Exercise plan adjustment method and device and storage medium

Abstract

The invention provides an exercise plan adjustment method and device and a storage medium. According to the method, the exercise guidance suggestions for delaying and / or adjusting the exercise plan can be provided for the user from the angle of a large period, the initial exercise plan is delayed or adjusted according to the selection of the user, and the reasonable exercise guidance suggestions can be provided before the user does exercises from the angle of a small period, so that the user experience is improved. The body injury caused by body reasons or weather reasons in the exercise process is avoided. Namely, various exercise guidance suggestions can be realized, so that the user can do more reasonable exercise according to the exercise plan, and an expected target is further achieved.

Description

Technical Field

[0001] This application relates to the field of sports health technology, and in particular, to a method, device, and storage medium for adjusting a sports plan. Background Art

[0002] With the increasing pressure of modern life, people are paying more and more attention to their own health.

[0003] Currently, more and more people improve their physical fitness through fitness. However, most people do not have a personal fitness coach. Therefore, the formulated sports plan may be unreasonable and cannot be reasonably adjusted according to the actual sports situation. Summary of the Invention

[0004] To solve the above technical problems, this application provides a method, device, and storage medium for adjusting a sports plan, aiming to reasonably adjust the user's sports plan and enable the user to exercise more reasonably.

[0005] In a first aspect, this application provides a method for adjusting a sports plan. The method is applied to an electronic device and includes: obtaining a first sports plan of a user, where the first sports plan is an initial sports plan formulated by the user, the first sports plan includes multiple training cycles, and training courses corresponding to each training cycle, and the training courses include core courses with a higher training intensity; for each training cycle, when there is an absent class in the core course within the training cycle, making a first sports guidance suggestion, where the first sports guidance suggestion does not include options corresponding to deferral suggestions and options corresponding to adjusting the sports plan; for the multiple training cycles included in the first sports plan, when the training courses of N training cycles are completed and there are absent classes in the completed N training cycles, making a second sports guidance suggestion, where the second sports guidance suggestion includes an option corresponding to a deferral suggestion, or the second sports guidance suggestion includes an option corresponding to a deferral suggestion and an option corresponding to adjusting the sports plan, and N is an integer greater than 0.

[0006] Among them, the electronic device can be, for example, a mobile phone, a tablet computer, etc.

[0007] Thus, by combining small cycles (each training cycle) and large cycles (multiple training cycles), and making reasonable sports guidance suggestions according to the completion status (whether there is an absent class) of the core courses in the small cycles and large cycles, the user can exercise reasonably and ensure the exercise effect.

[0008] , for specific implementation details in this aspect, reference can be made to Figure 30 the description part of the illustrated embodiments, which will not be elaborated here for the time being.

[0009] According to the first aspect, for each training cycle, when there is an absence of a core course during the training cycle, a first exercise guidance suggestion is made, including: for each training cycle, on a daily granularity, detecting once a day whether there is an absence of a course during the training cycle; when it is first detected that there is an absence of a course, making a first exercise guidance suggestion and stopping the detection of the absence of a course during the training cycle.

[0010] For the specific implementation details in this aspect, reference can be made to Figure 30 the description part of the embodiments shown, which will not be elaborated here for the time being.

[0011] According to the first aspect, or any one of the implementation manners of the above first aspect, the situation of absence of a course includes: the core course during the training cycle is not trained; or, the core course during the training cycle is trained, but the training does not meet the standard.

[0012] For the specific implementation details in this aspect, reference can be made to Figure 30 the description part of the embodiments shown, which will not be elaborated here for the time being.

[0013] According to the first aspect, or any one of the implementation manners of the above first aspect, when the core course during the training cycle is not trained, the first exercise guidance suggestion made is used to prompt the user to make up the training for the core course that has not been trained; when the core course during the training cycle is trained, but the training does not meet the standard, the first exercise guidance suggestion made is used to prompt the user to strictly train the core courses that have not started training during the training cycle according to the requirements.

[0014] According to the first aspect, or any one of the implementation manners of the above first aspect, for the multiple training cycles included in the first exercise plan, when the training courses of N training cycles are completed and there is an absence of a course in the N completed training cycles, a second exercise guidance suggestion is made, including: for the multiple training cycles included in the first exercise plan, when the training courses of N training cycles are completed and there is an absence of a course in the N completed training cycles, determining the number of remaining training cycles of the first exercise plan; when the number of remaining training cycles is greater than or equal to the first threshold, making a second exercise guidance suggestion including an option corresponding to a deferral suggestion and an option corresponding to adjusting the exercise plan; when the number of remaining training cycles in the remaining part is less than the first threshold, making a second exercise guidance suggestion including an option corresponding to a deferral suggestion and not including an option corresponding to adjusting the exercise plan.

[0015] For the specific implementation details in this aspect, reference can be made to Figure 30 the description part of the embodiments shown, which will not be elaborated here for the time being.

[0016] According to the first aspect, or any implementation of the above first aspect, after making the second exercise guidance suggestion, the method further includes: when N is 1, after the user clicks on the option corresponding to the deferral suggestion, defer the first exercise plan by 1 training cycle; when N is greater than 1, after the user clicks on the option corresponding to the deferral suggestion, start deferring from the training cycle of the first missed class.

[0017] For the specific implementation details in this aspect, reference can be made to Figure 30 the description part of the illustrated embodiment, which will not be elaborated here for the time being.

[0018] According to the first aspect, or any implementation of the above first aspect, when the second exercise guidance suggestion includes an option corresponding to a deferral suggestion and an option corresponding to adjusting the exercise plan, the method further includes: after the user clicks on the option corresponding to adjusting the exercise plan, generate a second exercise plan, where the second exercise plan is the adjusted exercise plan, and the second exercise plan includes the training cycles in the first exercise plan that have not been trained, and the training courses for each untrained training cycle have been adjusted.

[0019] Among them, the second exercise guidance suggestion in this scenario, for example Figure 31 the content in window 10d - 10 shown in

[0020] For the specific implementation details in this aspect, reference can be made to Figure 30 the description part of the illustrated embodiment, which will not be elaborated here for the time being.

[0021] According to the first aspect, or any implementation of the above first aspect, the first exercise plan or the second exercise plan is an exercise plan for running; the method further includes: during the process of the user training according to the first exercise plan or the second exercise plan, obtain the user's maximum oxygen uptake; when the maximum oxygen uptake increases by S levels, calculate the pace classification according to the user's personal best running performance in the most recent M months, where S is an integer greater than 1 and M is an integer greater than 0; make a third exercise guidance suggestion according to the calculated pace classification, and the second exercise guidance suggestion includes an option corresponding to a deferral suggestion, or the second exercise guidance suggestion includes an option corresponding to a deferral suggestion and an option corresponding to adjusting the exercise plan.

[0022] Among them, S is, for example, 2. M is, for example, 1.

[0023] Thus, when the exercise ability changes, such as improves, exercise guidance suggestions and an entrance for adjusting the exercise plan can be given in a timely manner, so as to adjust the exercise plan in a timely manner and make the user's subsequent exercise more reasonable.

[0024] For the specific implementation details in this aspect, reference can be made to Figure 28The description part of the illustrated embodiment will not be elaborated here for the time being.

[0025] According to the first aspect, or any implementation manner of the above first aspect, when the third exercise guidance suggestion includes options corresponding to deferral suggestions and options corresponding to adjusting the exercise plan, the method further includes: after the user clicks the option corresponding to adjusting the exercise plan, generating a third exercise plan, where the third exercise plan is the adjusted exercise plan, and the third exercise plan includes training cycles that have not been trained in the first exercise plan / the second exercise plan, and the training courses of each untrained training cycle have been adjusted.

[0026] Among them, the third exercise guidance suggestion, for example Figure 29 the content in window 10d-9 shown in

[0027] For the specific implementation details in this aspect, reference can be made to Figure 28 The description part of the illustrated embodiment will not be elaborated here for the time being.

[0028] According to the first aspect, or any implementation manner of the above first aspect, the method further includes: obtaining index data, physiological cycle data, and weather data for calculating the fatigue level; during the process of the user training according to the first exercise plan, or the second exercise plan, or the third exercise plan, making a fourth exercise guidance suggestion according to the fatigue level, physiological cycle data, and weather data, where the fourth exercise guidance suggestion is the exercise guidance suggestion corresponding to the fatigue level, or the exercise guidance suggestion corresponding to the physiological data, or the exercise guidance suggestion corresponding to the weather data.

[0029] Thus, exercise guidance suggestions can be given to the user from the perspectives of fatigue, physiological cycle, and weather, avoiding the user's body being damaged during exercise.

[0030] For the specific implementation details in this aspect, reference can be made to the description parts of the small-cycle fatigue adjustment plan, the small-cycle physiological cycle adjustment plan, and the small-cycle weather adjustment plan, which will not be elaborated here for the time being.

[0031] According to the first aspect, or any implementation manner of the above first aspect, making a fourth exercise guidance suggestion according to the fatigue level, physiological cycle data, and weather data includes: selecting a highest-priority exercise guidance suggestion as the fourth exercise guidance suggestion in the order that the priority of the exercise guidance suggestion corresponding to the fatigue level is higher than the priority of the exercise guidance suggestion corresponding to the physiological cycle data, and the priority of the exercise guidance suggestion corresponding to the physiological cycle data is higher than the priority of the exercise guidance suggestion corresponding to the weather data.

[0032] According to the first aspect, or any implementation of the above first aspect, the electronic device is also communicatively connected to a wearable device, which is used to provide index data for calculating the fatigue level. The index data includes one or more of morning pulse resting heart rate data, heart rate variability (HRV) data, heart rate data during the exercise phase, and sleep data. Among them, determining the fatigue level according to the index data includes: when the index data includes morning pulse resting heart rate data, calculating the fatigue level according to the morning pulse resting heart rate data; when the fatigue level calculated according to the morning pulse resting heart rate data is the highest level of fatigue, determining the fatigue level calculated according to the morning pulse resting heart rate data as the user's current fatigue level. The highest level of fatigue indicates that the user is currently not suitable for any training courses.

[0033] Among them, the wearable device, such as a smart watch, a bracelet, etc.

[0034] Optionally, the fatigue level can be divided into level 0 fatigue, level 1 fatigue, level 2 fatigue, level 3 fatigue, etc. Among them, the highest level of fatigue, for example, is level 3 fatigue.

[0035] Thus, by determining the fatigue level based on the morning pulse resting heart rate data with the highest priority among the index data for calculating the user's fatigue level provided by the wearable device, and when the fatigue level determined according to the morning pulse resting heart rate data is the highest level of fatigue, directly taking the fatigue level determined by the morning pulse resting heart rate data as the user's current fatigue level, it can not only ensure the accuracy of the result but also reduce the computational amount of the electronic device.

[0036] According to the first aspect, or any implementation of the above first aspect, the method further includes: when the index data does not include morning pulse resting heart rate data, or the fatigue level calculated according to the morning pulse resting heart rate data is not the highest level of fatigue, but the index data includes HRV data, calculating the fatigue level according to the HRV data; when the fatigue level calculated according to the HRV data is the highest level of fatigue, determining the fatigue level calculated according to the HRV data as the user's current fatigue level.

[0037] Thus, when the highest level of fatigue cannot be determined based on the morning pulse resting heart rate data, the HRV data is given priority. When the fatigue level determined by the HRV data is the highest level of fatigue, directly taking the fatigue level determined by the HRV data as the user's current fatigue level, so that more appropriate exercise guidance for the user's current physical condition can be given according to the determined fatigue level, avoiding damage to the body caused by the user's excessive exercise.

[0038] According to the first aspect, or any implementation of the above first aspect, the method further includes: when the indicator data does not include the morning pulse resting heart rate data, or the fatigue level calculated based on the morning pulse resting heart rate data is not the highest level of fatigue, and the indicator data does not include the HRV data, or the fatigue level calculated based on the HRV data is not the highest level of fatigue, but the indicator data includes the heart rate data during the exercise phase, calculating the acute-chronic workload ratio (ACWR) data according to the heart rate data during the exercise phase and the training duration of the currently completed training session; calculating the fatigue level according to the ACWR data; when the fatigue level calculated according to the ACWR data is the highest level of fatigue, determining the fatigue level calculated according to the ACWR data as the user's current fatigue level.

[0039] Thus, when the highest level of fatigue cannot be determined based on both the morning pulse resting heart rate data and the HRV data, the ACWR data is given priority. When the fatigue level determined by the ACWR data is the highest level of fatigue, the fatigue level determined by the ACWR data is directly used as the user's current fatigue level, so that more appropriate exercise guidance for the user's current physical state can be given according to the determined fatigue level, avoiding damage to the body caused by the user's excessive exercise.

[0040] According to the first aspect, or any implementation of the above first aspect, the method further includes: when the indicator data does not include the morning pulse resting heart rate data, or the fatigue level calculated based on the morning pulse resting heart rate data is not the highest level of fatigue, and the indicator data does not include the HRV data, or the fatigue level calculated based on the HRV data is not the highest level of fatigue, and the indicator data does not include the heart rate data during the exercise phase, after the training session ends, a first questionnaire is popped up. The first questionnaire includes multiple score options, and different score options correspond to different fatigue degrees; calculating the user's current training load according to the score selected by the user in the first questionnaire and the training duration; calculating the user's current ACWR data according to the training load, the historical ACWR data, and the parameter indicating the degree of attenuation of the training load over time. The historical ACWR data is the ACWR data corresponding to the user after the last training session, and the value of the parameter indicating the degree of attenuation of the training load over time is between 0 and 1; calculating the fatigue level according to the ACWR data; when the fatigue level calculated according to the ACWR data is the highest level of fatigue, determining the fatigue level calculated according to the ACWR data as the user's current fatigue level.

[0041] Among them, the first questionnaire, for example Figure 18 is the course feedback questionnaire popped up on the interface 10f.

[0042] Thus, in the case where the user is not wearing a wearable device or the wearable device does not provide heart rate data during the exercise phase, by displaying a subjective evaluation questionnaire on the electronic device, it is possible to ensure that the ACWR data can be calculated in any scenario, and then the fatigue level can be determined.

[0043] According to the first aspect, or any one of the implementation manners of the above first aspect, the method further includes: when the index data does not include the morning pulse resting heart rate data, or the fatigue level calculated based on the morning pulse resting heart rate data is not the highest fatigue level, and the index data does not include the HRV data, or the fatigue level calculated based on the HRV data is not the highest fatigue level, and the index data does not include the heart rate data during the exercise phase, or the fatigue level calculated based on the ACWR data is not the highest fatigue level, but the fatigue level calculated based on the morning pulse resting heart rate data is lower than the highest fatigue level, the fatigue level calculated based on the morning pulse resting heart rate data is determined as the current fatigue level of the user.

[0044] Among them, the fatigue level lower than the highest fatigue level, such as fatigue level 0, or fatigue level 1, or fatigue level 2, etc.

[0045] In this way, when the morning pulse resting heart rate data with the highest priority can determine the fatigue level, the fatigue level determined by the morning pulse resting heart rate data is preferentially used, which can better reflect the actual fatigue degree of the user and is beneficial to giving appropriate exercise guidance before exercise.

[0046] According to the first aspect, or any one of the implementation manners of the above first aspect, the method further includes: when the fatigue level cannot be calculated based on the morning pulse resting heart rate data, but the index data includes the HRV data, and the fatigue level calculated based on the HRV data is lower than the highest fatigue level, the fatigue level calculated based on the HRV data is determined as the current fatigue level of the user.

[0047] In this way, when the morning pulse resting heart rate data with the highest priority cannot determine the fatigue level, the HRV data with a priority lower than the morning pulse resting heart rate data but higher than other index data is preferentially used to determine the fatigue level, ensuring that the determined fatigue level can better reflect the actual fatigue degree of the user and is beneficial to giving appropriate exercise guidance before exercise.

[0048] According to the first aspect, or any one of the implementation manners of the above first aspect, the method further includes: when the fatigue level cannot be calculated based on the morning pulse resting heart rate data and the HRV data, but the index data includes the heart rate data during the exercise phase, and the fatigue level calculated based on the ACWR data calculated from the heart rate data during the exercise phase and the training duration is lower than the highest fatigue level, the fatigue level calculated based on the ACWR data is determined as the current fatigue level of the user.

[0049] In this way, when other index data with a higher priority than the ACWR data cannot determine the fatigue level, the ACWR data is used to determine the fatigue level, which further ensures that the determined fatigue level can better reflect the actual fatigue degree of the user and is conducive to giving appropriate exercise guidance before exercise.

[0050] According to the first aspect, or any implementation manner of the above first aspect, the method further includes: when the index data does not include the morning pulse resting heart rate data, or the fatigue level cannot be calculated based on the morning pulse resting heart rate data, and the index data does not include the HRV data, or the fatigue level cannot be calculated based on the HRV data, and the index data does not include the heart rate data during the exercise stage, or the fatigue level cannot be calculated based on the ACWR data, but the index data includes the sleep data, calculating the fatigue level according to the sleep data; when the fatigue level is calculated based on the sleep data, determining the fatigue level calculated based on the sleep data as the current fatigue level of the user; when the fatigue level cannot be calculated based on the sleep data, determining the lowest-level fatigue level as the current fatigue level of the user, and the lowest-level fatigue level indicates that the user is not fatigued currently.

[0051] In this way, when other index data with a higher priority than the sleep data cannot determine the fatigue level, the sleep data is used to determine the fatigue level, and when the sleep data cannot determine the fatigue level, it is defaulted that the user belongs to the lowest-level fatigue level, so as to ensure that a fatigue level can be determined in any case before the user exercises, and then appropriate exercise guidance can be given.

[0052] According to the first aspect, or any implementation manner of the above first aspect, calculating the fatigue level according to the sleep data includes: when the sleep data meets the preset conditions, displaying a second questionnaire, where the second questionnaire includes multiple sleep quality evaluation options, and different sleep quality evaluation options correspond to different scores; determining the fatigue level according to the score corresponding to the sleep quality option selected by the user in the second questionnaire.

[0053] Among them, the second questionnaire, for example Figure 14 the sleep quality questionnaire shown in (2) below.

[0054] According to the first aspect, or any implementation manner of the above first aspect, meeting the preset conditions includes: the sleep duration is less than the first preset duration; and / or, the number of night awakenings is greater than or equal to the preset number; and / or, the wake-up time is earlier than the average wake-up time of the previous week by the second preset duration.

[0055] Among them, the first preset duration, for example, is 5 hours (h).

[0056] Among them, the preset number of times is, for example, 3 times.

[0057] Among them, the second preset duration is, for example, 30 minutes (min).

[0058] According to the first aspect, or any implementation manner of the above first aspect, calculating the fatigue level based on the morning pulse resting heart rate data includes: when the fluctuation of the morning pulse resting heart rate data compared with the average value of the morning pulse resting heart rate in the previous week is within N1 bpm, determining that the fatigue level is the lowest fatigue level; when the morning pulse resting heart rate data exceeds the average value of the morning pulse resting heart rate in the previous week by N1 bpm to N2 bpm, displaying a third questionnaire, the third questionnaire includes multiple fatigue degree evaluation options, and different fatigue degree evaluation options correspond to different scores; determining the fatigue level according to the score corresponding to the fatigue degree option selected by the user in the third questionnaire; when both the morning pulse resting heart rate data and the morning pulse resting heart rate data of yesterday exceed the average value of the morning pulse resting heart rate in the previous week by N1 bpm to N2 bpm, determining that the fatigue level is a fatigue level between the highest level and the lowest level; when the morning pulse resting heart rate data, the morning pulse resting heart rate data of yesterday, and the morning pulse resting heart rate data of the day before yesterday all exceed the average value of the morning pulse resting heart rate in the previous week by N1 bpm to N2 bpm, determining that the fatigue level is the highest fatigue level; when the morning pulse resting heart rate data exceeds the average value of the morning pulse resting heart rate in the previous week by N3 bpm, determining that the fatigue level is the highest fatigue level; where 0 < N1 < N2 < N3.

[0059] Among them, the third questionnaire is, for example Figure 14 the borg questionnaire shown in (1) below.

[0060] Regarding the specific details of calculating the fatigue level based on the morning pulse resting heart rate data, reference can be made to Figure 13 and Figure 14 the description of the embodiments shown, which will not be elaborated here.

[0061] According to the first aspect, or any implementation manner of the above first aspect, calculating the fatigue level based on the HRV data includes: determining the fatigue level according to the RMSSD and LF / HF ratio in the HRV data, where RMSSD refers to the root mean square of the differences between adjacent normal cardiac cycles, and the LF / HF ratio refers to the ratio of low-frequency heart rate variability to high-frequency heart rate variability.

[0062] Regarding the specific details of calculating the fatigue level based on the HRV data, reference can be made to Figure 15 the description of the embodiments shown, which will not be elaborated here.

[0063] According to the first aspect, or any implementation of the first aspect above, the acute and chronic load ratio ACWR data is calculated based on the heart rate data of the exercise stage and the training duration of the currently completed training course, including: determining the heart rate interval in which the heart rate data of the exercise stage is located; wherein, from 50% of the maximum heart rate to 100% of the maximum heart rate, each increase of 10% is a heart rate interval, and each heart rate interval corresponds to an intensity level; determining the intensity level according to the determined heart rate interval; calculating the user's current training load according to the intensity level and the training duration; calculating the user's current ACWR data according to the training load, historical ACWR data and a parameter indicating the degree to which the training load decays over time, wherein the historical ACWR data is the ACWR data corresponding to the last time the user completed training, and the parameter indicating the degree to which the training load decays over time has a value between 0 and 1.

[0064] For details on determining ACWR data and calculating fatigue level based on the heart rate data during exercise provided by the wearable device, see Figure 16 The description of the illustrated embodiment will not be repeated here.

[0065] In a second aspect, the present application provides an electronic device. The electronic device includes: a memory and a processor, the memory and the processor are coupled; the memory stores program instructions, and when the program instructions are executed by the processor, the electronic device executes instructions of the method in the first aspect or any possible implementation of the first aspect.

[0066] In a third aspect, the present application provides a computer-readable medium for storing a computer program, wherein the computer program includes instructions for executing the method in the first aspect or any possible implementation of the first aspect.

[0067] In a fourth aspect, the present application provides a computer program, comprising instructions for executing the method in the first aspect or any possible implementation of the first aspect.

[0068] In a fifth aspect, the present application provides a chip, the chip comprising a processing circuit and a transceiver pin, wherein the transceiver pin and the processing circuit communicate with each other through an internal connection path, and the processing circuit executes the method in the first aspect or any possible implementation of the first aspect to control the receiving pin to receive a signal and control the sending pin to send a signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 A schematic diagram of a scenario for implementing motion plan adjustment is shown as an example;

[0070] Figure 2 The figure is a schematic diagram of the hardware structure of an electronic device for implementing the exercise plan adjustment;

[0071] Figure 3 Exemplarily shown Figure 2 Schematic diagram of the software structure of the electronic device shown

[0072] Figure 4 Schematic diagram of the hardware structure of another electronic device for implementing motion plan adjustment, shown exemplarily

[0073] Figure 5 Exemplarily shown Figure 4 Schematic diagram of the software structure of the electronic device shown

[0074] Figure 6 Schematic diagram of a system architecture for implementing motion plan adjustment, shown exemplarily

[0075] Figure 7 and Figure 8 Schematic diagram of the user interface involved in the process of starting the sports health APP to view the motion plan, shown exemplarily

[0076] Figure 9 Schematic diagram of course identifiers with different intensities at different times, shown exemplarily

[0077] Figure 10 Schematic diagram of a window showing only information related to core training days and regular training days, shown exemplarily

[0078] Figure 11 Schematic diagram of the user interface for giving prompt information according to different fatigue levels, shown exemplarily

[0079] Figure 12 Schematic diagram of the process for determining the fatigue level in a small cycle fatigue adjustment plan, shown exemplarily

[0080] Figure 13 Schematic diagram for determining the fatigue level based on morning pulse and resting heart rate data, shown exemplarily

[0081] Figure 14 Schematic diagram of the user interface of the questionnaire feedback shown when it is determined to be situation 1b based on morning pulse and resting heart rate data, shown exemplarily

[0082] Figure 15 Schematic diagram for determining the fatigue level based on heart rate variability data, shown exemplarily

[0083] Figure 16 Schematic diagram for determining the ACWR and then the fatigue level, shown exemplarily

[0084] Figure 17Another schematic diagram for exemplarily showing the determination of ACWR and further determining the fatigue level;

[0085] Figure 18 For exemplarily showing the Figure 17 user interface schematic diagram for popping up course feedback for the scenario of;

[0086] Figure 19 Schematic diagram for exemplarily showing the determination of fatigue level based on sleep data;

[0087] Figure 20 Schematic diagram of a window and user interface for exemplarily showing a better course;

[0088] Figure 21 Schematic diagram of a window for exemplarily showing a training sequence reminder;

[0089] Figure 22 and Figure 23 Schematic diagram of the user interface for setting the physiological cycle and the involved window for exemplarily showing;

[0090] Figure 24 Schematic diagram of the logic for giving exercise guidance suggestions according to the menstrual phase of the physiological cycle for exemplarily showing;

[0091] Figure 25 Schematic diagram of a window for the exercise guidance suggestions made for different menstrual phases for exemplarily showing;

[0092] Figure 26 Schematic diagram of the logic for giving exercise guidance suggestions according to the weather conditions for exemplarily showing;

[0093] Figure 27 Schematic diagram of a window for the exercise guidance suggestions made for different weather conditions for exemplarily showing;

[0094] Figure 28 Schematic diagram of the process for the adjustment plan of improving the large-cycle exercise ability for exemplarily showing;

[0095] Figure 29 Schematic diagram of a window for the exercise guidance suggestions given after the improvement of exercise ability for exemplarily showing;

[0096] Figure 30 Schematic diagram of the process for the adjustment plan of the large-cycle execution rate non-compliance for exemplarily showing;

[0097] Figure 31 Schematic diagram of a window for the exercise guidance suggestions given after the execution rate non-compliance for exemplarily showing;

[0098] Figure 32Schematic diagram of a window for various exercise guidance suggestions involved in the exercise adjustment plan provided by the embodiments of the present application shown by way of example. Detailed implementation manners

[0099] Next, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0100] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone.

[0101] The terms "first", "second", etc. in the description and claims of the embodiments of the present application are used to distinguish different objects, rather than to describe a specific order of the objects. For example, the first target object and the second target object are used to distinguish different target objects, rather than to describe the specific order of the target objects.

[0102] In the embodiments of the present application, words such as "exemplary" or "for example" are used to give examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0103] In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" refers to two or more. For example, a plurality of processing units refers to two or more processing units; a plurality of systems refers to two or more systems.

[0104] In the description of the embodiments of the present application, the user interface can also be referred to as an interface. Among them, the icons, controls, names, etc. included in the various interfaces shown by way of example can be replaced with other names according to the actual scenario.

[0105] With the increasing pressure of modern life, people are paying more and more attention to their own health. At present, more and more people improve their physical fitness through fitness. However, most people cannot afford to have a personal fitness coach. Therefore, the exercise plans formulated may be unreasonable and cannot be reasonably adjusted according to the actual exercise situation.

[0106] Optionally, as the mobile Internet industry gradually expands, in some possible implementation manners, a user can use a sports application (APP) to formulate a sports plan and perform sports based on the formulated sports plan to improve their physical fitness. However, in actual applications, due to various factors, the user may not strictly follow the sports plan. Therefore, if the user still performs sports according to the previous sports plan, not only will the expected effect not be achieved, but more seriously, the user's body may be damaged due to unreasonable sports.

[0107] In view of this, the embodiments of the present application provide a more comprehensive multi-dimensional sports plan adjustment method, aiming to reasonably adjust the user's sports plan so that the user can perform sports more reasonably.

[0108] Exemplarily, in some possible implementation manners, the sports plan adjustment method provided by the embodiments of the present application can be applied to an electronic device. The electronic device can be any one of portable devices such as a mobile phone, a tablet computer, a wearable device (such as a smart watch, a bracelet, etc.).

[0109] Exemplarily, in some other possible implementation manners, the sports plan adjustment method provided by the embodiments of the present application can also be applied to multiple portable devices, such as a mobile phone and a smart watch (hereinafter simply referred to as: watch). Through the cooperation of these two devices, the user's sports plan can be adjusted more reasonably.

[0110] The embodiments of the present application use the mobile phone 100 and the watch 200 to establish a communication connection and perform data interaction, such as Figure 1 shown in the scenario, to specifically illustrate the solution for adjusting the sports plan.

[0111] See Figure 2 , which exemplarily shows a schematic structural diagram of a mobile phone 100. As Figure 2 shown, the mobile phone 100 may include: a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a sensor module 180, a key 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc.

[0112] Among them, antenna 1 and antenna 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the mobile phone 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be multiplexed to improve the utilization rate of the antennas. For example, antenna 1 can be multiplexed as a diversity antenna for a wireless local area network. In some other implementation manners, the antenna can be used in combination with a tuning switch.

[0113] Among them, the mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G, etc. applied to the mobile phone 100.

[0114] Among them, the wireless communication module 160 can provide solutions for wireless communications including wireless local area networks (WLANs) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (IR), etc. applied to the mobile phone 100.

[0115] Specifically, in the technical solution provided by the embodiments of the present application, the mobile phone 100 can communicate with the smartwatch 200 through the wireless communication module 160 and the antenna.

[0116] Among them, the display screen 194 is used for displaying images, videos, etc. The display screen 194 includes a display panel. In some implementation manners, the mobile phone 100 can include 1 or N display screens 194, where N is a positive integer greater than 1. Specifically, in the embodiments of the present application, interactions with users, prompt messages, etc. can be implemented through the display screen.

[0117] In addition, it should be noted that in some possible implementation manners, the processor 110 may include one or more processing units. For example, the processor 110 may include an application processor (AP), a modem, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, a neural-network processing unit (NPU), etc. This is not listed one by one here, and this application does not limit this.

[0118] Optionally, these processing units may be independent devices, that is, each processing unit can be regarded as a processor.

[0119] Optionally, these processing units may also be integrated in one or more processors.

[0120] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the only limitation to this embodiment.

[0121] Specifically in the embodiment of this application, the mobile phone 100 can provide pre-exercise guidance for the user and adjust the exercise plan according to multi-dimensional index data through the application processor.

[0122] Optionally, the multi-dimensional index data may include, for example, data for determining the user's fatigue level, weather data, physiological cycle data, exercise ability data, execution rate data, etc.

[0123] Among them, the data for determining the fatigue level may include, for example, morning pulse resting heart rate data, heart rate variability data, acute and chronic load ratio data, sleep data, etc.

[0124] That's all for the introduction of the hardware structure of the mobile phone 100. It should be understood that Figure 2 the shown mobile phone 100 is only an example. In specific implementation, the mobile phone 100 may have more or fewer components than those shown in the figure, may combine two or more components, or may have different component configurations. Figure 2 The various components shown can be implemented in hardware, software, or a combination of hardware and software including one or more signal processing and / or application specific integrated circuits.

[0125] See Figure 3, An exemplary schematic diagram of the software structure of a mobile phone 100 is shown. Before describing the software structure of the mobile phone 100, first, the architecture that the software system of the mobile phone 100 can adopt is described.

[0126] Optionally, the software system of the mobile phone 100 can adopt a layered architecture, an event-driven architecture, a microkernel architecture, a microservices architecture, or a cloud architecture.

[0127] Optionally, the software system of the mobile phone 100 includes, but is not limited to, Windows system, Android system, and iOS system.

[0128] For ease of description, in the embodiments of the present application, taking the Android system with a layered architecture as an example, the software structure of the mobile phone 100 is described exemplarily.

[0129] As Figure 3 shown, the layered architecture of the mobile phone 100 divides the software into several layers, and each layer has a clear role and division of labor. The layers communicate with each other through software interfaces. In some implementation manners, the Android system of the mobile phone 100 is divided into five layers, from top to bottom, which are the application (APP) layer, the application framework (FWK) layer, the Android runtime and system libraries, the hardware abstraction layer (HAL), and the kernel layer.

[0130] The application layer may include a series of application packages.

[0131] As Figure 3 shown, the application packages may include applications such as sports health, settings, music, Bluetooth, gallery, etc., which are not listed one by one here, and the present application does not limit this.

[0132] Among them, the sports health application is an APP provided in the embodiments of the present application that can cooperate with wearable and health devices (such as the watch 200) to achieve scientific sports monitoring and health management, and provide professional data and rich activity experiences. Users can formulate exercise plans through the sports health APP to facilitate exercising according to the exercise plans.

[0133] Optionally, based on the exercise plan adjustment method provided in the embodiments of the present application, the exercise plans formulated by users using the sports health APP can be reasonably adjusted. For specific implementation details, see the following embodiments, and details are not described here for the time being.

[0134] The application framework layer provides application programming interfaces (APIs) and programming frameworks (which can be described as functions) for the applications in the application layer. In some embodiments, the application framework layer includes some predefined functions.

[0135] As Figure 3 shown, the application framework layer may include a notification manager, a content provider, a view system, a resource manager, a window manager, etc.

[0136] The notification manager enables the application to display notification information in the status bar. It can be used to convey messages of the notification type and can disappear automatically after a short stay without user interaction.

[0137] Specifically, in the embodiment of the present application, before the time when the user is accustomed to starting exercise, such as the previous hour, the notification manager can push prompt messages regarding exercise guidance.

[0138] Optionally, when the mobile phone 100 establishes a communication connection with the smartwatch 200 and the message synchronization of the sports health APP is enabled, the smartwatch 200 will also receive this prompt message.

[0139] The content provider is used to store and obtain data and enables these data to be accessed by the application.

[0140] The view system includes visible controls, such as controls for displaying text, controls for displaying pictures, etc.

[0141] The resource manager provides various resources for the application, such as the layouts and contents of various prompt message windows that need to be displayed in the interface.

[0142] The window manager is used to manage window programs. The window manager can obtain the size of the display screen, determine whether there is a status bar, lock the screen, and the current display interface (such as determining whether it is the interface 10d shown in (2) of the following embodiments). Figure 8 etc.

[0143] The system library and the runtime layer include the system library and the Android Runtime. The Android Runtime includes the core library and the virtual machine. The Android runtime is responsible for the scheduling and management of the Android system.

[0144] The core library consists of two parts: one part is the functional functions that the Java language needs to call, and the other part is the core library of Android.

[0145] The application layer and the application framework layer run in the virtual machine. The virtual machine executes the Java files of the application layer and the application framework layer as binary files. The virtual machine is used to perform functions such as object lifecycle management, stack management, thread management, security and exception management, and garbage collection.

[0146] The system library can include multiple functional modules. For example: surface manager, Media Libraries, 3D graphics processing library (e.g., OpenGL ES), 2D graphics engine (e.g., SGL), etc.

[0147] The surface manager is used to manage the display subsystem and provides the fusion of 2D and 3D layers for multiple applications.

[0148] The media library supports the playback and recording of various common audio and video formats, as well as static image files, etc. The media library can support multiple audio and video coding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.

[0149] The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, synthesis, and layer processing, etc.

[0150] Understandably, the above-mentioned 2D graphics engine is a drawing engine for 2D drawing.

[0151] The HAL layer is an interface layer located between the operating system kernel and the hardware circuit. The HAL layer includes but is not limited to: camera hardware abstraction layer, display driver hardware abstraction layer, power hardware abstraction layer.

[0152] The kernel layer is the layer between the hardware and the software. The kernel layer at least includes sensor drivers, display drivers, camera drivers, power management drivers, etc. Exemplarily, the sensor driver can be used to output the detection signal of a sensor (such as a touch sensor) to the view system, so that the view system displays the corresponding application interface in response to the detection signal.

[0153] The software structure of the mobile phone 100 is introduced here. Understandably, Figure 3 The layers in the shown software structure and the components included in each layer do not constitute a specific limitation on the mobile phone 100. In some other embodiments of the present application, the mobile phone 100 may include more or fewer layers than shown, and each layer may include more or fewer components, which are not limited in the present application.

[0154] See Figure 4 , an exemplary hardware structure of a watch 200 is shown. As Figure 4As shown, the smartwatch 200 may include: a processor 210, a sensor 220, a memory 230, an antenna 240, etc.

[0155] Among them, the processor 210 may be the nerve center and command center of the smartwatch 200. The processor 210 may generate operation control signals according to the instruction operation code and timing signal to complete the control of fetching and executing instructions. A memory may also be provided in the processor 210 for storing instructions and data. In some embodiments, the memory in the processor 210 is a cache memory.

[0156] Among them, the memory 230 may be used to store computer-executable program code, and the executable program code includes instructions. The memory 230 may be a volatile memory or a persistent memory. The computer-executable program code stored in the memory 230 may include one or more modules, and each module may include a series of instruction operations. The memory 230 may include a program storage area and a data storage area.

[0157] Furthermore, the processor 210 may be configured to communicate with the memory 230 to execute a series of instruction operations in the memory 230 on the smartwatch 200. Among them, the processor 210 executes various functions and data processing of the smartwatch 200 by running the computer program instructions stored in the memory 230.

[0158] Among them, the sensor 220 may include, for example, sensors for monitoring sleep, sensors for monitoring heart rate, etc., which are sensors capable of performing motion monitoring and health monitoring. These sensors can collect data on several dimensions such as sleep, morning pulse resting heart rate, and heart rate variability (HRV), and transmit this data to the mobile phone 100 so that the sports health APP of the mobile phone 100 can determine the user's current fatigue level based on the parameters of multiple dimensions and then give reasonable reminders.

[0159] Among them, the antenna 240 is used to send the data collected by the sensor 220 to the mobile phone 100 and receive the messages pushed by the sports health APP in the mobile phone 100.

[0160] The introduction to the hardware structure of the smartwatch 200 ends here. It should be understood that Figure 4 the smartwatch 200 shown is only an example. In specific implementations, the smartwatch 200 may have more or fewer components than those shown in the figure, may combine two or more components, or may have different component configurations. Figure 4 The various components shown may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and / or application-specific integrated circuits.

[0161] Refer to Figure 5 , which exemplarily shows the software structure of a watch 200. Understandably, the software structure of the watch 200 can also adopt a layered architecture, an event-driven architecture, a microkernel architecture, a microservices architecture, or a cloud architecture. The software system includes but is not limited to Android system, iOS system, etc.

[0162] For ease of explanation, in the embodiments of this application, taking the Android system with a layered architecture as an example, the software structure of the watch 200 is exemplarily described.

[0163] As Figure 3 shown, the layered architecture of the watch 200 divides the software into several layers, and each layer has a clear role and division of labor. The layers communicate with each other through software interfaces. In some implementation manners, the Android system of the watch 200 is divided into 4 layers, from top to bottom are the Application (APP) layer, the Application Framework (FWK) layer, the algorithms and internal libraries, and the kernel layer.

[0164] As Figure 5 shown, the application packages of the watch 200 may include a map application, a communication application, a music player, etc.

[0165] Understandably, the above-mentioned communication application, for example, includes an information application, a call record application, a contacts application, a call application, etc.

[0166] Continue to refer to Figure 5 , exemplarily, the application framework layer of the watch 200 may include various logic control services, communication protocols, etc.

[0167] Specifically in the embodiments of this application, in order to accurately determine the fatigue level of the user from multiple dimensions such as morning pulse resting heart rate, heart rate variability, acute:chronic workload ratio (ACWR), sleep, etc., the logic control services may, for example, include various logic control services such as sleep data acquisition, morning pulse resting heart rate calculation, heart rate variability calculation.

[0168] Among them, the communication protocol can be a communication protocol agreed with the watch 100, so as to facilitate the two to perform data interaction according to the agreed communication protocol.

[0169] The algorithms and internal libraries are used to manage various algorithms, such as sleep algorithms, heart rate algorithms, stress algorithms, etc., various basic libraries, such as security-related, barcode, payment-related basic libraries, and protocol stacks provided by chip manufacturers, such as traditional Bluetooth protocol stacks, low-power protocol stacks, etc.

[0170] The kernel layer includes the kernel core, the Hardware Abstraction Layer (HAL), and the hardware driver layer. Specifically in practical applications, the kernel core can interact with the upper layer through the Cortex Microcontroller Software Interface Standard (CMSIS) API, and the hardware abstraction layer can interact with the upper layer through the HAL API.

[0171] This concludes the introduction to the software structure of the watch 200. It can be understood that Figure 5 the layers in the shown software structure and the components included in each layer do not constitute specific limitations on the watch 200. In other embodiments of the present application, the watch 200 may include more or fewer layers than shown, and each layer may include more or fewer components, which are not limited in this application.

[0172] To better understand the exercise plan adjustment method provided in the embodiments of the present application, based on Figure 3 the mobile phone 100 with the shown software structure and Figure 5 the watch 200 with the shown software structure, in combination with Figure 6 a system for implementing the exercise plan adjustment method provided in the embodiments of the present application will be described.

[0173] Referring to Figure 6 , exemplarily, a system for implementing the exercise plan adjustment method may include a mobile phone 100 and a watch 200.

[0174] Specifically in the embodiments of the present application, a sports health APP is installed in the mobile phone 100. Optionally, the sports health APP may integrate the logic for intelligently adjusting the exercise plan according to five scenarios provided in the embodiments of the present application.

[0175] Optionally, the five scenarios, for example, include fatigue, physiological cycle, weather, improvement of exercise ability, and non-compliance with the execution rate.

[0176] Continuing to refer to Figure 6 , exemplarily, the processing of the integrated functions of the sports health APP can be implemented by a separate sports middle platform Kit (tool). The specific implementation of the sports middle platform Kit is not limited in this application.

[0177] In addition, it should be noted that the mobile phone 100 also needs to include a Software Development Kit (SDK) for realizing the interconnection with the watch 200. In the embodiments of the present application, this is called the interconnection SDK, but in actual applications, it can be named according to needs. In this way, the mobile phone 100 can realize the interconnection management of multiple devices through the interconnection SDK using the same account, and data synchronization can also be performed on multiple devices under the same account.

[0178] Continue to see Figure 6 , illustratively, a communication protocol is also required in the mobile phone 100. The mobile phone 100 and the watch 200 can establish a communication connection between the two based on their respective communication protocols.

[0179] Among them, watch 200 shows the logical control services, communication protocols, algorithms, etc. required to implement this case.

[0180] In addition, for the watch 200, its display screen can be used to display prompt information related to the adjustment of the exercise plan made by the mobile phone 100 according to the five major scenarios, course reminder information in the exercise plan, etc.

[0181] In addition, in some possible implementations, the system for implementing the exercise plan adjustment method may also include a sports health data cloud platform and a big data cloud platform, etc.

[0182] Optionally, the mobile phone 100 can interact with the sports health data cloud platform to achieve data cloud synchronization.

[0183] Optionally, the mobile phone 100 can also interact with the big data cloud platform to send the management data of faults or operations to the big data cloud platform, so that technical personnel can locate the abnormalities of the sports health APP based on the management data and update, maintain, etc. the sports health APP.

[0184] Based on the above system, when a user uses the sports health APP to exercise, the exercise plan adjustment method provided by the embodiment of the present application can be used to provide scientific guidance and suggestions for small cycles in scenarios such as fatigue, physiological cycle, weather, etc., and to adjust the exercise plan for large cycles in scenarios such as the improvement of the user's sports ability and the inconsistency of the execution rate, so as to ensure that the user's training is more scientific, avoid injuries and overtraining, and then achieve the user's exercise goals. For example, in the running exercise plan, the running goals of maintaining health, completing a 3 km race, completing a 5 km race, improving 5 km performance, improving 10 km performance, improving half marathon, and improving full marathon are achieved.

[0185] Optionally, in some possible implementations, for example, 4 to 10 days can be set as a small cycle, and 28 to 56 days (4 to 8 weeks) can be set as a large cycle.

[0186] For ease of explanation, the present application embodiment takes 7 days (1 week) as a small cycle and 41 days (6 weeks) as a large cycle as an example.

[0187] It should be understood that the above description is only an example for better understanding the technical solution of this embodiment, and is not the only limitation to this embodiment. In practical applications, the small cycle and the large cycle can be set according to actual conditions, and this application does not limit this.

[0188] The following describes the exercise plan adjustment method provided by the embodiments of the present application from the adjustment of the exercise plan in a small cycle and the adjustment of the exercise plan in a large cycle respectively.

[0189] Optionally, the adjustment of the exercise plan in a small cycle mainly provides scientific guidance and suggestions before the user exercises. The adjustment of the exercise plan in a large cycle can re-plan a new exercise plan according to the implementation degree of the current exercise plan and the change of the user's ability.

[0190] The following is the content of the scenarios involved in the adjustment of the exercise plan in a small cycle:

[0191] Scenario 1: Small cycle fatigue adjustment plan

[0192] Refer to Figure 7 In Fig. (1), exemplarily, the icons of some or all of the currently installed applications are displayed on the interface 10a of the mobile phone 100. These icons include the icon 10a-1 of the sports health APP.

[0193] Optionally, when the user clicks on the icon 10a-1, the mobile phone 100 responds to this operation and starts the sports health APP. After the sports health APP is started, the interface displayed on the display screen will change from Figure 7 the interface 10a shown in Fig. (1) to Figure 7 the interface 10b shown in Fig. (2).

[0194] Among them, the interface 10b can be the default interface displayed after the sports health APP is started. Optionally, the interface 10b is, for example, the interface corresponding to the "Health" option, that is, when the "Health" option shown in the bottom task bar (including the "Health" option, "Sports" option, "Device" option, "My" option) in the interface 10b is selected (in the Figure 7 style shown in Fig. (2)), the corresponding interface.

[0195] Continue to refer to Figure 7 Fig. (2). Exemplarily, the interface 10b can include various health-related function options, information, etc. For example, information related to the number of steps today, information related to medium and high intensity, information related to activity consumption, and corresponding graphs. Also, for example, function options and information corresponding to exercise records. Also, for example, the "Sleep" option for viewing sleep conditions. Also, for example, the "Heart Health" option for viewing heart-related data. Also, for example, the "Steps" option for viewing the recent number of walking steps. Also, for example, the "Physiological Cycle" option, "Weight" option, etc.

[0196] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the sole limitation of this embodiment. In practical applications, users can, according to their usage habits, edit the option cards displayed on interface 10b, such as adjusting the display positions of each option card, the option cards to be displayed and hidden on interface 10b, etc., and this application does not limit this.

[0197] Continue to refer to Figure 7 in (2), exemplarily, when the user clicks on the "Sports" option in interface 10b, the mobile phone 100 responds to this operation and will switch from interface 10b to the interface corresponding to the "Sports" option, such as Figure 8 the interface 10c shown in (1) therein. Among them, the style of the "Sports" option shown in the bottom task bar of interface 10c indicates that the "Sports" option is selected.

[0198] Refer to Figure 8 in (1), exemplarily, interface 10c may include various sports-related options, information, etc. For example, the number of kilometers accumulated by the user for outdoor running, various sports options (such as outdoor running, indoor running, walking, cycling, etc.). Also for example, the card corresponding to the formulated sports plan, such as Figure 8 the "XX Running Plan" card shown in (1) therein. Also for example, the "All Courses" option for viewing all fitness courses, the "All Plans" option for viewing all sports plans, etc.

[0199] It can be understood that in the embodiment of this application, "XX Running Plan" is only an exemplary illustration, and in practical applications, it can be named other names according to needs.

[0200] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the sole limitation of this embodiment. In practical applications, other cards can also be displayed on interface 10c, such as the course ranking card, the plan recommendation card, etc., and this application does not limit this.

[0201] Taking the running plan formulated by the user as an example, continue to refer to Figure 8 in (1), exemplarily, the "XX Running Plan" card can display the total cycle of the formulated running plan (31 days shown in the figure), the current progress (2 days shown in the figure), and the course arrangement for this week.

[0202] Continue to refer to Figure 8 in (1), exemplarily, in the part of the course arrangement for this week in the "XX Running Plan" card, different icons can be used to identify the sports courses. For example, for core courses, that is, courses with a relatively high training intensity, a dumbbell icon can be used. For ordinary courses, that is, courses with a relatively low training intensity, a circle icon can be used.

[0203] In addition, it should be noted that for different exercise goals, such as running goals, when formulating or adjusting an exercise plan, the core courses and general courses can follow the following conditions.

[0204] For the scenario with only core courses, when the user's goal is to maintain health, the number of core training days (i.e., the dates with core courses) available for the user to train per week in the exercise plan can be, for example, 2 days.

[0205] For the scenario with only core courses, when the user's goal is to get started as a novice, the number of core training days available for the user to train per week in the exercise plan can be, for example, 2 days or 3 days.

[0206] For the scenario with only core courses, when the user's goal is to improve performance, the number of core training days available for the user to train per week in the exercise plan can be, for example, 3 days.

[0207] For the scenario with both core courses and general courses, when the user's goal is to get started as a novice, the number of training days available for the user to choose per week in the exercise plan (including the number of core training days and general training days) can be, for example, 3 days or more. Optionally, when the number of training days is 3 days, for example, the core training days are 2 days and the general training days are 1 day.

[0208] For the scenario with both core courses and general courses, when the user's goal is to get started as a novice, the number of training days available for the user to choose per week in the exercise plan can be, for example, 3 days or more.

[0209] For the scenario with both core courses and general courses, when the user's goal is to improve performance, the number of training days available for the user to choose per week in the exercise plan can be, for example, 3 days or more.

[0210] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment and does not serve as the only limitation to this embodiment. In actual applications, the number of training days available for the user to choose per week in the exercise plan can be reasonably adjusted according to the user's physical condition, and this application does not limit this.

[0211] In addition, since the "XX Running Plan" card shows the course arrangement for a week. In order to distinguish the courses in the past time, the current time, and the future time, different colors and styles can be used for identification. Regarding the styles of the general course identification in the past time, the general course identification in the current time, the general course identification in the future time, the core course identification in the past time, the core course identification in the current time, and the core course identification in the future time, in some possible implementation manners, they can be as Figure 9 shown.

[0212] It should be understood that the above description is only an example listed for a better understanding of the technical solution of this embodiment, and is not the only limitation to this embodiment. In practical applications, other styles of icons can also be used to identify courses of different time and different training intensities, and this application does not limit this.

[0213] by Figure 9 Take the style shown as an example. Figure 8 In the "XX Running Plan" card shown in (1), the specific course arrangement for this week is as follows: the past Monday (11th) is scheduled for ordinary courses, today (Wednesday, 13th) is scheduled for ordinary courses, and the upcoming Friday (15th) is scheduled for core courses.

[0214] For example, when the user wants to exercise, he can click on the "XX running plan" card. In response to this operation, the mobile phone 100 will jump from the interface 10c to the interface corresponding to the XX running plan, such as Figure 8 Interface 10d shown in (2).

[0215] See also Figure 8 In (2), illustratively, the interface 10d may include multiple cards, such as a card 10d-1 for completion of the day's courses, a card 10d-2 for this week's course schedule, cards for all courses included in the selected date, such as a card 10d-3 corresponding to a pre-run warm-up exercise course and a card 10d-4 corresponding to a pleasant experience run course, and an icon 10d-0 for opening an introduction to a core training day and a normal training day.

[0216] Optionally, when the user clicks the icon 10d-0, the mobile phone 100 responds to the operation by Figure 8 The interface 10d shown in (2) pops up as follows Figure 10 Window 10d-01 is shown.

[0217] See also Figure 10 For example, the window 10d-01 displays relevant information about the core training day and the ordinary training day. When the user clicks the "Got it" option displayed in the window 10d-01, the mobile phone 100 responds to the operation by closing the window 10d-01, that is, the user interface returns to Figure 8 Interface 10d shown in (2).

[0218] In addition, it should be noted that in the small cycle fatigue adjustment scenario, the mobile phone 100 displays Figure 8In the case of the interface 10d shown in (2), the mobile phone 100 can determine the current fatigue level of the user based on the index data for determining the fatigue level provided by the watch 200 worn by the user, or the data evaluated by the user collected by the questionnaire feedback form displayed on the mobile phone 100. Furthermore, according to the fatigue level of the user, a prompt information window (subsequently referred to as: window) is popped up in the interface 10d, thereby realizing the movement guidance for the user, that is, realizing the adjustment of minor cycle fatigue.

[0219] Optionally, in the embodiments of the present application, the state of the user is divided into non-fatigued (non-fatigue) and fatigued. Among them, fatigue can be divided into multiple levels as needed, such as level 1 (subsequently referred to as: level 1 fatigue), level 2 (subsequently referred to as: level 2 fatigue), and level 3 (subsequently referred to as: level 3 fatigue), and non-fatigue can also be expressed as level 0 fatigue.

[0220] Regarding different user states, the reminder strategies (movement guidance) that can be followed are shown in Table 1.

[0221] Table 1 Movement guidance corresponding to different user states

[0222] Fatigue level Exercise guidance Level 0 fatigue No reminder Level 1 fatigue Remind the user to pay attention to their physical condition during the course and ensure sufficient rest Level 2 fatigue It is recommended that the user not train today or take regular courses with a low training intensity Level 3 fatigue It is recommended that the user not perform any training today

[0223] Optionally, in the case of level 0 fatigue, that is, non-fatigue, since there is no need to give additional reminders to the user, the interface 10d can remain in the Figure 8 style shown in (2).

[0224] Optionally, in the case of level 1 fatigue, the relevant content for reminding the user to pay attention to their physical state and ensure sufficient rest during the execution of the course in the window popped up in the interface 10d can be as Figure 11 shown in (1). That is, in this case, the style of the window displayed in the interface 10d is Figure 11 the window 10d-51 shown in (1).

[0225] Optionally, in the case of level 1 fatigue, the relevant content for suggesting that the user not carry out training today or carry out ordinary courses with a low training intensity in the window popped up in the interface 10d can be as Figure 11 shown in (2). That is, in this case, the style of the window displayed in the interface 10d is Figure 11 the window 10d-52 shown in (2).

[0226] Optionally, in the case of level 1 fatigue, the relevant content for suggesting that the user not carry out any training today in the window popped up in the interface 10d can be as Figure 11 shown in (3). That is, in this case, the style of the window displayed in the interface 10d is Figure 11 the window 10d-53 shown in (3).

[0227] It should be noted that when the user clicks on Figure 11 the "Got it" option in window 10d-51 shown in (1) of Figure 11 or the "Got it" option in window 10d-52 shown in (2) of Figure 11 or the "Got it" option in window 10d-53 shown in (3) of

[0228] In addition, it should be noted that Figure 11 the courses on ordinary training days shown in window 10d-52 shown in (2) of

[0229] that is, the training days with ordinary courses arranged; the courses with high training intensity, that is, the training days with core courses arranged.

[0230] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the sole limitation of this embodiment.

[0231] Optionally, during the implementation of the small cycle fatigue adjustment process, the specific processing logic for determining the fatigue level implemented on the mobile phone 100 side can be as Figure 12 shown.

[0232] S101, the mobile phone 100 determines whether at least one of the fatigue levels determined according to the morning pulse resting heart rate, or HRV, or ACWR is a level 3 fatigue.

[0233] Among them, the morning pulse resting heart rate refers to the average resting heart rate of the user 2 hours before going to bed.

[0234] Among them, HRV refers to the minute differences that exist between successive heartbeats. In this embodiment, specifically, the RMSSD (the square root of the mean of the sum of the squares of the differences between adjacent normal R-R intervals), the ratio of low frequency (LF) to high frequency (HF) (LF / HF) determined according to HRV data are used to determine the fatigue level.

[0235] Among them, the R-R interval generally refers to the time interval between two heartbeats.

[0236] Among them, ACWR refers to the ratio of the training volume completed within 1 week (acute workload or acute load) to the average training volume completed within 4 weeks (average chronic workload or average chronic load).

[0237] Optionally, when any one of the fatigue levels determined based on the data of these three dimensions is level 3 fatigue, it can be determined that the user's current fatigue level is level 3 fatigue.

[0238] Correspondingly, when it is determined that the user's current fatigue level is level 3 fatigue, a window 10d-53 as shown in (3) in Figure 11 can pop up in the interface 10d.

[0239] When there is no level 3 fatigue among the fatigue levels determined based on the data of these three dimensions, the following priority can be followed (morning pulse resting heart rate > HRV > ACWR > sleep), select the data corresponding to the priority, and determine the user's fatigue level according to the calculation logic corresponding to this dimension.

[0240] Optionally, when a specific fatigue level, such as level 0 fatigue, or level 1 fatigue, or level 2 fatigue, is determined based on the data of high priority, the mobile phone 100 can stop the operation of determining the fatigue level based on the data of low priority. In this way, it is not necessary to calculate the fatigue level according to the data of each dimension, reducing the calculation amount.

[0241] S102, the mobile phone 100 determines whether the fatigue level determined based on the morning pulse resting heart rate data is level 0 fatigue, or level 1 fatigue, or level 2 fatigue.

[0242] Optionally, in the scenario where the fatigue level determined based on the morning pulse resting heart rate data is level 0 fatigue, or level 1 fatigue, or level 2 fatigue, it can be determined that the user's current fatigue level is the fatigue level determined based on the morning pulse resting heart rate data. Otherwise, that is, when the fatigue level cannot be determined based on the morning pulse resting heart rate data, the fatigue level can be determined based on the HRV data with a priority level lower than that of the morning pulse resting heart rate, that is, step S103 is executed.

[0243] S103, the mobile phone 100 determines whether the fatigue level determined based on the HRV data is level 1 fatigue or level 2 fatigue.

[0244] Optionally, in the scenario where the fatigue level determined based on the HRV data is level 0 fatigue, or level 1 fatigue, or level 2 fatigue, it can be determined that the user's current fatigue level is the fatigue level determined based on the HRV data. Otherwise, that is, when the fatigue level cannot be determined based on the HRV data, the fatigue level can be determined based on the ACWR data with a priority level lower than that of the HRV, that is, step S104 is executed.

[0245] S104 , the mobile phone 100 determines whether the fatigue level determined according to the ACWR data is level 1 fatigue or level 2 fatigue.

[0246] Optionally, in a scenario where the fatigue level determined based on the ACWR data is fatigue level 0, fatigue level 1, or fatigue level 2, it can be determined that the user's current fatigue level is the fatigue level determined based on the ACWR data. Otherwise, that is, when the fatigue level cannot be determined based on the ACWR data, the fatigue level can be determined based on sleep data that has a lower priority than HRV, that is, step S104 is executed.

[0247] S105 , the mobile phone 100 determines whether the fatigue level determined based on the sleep data is level 1 fatigue or level 2 fatigue.

[0248] Optionally, in a scenario where the fatigue level determined based on the sleep data is level 0 fatigue, level 1 fatigue, or level 2 fatigue, it can be determined that the user's current fatigue level is the fatigue level determined based on the sleep data. Otherwise, that is, when the fatigue level cannot be determined based on the sleep data, it can be assumed that the user is not currently fatigued, that is, the fatigue level is level 0 fatigue.

[0249] In addition, it should be noted that in some possible implementations, when executing step S102, step S103, step S104, and step S105, it is possible to first determine whether the data of the corresponding dimension is valid, so as to further ensure the accuracy of the determined fatigue level.

[0250] For the judgment rules on whether the morning pulse resting heart rate data, HRV data, ACWR data, and sleep data are valid, please refer to the corresponding standards and will not be repeated here.

[0251] Therefore, the mobile phone 100 determines the user's current fatigue level based on multi-dimensional data and in accordance with the priority of morning pulse resting heart rate>HRV>ACWR>sleep, thereby accurately detecting the user's fatigue level and reducing unnecessary calculations. In this way, after determining the user's current fatigue level, the mobile phone 100 can make small-cycle fatigue adjustments, specifically, giving guidance and suggestions suitable for the user's current fatigue level before fitness, thereby avoiding the occurrence of excessive exercise that causes damage to the user's body as much as possible.

[0252] The following, in conjunction with the accompanying drawings, describes the specific logic of determining fatigue level based on morning pulse resting heart rate data, HRV data, ACWR data, and sleep data.

[0253] The following is the content of determining fatigue level based on morning pulse resting heart rate data:

[0254] See Figure 13 Exemplarily, when the user wears the watch 200 at night during sleep, the watch 200 will determine the user's morning resting heart rate, i.e., the average resting heart rate in the 2 hours before going to bed, according to the morning resting heart rate calculation logic and heart rate algorithm, etc.

[0255] Optionally, regarding the user's bedtime, it can be determined based on the sleep data collected by the watch 200 in the past period of time for the user.

[0256] In addition, in order to distinguish whether the morning resting heart rate is of the first day or the second day, in some possible implementation manners, 8:00 p.m. every day can be selected as the dividing line. That is to say, when the bedtime is earlier than 8:00 p.m., the determined morning resting heart rate is of the first day (the previous day); when the bedtime is later than 8:00 p.m., the determined morning resting heart rate is of the second day.

[0257] In addition, it should also be noted that during the user's sleep, the watch 200 can periodically record the resting heart rate data, such as recording once every minute. In this way, after the user wakes up, the average value of the resting heart rate in the 2 hours before going to bed can be used as the morning resting heart rate.

[0258] In addition, it should also be noted that in order to ensure data validity, for the case where the entire sleep duration is less than 2 hours, the morning resting heart rate can be calculated according to the actual sleep time.

[0259] Continue to see Figure 13 Exemplarily, after the watch 200 obtains the user's morning resting heart rate data for today, when a communication connection is established between the watch 200 and the mobile phone 100, the watch 200 will send the user's morning resting heart rate data for today to the mobile phone 100.

[0260] Continue to see Figure 13 Exemplarily, after the mobile phone 100 receives the morning resting heart rate data sent by the watch 200, it can judge the user's heart rate fluctuation range according to the morning resting heart rate data, and then determine the user's fatigue level today according to the heart rate fluctuation range.

[0261] It should be noted that in actual applications, the user may sleep and rest multiple times on the same day. For the case of multiple sleeps in one day, when the user opens the sports health APP to view the exercise plan, such as the interface 10d shown in (2) of the display interface of the mobile phone 100 Figure 8 In a possible implementation manner, among multiple sleeps, the morning resting heart rate data of the one with the longest sleep duration can be selected to judge the user's heart rate fluctuation range.

[0262] Optionally, the heart rate fluctuation range may include Figure 13 the 5 cases shown in

[0263] Continue to refer to Figure 13 , for example, for the case where the user's heart rate today fluctuates within N1 bpm (beat per minute) from the average value of the heart rate last week, that is, case 1a, it can be determined that the user is not fatigued today, that is, the fatigue level is level 0 fatigue.

[0264] Continue to refer to Figure 13 , for example, for the case where the user's heart rate today exceeds the average value of last week by N1 - N2 bpm (including both endpoint values) (the heart rate before today did not exceed), that is, case 1b. To avoid inaccurate determination of the fatigue level caused by temporary fluctuations in the heart rate exceeding the average value of last week by N1 - N2 bpm due to special circumstances. In one possible implementation, a Borg questionnaire can be popped up on the user interface of the mobile phone 100 for the user to conduct self-assessment, and then the fatigue level of the user today can be determined based on the assessment.

[0265] It should be noted that since the logic for determining the fatigue level provided in the embodiments of the present application also includes determining the fatigue level based on the dimension of sleep data. When the sleep data meets the preset conditions, the user also needs to intervene and enter self-assessment. Therefore, when the Borg questionnaire is popped up, a sleep quality questionnaire can also be popped up together to facilitate the user to complete the assessment together and avoid popping up the questionnaire again when the sleep data is needed to determine the fatigue level later.

[0266] For example, when the heart rate fluctuation range determined based on the morning pulse resting heart rate data belongs to case 1b, when the user opens the sports health APP and enters Figure 8 the interface 10d shown in (2) of Figure 14 , the mobile phone 100 can directly jump to the questionnaire feedback interface (interface 10e) shown in (1) of

[0267] Refer to Figure 14 in (1). For example, the interface 10e includes 2 questionnaires, such as questionnaire 10e-1 and questionnaire 10e-2. Among them, questionnaire 10e-1 is a questionnaire for determining the user's current fatigue level, that is, the above-mentioned Borg questionnaire; questionnaire 10e-2 is a questionnaire for determining the user's sleep quality last night, that is, the above-mentioned sleep quality questionnaire. Among them, the Borg questionnaire includes 11 levels of fatigue corresponding to different scores (0 - 10 in sequence). Swiping up in the interface 10e shown in Figure 14 (1) can display the complete sleep quality questionnaire. As shown in Figure 14 (2), the sleep quality questionnaire includes 4 options.

[0268] When the user selects an option from the Borg questionnaire and the sleep quality questionnaire shown in interface 10e according to the current physical state, and clicks the submit option 10e-3, in the process of determining the fatigue level based on the morning pulse resting heart rate, the mobile phone 100 will determine the current fatigue level according to the score corresponding to the fatigue degree selected by the user in the Borg questionnaire.

[0269] Optionally, the relationship between the self-assessment score obtained from the Borg questionnaire and the fatigue level can be as shown in Table 2.

[0270] Table 2 Relationship between the self-assessment score obtained from the Borg questionnaire and the fatigue level

[0271] User self - assessment score (including endpoint values) Fatigue level 0 - 3 points Level 0 fatigue 4 points Level 1 fatigue 5 - 7 points Level 2 fatigue 8 points and above Level 3 fatigue

[0272] Thus, in the case of 1b, based on the self-assessment score obtained from the Borg questionnaire and Table 2, the mobile phone 100 can quickly determine the current fatigue level of the user.

[0273] Optionally, Table 2 can be pre-stored in the storage medium of the mobile phone 100 locally, such as the internal memory.

[0274] Continue to refer to Figure 13 , for example, for the case where the heart rates of the user for two consecutive days, today and yesterday, both exceed the weekly average value by N1 - N2 bpm, that is, case 1c, there is no need to pop up interface 10e, that is, it is not necessary to determine based on the self-assessment score of the user, and it is directly determined that the fatigue level of the user today is level 2 fatigue.

[0275] Continue to refer to Figure 13 , for example, for the case where the heart rates of the user for three consecutive days, today, yesterday, and the day before yesterday, all exceed the weekly average value by N1 - N2 bpm, that is, case 1d, there is no need to pop up interface 10e, that is, it is not necessary to determine based on the self-assessment score of the user, and it is directly determined that the fatigue level of the user today is level 3 fatigue.

[0276] Continue to refer to Figure 13 , for example, for the case where the user's signaling exceeds the weekly average value by N3 bpm or more, indicating that the heart rate fluctuation today is not caused by special circumstances. In this case, there is no need to pop up interface 10e, that is, it is not necessary to determine based on the self-assessment score of the user, and it is directly determined that the fatigue level of the user today is level 3 fatigue.

[0277] It should be noted that the above N1, N2, and N3 satisfy the following relationship: 0 < N1 < N2 < N3.

[0278] Optionally, in some possible implementation manners, the value of N1 can be, for example, 5, the value of N2 can be, for example, 10, and the value of N3 can be, for example, 11.

[0279] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment and does not serve as the sole limitation of this embodiment. In practical applications, the specific values of N1, N2, and N3 can be adaptively adjusted according to the actual situation of the user, and this application does not limit this.

[0280] Thus, the fatigue level is determined according to the morning pulse resting heart rate data.

[0281] The following is the content of determining the fatigue level according to the HRV data:

[0282] See Figure 14 , for example, when the user wears the watch 200, the watch 200 will record the heart rate variability data during the period when the user wears the watch 200 according to the heart rate variability calculation logic and heart rate algorithm, etc., and send the heart rate variability data to the mobile phone 100 by establishing a communication connection with the mobile phone 100.

[0283] Continue to see Figure 14 , for example, after receiving the heart rate variability data sent by the watch 200, the mobile phone 100 can determine the current fatigue level of the user according to the heart rate variability data.

[0284] Optionally, the mobile phone 100 can determine the current fatigue level of the user according to the RMSSD and LF / HF ratios determined from the heart rate variability data.

[0285] Among them, RMSSD refers to the root mean square of the differences between adjacent normal cardiac cycles. It is an important index of heart rate variability and is used to reflect the activity of the body's parasympathetic nerves.

[0286] Among them, the LF / HF ratio refers to the ratio of low-frequency heart rate variability to high-frequency heart rate variability. Usually, the smaller the LF / HF ratio, the better the function of the user's autonomic nervous system and the better the heart health status.

[0287] Regarding the calculation of the RMSSD and LF / HF ratios, it can be based on the relevant literature of heart rate variability and will not be elaborated here.

[0288] In addition, it should be noted that in order to ensure the accuracy of the determined fatigue level, the data such as RMSSD, LF, HF, and RR intervals measured during sleep need to be consistent with the HRV change trend.

[0289] Optionally, the consistency can be stipulated to reach 80%.

[0290] Based on these two heart rate variability indexes of RMSSD and LF / HF ratios, multiple situations can be divided, such as Figure 15 the 5 situations of situation 2a to situation 2e shown in

[0291] Continue to refer to Figure 14 , for example, for the case where RMSSD is higher than a milliseconds and the LF / HF ratio is lower than x, that is, case 2a, it can be determined that the user is not fatigued today, that is, the fatigue level is level 0 fatigue.

[0292] Continue to refer to Figure 14 , for example, for the case where RMSSD is between b and a milliseconds (including the endpoint values) and the LF / HF ratio is between x and y (including the endpoint values), that is, case 2b, it can be determined that the user is fatigued today, and the fatigue level is level 1 fatigue.

[0293] Continue to refer to Figure 14 , for example, for the case where RMSSD is between c and b milliseconds (including the endpoint values) and the LF / HF ratio is between y and z (including the endpoint values), that is, case 2c, it can be determined that the user is fatigued today, and the fatigue level is level 2 fatigue.

[0294] Continue to refer to Figure 14 , for example, for the case where RMSSD is lower than c milliseconds and the LF / HF ratio is higher than z, that is, case 2d, it can be determined that the user is fatigued today, and the fatigue level is level 3 fatigue.

[0295] Continue to refer to Figure 14 , for example, when RMSSD and the LF / HF ratio do not belong to case 2a, or case 2b, or case 2c, or case 2d, it can be determined that the user is not fatigued today, that is, the fatigue level is level 0 fatigue.

[0296] It should be noted that the above a, b, and c satisfy the following relationship: a > b > c > 0.

[0297] Optionally, in some possible implementation manners, the value of a can be, for example, 70, the value of b can be, for example, 50, and the value of c can be, for example, 30.

[0298] In addition, it should also be noted that the above x, y, and z satisfy the following relationship: 0 < x < y < z.

[0299] Optionally, in some possible implementation manners, the value of x can be, for example, 1.0, the value of y can be, for example, 1.5, and the value of z can be, for example, 2.0.

[0300] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the only limitation to this embodiment. In actual applications, the specific values of a, b, and c, as well as x, y, and z, can be adaptively adjusted according to the actual situation of the user, and this application does not limit this.

[0301] Thus, the determination of the fatigue level according to the HRV data is realized.

[0302] The following is the content for determining the fatigue level based on ACWR data:

[0303] Regarding the determination of the fatigue level based on ACWR data, it can be divided into two scenarios: the scenario where the user wears the watch 200, calculates the ACWR based on the heart rate data provided by the watch 200, and then determines the fatigue level (hereinafter referred to as: Scenario 1.1); and the scenario where the mobile phone 100 does not interact with the watch 200, calculates the ACWR based on the RPE value and training duration obtained from the course feedback, and then determines the fatigue level (hereinafter referred to as: Scenario 1.2). The following will respectively combine Figure 16 and Figure 17 to illustrate Scenario 1.1 and Scenario 1.2.

[0304] Scenario 1.1:

[0305] Referring to Figure 16 , exemplarily, when the user wears the watch 200, the watch 200 will obtain the heart rate data of the user at the end of each training according to the acquisition logic and heart rate algorithm related to the heart rate data, and send the obtained heart rate data to the mobile phone 100.

[0306] Continuing to refer to Figure 16 , exemplarily, after receiving the heart rate data sent by the watch 200, the mobile phone 100 will calculate the ACWR based on the heart rate data, and then determine the fatigue level according to the ACWR.

[0307] It can be understood that ACWR refers to the ratio of the training volume (acute workload or acute load) completed within 1 week and the average training volume (average chronic workload or chronic load mean) completed within 4 weeks. That is, ACWR = the ratio of the acute load completed by the user within 1 week and the chronic load mean completed within 4 weeks.

[0308] Optionally, in some implementation manners, the calculation of ACWR can adopt the method of Exponentially Weighted Moving-Average (EWMA). Specifically, the current ACWR of the user can be determined according to the following formula (1).

[0309] ACWR = Training load × λa + [(1 - λa) × ACWR_Yesterday] Formula (1)

[0310] Wherein, λa represents the degree of attenuation of the training load over time, and the specific value is between 0 and 1.

[0311] In addition, the degree of attenuation of the training load represented by λa satisfies the following formula (2).

[0312] λa = 2 / (N + 1) Formula (2)

[0313] Among them, N is the time decay constant, usually the time window for acute load and chronic load. Among them, the time window for acute load is 7 days, that is, 1 week; the time window for chronic load is 28 days, that is, 4 weeks.

[0314] For example, if the acute load of the user in the recent 1 week is 4, and the acute loads corresponding to the previous 1, 2, and 3 weeks are 1, 2, and 3 respectively. Then the chronic load coupling for 4 weeks = 1 + 2 + 3 + 4 = 10, and the average chronic load = 10 / 4 = 2.5.

[0315] Among them, the training load in formula (1) can be determined according to the pre-divided intensity levels and training duration (min), specifically according to the following formula (3).

[0316] Training load = intensity level × training duration (min) Formula (3)

[0317] Optionally, the intensity levels can be divided according to heart rate intervals. Specifically, based on the heart rate data of all trainings (such as running + strength), the average value is calculated. Using the training interval stimulus amount method, according to the individual's maximum heart rate, the individual's heart rate can be divided into five levels, starting from 50% of the maximum heart rate and increasing by 10% for each interval.

[0318] Optionally, the intensity levels can be divided according to 5 heart rate intervals, specifically as shown in Table 3.

[0319] Table 3 Relationship between heart rate and intensity level

[0320] Intensity level Heart rate range 1 50% - 60HRmax 2 60% - 70HRmax 3 70% - 80HRmax 4 80% - 90HRmax 5 90% - 100HRmax

[0321] Thus, based on the heart rate data sent by the watch 200 after each training session and Table 3, the mobile phone 100 can determine the training level, and then determine the training load according to the training duration and formula (3).

[0322] For example, if the user's maximum heart rate is 195 beats / min and exercises at a heart rate of 160 beats / min for 20 min, the calculated heart rate interval for the exercise is 160 / 195 × 100% = 82%, within the range corresponding to intensity level 4. Therefore, the calculated training load is 4 × 20 = 80.

[0323] Correspondingly, after determining the training load, according to the ACWR of yesterday (ACWR_yesterday, or the ACWR corresponding to the previous training session) and formulas (1) and (2), the user's current ACWR can be quickly determined.

[0324] Optionally, ACWR can be divided into 4 intervals, and these 4 intervals can be regarded as 4 specific situations, such as Figure 16Situations 3a, 3b, 3c, and 3d shown in []. And these four intervals can respectively correspond to different fatigue levels.

[0325] Regarding the relationship between ACWR and the fatigue level, it can be as shown in Table 4.

[0326] Table 4 Relationship between ACWR and the fatigue level

[0327] ACWR value Fatigue level ACWR<d Level 0 fatigue d ≤ ACWR < e Level 1 fatigue e ≤ ACWR ≤ f Level 2 fatigue ACWR > f Level 3 fatigue

[0328] Thus, based on the calculated value of ACWR and Table 4, the mobile phone 100 can quickly determine the user's current fatigue level.

[0329] Optionally, Table 4 can be pre-stored in the storage medium local to the mobile phone 100, such as the internal memory.

[0330] It should be noted that the above d, e, and f satisfy the following relationship: 0 < d < e < f.

[0331] Optionally, in some possible implementation manners, the value of d can be, for example, 1.4, the value of e can be, for example, 1.5, and the value of f can be, for example, 2.0.

[0332] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment and does not serve as the only limitation to this embodiment. In practical applications, the specific values of d, e, and f can be adaptively adjusted according to the actual situation of the user, and this application does not limit this.

[0333] Thus, in the case of interaction between the mobile phone 100 and the smartwatch 200, it is realized to calculate ACWR based on the heart rate data provided by the smartwatch 200, and further determine the fatigue level.

[0334] Scenario 1.2:

[0335] See Figure 17 , for example, in the case where the user does not wear the smartwatch 200, or there is no communication connection established between the smartwatch 200 and the mobile phone 100, the mobile phone 100 can pop up a course feedback form, such as the rating of perceived exertion (RPE) scale, after each training session of the user, and then calculate ACWR based on the RPE value selected by the user in the RPE table and the training duration (min), and further determine the fatigue level according to ACWR.

[0336] Optionally, the manner of popping up the RPE table can be, for example, to pop up a window 10f-1 in the interface 10f corresponding to the end of the training session, such as Figure 18 shown in the interface 10f.

[0337] Optionally, for self - assessment by the user in window 10f - 1, the selectable RPE values may include 11 scores from 0 to 10, and the description corresponding to each score is similar to the description corresponding to the same score in the borg questionnaire shown in (1) in Figure 11 and will not be elaborated here.

[0338] Optionally, each RPE score can be regarded as an intensity level. That is, in the absence of the watch 200, the mobile phone 100 can be based on the following formula (4).

[0339] Training load = RPE value × training duration (min) Formula (4)

[0340] Thus, in the case where the mobile phone 100 does not interact with the watch 200, according to the ACWR of yesterday (ACWR_yesterday, or the ACWR corresponding to the previous training session) and formulas (1) and (2) given in Scenario 1.1, the user's current ACWR can be quickly determined.

[0341] Correspondingly, after determining the ACWR, according to Table 4 given in Scenario 1.1, the mobile phone 100 can quickly determine the user's current fatigue level.

[0342] Thus, it is realized to calculate the ACWR based on the RPE value and training duration obtained from the course feedback, and further determine the fatigue level.

[0343] The following is the content for determining the fatigue level based on sleep data:

[0344] See Figure 19 , for example, in the case where the user wears the watch 200 while sleeping, the watch 200 will obtain the sleep data of the user during sleep according to the sleep data acquisition logic and sleep algorithm, etc.

[0345] Optionally, the watch 200 can be timed, or after detecting that the user wakes up, send the sleep data to the mobile phone 100 that has established a communication connection.

[0346] Continue to see Figure 19 , for example, after receiving the sleep data sent by the watch 200, the mobile phone 100 will determine whether the user's sleep meets any one or more of the following three conditions according to the received sleep data.

[0347] Condition 1: Sleep duration < the first preset duration;

[0348] Condition 2: Number of night awakenings ≥ preset number;

[0349] Condition 3: Average wake - up time earlier than the second preset duration compared to the previous week.

[0350] Optionally, the first preset duration is, for example, 5 hours (h).

[0351] Optionally, the preset number of times is, for example, 3 times.

[0352] Optionally, the second preset duration is, for example, 30 minutes (min).

[0353] Optionally, when the mobile phone 100 determines that the user's sleep meets at least one of the above three conditions based on the sleep data, when the user opens the Sports Health APP and is in interface 10d, it will jump from interface 10d to interface 10e shown in Figure 13, and then determine the fatigue level according to the results selected by the user in the sleep quality questionnaire in interface 10e.

[0354] It should be understood that the priority of the mobile phone 100 using the sleep data to determine the fatigue level is lower than the priority of using the morning pulse resting heart rate data to determine the fatigue level. Therefore, if in the stage of using the morning pulse resting heart rate data to determine the fatigue level, situation 1b occurs, the sleep quality questionnaire will be popped up together when the borg questionnaire is popped up, that is, both questionnaires are displayed in interface 10e. Therefore, when entering the link of determining the fatigue level according to the sleep data without determining the fatigue level based on the morning pulse resting heart rate data, HRV data, and ACWR data, there is no need to jump to interface 10e again, and the fatigue level can be directly determined according to the results selected by the user in the sleep quality questionnaire in situation 1b of the user.

[0355] Through Figure 11 As can be seen from interface 10e shown in (2) of Figure 13, the sleep quality questionnaire includes 4 options. In practical applications, these 4 options can be corresponding to 4 specific situations, such as very good corresponding to situation 4a, good corresponding to situation 4b, poor corresponding to situation 4c, and very poor corresponding to situation 4d. Among them, these 4 situations can correspond to different scores, and different scores can correspond to different fatigue levels.

[0356] Optionally, the scores corresponding to each option in the sleep quality questionnaire, and the relationship between different scores and the fatigue level can be as shown in Table 4.

[0357] Table 5 The scores corresponding to each option in the sleep quality questionnaire, and the relationship between different scores and the fatigue level

[0358] Sleep quality questionnaire options User self - assessment score Fatigue level Very good 0 points Level 0 fatigue Good 1 point Level 0 fatigue Poor 2 points Level 1 fatigue Very poor 3 points Level 2 fatigue

[0359] Thus, in the case where the sleep data meets any one or more of the above three conditions, based on the options selected by the user in the sleep quality questionnaire and Table 5, the mobile phone 100 can quickly determine the user's current fatigue level.

[0360] Optionally, Table 5 can be pre-stored in a storage medium local to the mobile phone 100, such as the internal memory.

[0361] Thus, the determination of the fatigue level based on sleep data is achieved.

[0362] In the small-cycle fatigue adjustment solution provided in the embodiments of the present application, by combining the health-related data collected by the smart wearable device, such as the watch 200 in the above embodiments, such as morning pulse resting heart rate data, HRV data, heart rate data (calculating ACWR), sleep data, etc. with the self-evaluation results collected from various subjective evaluation questionnaires displayed on the smart device used by the user, such as the mobile phone 100, the four specific fatigue level determination methods of determining the fatigue level by morning pulse resting heart rate data, determining the fatigue level by HRV data, determining the fatigue level by ACWR data, and determining the fatigue level by sleep data are mutually complementary, and in the priority order of morning pulse resting heart rate having a higher priority than HRV, HRV having a higher priority than ACWR, and ACWR having a higher priority than sleep, a fatigue level is selected from the fatigue levels determined from these four dimensions, making the finally determined fatigue level more reasonable and accurate, so as to be able to give appropriate guidance suggestions (i.e., reasonably adjust the plan) before the user exercises, and avoid the user causing damage to the body due to excessive exercise.

[0363] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the sole limitation of this embodiment. In practical applications, other methods can also be used to determine the fatigue level of the user, and then make appropriate exercise guidance suggestions according to the fatigue level.

[0364] In addition, it should be noted that in some possible implementation manners, the above process of determining the fatigue level can also be determined before the user opens the sports health APP or opens the Figure 8 interface 10d shown in (2) in the Figure 8 For this situation, that is, when the user interface switches to the Figure 11 interface 10d shown in (2) in the

[0365] In addition, it should also be noted that there are not courses every day in a week, or the courses today have already been trained by the user. To avoid the situation where when there is no course or the user has already completed the training course and the user opens the Figure 8 interface 10d shown in (2) in the Figure 11Among (1), or (2), or (3), the window 10d-51, or the window 10d-52, or the window 10 is shown. Before giving exercise guidance suggestions according to the determined fatigue level, it can be further determined whether there is a course today, or whether the course today has been trained. If there is no course today, or the course today has been trained, exercise guidance suggestions may not be given according to the determined fatigue level. On the contrary, if there is a course today and the course today has not been trained, exercise guidance suggestions are given according to the determined fatigue level.

[0366] In addition, it should be noted that in order to prevent users from overtraining and causing damage to their bodies. In some possible implementation manners, it can be set that the user selects core courses for training on two consecutive days, or the load this week has met the load standard of the core courses. If the course today is also a core course, in the Figure 8 interface 10d shown in (2), a pop-up window reminds the user that they can choose to rest today or practice the general courses this week. That is, for this situation, the current fatigue level of the user may not be considered.

[0367] Optionally, for the window popped up on the interface 10d in the case of overload, such as Figure 20 the window 10d-54 shown in (1).

[0368] It should be noted that the premise of suggesting that the user practice the general courses this week is that there are still general courses available for training this week. Specifically, when there are still general courses available for training this week, in addition to the "Got it" option and the "Rest today" option, the "Change course" option can also be displayed in the window 10d-54.

[0369] Among them, when the user clicks the "Got it" option or the "Rest today" option, the mobile phone 100 can close the window 10d-54 in response to this operation behavior. When the user clicks the "Change course" option, the mobile phone 100 can close the window 10d-54 in response to this operation behavior, and display a window of "Adjusting the plan for you..." in the interface 10d, as Figure 20 shown in (2).

[0370] Exemplarily, in the case where the trainable courses today shown in the interface 10d shown in (2) include core courses, after the user clicks the "Change course" option and adjusts the plan, the interface 10d shown in (3) will be presented, that is, the trainable courses today will be adjusted to general courses. Figure 20 Figure 20

[0371] Thus, it is possible to prevent users from taking high-intensity training courses for multiple consecutive days and ensure that the user's body is not damaged. ​​

[0372] In addition, it should be noted that in actual applications, users may not train according to the course order edited in the exercise plan. This may not only affect the training effect, but also cause damage to the user's body. For example, before taking a regular course or a core course, it is usually necessary to practice a warm-up course first, but the user may not follow this order and directly click on a regular course or a core course for training. In this case, a window 10d-55 as shown in Figure 21 may pop up in interface 10d.

[0373] Exemplarily, when the user clicks the "Cancel" option in window 10d-55, the mobile phone 100 can, in response to this operation, exit the selected regular course or training course, that is, return to interface 10d again. When the user clicks the "Continue Training" option in window 10d-55, the mobile phone 100 can, in response to this operation, start the regular course or training course.

[0374] It should be understood that the above description is only an example listed for better understanding of the technical solution of this embodiment and does not serve as the sole limitation of this embodiment.

[0375] Scenario 2: Small cycle physiological cycle adjustment plan (this scenario is mainly for female users)

[0376] Before describing this scenario, first, the prerequisite for implementing this scenario, that is, setting the physiological cycle, will be described.

[0377] Optionally, in a possible implementation, the user can actively click on the "Physiological Cycle" option displayed in interface 10b as shown in Figure 7 (2) therein. In response to this operation, the mobile phone 100 can jump from interface 10b to the physiological cycle interface, such as interface 10e as shown in Figure 22 (1) therein.

[0378] Referring to Figure 22 (1) therein, exemplarily, interface 10e may include more options 10e-1, switch 10e-2, etc.

[0379] Among them, when the user clicks on more option 10e-1, the mobile phone 100 can, in response to this operation, display a window 10e-3 as shown in Figure 22 (2) therein in interface 10e.

[0380] Among them, when the user clicks on switch 10e-2, the mobile phone 100 can, in response to this operation, set today as the start time of the menstrual period. And, a menstrual period identifier and an ovulation period identifier will be displayed in the corresponding date in the record area.

[0381] Among them, when the user clicks on the "Settings" option in window 10e-3, the mobile phone 100 responds to this operation and will jump from interface 10e to the menstrual period settings interface, such as Figure 23 the interface 10f shown in (1) of

[0382] Optionally, two options, "Menstrual period length" and "Cycle length", can be displayed in interface 10f.

[0383] Optionally, in one possible implementation, the menstrual period length can default to 5 days and the cycle length can default to 30 days.

[0384] Optionally, in some other possible implementations, the user can click on the "Menstrual period length" option, and the mobile phone 100 responds to this operation and can pop up on interface 10f a Figure 23 menstrual period length setting window 10f-1 as shown in (2) of

[0385] Optionally, in some other possible implementations, the user can click on the "Cycle length" option, and the mobile phone 100 responds to this operation and can pop up on interface 10f a Figure 23 cycle length setting window 10f-2 as shown in (3) of

[0386] Optionally, in another possible implementation, for example, in the case where the user does not open interface 10e from the "Physiological cycle" option entry on interface 10b, and then opens interface 10f through the "Settings" option in window 10e-3, and completes the physiological cycle settings through the menstrual period length setting window 10f-1 and the cycle length setting window 10f-2. When the user opens Figure 8 the interface 10d shown in (2) of Figure 23 a window 10d-6 as shown in (4) of

[0387] Exemplarily, when the user clicks on the "Go to settings" option in window 10d-6, in one possible implementation, the mobile phone 100 responds to this operation and can jump to Figure 22 the interface 10e shown in (1) of Figure 23 and then complete the physiological cycle settings according to the above setting process. In another possible implementation, it can also directly jump to

[0388] Thus, the setting of the physiological cycle is completed.

[0389] After the physiological cycle is set, the mobile phone 100 will periodically (such as once a day) obtain the recorded physiological cycle data, and then determine the current stage according to the set physiological cycle (menstrual period length, cycle length, etc.) and the recorded physiological cycle data (which can be the predicted start time of the menstrual period according to the set physiological cycle, or generated after the user turns on the switch 10e-2). In this way, reasonable exercise guidance suggestions, that is, exercise plan adjustments, can be made based on the current stage.

[0390] Optionally, in some possible implementation manners, five stages (five situations) can be divided according to the physiological cycle and the recorded physiological cycle data.

[0391] Such as Figure 24 As shown, the stage corresponding to situation 5a can be called the menstrual period, specifically the D1 - D2 days at the start of the menstrual period; the stage corresponding to situation 5b can be called the postmenstrual period, specifically the D3 - D4 days after the start of the menstrual period; the stage corresponding to situation 5c can be called the proliferative phase, specifically the D5 - D6 days after the start of the menstrual period; the stage corresponding to situation 5d can be called the secretory phase, specifically the D7 - D8 days after the start of the menstrual period; the stage corresponding to situation 5e can be called the premenstrual period, specifically the D9 - D10 days after the start of the menstrual period, or it can also be said to be the preset number of days before the start of the menstrual period, such as 2 - 4 days.

[0392] It should be noted that the above D1, D2, D3, D4, D5, D6, D7, D8, D9, D10 satisfy the following relationship: 0 < D1 < D2 < D3 < D4 < D5 < D6 < D7 < D8 < D9 < D10.

[0393] Optionally, in some possible implementation manners, the value of D1 can be, for example, 1, the value of D2 can be, for example, 3, the value of D3 can be, for example, 4, the value of D4 can be, for example, 7, the value of D5 can be, for example, 8, the value of D6 can be, for example, 14, the value of D7 can be, for example, 15, the value of D8 can be, for example, 25, the value of D9 can be, for example, 26, and the value of D10 can be, for example, 28.

[0394] It should be understood that the above description is only an example listed for better understanding of the technical solution of this embodiment, and does not serve as the only limitation to this embodiment. In actual applications, the specific values of D1, D2, D3, D4, D5, D6, D7, D8, D9, D10 can be adaptively adjusted according to the menstrual period length and cycle length, etc. in the physiological cycle actually set by the user, and this application does not limit this.

[0395] Continue to refer to Figure 24, Exemplarily, for case 5a, since menstruation has just started. In this case, exercise guidance suggestions such as "The stage of frequent occurrence of female dysmenorrhea, it is recommended that the user not perform any training" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 25 the window 10d-72 shown in (2) of

[0396] Continuing to refer to Figure 24 , Exemplarily, for case 5b, since menstruation has started for several days and is about to end. In this case, exercise guidance suggestions such as "It is not recommended that the user take core courses, it is recommended to rest or practice general courses" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 25 the window 10d-73 shown in (3) of

[0397] Continuing to refer to Figure 24 , Exemplarily, for cases 5c and 5d, since menstruation has ended at this stage, no special adjustment needs to be made and no prompt is given to the user. That is, no prompt to the user is popped up in the interface 10d.

[0398] Continuing to refer to Figure 24 , Exemplarily, for case 5e, since menstruation is about to come. In this case, exercise guidance suggestions such as "Prompt the user that menstruation is about to come, let the user get prepared, and pay attention to appropriately reducing the amount of training according to their own physical condition during menstruation" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 25 the window 10d-71 shown in (1) of

[0399] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the only limitation to this embodiment.

[0400] In addition, it should be noted that in some possible implementation manners, the above process of determining the current stage may also be determined before the user opens the sports health APP or opens Figure 8 the interface 10d shown in (2) of Figure 8 For this situation, that is, when the user interface is switched to Figure 25 the interface 10d shown in (2) of Figure 25The window 10d-72 shown in (2), or Figure 25 the window 10d-73 shown in (3).

[0401] In addition, it should be noted that there are no courses every day of the week, or the user has already trained for today's course. To avoid the situation where there is no course or the user has already completed the training, and the user opens Figure 8 the interface 10d shown in (2), the mobile phone 100 displays on this interface Figure 25 the window 10d-71 shown in (1), or Figure 25 the window 10d-72 shown in (2), or Figure 25 the window 10d-73 shown in (3). Before giving exercise guidance suggestions according to the determined menstrual phase, it can be further determined whether there is a course today or whether today's course has been trained. If there is no course today or today's course has been trained, exercise guidance suggestions may not be given according to the determined menstrual phase. On the contrary, if there is a course today and today's course has not been trained, exercise guidance suggestions are given according to the determined menstrual phase.

[0402] In addition, it should be noted that the mobile phone 100 can also determine the time point when the user is used to starting training according to the time when the user trains every day. In this way, when the user enables the notification permission of the Sports Health APP, the Sports Health APP can send corresponding notification messages according to the determined menstrual phase before the time point when the user is used to starting training, such as Figure 25 the content in the window 10d-71 shown in (1), or Figure 25 the content in the window 10d-72 shown in (2), or Figure 25 the content in the window 10d-73 shown in (3), so as to give exercise guidance suggestions in advance and enable the user to arrange time more reasonably.

[0403] Therefore, for female users, reasonable exercise guidance suggestions are made according to the user's physiological cycle to avoid improper exercise during the physiological cycle and causing damage to the body.

[0404] Scenario 3: Small cycle weather adjustment plan (mainly for outdoor sports)

[0405] It can be understood that the weather affecting outdoor sports can be divided into abnormal weather such as rain, snow, and storms, temperature abnormal weather such as high temperature or low temperature, and weather such as air pollution. Specifically in the embodiment of the present application, when the mobile phone 100 makes adjustments (gives exercise guidance suggestions) according to weather data, such as the daily weather data obtained by the installed weather application, it can start from these three types of weather.

[0406] SeeFigure 26 , exemplarily, in the case where today's temperature is too high or too low, corresponding exercise guidance suggestions can be given according to the specific temperature. For example, in case 6a, that is, when the temperature is greater than or equal to tem1 °C, exercise guidance suggestions such as "Prompt the user of the high temperature risk and suggest that the user does not train today or change to indoor training" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 27 the window 10d-81 shown in (1) of

[0407] Continue to refer to Figure 26 , exemplarily, in case 6b, that is, when the temperature is greater than or equal to tem2 °C and less than tem1 °C, exercise guidance suggestions such as "Suggest that the user rest or practice general courses today, or change to indoor training" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 27 the window 10d-82 shown in (2) of

[0408] Continue to refer to Figure 26 , exemplarily, in case 6c, that is, when the temperature is greater than tem4 °C and less than or equal to tem3 °C, exercise guidance suggestions such as "Prompt the user of the injury risk, emphasize sufficient warm-up or change to indoor training" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 27 the window 10d-83 shown in (3) of

[0409] Continue to refer to Figure 26 , exemplarily, in case 6d, that is, when the temperature is less than or equal to tem3 °C, exercise guidance suggestions such as "Prompt the user of the injury risk, emphasize sufficient warm-up, suggest resting today or changing to indoor training" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 27 the window 10d-84 shown in (4) of

[0410] It should be noted that the above tem1, tem2, tem3, and tem4 satisfy the following relationship: tem4 ≤ 0 < tem3 < tem2 < tem1.

[0411] Optionally, in some possible implementation manners, the value of tem1 can be, for example, 35, the value of tem2 can be, for example, 30, the value of tem3 can be, for example, 10, and the value of tem4 can be, for example, 0.

[0412] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment and does not serve as the sole limitation of this embodiment. In actual applications, the specific values of tem1, tem2, tem3, and tem4 can be determined according to the division criteria corresponding to high-temperature weather and local weather, and this application does not limit this.

[0413] Continue to refer to Figure 26 , for example, for air quality, it can be divided according to the Air Quality Index (AQI). For example, in case 7a, that is, when today's AQI is between aqi1 and aqi2 (including the endpoint values), it can be considered that today's air quality is excellent or good. For this situation, the user can normally execute the outdoor exercise plan, so no reminder is required. That is, it is not in Figure 8 the window corresponding to the coach's advice is displayed in the interface 10d shown in (2) of

[0414] Continue to refer to Figure 26 , for example, in case 7b, that is, when today's AQI is between aqi3 and aqi4 (including the endpoint values), it can be considered that today's air quality is relatively poor and belongs to mild or moderate pollution. For this situation, in order to ensure the health of the user, exercise guidance suggestions such as "prompt the user of the air quality risk and suggest that the user rest or change to indoor training" can be given. Specifically in actual applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 27 the window 10d-85 shown in (5) of

[0415] Continue to refer to Figure 26 , for example, in case 7c, that is, when today's AQI is between aqi5 and aqi6 (including the endpoint values), it can be considered that today's air quality is very poor and belongs to heavy or severe pollution. For this situation, in order to ensure the health of the user, exercise guidance suggestions such as "prompt the user of the air quality risk and suggest that the user rest or change to indoor training" can be given. Specifically in actual applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 27 the window 10d-85 shown in (5) of

[0416] It should be noted that the above aqi1, aqi2, aqi3, aqi4, aqi5, and aqi6 satisfy the following relationship: 0 ≤ aqi1 < aqi2 < aqi3 < aqi4 < aqi5 < aqi6.

[0417] Optionally, in some possible implementation manners, the value of aqi1 can be, for example, 0, the value of aqi2 can be, for example, 100, the value of aqi3 can be, for example, 101, the value of aqi4 can be, for example, 200, the value of aqi5 can be, for example, 201, and the value of aqi6 can be, for example, 500.

[0418] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the only limitation to this embodiment. In practical applications, the specific values of aqi1, aqi2, aqi3, aqi4, aqi5, and aqi6 can be determined according to the air quality index and the corresponding classification criteria, and this application does not limit this.

[0419] In addition, it should also be noted that in practical applications, the classification of air quality can also refer to other indicators, such as PM2.5 (referring to suspended particulate matter with an aerodynamic equivalent diameter less than or equal to 2.5 micrometers (one micrometer is equal to one millionth of a meter)) to determine, and this application does not limit this.

[0420] Continue to refer to Figure 26 , for example, in the case of abnormal weather such as rain, snow, and storms today, since outdoor sports cannot be carried out, sports guidance suggestions such as "it is recommended that the user change to indoor training" can be given. Specifically in practical applications, this suggestion can be displayed in Figure 8 the interface 10d shown in (2) of Figure 27 and the window 10d-86 shown in (6) of

[0421] It should be understood that the above description is only an example listed for better understanding the technical solution of this embodiment, and does not serve as the only limitation to this embodiment.

[0422] In addition, it should be noted that in some possible implementation manners, the above process of determining the weather condition can also be determined before the user opens the Sports Health APP or opens Figure 8 the interface 10d shown in (2) of Figure 8 . For this situation, that is, when the user interface switches to Figure 27 the interface 10d shown in (2) of Figure 27 , the mobile phone 100 can directly display sports guidance suggestions suitable for the current weather condition according to the already determined weather condition in this interface, such as Figure 27 the window 10d-81 shown in (1) of Figure 27 , or Figure 27 the window 10d-82 shown in (2) ofFigure 27 The window 10d-86 shown in (6).

[0423] In addition, it should be noted that there are not classes every day of the week, or the user has already trained for today's class. To avoid the situation where there is no class or the user has already completed the training, when the user opens Figure 8 the interface 10d shown in (2) of the mobile phone 100, the mobile phone 100 displays on this interface Figure 27 the window 10d-81 shown in (1), or Figure 27 the window 10d-82 shown in (2), or Figure 27 the window 10d-83 shown in (3), or Figure 27 the window 10d-84 shown in (4), or Figure 27 the window 10d-85 shown in (5), or Figure 27 the window 10d-86 shown in (6). Before giving exercise guidance advice according to the determined weather conditions, it can be further judged whether there is a class today or whether today's class has been trained. If there is no class today or today's class has been trained, exercise guidance advice may not be given according to the determined weather conditions. On the contrary, if there is a class today and today's class has not been trained, exercise guidance advice is given according to the determined weather conditions.

[0424] In addition, it should be noted that the mobile phone 100 can also determine the time point when the user is used to starting training according to the time when the user trains every day. In this way, when the user enables the notification permission of the Sports Health APP, the Sports Health APP can send corresponding notification messages according to the weather conditions today before the time point when the user is used to starting training, such as Figure 27 the content in the window 10d-81 shown in (1), or Figure 27 the content in the window 10d-82 shown in (2), or Figure 27 the content in the window 10d-83 shown in (3), or Figure 27 the content in the window 10d-84 shown in (4), or ​ the content in the window 10d-85 shown in (5), or ​ the content in the window 10d-86 shown in (6), so as to give exercise guidance advice in advance and enable the user to arrange time more reasonably.

[0425] In addition, it should be noted that in some possible implementation manners, the above-listed various weather conditions, such as rain, snow, storm, high temperature / low temperature, and air pollution, may coexist. Since it is recommended that the user change outdoor exercise to indoor exercise in these weather conditions, only according to the priority, in ​In the interface 10d shown in (2), it is sufficient to pop up a prompt window corresponding to the coach's advice once.

[0426] Optionally, the various weather meteorological conditions listed above can satisfy the following priority: rain, snow, storm weather > temperature (high temperature or low temperature) > air quality (mild, moderate, severe, or serious pollution).

[0427] For example, on a rainy day today, and the temperature is between ​ In the scenario shown in case 6a in (8) and the air quality belongs to case 7b, when the user opens the interface 10d of the Sports Health APP, the window 10d-86 shown in (6) can be popped up on the interface 10d. Or, one hour before the user's habitual exercise time, the coach's advice in the window 10d-86 can be pushed through the notification manager. ​ It should be understood that the above description is only an example listed for better understanding of the technical solution of this embodiment and does not serve as the sole limitation of this embodiment.

[0428] Thus, reasonable exercise guidance advice can be given according to the weather conditions of the day, avoiding the user from exercising in unsuitable outdoor conditions and causing damage to the body.

[0429] In addition, it should be noted that in some possible implementation manners, the scenarios 1, 2, and 3 involved in the adjustment of the above-mentioned short-term exercise plan may also coexist concurrently. To avoid continuously popping up multiple prompt windows corresponding to the coach's advice on the interface 10d shown in (2) and affecting the user experience. These 3 short-term scenarios can also pop up only one prompt window corresponding to the coach's advice according to the set priority.

[0430] Optionally, the scenarios 1 (fatigue), 2 (physiological cycle), and 3 (weather) can satisfy the following priority: the fatigue reminder corresponding to scenario 1 > the physiological cycle reminder corresponding to scenario 2 > the weather environment reminder corresponding to scenario 3. ​ For example, in the scenario where the user's current physical condition is at level 3 fatigue, the current physiological cycle is in the proliferative phase, and the weather belongs to case 6b, when the user opens the interface 10d of the Sports Health APP, the window 10d-53 shown in (3) can be popped up on the interface 10d. Or, one hour before the user's habitual exercise time, the coach's advice in the window 10d-53 shown in (3) can be pushed through the notification manager.

[0431]

[0432] ​ ​

[0433] ​​​​For another example, in a scenario where the user's current physical condition is at level 0 fatigue, the current physiological cycle is in the proliferative phase, and the weather belongs to situation 6b. Since neither level 0 fatigue nor the proliferative phase requires a reminder, when the user opens the interface 10d of the sports health APP, the window 10d-82 shown in ​ (3) can pop up on the interface 10d. Or, one hour before the user's habitual exercise time, the coach's suggestions in the window 10d-82 shown in ​ (3) can be pushed through the notification manager. ​ In (3) ​ the coach's suggestions in the window 10d-82 shown in (3).

[0434] It should be understood that the above description is only an example listed for better understanding of the technical solution of this embodiment and does not serve as the sole limitation of this embodiment.

[0435] Thus, when multiple small-cycle scenarios occur concurrently, the adjustment of the exercise plan is realized, making the given exercise guidance suggestions more reasonable and ensuring the user experience.

[0436] The following is the content of the scenarios involved in the adjustment of the exercise plan for the large cycle:

[0437] Scenario 4: Adjustment plan for improving large-cycle exercise ability

[0438] Taking running as an example, that is, the ability to be improved in the large cycle is the running ability. Referring to ​ , exemplarily, the adjustment plan for improving the running ability implemented by the mobile phone 100 may include step S201 to step S203.

[0439] S201, determine whether the user's maximum oxygen uptake has increased by S levels.

[0440] Among them, the maximum oxygen uptake (VO2 max) refers to the maximum amount of oxygen taken in by the human body per minute under maximum load. It is one of the important indicators to measure the aerobic exercise ability of the human body.

[0441] Optionally, in some possible implementation manners, the maximum oxygen uptake can be obtained through a wearable device worn by the user, such as the watch 200.

[0442] Optionally, S is an integer greater than 1.

[0443] Optionally, in some possible implementation manners, S is 2. That is, when the user's maximum oxygen uptake increases by 2 levels, it is considered that the user's exercise ability has improved, thus excluding the accidental increase of 1 level.

[0444] Continuing to refer to ​ , exemplarily, when the user's maximum oxygen uptake increases by S levels, such as 2 levels, step S202 can be entered. Conversely, this detection of improving exercise ability can be exited, and when the next detection condition is met, step S201 can be executed again.

[0445] Optionally, the mobile phone 100 can perform the operation of step S201, that is, detecting whether the user's maximum oxygen uptake has increased by S levels, once a day.

[0446] In addition, it should be noted that usually within the cycle corresponding to a single exercise plan, the number of times the user's exercise ability improves is limited, that is, the situation where the maximum oxygen uptake increases by S levels will not occur frequently. Therefore, in some possible implementation manners, it can be set that after the mobile phone 100 detects that the maximum oxygen uptake has increased by S levels once, subsequent detections will no longer be performed.

[0447] S202, calculate the pace classification according to the personal best running result within the most recent N months.

[0448] Optionally, the personal best running result within N months can be obtained from the sports health APP.

[0449] Optionally, N is an integer greater than 0.

[0450] Optionally, in some possible implementation manners, N is 1. That is, calculate the pace classification according to the personal best running result of the user within the most recent 1 month.

[0451] It should be noted that the maximum oxygen uptake of users of different genders and ages will vary. Therefore, in the process of calculating the pace classification according to the personal best running result of the user within the most recent 1 month, the pace classification of the user can be determined according to the user's gender and age, in combination with the V02 max standard reference table. Regarding the V02 max standard reference table, this application does not make specific descriptions.

[0452] S203, update the user's running plan according to the latest pace classification.

[0453] Optionally, if there is no improvement in the latest pace classification, the user's running plan will not be updated. That is, the window 10d-9 as shown in ​ will not be popped up on the interface 10d.

[0454] Optionally, if there is an improvement in the latest pace classification, the window 10d-9 as shown in ​ can be popped up on the interface 10d. Among them, when the user clicks the "Close" option in the window 10d-9, the mobile phone 100 responds to this operation, closes the window 10d-9, and does not adjust the current exercise plan, that is, the user will continue to train according to the existing exercise plan subsequently; when the user clicks the "Adjust Plan" option, the mobile phone 100 responds to this operation, closes the window 10d-9, and adjusts the exercise plan corresponding to the remaining cycle according to the latest pace classification.

[0455] Optionally, the adjusted exercise plan will come into effect next week, that is, the courses starting next week will be updated to the courses corresponding to the adjusted exercise plan.

[0456] In addition, it should be noted that for the adjustment of the exercise plan triggered by the improvement of exercise ability, the original cycle of the exercise plan remains unchanged. For example, when the cycle corresponding to the exercise plan initially formulated by the user is 6 weeks, after adjustment due to the improvement of exercise ability midway, the cycle corresponding to the entire exercise plan is still 6 weeks, that is, the end time of the adjusted exercise plan is the same as the end time of the exercise plan before adjustment, but only the courses between the adjusted time and the end time have changed, such as the exercise intensity has changed.

[0457] Considering the adjustment of the exercise plan triggered by the improvement of exercise ability, the total cycle remains unchanged. Therefore, in some possible implementation manners, when there is an improvement in the latest pace grading, it can be further determined whether the remaining training cycle is greater than or equal to W weeks.

[0458] Optionally, W is an integer greater than 1.

[0459] Optionally, in a possible implementation manner, W is 2. That is, when the remaining training cycle is greater than or equal to 2 weeks, a window 10d-9 will pop up in the interface 10d to remind the user that the exercise ability has improved, and provide an option of "adjust plan" to allow the adjustment of the exercise plan. Otherwise, that is, when the remaining training cycle is less than 2 weeks (the remaining time is too short, and adjusting the exercise plan has little significance for subsequent ability improvement), the window that pops up in the interface 10d only reminds the user that the exercise ability has improved, but does not provide the option of "adjust plan".

[0460] Thus, it is possible to adjust the exercise plan midway according to the change of the user's exercise ability within the cycle corresponding to the exercise plan, and give exercise guidance suggestions, so that the user's exercise ability can be better improved within a fixed exercise cycle.

[0461] It should be understood that the above embodiments only take running, an aerobic exercise, as an example. In practical applications, the large-cycle exercise ability improvement adjustment scheme is also applicable to other types of exercises, such as strength exercises (such as weightlifting). Exemplarily, for strength exercises, strength tests can be regularly conducted. When there is an improvement in the strength grading corresponding to the strength test results, the exercise plan can be adjusted according to the latest strength grading to change the courses within the remaining time. Otherwise, no adjustment is made.

[0462] Scenario 5: Adjustment scheme for large-cycle execution rate

[0463] Still taking running as an example, refer to ​, Exemplarily, the large-cycle execution rate non-compliance adjustment solution implemented by the mobile phone 100 may include steps S301 to S306.

[0464] S301, Is the user currently maintaining health, or is it a novice entry / performance improvement?

[0465] Specifically, when the exercise plan initially formulated by the user is for maintaining health, the mobile phone 100 may execute step S302. When the exercise plan initially formulated by the user is novice entry / performance improvement, the mobile phone 100 may execute step S306.

[0466] S302, In the most recent W1 weeks, are there courses in more than or equal to W2 core training days that have not met the standards?

[0467] Optionally, W1 and W2 are integers greater than 0.

[0468] Understandably, the values of W1 and W2 can be the same or different.

[0469] Optionally, in some possible implementation manners, W1 is 2 and W2 is also 2. Specifically, it can be determined according to the user's exercise goal.

[0470] Understandably, in the exercise plan, the core courses have a greater impact on the exercise ability. Therefore, when judging that the execution rate does not meet the standard, that is, the course does not meet the standard, it is judged whether the course training on the core training days meets the standard.

[0471] Among them, the core training day is the day when the core course is arranged.

[0472] Among them, the course training meeting the standard means that the ratio of the load generated by the user's actual training to the training load required by the course is greater than or equal to a preset threshold, such as 50%. Therefore, the course training not meeting the standard refers to the situation where the ratio of the load generated by the user's actual training to the training load required by the course is less than this preset threshold (such as 50%).

[0473] Optionally, in some possible implementation manners, the reason for the training course not meeting the standard may be due to absenteeism.

[0474] Optionally, in some possible implementation manners, the situation where the user does not conduct the training of this core course or the training does not meet the standard can be regarded as absenteeism.

[0475] Optionally, in some possible implementation manners, for the absenteeism phenomenon, reminders can be made from two perspectives: the small cycle (with a granularity of days, detected every day, and no longer detected this week after one absenteeism is identified) and the large cycle (with a granularity of weeks, detected every week).

[0476] Situation 1.1 (the situation of missing classes due to the absence of core courses in the small cycle):

[0477] Optionally, when it is first detected within this week that the user misses 1 core course, a pop-up window on interface 10d can prompt the user with sports guidance suggestions similar to "Just complete the makeup practice within this week. Failure to do so may cause the sports plan to be postponed or pose a risk to achieving the goal."

[0478] Situation 1.2 (core courses are trained in the small cycle, but the training fails to meet the standard):

[0479] Optionally, in a possible implementation, after this core course training, it can be determined whether the training of this core course meets the standard based on the recorded training data. If it does not meet the standard, a pop-up window on interface 10d can prompt the user with something like "This training did not meet the standard. Pay attention to training strictly according to the course requirements next time, otherwise it may cause the sports plan to be postponed or pose a risk to achieving the goal."

[0480] Situation 2.1 (the training of week W1-1 has been completed currently)

[0481] Taking W1 as 2 as an example, optionally, when the training course of 1 week has been completed currently, if there are no problems in Situation 1.1 or Situation 1.2 during this week, no prompt is needed. When there are problems in Situation 1.1 or Situation 1.2 during this week, a window 10d-10 as shown in ​ can be popped up on interface 10d.

[0482] Optionally, when the user clicks the "Postpone" option in window 10d-10, the mobile phone 100 can respond to this operation and postpone for one week.

[0483] Optionally, when the user clicks the "Adjust Plan" option in window 10d-10, the mobile phone 100 can respond to this operation and regenerate the sports plan. Among them, when the number of complete weeks without training is greater than or equal to W5 weeks, the sports plan can be regenerated. Exemplarily, the end time corresponding to the generated sports plan in this case can be the same as the initial sports plan.

[0484] Optionally, in another possible implementation, when the number of complete weeks without training is less than W5 weeks, the "Adjust Plan" option may not be provided in window 10d-10. That is, the training is still carried out according to the initial sports plan.

[0485] Among them, W5>W4>W3≥W2≥W1. Optionally, in some possible implementations, W5 can be 4.

[0486] Situation 2.2 (the training of greater than or equal to W1 weeks has been completed currently)

[0487] Still taking W1 as 2 as an example, optionally, when the currently completed training course is greater than or equal to 2 weeks, if there are no problems with Case 1.1 or Case 1.2 in these 2 weeks, no prompt needs to be given. When there are problems with Case 1.1 or Case 1.2 in these 2 weeks, a window 10d-10 as shown in ​ Figure 10d-10 may pop up on interface 10d.

[0488] Optionally, when the user clicks the "Postpone" option in window 10d-10, in response to this operation, mobile phone 100 will postpone the courses starting from the week when the first core course is missed.

[0489] Optionally, when the user clicks the "Adjust Plan" option in window 10d-10, in response to this operation, mobile phone 100 can adjust the exercise plan according to the adjustment plan logic in Case 2.1.

[0490] It should be understood that the above description is only an example listed for better understanding of the technical solution of this embodiment and does not serve as the sole limitation of this embodiment.

[0491] S303. The user determines whether to postpone or adjust the plan.

[0492] Optionally, when the user clicks the "Postpone" option in window 10d-10, step S304 is executed. In response to this operation, mobile phone 100 will postpone the courses starting from the week when the first core course is missed. That is, after postponement, the course content remains unchanged, but the period corresponding to the exercise plan becomes longer.

[0493] Optionally, when the user clicks the "Adjust Plan" option in window 10d-10, step S305 is executed. In response to this operation, mobile phone 100 will regenerate the exercise plan. For details on regenerating the exercise plan, reference can be made to Case 2.1 and Case 2.2 above, which will not be elaborated here.

[0494] S304. Postpone starting from the natural week when the first core training day fails to meet the standard.

[0495] S305. Regenerate the subsequent running plan.

[0496] S306. Whether there are courses with more than or equal to W4 core training days that fail to meet the standard in the most recent W3 weeks.

[0497] Optionally, W3 and W4 are integers greater than 0.

[0498] It can be understood that the values of W3 and W4 can be the same or different.

[0499] Optionally, in some possible implementation manners, W3 is 2 and W4 is also 3. The body can be determined according to the user's exercise goal.

[0500] Continue to refer to ​ , for example, in the case where there are less than W4 core training days in the recent W3 weeks that fail to meet the standard, a window can be popped up in the interface 10d according to the logic of the above case 1.1, or case 1.2, or case 2.1, or case 2.2, and corresponding exercise guidance suggestions can be given. In the embodiment of the present application, still taking the window 10d-10 shown in ​ as an example.

[0501] Therefore, according to the execution rate of the user within the corresponding period of the exercise plan, the exercise plan can be adjusted midway, and exercise guidance suggestions can be given, enabling the user to exercise better.

[0502] In addition, it should be noted that, in some possible implementation manners, the scenarios 1, 2, and 3 involved in the adjustment of the exercise plan for the above small cycle, and the scenarios 4 and 5 involved in the adjustment of the exercise plan for the large cycle may coexist concurrently. For the absenteeism logic reminder, exercise ability improvement reminder, training overload reminder, execution rate mismatch reminder, various questionnaire feedback pop-ups, and the three small cycle scenarios (scenarios 1, 2, and 3) that appear in these 5 scenarios, pop-up reminders can be made according to the set priorities.

[0503] Optionally, the priority relationship of the above reminders can be as follows: absenteeism logic reminder > ability change reminder > training overload reminder > execution rate mismatch reminder > questionnaire feedback pop-up > (fatigue, physiology, weather).

[0504] Among them, for the priorities corresponding to the three small cycle scenarios, according to the fatigue reminder corresponding to scenario 1, the physiological cycle reminder corresponding to scenario 2, and the weather environment reminder corresponding to scenario 3 given in the above embodiment, and only one scenario is reminded.

[0505] Therefore, when multiple scenarios coexist concurrently, the adjustment of the exercise plan is realized, making the given exercise guidance suggestions more reasonable and ensuring the user experience.

[0506] In addition, it should also be noted that in the exercise plan adjustment method provided in the embodiment of the present application, for all the courses shown in the interface 10d this week, the user can randomly select and train according to needs.

[0507] For example, if today is the 13th and there is a course on the 15th, the user can choose not to train the course on the 13th and choose to train the course on the 15th.

[0508] Accordingly, when the user finishes the course for the 15th day on the 13th day, the course for the 15th day can show that it has been clocked in (trained).

[0509] Accordingly, when the user does not train the course on the 13th day, the user can make up the training for the course on the 14th day on the 14th day when there is no course schedule, or at other times during this week. After the make-up training for the course on the 13th day is completed, the course on the 13th day can also show that it has been clocked in.

[0510] That is, the user can make up the courses that were not trained before at any time during this week, and can also complete the training for other courses that have not been practiced this week in advance.

[0511] Understandably, in order to prevent the user from overexercising, the courses for next week and last week can be set so that the user cannot select them, thus preventing the user from overexercising within a week.

[0512] It should be understood that the above descriptions are only examples listed for better understanding of the technical solution of this embodiment, and do not serve as the sole limitation of this embodiment.

[0513] In addition, it should also be noted that in order to better improve the user experience, the exercise plans described in the embodiments of this application can end in the following ways.

[0514] Method 1: Automatically end after the last day of the exercise plan ends.

[0515] Method 2: After the user completes the last training session of the last training week, a window with a closing entry is popped up for the user to actively choose to end. In this way, the user can end the exercise plan in advance without waiting until the last day of the exercise plan to end.

[0516] Method 3: An entry to terminate the exercise plan can be provided in the menu list, so that it is convenient for the user to end the exercise plan at any stage of the exercise plan.

[0517] It should be understood that the above descriptions are only examples listed for better understanding of the technical solution of this embodiment, and do not serve as the sole limitation of this embodiment.

[0518] In addition, it should also be noted that the embodiments of this application mainly take the running scenario as an example. In actual applications, the exercise plan adjustment method provided in the embodiments of this application can also be applicable to other exercise scenarios, such as cycling, swimming, mountain climbing, etc., and this application does not make any restrictions on this.

[0519] In addition, it should also be noted that the window for displaying various exercise guidance suggestions in the embodiments of this application can be displayed at any position on the user interface, such as interface 10d, and this application does not make any restrictions on this.

[0520] In addition, it can be understood that, in order for the electronic device to implement the above functions, it includes the corresponding hardware and / or software modules for executing each function. Combining the algorithm steps of each example described in the embodiments disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in combination with the embodiments, but such implementation should not be considered to exceed the scope of the present application.

[0521] In addition, it should be noted that, in actual application scenarios, the above-described motion plan adjustment methods provided by the various embodiments implemented by the electronic device can also be executed by a chip system included in the electronic device. Among them, the chip system can include a processor. The chip system can be coupled to the memory, so that when the chip system runs, it calls the computer program stored in the memory to implement the steps executed by the above-described electronic device. Among them, the processor in the chip system can be an application processor or a processor other than an application processor.

[0522] In addition, the embodiments of the present application further provide a computer-readable storage medium. Computer instructions are stored in the computer storage medium. When the computer instructions run on the electronic device, the electronic device is caused to execute the above-related method steps to implement the motion plan adjustment method in the above embodiments.

[0523] In addition, the embodiments of the present application further provide a computer program product. When the computer program product runs on the electronic device, the electronic device is caused to execute the above-related steps to implement the motion plan adjustment method in the above embodiments.

[0524] In addition, the embodiments of the present application further provide a chip (which can also be a component or a module). The chip can include one or more processing circuits and one or more transceiver pins; among them, the transceiver pins and the processing circuits communicate with each other through an internal connection path, and the processing circuits execute the above-related method steps to implement the motion plan adjustment method in the above embodiments to control the receiving pin to receive a signal and control the sending pin to send a signal.

[0525] In addition, through the above description, it can be seen that the electronic device, computer-readable storage medium, computer program product, or chip provided by the embodiments of the present application are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be elaborated here.

[0526] To illustrate in detail the beneficial effects of the motion plan adjustment method provided by the embodiments of the present application, the following will be described by comparing with the related art.

[0527] Compared with the current situation where the exercise plan cannot be adjusted during the exercise process once it is formulated, the exercise plan adjustment method provided by this application can not only give users exercise guidance suggestions for delaying and / or adjusting the exercise plan from the perspective of a large cycle, and delay or adjust the initial exercise plan according to the user's selection, but also give reasonable exercise guidance suggestions to users before exercise from the perspective of a small cycle, avoiding physical damage during the exercise process due to physical reasons or weather reasons. That is, it can achieve various exercise guidance suggestions as shown in ​ so that users can exercise more reasonably according to the exercise plan and thus achieve the expected goals.

[0528] As mentioned above, the above embodiments are only used to illustrate the technical solutions of this application, rather than limiting it; although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for adjusting a motion plan, characterized in that, Applied to an electronic device, the method includes: Obtain a user's first exercise plan, where the first exercise plan is an initial exercise plan formulated by the user. The first exercise plan includes multiple training cycles and training courses corresponding to each training cycle. The training courses include core courses with a relatively high training intensity. For each training cycle, when there is an absence of a core course within the training cycle, make a first exercise guidance suggestion that does not include options corresponding to postponement suggestions and options corresponding to adjusting the exercise plan. For the multiple training cycles included in the first exercise plan, when the training courses of N training cycles are completed and there are absences in the N completed training cycles, make a second exercise guidance suggestion. The second exercise guidance suggestion includes the option corresponding to the postponement suggestion, or the second exercise guidance suggestion includes the option corresponding to the postponement suggestion and the option corresponding to adjusting the exercise plan, where N is an integer greater than 0.

2. The method according to claim 1, characterized in that, The step of, for each training cycle, when there is an absence of a core course within the training cycle, making a first exercise guidance suggestion includes: For each training cycle, detect whether there is an absence of a course in the training cycle once a day at a daily granularity. When it is first detected that there is an absence of a course, make the first exercise guidance suggestion and stop detecting the absence of a course in the training cycle.

3. The method according to claim 1 or 2, characterized in that, The situation of absence of a course includes: The core course within the training cycle has not been trained. Or, The core course within the training cycle has been trained, but the training does not meet the standard.

4. The method according to claim 3, wherein When the core course within the training cycle has not been trained, the first exercise guidance suggestion made is used to prompt the user to make up the training for the core course that has not been trained. When the core course within the training cycle has been trained, but the training does not meet the standard, the first exercise guidance suggestion made is used to prompt the user to strictly follow the requirements for the core courses that have not yet started training within the training cycle.

5. The method according to claim 1, characterized in that The step of, for the multiple training cycles included in the first exercise plan, when the training courses of N training cycles are completed and there are absences in the N completed training cycles, making a second exercise guidance suggestion includes: For the multiple training cycles included in the first exercise plan, when the training courses of N training cycles are completed and there are absences in the N completed training cycles, determine the number of remaining training cycles of the first exercise plan. When the number of remaining training cycles is greater than or equal to a first threshold, make the second exercise guidance suggestion that includes the option corresponding to the postponement suggestion and the option corresponding to adjusting the exercise plan. When the number of remaining training cycles is less than the first threshold, make the second exercise guidance suggestion that includes the option corresponding to the postponement suggestion and does not include the option corresponding to adjusting the exercise plan.

6. The method according to claim 1 or 5, characterized in that, After making the second exercise guidance suggestion, the method further includes: When N is 1, after the user clicks on the option corresponding to the extension suggestion, the first exercise plan is extended by 1 training cycle; When N is greater than 1, after the user clicks on the option corresponding to the extension suggestion, the extension starts from the training cycle of the first missed class.

7. The method according to claim 1 or 5, characterized in that, When the second exercise guidance suggestion includes the option corresponding to the extension suggestion and the option corresponding to adjusting the exercise plan, the method further includes: After the user clicks on the option corresponding to adjusting the exercise plan, a second exercise plan is generated. The second exercise plan is the adjusted exercise plan, and the second exercise plan includes the training cycles in the first exercise plan that have not been trained, and the training courses for each untrained training cycle are adjusted.

8. The method according to claim 7, wherein The first exercise plan or the second exercise plan is an exercise plan for running; The method further includes: During the process of the user training according to the first exercise plan or the second exercise plan, the maximum oxygen uptake of the user is obtained; When the maximum oxygen uptake increases by S levels, according to the user's personal best running results in the most recent M months, the pace classification is calculated, where S is an integer greater than 1 and M is an integer greater than 0; According to the calculated pace classification, a third exercise guidance suggestion is made. The second exercise guidance suggestion includes the option corresponding to the extension suggestion, or the second exercise guidance suggestion includes the option corresponding to the extension suggestion and the option corresponding to adjusting the exercise plan.

9. The method according to claim 8, wherein When the third exercise guidance suggestion includes the option corresponding to the extension suggestion and the option corresponding to adjusting the exercise plan, the method further includes: After the user clicks on the option corresponding to adjusting the exercise plan, a third exercise plan is generated. The third exercise plan is the adjusted exercise plan, and the third exercise plan includes the training cycles in the first exercise plan / the second exercise plan that have not been trained, and the training courses for each untrained training cycle are adjusted.

10. The method according to claim 9, wherein The method further includes: Obtaining index data, physiological cycle data, and weather data for calculating the fatigue level; During the process of the user training according to the first exercise plan, or the second exercise plan, or the third exercise plan, according to the fatigue level, the physiological cycle data, and the weather data, a fourth exercise guidance suggestion is made. The fourth exercise guidance suggestion is the exercise guidance suggestion corresponding to the fatigue level, or the exercise guidance suggestion corresponding to the physiological data, or the exercise guidance suggestion corresponding to the weather data.

11. The method according to claim 10, wherein The making of the fourth exercise guidance suggestion according to the fatigue level, the physiological cycle data, and the weather data includes: Selecting an exercise guidance suggestion with the highest priority as the fourth exercise guidance suggestion in the order that the priority of the exercise guidance suggestion corresponding to the fatigue level is higher than the priority of the exercise guidance suggestion corresponding to the physiological cycle data, and the priority of the exercise guidance suggestion corresponding to the physiological cycle data is higher than the priority of the exercise guidance suggestion corresponding to the weather data.

12. An electronic device, characterized in that, The electronic device includes: a memory and a processor, the memory and the processor being coupled; the memory stores program instructions, and when the program instructions are executed by the processor, the electronic device is caused to execute the motion plan adjustment method according to any one of claims 1 to 11.

13. A computer-readable storage medium, characterized in that, It includes a computer program, and when the computer program runs on an electronic device, the electronic device is caused to execute the motion plan adjustment method according to any one of claims 1 to 11.

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