connected to other electronic devices through any module in the communication unit 101, so as to obtain exercise data or training effect of the user; and the processor 102 may run an exercise health program stored in the memory 103 to determine a percentage of recovery based on the exercise data or training effect of the user, and provide exercise guidance to the user via the percentage of recovery.

Alternatively, the processor 102 may include one or more processing units. The processor 102 may integrate an application processor, which primarily handles operating systems, user interfaces, applications, etc., and a modem processor, which primarily handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 102.

The audio circuitry 106 (including the speaker 1061 and the microphone 1062) may provide an audio interface between a user and the electronic device 100. The audio circuit 106 may transmit the electrical signal converted from the received audio data to the speaker 1061, and the audio signal is converted into a sound signal by the speaker 1061 and output. On the other hand, the microphone 1062 converts the collected sound signals into electrical signals, which are received by the audio circuit 106 and converted into audio data for further processing, such as transmission or storage. In the embodiment of the present application, after the processor 102 determines the recovery percentage of the user at a plurality of time points, a voice prompt may be output through the audio circuit 106 and the speaker 1061 thereof to guide the user to move so as to obtain the excessive recovery. In the embodiment of the present application, the audio circuit 106 and the microphone 1062 thereof may also collect voice information of the user to determine whether the user starts exercise to determine whether to start the exercise health program.

The electronic device 100 may also include one or more sensors 107, such as light sensors, motion sensors, ultrasonic sensors, and other sensors. The electronic device 100 can implement a motion recording function and a motion guiding function according to the user motion data collected by the sensor 107.

The electronic device 100 may also include a camera 108 inside to capture images. Of course, the electronic device 100 may not include the camera 108. For example, the electronic device 100 may be a smart watch or a smart bracelet that does not include a camera.

Optionally, the electronic device 100 may further include a positioning module 109, which may measure geographic location data of the user. When the user is doing outdoor long-distance sports (e.g., running outdoors, riding outdoors, etc.), the electronic device 100 may implement an exercise recording function according to the geographic location data of the user. The positioning module 109 may be a Global Positioning System (GPS) module or a beidou module, and the embodiment of the present application is not limited herein.

It is to be understood that the structure of the terminal device shown in fig. 2 does not constitute a limitation on the electronic device, and the electronic device provided in the embodiments of the present application may include more or less components than those shown, or combine some components, or arrange different components.

The electronic device may execute the exercise guidance method according to the embodiment of the present application to determine a recovery percentage corresponding to the exercise data or the training effect according to the exercise data or the training effect of the user, and push prompt information to the user according to the recovery percentage to guide the user to exercise. Since the recovery percentage is used to represent the exercise yield, it reflects the ratio of the exercise body substance or function in the recovery time to the exercise body substance or function before the exercise. The prompt information generated based on the recovery percentage can guide the user to adjust the exercise intensity, time and the like of the user, so that the user is helped to obtain the excessive recovery, and the beneficial effect of the excessive recovery is effectively utilized. The motion data of the user can be collected by the electronic device or other electronic devices and sent to the electronic device executing the motion guidance method of the embodiment of the application.

Fig. 3A is a schematic diagram illustrating a scenario in which the embodiment of the present application may be applied. Referring to fig. 3A, the application scenario includes an electronic device 31 and an electronic device 32, where the electronic device 32 may collect motion data of a user through a sensor of the electronic device 32, and send the motion data to the electronic device 31, the electronic device 31 determines a recovery percentage corresponding to the motion data according to the motion data of the user, and pushes prompt information to the user according to the recovery percentage to guide the user to move. As shown in fig. 3A, the electronic device 31 may be a smart phone, and the electronic device 32 may be a smart watch. It can be understood that, in an implementation manner, the electronic device 32 may collect motion data of the user through a sensor of the electronic device, determine a training effect according to the motion data, send the training effect to the electronic device 31, determine a recovery percentage corresponding to the training effect according to the training effect of the user by the electronic device 31, and push prompt information to the user according to the recovery percentage to guide the user to move. In some embodiments, the electronic device 31 may also upload the motion data to the server 33 to implement a motion recording function.

Fig. 3B is a schematic diagram illustrating another scenario in which the embodiments of the present application may be applied. Referring to fig. 3B, the application scenario includes the electronic device 32, where the electronic device 32 may collect motion data of a user through a sensor thereof, determine a recovery percentage corresponding to the motion data according to the motion data of the user, and push prompt information to the user according to the recovery percentage to guide the user to move. As shown in fig. 3B, the electronic device 32 is a smart watch. In some embodiments, the electronic device 32 may also upload the motion data to the server 33 to implement a motion recording function.

It can be understood that, in another scenario, the electronic device 32 in fig. 3B may also be replaced with the electronic device 31, that is, the electronic device 31 may collect the motion data of the user through its own sensor, determine the recovery percentage corresponding to the motion data according to the motion data of the user, and push the prompt information to the user according to the recovery percentage to guide the user to move. The electronic device 31 may be a smartphone.

The following describes the exercise guidance method according to the embodiment of the present application with specific examples. For example, the embodiment of the present application is exemplified by a user running.

Fig. 4 is a flowchart of a motion guidance method according to an embodiment of the present application, where an execution subject according to the embodiment of the present application may be the electronic device or a processor of the electronic device, and as shown in fig. 4, the method according to the embodiment may include:

step 101, receiving a first operation of a user.

The electronic device detects a first operation of the user to trigger the following steps to determine a recovery percentage according to the motion data, and guides the user to move through the recovery percentage, and the specific implementation manner of the electronic device can be seen in the explanation of the following embodiments. It is understood that the electronic device detects the first operation, and may also be understood as receiving a first instruction of the user, where the first instruction is generated from the first operation of the user.

For example, the first instruction may be an instruction to start an exercise health program, or an instruction to start an exercise recording function in some form of exercise, or a power-on instruction of the electronic device, or a message sent by another electronic device after a communication connection is established with the other electronic device. For example, when the electronic device is a smartphone, the other electronic device may be a smart watch, a smart bracelet, a smart ring, or smart glasses, etc. The sport form can be any one or more of outdoor running, indoor running, outdoor riding and the like. The communication connection may be a bluetooth connection or the like. The message may be a connection success message.

The first instruction may result from a user operating the electronic device. When the first instruction may be an instruction to start an exercise health program, or to start an exercise recording function of a certain exercise form, or to start up an electronic device, the electronic device may receive the first instruction in the following manner:

the first method is as follows: the electronic device receives the first instruction input by the user through the touch display screen, for example, the electronic device receives the first instruction input by the user through the touch display screen. In one example, the user clicks a graphic component in the user interface, which may be an icon of an exercise health program, by using a finger, a stylus pen, or another control object that can be detected by touching the display screen, and the electronic device obtains the first instruction, that is, detects the first operation of the user, after detecting the above-mentioned clicking operation by touching the display screen.

Referring to fig. 9, the user clicks the "sports health" icon in the user interface with a finger, and the electronic device obtains the first instruction after detecting that the user clicks the "sports health" icon through the touch display screen.

For another example, the graphical component may be a "start motion" graphical component that triggers the electronic device to collect and record motion data for the user.

Referring to fig. 9, a user clicks a "start motion" graphic component in a user interface by a finger, and in the embodiment of the application, after detecting that the user clicks the "start motion" graphic component by touching a display screen, the electronic device obtains the first instruction.

As another example, the image component may be a graphical component in the form of sports, such as an "outdoor running" graphical component, which in this embodiment is used to trigger the electronic device to collect and record sports data of the user during outdoor running.

Referring to fig. 12, a user clicks the "outdoor running" graphic component in the user interface by a finger, and in the embodiment of the application, after detecting that the user clicks the "outdoor running" graphic component through the touch display screen, the electronic device obtains the first instruction.

The second method comprises the following steps: the electronic device can receive the first instruction input by the user through the function keys of the electronic device. The function key can be one key or a plurality of keys such as a startup and shutdown key, a volume increasing and decreasing key and the like. For example, the user presses the power on/off key for a short time, in this embodiment of the application, the electronic device obtains the first instruction after detecting that the user presses the power on/off key for a short time.

The third method comprises the following steps: the electronic device receives the first instruction input by the user through the microphone. For example, after receiving a voice command from a user, the microphone 1062 in the audio circuit 106 in the electronic device converts the voice command into an electrical signal, and the audio circuit converts the electrical signal into audio data and sends the audio data to the processor 102 of the electronic device, and the processor 102 processes the audio data to obtain the first command.

The method is as follows: the electronic device receives the first instruction input by the user through one or more of the sensor and the camera. For example, the processor 102 of the electronic device may receive the first instruction input by the user through one or more of the sensor 107, or the camera 108. Illustratively, the user may instruct the exercise health program to be started by a gesture, and the processor 102 may obtain the first instruction after detecting the gesture by one or more of the sensor 107 and the camera 108.

And 102, responding to the first operation, and acquiring the motion data of the current motion of the user.

The exercise data of this exercise may include data generated during the exercise of the user, such as heart rate, number of steps, exercise time, and the like, and the specific content of the exercise data is not limited thereto. For example, the exercise data of the exercise may include one or more items of data such as heart rate or step number at different time points.

And the electronic equipment responds to the first instruction, and obtains the motion data of the current motion of the user through a sensor of the electronic equipment, other electronic equipment or a server.

For example, in some embodiments, the motion data may originate from a sensor of the electronic device itself, such as sensor 107 shown in FIG. 2. Illustratively, as shown in fig. 3B, the main execution body of the embodiment of the present application is an electronic device 32, and a processor of the electronic device 32 receives a first instruction and collects motion data of a user through a sensor of the electronic device 32 in response to the first instruction. In other embodiments, the motion data may be derived from other electronic devices, for example, as shown in fig. 3A, an execution subject of the embodiment of the present application is the electronic device 31, a processor of the electronic device 31 receives the first instruction and obtains the motion data of the user collected by the sensor of the electronic device 32 in response to the first instruction, and after the electronic device 32 establishes a communication connection with the electronic device 31, the electronic device 32 may send the motion data of the user to the electronic device 31 in real time or periodically when the sensor of the electronic device 32 collects the motion data of the user. In other embodiments, the motion data is derived from a server, for example, as shown in fig. 3A, an execution subject of the embodiment of the present application is an electronic device 31, a processor of the electronic device 31 receives a first instruction, and in response to the first instruction, obtains, by the server, motion data of a user collected by a sensor of the electronic device 32, where the electronic device 32 and the electronic device 31 may log in to the same account, and the electronic device 31 obtains, from the server, the motion data of the same account, where the motion data may be derived from the electronic device 32.

Optionally, in some embodiments, in response to the first instruction, the processor of the electronic device may further obtain historical motion record information, which may include motion data of historical motions, e.g., motion data of historical N motions. The motion data of the historical motion may be stored in the server, and after the electronic device receives the first instruction, the electronic device may obtain the motion data of the historical motion from the server. The exercise data of the historical exercise may include one or more items of data such as heart rate, or number of steps at different time points. In another implementation, the historical movement record information may include training effects and movement end times of the historical movement. The historical movement record information may further include one or more items of information such as historical movement duration or movement starting time.

And 103, determining the training effect of the exercise according to the exercise data of the exercise of the user.

The training effect may represent the amount of exercise of this exercise, as described above, for example, the training effect may be determined according to a heart rate, and the specific determination manner of the training effect may refer to the explanation of the foregoing embodiment, which is not described herein again. For another example, the training effect may be determined by one or more of the number of steps or other exercise data parameters, which are not necessarily illustrated in the embodiments of the present application.

The training effect is related to the exercise time, i.e. to the length of the period of time during which the exercise is performed, the intensity of the exercise, etc. Exemplarily, a user performs outdoor running training, the user runs for 5 minutes outdoors, the training effect of the user exercise at this time is the training effect of the user running for 5 minutes outdoors, then the user continues to run outdoors, along with the lapse of time, the user runs for 10 minutes outdoors, and the amount of exercise of this time is the amount of exercise of the user running for 10 minutes outdoors, that is, the training effect is the training effect of the user running for 10 minutes outdoors. In other words, the training effect of the exercise reflects the real-time exercise amount of the exercise of the user.

The training effect of the exercise is determined in the exercise process of the user, and the training effect changes along with the increase of the exercise time of the user. The electronic device determining the training effect of the exercise may be a periodic determination, a real-time determination, or a determination based on a user trigger.

For example, the electronic device may determine the training effect of the exercise periodically, that is, the training effect of the exercise is determined at fixed time intervals, and the time intervals may be any time length, for example, 3 minutes, 5 minutes, and the like. For example, the time interval is 5 minutes, i.e. the training effect is determined every 5 minutes. For example, after the user starts running outdoors, one training effect is determined when the user runs for 5 minutes, and one training effect is determined when the user runs for 10 minutes.

For example, the electronic device may determine the training effect of the exercise in real time, that is, after the user starts to exercise, the training effect of the exercise is determined in real time, and the training effect changes in real time along with the exercise of the user.

The electronic device may determine the training effect of the exercise based on user triggering, that is, after the user starts the exercise, when the electronic device receives an instruction for determining the training effect of the exercise, the electronic device determines the training effect of the exercise based on the instruction. The instructions for determining the training effect of the exercise may be instructions for displaying a percentage of recovery. Taking the embodiment shown in fig. 9 as an example, when the user clicks the "recovery curve" displayed on the user interface 12, the electronic device determines the training effect of the exercise this time, determines the recovery curve based on the training effect, and switches to the user interface 13. For another example, referring to fig. 12, when the user performs a left-sliding operation on the user interface 32, the electronic device determines a training effect of the exercise this time based on the left-sliding operation, determines a recovery curve based on the training effect, and switches to the user interface 33.

And step 104, determining the recovery percentage corresponding to the training effect according to the training effect of the exercise.

After the user starts a movement, along with the movement of the user, the training effect of the movement changes, and the recovery percentage value and the change trend also change in the recovery period corresponding to the training effect. For example, as shown in fig. 5A, when the time of the user's movement reaches the time corresponding to point a, the corresponding percentage of recovery may vary with the recovery time as shown in curve C1. When the time of the user's motion reaches the time corresponding to point B, the corresponding percentage of recovery may change with recovery time as shown by curve C2. When the time of the user's movement reaches the time corresponding to point C, the corresponding percentage of recovery may change with recovery time as shown by curve C3. It can be seen that the recovery percentage values and the variation trends in the recovery time are different for different training effects.

Similar to the training effect of the exercise, the recovery percentage may be determined periodically, in real time, or based on user triggers. It should be noted that the period for determining the recovery percentage may be the same as the period for determining the training effect, or may be different from the period for determining the training effect.

The recovery percentage corresponding to the training effect may include the recovery percentage at each time within the recovery time.

The recovery percentage is used to represent the athletic return, as described above, which may be no return, negative return, or positive return. For example, when the time of the user movement reaches the time corresponding to the point a at the beginning stage after the user starts a movement, it can be determined through the above steps that the value and the variation trend of the recovery percentage in the recovery time when the user movement ends the movement at the point a can be as shown by a curve C1, as shown by a curve C1, and the maximum value of the recovery percentage in the recovery time is 1, that is, it indicates that the movement ends at the point a and positive benefits cannot be obtained. Assuming that the user does not end the exercise at the point a, but continues the exercise, when the time of the user's exercise reaches the time corresponding to the point B, it can be determined through the above steps that the value and the variation trend of the recovery percentage can be as shown by a curve C2 in the recovery time when the user ends the exercise at the point B, as shown by a curve C2, and the maximum value of the recovery percentage in the recovery time is greater than 1, which indicates that the user can obtain a positive benefit when the user ends the exercise at the point B. Assuming that the user does not finish the exercise at the point B, the user still continues to run, and the excessive exercise may cause the body energy substance of the user not to recover within a period of time, and a negative benefit is generated, for example, when the exercise time of the user reaches the time corresponding to the point C, it may be determined through the above steps that within the recovery time of finishing the exercise at the point C, the value and the variation trend of the recovery percentage may be as shown by a curve C3, as shown by a curve C3, the maximum value of the recovery percentage within the recovery time is less than 1, that is, it indicates that the exercise at the point C cannot obtain a positive benefit. The embodiment of the application can determine the recovery percentage through the steps, so that exercise guidance is provided for the user based on the recovery percentage, for example, when positive income can be obtained through the determination of the recovery percentage, the user is prompted to obtain the positive income after the exercise is recovered, so that the user is prompted to reasonably stop the exercise, and negative income caused by excessive exercise is avoided.

In some embodiments, after the electronic device determines the recovery percentage, the recovery percentage may be displayed to the user. For example, the electronic device may display the recovery percentage versus the movement time and the recovery time in a curved manner. Such as curve C1, curve C2, and curve C3 shown in fig. 5A. As another example, the electronic device may display the recovery percentage in the form of a histogram. Such as a histogram as shown in fig. 5B. The specific form of the presentation is not limited thereto. For example, the horizontal axis of the graph may be a time axis, and the vertical axis may be a recovery percentage axis, the graph being used to represent the values of the recovery percentage at respective times within the recovery time after the exercise is ended at one time. For another example, the horizontal axis of the histogram may be a time axis, and the vertical axis may be a recovery percentage axis, and the histogram indicates the value of the recovery percentage at each time point in the recovery time after the end of the exercise at one time point. In some embodiments, the histogram may show the maximum recovery percentage in the recovery time, i.e. the maximum recovery percentage in the recovery time for ending the current movement at point a is at t, as shown in fig. 5B_AA value of 1 indicates no benefit in the recovery time. The maximum value of the recovery percentage in the recovery time for ending the motion at the point B is t_BI.e., greater than 1, indicates a positive gain in recovery time. The maximum value of the recovery percentage in the recovery time for ending the motion at the point C is t_CThat is, less than 1, indicates that the athletic gains are all negative gains in the recovery time.

An implementation manner may determine whether there is a recovery percentage greater than 1 in recovery percentages at different time points within a recovery time after the exercise is ended at a time, if so, it may be determined that the exercise is ended at the time to obtain a positive benefit, if not, it may be determined whether there is a recovery percentage equal to 1 in recovery percentages at different time points, if so, it may be determined that the exercise is ended at the time, and the original body material or function level is at most restored within the recovery time, i.e., no benefit is obtained, and if not, it may be determined that the exercise is ended at the time, and both of the gains are negative benefits within the recovery time.

Illustratively, the specific illustration form of the recovery percentage is a curve, which may be a recovery curve, and an example is that the horizontal axis of the recovery curve is a time axis, and the vertical axis is a percentage axis. Referring to fig. 5A, fig. 5A is a schematic diagram of a recovery curve provided in an embodiment of the present application, where a solid line is a percentage of the current exercise, also called a exercise percentage,the exercise percentage may represent a ratio of the exercise body material or function at a moment in the exercise time to the exercise body material or function before the present exercise. The dotted line is the recovery percentage after the end of the motion, the end time of the motion is taken as the current time, the dotted line is the recovery percentage after the motion is stopped at the current time, the current time is the time point corresponding to the intersection of the solid line and the dotted line, that is, the motion is stopped at the current time, the time corresponding to the dotted line is the future recovery time, that is, the time after the motion is ended at the current time, the recovery time axis is not shown in fig. 5A, and fig. 5A shows the change of the recovery percentage in the recovery time with the time. For example, as shown in fig. 5A, the origin of the coordinate system is the starting time of the current exercise, and the percentage of the exercise at the starting time of the current exercise is 100%, that is, the user returns to the original level before starting the current exercise. After the exercise starts, the value of the exercise percentage begins to decrease as the exercise is consumed. For example, as exercise is consumed, the amount of body substances such as glycogen and fat in the body of the user gradually decreases, and the exercise percentage gradually decreases. For example, at the current time t₀At point, its percent recovery is P (t)₀) The solid line includes the start time to t of the current exercise₀The percentage of movement of the point, i.e. the percentage of the body material or function of the exercise at the time of the present exercise, and the dotted line is included at t₀The recovery percentage after the point finishes the exercise, that is, the recovery percentage after the exercise is finished, as shown by a dotted line in the figure, after the exercise is finished, the value of the recovery percentage starts to rise along with rest supplement. For example, as the user rests and supplements, the number of myoglycogen in the user gradually increases, and the percentage of recovery gradually increases. In some cases, the recovery percentage after the exercise is finished can be increased to 100%, that is, the exercise is recovered to the original level, and the exercise does not have profit, for example, t₀When the time is the time corresponding to the point a as shown in fig. 5A, the curve C1 is the recovery percentage after the movement is finished at the time corresponding to the point a, and there is no excessive recovery in the present movement. In some cases, the percentage of recovery after the end of the exerciseThe ratio may be increased to over 100%, i.e. over the original level, this exercise may obtain positive benefits, i.e. this exercise may obtain excessive recovery, e.g. t₀The curve C2 is the recovery percentage after ending the exercise at the time corresponding to the point B, which can obtain the positive benefit, when the time corresponding to the point B is shown in fig. 5A. In some cases, the percentage of recovery after the end of the exercise cannot be recovered to 100% over a period of time, i.e., there is no over-recovery for the exercise, e.g., t₀As shown in fig. 5A, when the time corresponds to point C, the curve C3 is the recovery percentage after the movement is finished at the time corresponding to point C, the excessive recovery cannot be obtained in the movement, and the body material or function cannot be recovered to the original level in the recovery time. Therefore, different amounts of exercise and different end times in the exercise process correspond to different dotted lines, that is, different recovery curves correspond to the exercise after the exercise is finished, so that the amount of exercise, the exercise end time and the like of the user in the exercise can be guided based on the recovery curves, and the user can obtain corresponding exercise benefits after the exercise is finished.

For example, after the user starts running, the number of in vivo myoglycogen decreases with exercise consumption, so that the exercise percentage during the exercise of this time decreases, and when the current time is the time corresponding to the point a, the recovery percentage during the recovery time after the exercise of this time is ended at the current time is determined through the above steps of the embodiment of the present application, that is, a curve C1 shown in fig. 5A is obtained, and as can be seen from the curve C1, the exercise of this time cannot obtain a positive benefit. Then, the user continues to run, the exercise percentage during the exercise of this time continues to decrease as the exercise is consumed, and when the current time is the time corresponding to the point B, the recovery percentage in the recovery time after the exercise of this time is finished at the current time is determined through the above steps of the embodiment of the present application, that is, the curve C2 shown in fig. 5A is obtained, as can be seen from the curve C2, the exercise of this time can obtain a positive gain, thereby obtaining an excessive recovery. After determining that the positive gain can be obtained by the exercise at this time, the electronic device may prompt the user to stop the exercise in time when the recovery curve starts to move down, so as to avoid a negative gain caused by the excessive exercise at this time, i.e., the user does not continue to run to a time corresponding to point C after the positive gain, i.e., curve C3 at point C does not appear, so as to ensure that the user has a positive gain during the exercise at this time, thereby obtaining excessive recovery, so as to promote the improvement of the function and capability of the exercise body of the user, for example, one or more items of strength, speed or durability of the exercise body are improved.

Illustratively, the specific display form of the recovery percentage is a bar graph, and an example is that the horizontal axis of the bar graph is a time axis and the vertical axis is a recovery percentage axis. Referring to fig. 5B, fig. 5B is a schematic diagram of a recovery percentage provided by an embodiment of the present application, which is illustrated with reference to the solid line of fig. 5A, for example, the recovery percentage after the end of the movement at the time corresponding to the point a may be referred to as t of fig. 5B_A，t_AThe time may be the time corresponding to the maximum value of the recovery percentage after the end of the exercise, and since the exercise is ended at the time corresponding to the point a, the positive gain cannot be obtained in the exercise, and the maximum value of the recovery percentage in the recovery time is 1, that is, there is no gain, t in fig. 5B_AThe corresponding recovery percentage was 1. In some cases, the recovery percentage after ending the motion at the time corresponding to B points may be seen in t of fig. 5B_B，t_BThe time corresponding to the maximum recovery percentage value after the end of the exercise may be used, and since the exercise is ended at the time corresponding to the point B, the exercise may obtain a positive benefit, so t in fig. 5B_BCorresponding to a recovery percentage of greater than 1. In some cases, the recovery percentage after ending the motion at the time corresponding to C point may be seen in t of fig. 5B_C，t_CThe time corresponding to the maximum recovery percentage value after the end of the exercise may be, since the exercise is ended at the time corresponding to the point C, the positive gain cannot be obtained in the exercise, and the maximum recovery percentage value in the recovery time is less than 1, that is, the negative gain, t in fig. 5B_CThe corresponding percent recovery is less than 1.

In some embodiments, in the histogram, the t_A、t_B、t_COr the exercise can be recovered after the exercise is finishedThe width of each column may be the duration of a time period, for example, the center of the time period may be the time period corresponding to the time corresponding to the maximum of the recovery percentage, than the time corresponding to the first 100% being reached. With t_BFor example, the starting position of the cylinder on the time axis may be a time point when the recovery percentage after the end of the exercise reaches 100% for the first time, and the ending position may be a time point when the recovery percentage after the end of the exercise reaches 100% for the second time.

In some embodiments, the historical exercise record information may be further combined to determine the recovery percentages of different time points within the recovery time after the exercise is finished at a time, so as to improve the accuracy of the subsequent exercise guidance.

Optionally, the embodiment of the present application may also provide guidance for the user's movement based on the recovery percentage determined in the above step through step 105.

And 105, generating prompt information according to the recovery percentage, wherein the prompt information is used for guiding the user to move.

The electronic device may display the reminder on a display screen, or may provide the reminder to the user by way of voice prompts, or a combination of display and voice prompts.

After the electronic device determines the recovery percentage, the electronic device may generate a prompt for directing the user to move based on the recovery percentage, for example, prompting the user to increase the intensity or speed of the movement, or prompting the user to stop the movement, or prompting the user to overrun the recovery period. The prompt message can be sent through a loudspeaker, or can be displayed to the user in a text mode or an image mode through a display panel. For example, when the electronic device is a smart watch and it is determined through the above steps that the maximum value of the recovery percentage in the recovery time of the current exercise of the user is equal to 1, i.e., there is no profit, the smart watch may display the contents shown in fig. 6 in the display screen, "the exercise effect will be improved if the speed is increased".

For example, in the exercise process, when it is determined that there is a positive profit in the recovery time through the above steps, a first prompt message may be generated, where the first prompt message is used to prompt the user that the exercise may obtain the excessive recovery, and optionally, the first prompt message is also used to prompt the time for obtaining the excessive recovery. In the exercise process, the situation that the excessive exercise cannot be obtained in the recovery time is determined through the steps, and when the maximum value of the recovery percentage in the recovery time is smaller than 1, second prompt information can be generated and used for prompting the user of the excessive exercise.

In some embodiments, the electronic device may also generate a third prompt to prompt the user for a start time for over recovery, such as the time at point P1 shown in fig. 5A, when it is determined that there is positive revenue within the recovery time. Optionally, the third prompt message is also used to prompt the user of the end time of the over recovery, such as the time at point P3 shown in fig. 5A. Optionally, the third prompting message is also used for prompting the next movement in the period of excessive recovery, for example, P1 to P2, or P1 to P3.

In addition, the electronic equipment can also store the motion data of the motion to the local or upload the motion data to the cloud server.

According to the exercise guidance method provided by the embodiment of the application, the electronic equipment can determine the training effect of the exercise according to the exercise data of the exercise of the user, and then determine the recovery percentage according to the training effect of the exercise so as to guide the user to exercise based on the recovery percentage. Therefore, the electronic equipment can determine the recovery percentages corresponding to the training effects in different time periods in the user movement process, and give prompt information to the user based on the recovery percentages, so that the user can timely adjust the movement amount and the movement ending time of the movement based on the prompt information to help the user to obtain excessive recovery, further effectively utilize the beneficial effect of the excessive recovery, and solve the problem that the user cannot know the movement income after the movement is ended and blindly move. Therefore, the electronic equipment can determine the recovery percentage in time by the method, and provides effective guidance for the movement of the user.

Explanation is given to the step 104 for determining the recovery percentage corresponding to the training effect according to the training effect of the exercise. The recovery percentage in the recovery time after the current time ends the exercise can be determined according to the training effect of the exercise, and the recovery percentage can be used as the percentage form of the exercise income. The specific implementation manner of determining the recovery percentage may be many, and one implementation manner is to determine the recovery percentage in the recovery time after the current exercise is finished at the current time according to a fused training effect, where the fused training effect is determined according to the training effect of the current exercise and the training effect of the historical exercise.

Fig. 7 is a flowchart of a method for determining a recovery percentage according to an embodiment of the present application, where an execution subject according to the embodiment of the present application may be the electronic device or a processor of the electronic device, and this embodiment is a specific implementation manner of the step 104, as shown in fig. 7, the method according to the embodiment may include:

and 1041, determining the fused training effect according to the training effect of the exercise, the training effects of the historical N exercises and the end time of the historical N exercises.

Illustratively, the fused training effect can be calculated by the following formula (1).

Wherein TE_newIs the post-fusion training effect, TE_nIs the training effect, TE₀Is the real-time training effect of this exercise, TE₁To TE_NIs the training effect of N historical exercises, a_nIs the weight of the nth training effect.

In some examples, a_nCan be calculated by the following formula (2).

Wherein, t₀Is the real time of the present movement, i.e. whenFront time, t₁To t_NIs the end time of the historical N movements, and c is a preset constant.

Step 1042, determining the recovery percentage of different time points after the current time finishes the exercise according to the fused training effect.

I.e. according to TE_newDetermining t₀Percent recovery at different time points thereafter.

For example, the recovery percentage of a single time point can be calculated by the following formula (3).

Wherein, P (t)₀) Is t₀Percent recovery of b₀、b₁、b₂The specific value of the preset constant can be flexibly set according to the requirement.

And then, calculating the recovery percentages of different time points in the recovery time according to the above formulas (1) to (3), wherein the different time points in the recovery time can be time points every preset time after the real-time of the motion, and the preset time can be any time such as 30 minutes, 15 minutes and the like. The percent recovery at different time points within the recovery time are concatenated to obtain a future recovery curve, such as the dashed line shown in fig. 5A. The user can view the recovery curve in real time during the exercise. Taking 30 minutes as an example, t in the above formula₀Respectively changed to t₀+30，t₀+2*30，t₀+3*30，……，t₀+ N + 30, determining t by the above formula₀+30，t₀+2*30，t₀+3*30，……，t₀Percentage recovery of + N30, resulting in t₀The point ends the recovery curve after the movement.

According to the exercise guidance method provided by the embodiment of the application, the electronic equipment can determine the training effect of the exercise according to the exercise data of the exercise of the user, and then determine the recovery percentages of different time points after the exercise of the current time is finished according to the training effect of the exercise, so as to guide the user to exercise based on the recovery percentages. Therefore, the electronic equipment can determine the recovery percentages corresponding to the training effects in different time periods in the user movement process, and provides prompt information based on the recovery percentages, so that the user can timely adjust the movement amount and the movement ending time of the movement based on the prompt information to help the user to obtain excessive recovery, the beneficial effects of the excessive recovery are effectively utilized, and the problem that the user cannot know the movement benefits after the movement is ended and blindly moves is solved. Therefore, the electronic equipment can determine the recovery percentage in time by the method, and provides effective guidance for the movement of the user.

When the recovery percentages of different time points after the current exercise is finished at the current time are determined, the accuracy of the determined recovery percentages can be improved by combining the training effect of the historical N exercises and the finishing time of the historical N exercises, so that accurate guidance is provided for the exercise of the user.

Fig. 8 is a flowchart of another exercise guidance method according to an embodiment of the present application, where an electronic device 31 is a smartphone and an electronic device 32 is a smartwatch, for example, and a dotted line in fig. 8 indicates optional, as shown in fig. 8, the method according to the present embodiment may include:

step 201, the smart watch establishes connection with the smart phone.

For example, a smart watch and a smart phone may establish a bluetooth connection. It is understood that the smart watch and the smart phone may also establish a connection through the server, for example, login to the same account. This step is an optional step, in other words, the smart watch and the smart phone may not establish a connection.

Step 202, receiving a first instruction.

For explanation of the first instruction, reference may be made to step 101 in the embodiment shown in fig. 4, which is not described herein again.

It should be noted that, in the above explanation of the first instruction, the first instruction is input by the user, for example, the user clicks a "start movement" button in the user interface, or the user operates the electronic device to establish a first connection with wifi of the gym, or the user operates the electronic device to establish a first connection with the treadmill, and the like. The first instruction may also be non-user input, for example, after the user enters the gym, the electronic device connects wifi of the gym, and the electronic device automatically generates the first instruction. The electronic equipment is not connected with the wifi of the gymnasium for the first time. For another example, the electronic device detects a treadmill and the electronic device automatically generates the first instruction. The electronic device is not connected to the treadmill for the first time. The specific form of the first instruction is not limited thereto.

Taking the first instruction as an example of the user input, the smartphone displays the user interface 11 shown in fig. 9, the user interface 11 may include a "start movement" button 111, the user clicks the "start movement" button 111, in response to the clicking operation of the user, the smartphone performs the following step 203, and switches the user interface to the user interface 12, the user interface 12 may include information of movement time, distance, pace, heat, and the like, and the user interface 12 may further include an image component of a "recovery curve".

Step 203, responding to the first instruction, sending a training effect request message, where the training effect request message is used to instruct the smart watch to feed back a training effect.

And step 204, the intelligent watch acquires the motion data of the user through a sensor of the intelligent watch, and determines the training effect of the motion according to the motion data.

For an explanation of the training effect, reference may be made to the explanation of step 103, which is not described herein again.

The smart watch can acquire the motion data of the user in real time or acquire the motion data of the user at preset time intervals, the acquisition mode can be flexibly set, and the embodiment of the application is not limited by the acquisition mode. The intelligent watch can acquire through a sensor of the intelligent watch, or acquire through a treadmill and the like.

In some embodiments, the smart watch may also display a user interface 21 as shown in fig. 10, where the user interface 21 may include information of exercise time, distance, pace, heat, etc., i.e., the smart phone displays the information of exercise time, distance, pace, heat, etc. synchronously with the smart watch.

And step 205, the smart watch sends the training effect of the exercise to the smart phone.

Step 206, the smartphone determines the recovery percentage after the current exercise is finished at the current time point according to the training effect of the current exercise.

For a detailed explanation of step 206, reference may be made to the explanation of step 104, which is not described herein again. That is, the recovery percentage after the current time point finishes the current motion is the recovery percentage within the recovery time after the current time point finishes the current motion.

Step 207, the smart phone displays a recovery curve in the user interface according to the recovery percentage after the current movement is ended at the current time point.

For example, the user clicks the image component of the "recovery curve" of the user interface 12, and in response to the clicking operation, the user interface of the smartphone is switched to the user interface 13, the recovery curve is displayed in the user interface 13, and the recovery percentages at different time points are shown to the user through the recovery curve.

Step 208, the smart phone determines whether positive income exists in the recovery time, if yes, step 209 is executed, and if not, step 211 is executed.

The smartphone may determine whether there is a positive benefit in the recovery time according to the recovery percentage determined in the above step, for example, when there is a recovery percentage greater than 1 in the recovery percentage corresponding to the training effect, there is a positive benefit, otherwise, step 211 is executed.

And step 209, the smart phone sends a first prompt message to the smart watch.

The first prompt message is used for prompting the user that the user can obtain the excessive recovery when the user moves so as to prompt the user that positive income exists when the user moves, the excessive recovery can be obtained, and the exercise effect can be reduced when the user moves excessively.

Step 210, the smart watch prompts the user that the movement may be subject to excessive recovery.

The smart watch may prompt the user for the movement via one or more of voice, text, vibration, graphics, or a prompt signal to obtain an excess recovery.

Taking the cue signal as an example, the smart watch may display a green light when positive revenue is available. When the positive gain begins to decrease, for example, the maximum value of the recovery percentage in the recovery time decreases from 110% to 109%, the smart watch may flash the green light to prompt the user to stop the exercise in time, so as to avoid excessive exercise. When the user does not stop the exercise, for example, when the maximum value of the recovery percentage in the recovery time is decreased from 109% to 103%, the smart watch may accelerate the blinking frequency of the green light to prompt the user to stop the exercise in time.

Step 211, the smartphone determines whether there is no profit in the recovery time, if yes, step 212 is executed, and if not, step 214 is executed.

For example, when there is a recovery percentage equal to 1 in the recovery percentages corresponding to the training effect, there is no benefit, otherwise step 214 is performed.

And step 212, the smart phone sends a fourth prompt message to the smart watch.

The fourth prompt message is used for prompting the user that the exercise is not profitable and the exercise intensity or speed needs to be increased.

The intelligent watch can prompt the user that the user does not have the benefit of exercise through one or more items of voice, characters, vibration, graphics, prompt signals and the like, and the exercise intensity or speed needs to be increased.

Taking the prompt signal as an example, when there is at most no profit in the recovery time, the smart watch may display yellow light to prompt the user that there is no profit in the exercise, requiring an increase in exercise intensity or speed. The user increases the intensity or speed of the exercise based on the prompt, and the smart watch may switch from yellow light to green light when positive revenue is available.

Step 213, the smart watch prompts to increase the intensity or speed of the exercise.

And step 214, the smart phone sends second prompt information to the smart watch.

The second prompt message is used for prompting the user of negative exercise income.

The smart watch may prompt the user for negative exercise benefits through one or more of voice, text, vibration, graphics, or a prompt signal.

Taking the prompt signal as an example, when the recovery time is at most negative income, the smart watch can display red light to prompt negative income of sports, stop the sports in time and avoid excessive sports. When the user does not stop moving, the intelligent watch can accelerate the flashing frequency of the red light so as to prompt the user to stop the movement in time.

Step 215, the smart watch prompts the user to stop the exercise.

It should be noted that, in another implementation manner, the smart watch may also send the motion data to the smart phone, and the smart phone determines the training effect.

The smart watch may prompt the user through one or more items of voice, text, vibration, graphics, or a prompt signal, for example, as an illustrative example, and may also prompt the user through another manner, for example, through a treadmill, or prompt the user through another smart home device (for example, a bluetooth speaker, a smart television, and the like), which is not necessarily illustrated in the embodiment of the present application.

In this embodiment, the smart watch may determine the training effect of the exercise through the exercise data of the exercise of the user, and then send the training effect of the exercise to the smart phone, and the smart phone determines the recovery percentage after the exercise is finished at the current time point according to the training effect, and then guides the user to exercise according to the recovery percentage after the exercise is finished at the current time point. Like this, be of value to the user and in time adjust this amount of exercise and the motion finish time of motion based on the suggestion of intelligent wrist-watch to help the user to obtain the excess and resume, and then effectively utilize the beneficial effect that the excess was resumed, solved the user and can't learn the income of this motion after, and the problem of carrying out the motion blindly. Therefore, the recovery percentage can be determined in time, and effective guidance is provided for the movement of the user.

It should be noted that, different from the case where the smart watch sends the training effect to the smart phone in the foregoing embodiment, in another implementation manner, the smart watch may send the motion data to the smart phone, and the smart phone determines the training effect, which may obtain the same technical effect as that in the foregoing embodiment, and details are not repeated here. In another implementation manner, the treadmill may obtain the exercise data, send the exercise data to the smart phone, and determine the training effect by the smart phone, which may obtain the same technical effect as the above embodiment, and details are not repeated here.

Fig. 11 is a flowchart of another exercise guidance method according to an embodiment of the present application, where the embodiment of the present application takes a smart watch as an example for illustration, and as shown in fig. 11, the method according to the embodiment of the present application may include:

step 301, the smart watch receives a first instruction.

The present embodiment takes as an example a click operation of the user on the "running outdoors" button in the user interface resulting from the first instruction. For example, the smart watch displays the user interface 31 as shown in fig. 12, the user interface 31 may include an "outdoor run" button 311, an "indoor run" button 312, the user clicks the "outdoor run" button 311, the smartphone performs the following step 301 in response to the user's clicking operation, and switches the user interface to the user interface 32, and the user interface 32 may include information of exercise time, distance, pace, heat, and the like.

Step 302, the smart watch starts to collect exercise data of the user in response to the first instruction, and determines a training effect of the exercise according to the exercise data.

And step 303, the smart watch determines the recovery percentage after the current exercise is finished at the current time point according to the training effect of the exercise.

For a detailed explanation of step 303, reference may be made to the explanation of step 104, which is not described herein again. That is, the recovery percentage after the current time point finishes the current motion is the recovery percentage within the recovery time after the current time point finishes the current motion.

And 304, the smart watch receives a left-sliding operation of the user on the user interface, and responds to the left-sliding operation, and the smart watch displays a recovery curve.

The embodiment takes a specific display form of the recovery percentage as an example of the recovery curve, for example, the user interface of the smart watch is switched to the user interface 33, and the recovery curve is displayed in the user interface 33, where "0" represents no benefit, "+" represents positive benefit, and "-" represents negative benefit.

Step 305, the smart watch determines whether positive income exists in the recovery time, if yes, step 306 is executed, and if not, step 308 is executed.

Step 306, the smart watch determines whether the positive gain is attenuated, if yes, step 307 is executed.

For example, the smart watch compares the recovery curve corresponding to the current training effect with the recovery curve corresponding to the previous training effect to determine whether the positive gain is attenuated, i.e., the peak of the recovery curve is decreased.

Step 307, the smart watch prompts the user that the excessive movement will reduce the exercise effect.

Step 308, the smart phone determines whether there is no profit in the recovery time, if yes, step 309 is executed, and if not, step 310 is executed.

Step 309, the smart watch prompts to increase the intensity or speed of the exercise.

Step 310, the smart watch prompts the user to stop exercising.

The prompting method of the smart watch according to the embodiment of the application may refer to the prompting method of step 210, step 213, or step 215 in the embodiment shown in fig. 8, and is not described herein again.

In this embodiment, the smart watch may determine the real-time training effect of the current exercise through the exercise data of the current exercise of the user, then determine the recovery percentage after the current exercise is finished at the current time point according to the training effect, and then guide the user to exercise according to the recovery percentage after the current exercise is finished at the current time point. Like this, be of value to the user and in time adjust this amount of exercise and the motion finish time of motion based on the suggestion of intelligent wrist-watch to help the user to obtain the excess and resume, and then effectively utilize the beneficial effect that the excess was resumed, solved the user and can't learn the income of this motion after, and the problem of carrying out the motion blindly. Therefore, the recovery percentage can be determined in time, and effective guidance is provided for the movement of the user.

In some embodiments, the user may also be guided in motion by graphical or textual representations. Taking the positive profit existing in the recovery time as an example, when the positive profit exists in the recovery time corresponding to the training effect of the user, the user may be prompted to stop the exercise this time by a circular mark on the user interface displaying the recovery curve, for example, as shown in fig. 13, when the positive profit exists, the user may be prompted to stop the exercise this time by a circular mark 411 on the user interface displaying the recovery curve, and the circular mark 411 may be located at the intersection of the solid line and the dotted line. When the user does not stop the movement and continues to move to cause the reduction of the recovery curve, the circular mark 411 can be flickered to prompt the user to stop the movement as soon as possible, and the flickering frequency of the circular mark 411 can be related to the reduction speed of the recovery curve.

It should be noted that, different from the above embodiment in which the smart watch acquires the motion data through its sensor to determine the training effect, in another implementation manner, the smart phone may acquire the motion data through its sensor to determine the training effect, which may acquire the same technical effect as that in the above embodiment, and details are not repeated here.

It should be noted that, in the above embodiment, the recovery percentage of the current exercise after the current time is determined is taken as an example, the exercise guidance method in the embodiment of the present application is not limited to this, and for example, the expected recovery percentage may also be determined. For example, the exercise data of the exercise obtained in the above method steps may be exercise data corresponding to a training plan, and then the training effect determined by the exercise guidance method of the embodiment of the present application is a training effect corresponding to the training plan, and based on the training effect corresponding to the training plan, the recovery percentage corresponding to the training plan is determined, so that a training plan that can obtain excessive recovery can be formulated for the user. It can be understood that, when the user exercises based on the training plan, the recovery percentage of the exercise ending at the current time can be determined by the method, so that the recovery percentage of the exercise ending at the current time is adjusted in time, the actual exercise of the user is completed as much as possible according to the training plan, and the actual exercise of the user is monitored.

The above embodiments of the method may be combined with each other to provide effective guidance for the user's movement, and the technical effect is similar to that of the above embodiments and will not be described herein again. For example, the combination of the embodiments shown in fig. 7 and fig. 11, that is, the smart watch may determine the recovery percentage by using the determination method of the recovery percentage of the embodiment shown in fig. 7, so as to provide effective guidance for the user's movement based on the recovery percentage.

Further embodiments of the present application further provide an electronic device, configured to perform the method in the above method embodiments. As shown in fig. 14, the electronic device may include: a display 1001, one or more processors 1002; a memory 1003; the various devices described above may be connected by one or more communication buses 1005. Wherein the memory 1003 stores one or more computer programs 1004, the one or more processors 1002 are configured to execute the one or more computer programs 1004, and the one or more computer programs 1004 include instructions that can be configured to perform the steps performed by the electronic device in the above method embodiments. The electronic device may be any form of electronic device described above, such as a smartphone, a smartwatch, or the like.

For example, the one or more processors 1002 are operable to execute the one or more computer programs 1004 to perform the following: in response to the first operation, a training effect for a first period of time is acquired, the training effect being indicative of an amount of motion for the first period of time. And determining the recovery percentage corresponding to the training effect according to the training effect in the first time period. And generating prompt information according to the recovery percentage, wherein the prompt information is used for guiding the user to move.

In some embodiments, the percentage of recovery corresponding to the training effect includes a percentage of recovery at a plurality of time points after the first time period, and when a maximum value of the percentage of recovery at the plurality of time points is equal to 1, the prompt information includes fourth prompt information for prompting the user to increase the exercise intensity; or when the maximum value of the recovery percentage in the recovery percentages at the plurality of time points is less than 1, the prompt message comprises a second prompt message, and the second prompt message is used for prompting the user to stop the movement.

In some embodiments, the percentage of recovery corresponding to the training effect includes a percentage of recovery at a plurality of time points after the first time period, and when a maximum value of the percentage of recovery at the plurality of time points is greater than 1, the prompt message includes a first prompt message for prompting that there is excessive recovery.

In some embodiments, the first prompt message is also used to prompt the time for the over-recovery.

In some embodiments, there is also implemented: and generating third prompt information according to the excessive recovery time, wherein the third prompt information is used for prompting the user to do exercise at the excessive recovery time.

In some embodiments, determining a recovery percentage corresponding to the training effect according to the training effect of the first time period includes: respectively determining the fused training effect of each time point according to the training effect of the first time period, a plurality of time points after the first time period, the training effects of the N second time periods and the end time of the N second time periods; and determining the recovery percentage of each time point according to the fused training effect of each time point.

In some embodiments, determining the fused training effect of each time point according to the training effect of the first time period, a plurality of time points after the first time period, the training effects of the N second time periods, and the end times of the N second time periods respectively includes:

according to the formula respectively

Determining a weight a of an nth training effect for each time point_n。

According to the formula respectively

Determining a fused training effect TE for each time point_new。

Wherein, t₀Is a point in time after the first time period, TE₀Is the training effect of the first time period, t₁To t_NIs the end time of the N second time periods, c is a predetermined constant, TE₁To TE_NIs the training effect for the N second time periods.

In some embodiments, determining the percentage of recovery for each time point based on the fused training effect for each time point comprises:

according to the formula respectively

The percent recovery for each time point was determined.

In some embodiments, obtaining the training effect for the first time period comprises: motion data is acquired. And determining the training effect of the first time period according to the motion data in the first time period.

In some embodiments, at least one of the following is also implemented: displaying the recovery percentage; alternatively, sending a recovery percentage; or sending prompt information.

Of course, the electronic device shown in fig. 14 may further include other devices such as an audio module, which is not limited in this embodiment. When it includes other devices, it may be specifically the electronic apparatus shown in fig. 2.

The electronic device according to the embodiment of the present application may be configured to execute the steps of the method embodiments shown in fig. 4, fig. 7, fig. 8, or fig. 9, and for reference, for technical principles and technical effects, reference may be made to the explanation of the method embodiments, which is not described herein again.

Further embodiments of the present application also provide a computer storage medium, which may include computer instructions, and when the computer instructions are executed on an electronic device, the electronic device may be caused to perform the steps performed by the electronic device in the above method embodiments.

Further embodiments of the present application also provide a computer program product, which when run on a computer causes the computer to perform the steps performed by the electronic device in the above-mentioned method embodiments.

Other embodiments of the present application further provide an apparatus, where the apparatus has a function of implementing the behavior of the electronic device in the foregoing method embodiments. The functions can be realized by hardware, and the functions can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above functions, for example, a receiving unit or module, a processing unit or module.

Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.

In the several embodiments provided in the embodiments of the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical functional division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another device, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, that is, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

The processor mentioned in the above embodiments may be an integrated circuit chip having signal processing capability. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The processor may be a general purpose processor, a Digital Signal Processor (DSP), an application-specific integrated circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, or discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by a hardware encoding processor, or implemented by a combination of hardware and software modules in the encoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

The memory referred to in the various embodiments above may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), double data rate SDRAM, enhanced SDRAM, SLDRAM, Synchronous Link DRAM (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (personal computer, server, network device, or the like) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of motion guidance, the method comprising:

acquiring a training effect of a first time period in response to a first operation, wherein the training effect is used for representing the quantity of motion of the first time period;

determining a recovery percentage corresponding to the training effect according to the training effect of the first time period;

and generating prompt information according to the recovery percentage, wherein the prompt information is used for guiding the user to move.

2. The method according to claim 1, wherein the recovery percentage corresponding to the training effect comprises recovery percentages at a plurality of time points after the first time period, and when a maximum value of the recovery percentages at the plurality of time points is equal to 1, the prompt message comprises a first prompt message for prompting a user to increase exercise intensity; or,

3. The method of claim 1, wherein the percentage of recovery corresponding to the training effect comprises a percentage of recovery at a plurality of time points after the first time period, and wherein the prompt message comprises a third prompt message indicating that there is excessive recovery when a maximum value of the percentage of recovery at the plurality of time points is greater than 1.

4. The method of claim 3, wherein the third prompting message is further used to prompt a time for over-recovery.

5. The method of claim 4, further comprising:

and generating fourth prompt information according to the excessive recovery time, wherein the fourth prompt information is used for prompting the user to move at the excessive recovery time.

6. The method according to any one of claims 1 to 5, wherein the determining the recovery percentage corresponding to the training effect according to the training effect of the first time period comprises:

respectively determining the fused training effect of each time point according to the training effect of the first time period, a plurality of time points after the first time period, the training effects of N second time periods and the end time of the N second time periods;

determining the recovery percentage of each time point according to the fused training effect of each time point;

wherein N is any positive integer.

7. The method of claim 6, wherein the determining the fused training effect for each time point according to the training effect for the first time period, a plurality of time points after the first time period, the training effects for N second time periods, and the end times of the N second time periods comprises:

according to the formula respectively

Determining a weight a of the nth training effect for each of the time points_n；

According to the formula respectively

Determining a fused training effect TE for each of the time points_new；

Wherein, t₀Is one of said points in time, TE, after said first period of time₀Is the training effect of the first time periodFruit, t₁To t_NIs the end time of the N second time periods, c is a predetermined constant, TE₁To TE_NIs the training effect for the N second time periods.

8. The method according to claim 6 or 7, wherein the determining the recovery percentage for each time point according to the fused training effect for each time point comprises:

according to the formula respectively

Determining a recovery percentage for each of the time points;

9. The method of any one of claims 1 to 8, wherein the obtaining of the training effect for the first time period comprises:

acquiring motion data;

and determining the training effect of the first time period according to the motion data in the first time period.

10. The method according to any one of claims 1 to 8, characterized in that the method further comprises at least one of:

displaying the recovery percentage; or,

sending the recovery percentage; or,

and sending the prompt message.

11. An electronic device, characterized in that the electronic device comprises: one or more processors, memory, and a display screen; the display screen is used for displaying content according to the indication of the one or more processors; the memory is used for storing one or more programs; the one or more processors are configured to execute the one or more programs to perform the following acts:

12. The electronic device according to claim 11, wherein the recovery percentage corresponding to the training effect includes recovery percentages at a plurality of time points after the first time period, and when a maximum value of the recovery percentages at the plurality of time points is equal to 1, the prompt message includes a first prompt message for prompting a user to increase exercise intensity; or,

13. The electronic device of claim 11, wherein the percentage of recovery corresponding to the training effect comprises percentages of recovery at a plurality of time points after the first time period, and wherein when a maximum value of the percentages of recovery at the plurality of time points is greater than 1, the prompt message comprises a third prompt message for prompting that there is excessive recovery.

14. The electronic device of claim 13, wherein the third prompting message is further configured to prompt a time for over-recovery.

15. The electronic device of claim 14, further enabled to:

16. The electronic device of any of claims 11-15, wherein the determining a recovery percentage for the training effect according to the training effect for the first time period comprises:

wherein N is any positive integer.

17. The electronic device of claim 16, wherein the determining the fused training effect for each time point according to the training effect for the first time period, a plurality of time points after the first time period, the training effects for N second time periods, and the end times for N second time periods comprises:

according to the formula respectively

According to the formula respectively

Determining a fused training effect TE for each of the time points_new；

Wherein, t₀Is one of said points in time, TE, after said first period of time₀Is the training effect of the first time period, t₁To t_NIs the end time of the N second time periods, c isA predetermined constant, TE₁To TE_NIs the training effect for the N second time periods.

18. The electronic device according to claim 16 or 17, wherein the determining the recovery percentage for each time point according to the fused training effect for each time point comprises:

according to the formula respectively

Determining a recovery percentage for each of the time points;

19. The electronic device of any of claims 11-18, wherein obtaining the training effect for the first time period comprises:

acquiring motion data;

20. The electronic device according to any of claims 11 to 18, further implementing at least one of:

displaying the recovery percentage; or,

sending the recovery percentage; or,

and sending the prompt message.

21. A computer-readable storage medium, comprising a computer program which, when executed on a computer, causes the computer to perform the method of any one of claims 1-10.

22. A chip comprising a processor and a memory, the memory for storing a computer program, the processor for calling and running the computer program stored in the memory to perform the method of any one of claims 1-10.