Motion plan adjustment method, device, and storage medium

Abstract

The application provides a sports plan adjustment method and device and a storage medium. The method can not only give sports guidance suggestions for delaying and / or adjusting the sports plan from the perspective of a large period, and delay or adjust the initial sports plan according to the selection of a user, but also give reasonable sports guidance suggestions before the user performs sports from the perspective of a small period, so as to avoid damage to the body caused by the body or weather during the sports process. That is, various sports guidance suggestions can be realized, so that the user can perform more reasonable sports according to the sports plan, and thus the desired target can be achieved.

Description

Technical Field

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

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

[0003] Currently, more and more people are improving their physical fitness through exercise. However, most people cannot afford a personal trainer. Therefore, their exercise plans may be unreasonable and unable to be adjusted appropriately based on their actual exercise situation. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a method, device, and storage medium for adjusting exercise plans, aiming to rationally adjust users' exercise plans so that users can exercise more effectively.

[0005] Firstly, this application provides a method for adjusting an exercise plan. This method is applied to an electronic device and includes: acquiring a user's first exercise plan, which is an initial exercise plan created by the user, the first exercise plan including multiple training cycles and training courses corresponding to each training cycle, the training courses including core courses with high training intensity; for each training cycle, if there are absences in the core courses within the training cycle, making a first exercise guidance suggestion, the first exercise guidance suggestion not including options for postponement suggestions and options for adjusting the exercise plan; for the multiple training cycles included in the first exercise plan, if N training cycles of training courses are completed, and there are absences in the completed N training cycles, making a second exercise guidance suggestion, the second exercise guidance suggestion including options for postponement suggestions, or the second exercise guidance suggestion including options for postponement suggestions and options for adjusting the exercise plan, where N is an integer greater than 0.

[0006] Electronic devices, such as mobile phones and tablets.

[0007] Therefore, by combining short cycles (each training cycle) and long cycles (multiple training cycles), reasonable exercise guidance suggestions are made based on the completion status of core courses in the short and long cycles (whether there are any absences), so that users can exercise in a reasonable way and ensure the exercise effect.

[0008] For specific implementation details in this area, please refer to [link / reference]. Figure 30 The description of the illustrated embodiment will not be repeated here.

[0009] According to the first aspect, for each training cycle, if there are any absences in the core courses within the training cycle, the first exercise guidance suggestion shall be made, including: for each training cycle, checking for any absences once a day on a daily basis; if an absence is detected for the first time, the first exercise guidance suggestion shall be made, and the detection of absences for the training cycle shall be stopped.

[0010] For specific implementation details regarding this aspect, please refer to [link / reference]. Figure 30 The description of the illustrated embodiment will not be repeated here.

[0011] According to the first aspect, or any of the above implementations of the first aspect, absences include: the core courses within the training period were not trained; or, the core courses within the training period were trained, but the training did not meet the standards.

[0012] For specific implementation details regarding this aspect, please refer to [link / reference]. Figure 30 The description of the illustrated embodiment will not be repeated here.

[0013] According to the first aspect, or any of the implementation methods of the first aspect above, if the core courses within the training period have not been trained, the first exercise guidance suggestion is used to prompt the user to make up for the core courses that have not been trained; if the core courses within the training period have been trained, but the training has not reached the standard, the first exercise guidance suggestion is used to prompt the user to strictly follow the requirements for the core courses that have not yet started training within the training period.

[0014] According to the first aspect, or any implementation of the first aspect above, for multiple training cycles included in the first exercise plan, if N training cycles have been completed and there are absences in the completed N training cycles, a second exercise guidance suggestion is made, including: for multiple training cycles included in the first exercise plan, if N training cycles have been completed and there are absences in the completed N training cycles, determining the number of remaining training cycles in the first exercise plan; if the number of remaining training cycles is greater than or equal to a first threshold, making a second exercise guidance suggestion that includes options corresponding to postponement suggestions and options corresponding to adjusting the exercise plan; if the number of remaining training cycles is less than the first threshold, making a second exercise guidance suggestion that includes options corresponding to postponement suggestions but does not include options corresponding to adjusting the exercise plan.

[0015] For specific implementation details regarding this aspect, please refer to [link / reference]. Figure 30 The description of the illustrated embodiment will not be repeated here.

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

[0017] For specific implementation details regarding this aspect, please refer to [link / reference]. Figure 30 The description of the illustrated embodiment will not be repeated here.

[0018] According to the first aspect, or any of the implementation methods of the first aspect above, when the second exercise guidance suggestion includes the option corresponding to the postponement suggestion and the option corresponding to the adjustment of the exercise plan, the method further includes: when the user clicks the option corresponding to the adjustment of the exercise plan, a second exercise plan is generated. The second exercise plan is an adjusted running plan. The second exercise plan includes the training cycles that were not trained in the first exercise plan, and the training courses of each training cycle that was not trained have been adjusted.

[0019] Among them, the second movement guidance suggestion in this scenario, for example Figure 31 The contents of window 10d-10 are shown in the image.

[0020] For specific implementation details regarding this aspect, please refer to [link / reference]. Figure 30 The description of the illustrated embodiment will not be repeated here.

[0021] According to the first aspect, or any implementation of the first aspect above, the first exercise plan or the second exercise plan is an exercise plan for running; the method further includes: obtaining the user's VO2 max during the user's training according to the first exercise plan or the second exercise plan; if the VO2 max increases by level S, calculating a pace grade based on 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; and making a third exercise guidance suggestion based on the calculated pace grade, wherein the second exercise guidance suggestion includes options corresponding to the postponement suggestion, or the second exercise guidance suggestion includes options corresponding to the postponement suggestion and options corresponding to adjusting the exercise plan.

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

[0023] Therefore, when athletic ability changes, such as improving, timely exercise guidance and suggestions can be provided, as well as an entry point for adjusting the exercise plan, so that the user's subsequent exercise is more reasonable.

[0024] For specific implementation details regarding this aspect, please refer to [link / reference]. Figure 28The description of the illustrated embodiment will not be repeated here.

[0025] According to the first aspect, or any of the implementation methods of the first aspect above, when the third exercise guidance suggestion includes the option corresponding to the postponement suggestion and the option corresponding to the adjustment of the exercise plan, the method further includes: when the user clicks the option corresponding to the adjustment of the exercise plan, a third exercise plan is generated. The third exercise plan is the adjusted running plan. The third exercise plan includes the training cycles that were not trained in the first exercise plan / second exercise plan, and the training courses of each training cycle that was not trained have been adjusted.

[0026] Among them, the third exercise guidance suggestion, for example Figure 29 The contents of window 10d-9 are shown in the image.

[0027] For specific implementation details regarding this aspect, please refer to [link / reference]. Figure 28 The description of the illustrated embodiment will not be repeated here.

[0028] According to the first aspect, or any implementation of the first aspect above, the method further includes: acquiring indicator data, physiological cycle data, and weather data for calculating fatigue level; during the user's training according to the first exercise plan, or the second exercise plan, or the third exercise plan, making a fourth exercise guidance suggestion based on fatigue level, physiological cycle data, and weather data, wherein the fourth exercise guidance suggestion is an exercise guidance suggestion corresponding to fatigue level, or an exercise guidance suggestion corresponding to physiological data, or an exercise guidance suggestion corresponding to weather data.

[0029] Therefore, exercise guidance and suggestions can be provided to users from the perspectives of fatigue, physiological cycle and weather, so as to avoid injury to users' bodies during exercise.

[0030] For specific implementation details regarding this aspect, please refer to the descriptions of the small-cycle fatigue adjustment scheme, the small-cycle physiological cycle adjustment scheme, and the small-cycle weather adjustment scheme; these will not be elaborated upon here.

[0031] Based on the first aspect, or any of the above implementations of the first aspect, a fourth exercise guidance suggestion is made based on fatigue level, physiological cycle data, and weather data. This includes selecting the exercise guidance suggestion with the highest priority as the fourth exercise guidance suggestion, following the order that the priority of the exercise guidance suggestion corresponding to fatigue level is higher than that of the exercise guidance suggestion corresponding to physiological cycle data, and the priority of the exercise guidance suggestion corresponding to physiological cycle data is higher than that of the exercise guidance suggestion corresponding to weather data.

[0032] According to the first aspect, or any implementation of the first aspect above, the electronic device is also communicatively connected to a wearable device, which provides index data for calculating fatigue levels. The index data includes one or more of the following: morning resting heart rate data, heart rate variability (HRV) data, heart rate data during exercise, and sleep data. Determining the fatigue level based on the index data includes: calculating the fatigue level based on the morning resting heart rate data when the index data includes it; and determining the fatigue level calculated based on the morning resting heart rate data as the highest level of fatigue when it is the highest level, indicating that the user is currently unsuitable for any training session.

[0033] Wearable devices, such as smartwatches and fitness trackers.

[0034] Optionally, fatigue levels can be divided into Level 0 fatigue, Level 1 fatigue, Level 2 fatigue, Level 3 fatigue, etc., with Level 3 being the highest fatigue level.

[0035] Therefore, the fatigue level is determined by the highest priority morning resting heart rate data among the indicators provided by the wearable device for calculating the user's fatigue level. When the fatigue level determined by the morning resting heart rate data is the highest level, the fatigue level determined by the morning resting heart rate data is directly used as the user's current fatigue level. This can ensure the accuracy of the results while reducing the computational load on the electronic device.

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

[0037] Therefore, when the highest level of fatigue cannot be determined based on morning resting heart rate data, HRV data is given priority. When the fatigue level determined by HRV data is the highest level of fatigue, the fatigue level determined by HRV data is directly used as the user's current fatigue level. This allows for more suitable exercise guidance based on the determined fatigue level, preventing the user from overexerting themselves and causing injury.

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

[0039] Therefore, when the highest level of fatigue cannot be determined based on morning resting heart rate data and HRV data, ACWR data is given priority. When the fatigue level determined by ACWR data is the highest level of fatigue, the fatigue level determined by ACWR data is directly used as the user's current fatigue level. This allows for more suitable exercise guidance based on the determined fatigue level, preventing the user from overexerting themselves and causing injury.

[0040] According to the first aspect, or any implementation of the first aspect above, the method further includes: when the indicator data does not include morning resting heart rate data, or the fatigue level calculated based on the morning resting heart rate data is not the highest fatigue level, and the indicator data does not include HRV data, or the fatigue level calculated based on the HRV data is not the highest fatigue level, and the indicator data does not include heart rate data during exercise, after the training course ends, a first questionnaire pops up, which includes multiple score options, with different score options corresponding to different levels of fatigue; the user's current training load is calculated based on the score selected by the user in the first questionnaire and the training duration; the user's current ACWR data is calculated based on the training load, historical ACWR data, and a parameter indicating the degree of decay of training load over time, where historical ACWR data is the ACWR data corresponding to the user's last completed training, and the parameter indicating the degree of decay of training load over time takes a value between 0 and 1; the fatigue level is calculated based on the ACWR data; if the fatigue level calculated based on the ACWR data is the highest fatigue level, the fatigue level calculated based on the ACWR data is determined as the user's current fatigue level.

[0041] The first questionnaire, for example Figure 18 The course feedback questionnaire pops up on the 10th page of the interface.

[0042] Therefore, even when the user is not wearing a wearable device or the wearable device does not provide heart rate data during exercise, displaying a subjective evaluation questionnaire on an electronic device ensures that ACWR data can be calculated regardless of the scenario, thereby determining the fatigue level.

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

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

[0045] In this way, when the highest priority morning resting heart rate data can determine the fatigue level, prioritizing the use of the fatigue level determined by the morning resting heart rate data is more likely to reflect the user's actual fatigue level and is more conducive to providing appropriate exercise guidance before exercise.

[0046] According to the first aspect, or any implementation of the first aspect above, the method further includes: when the fatigue level cannot be calculated based on the morning resting heart rate data, but the indicator data includes 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 user's current fatigue level.

[0047] In this way, when the highest priority morning resting heart rate data cannot determine the fatigue level, HRV data, which has a lower priority than the morning resting heart rate data but a higher priority than other indicators, is used to determine the fatigue level. This ensures that the determined fatigue level can better reflect the user's actual fatigue level and is conducive to providing appropriate exercise guidance before exercise.

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

[0049] In this way, when other indicators with higher priority than ACWR data cannot determine the fatigue level, ACWR data is used to determine the fatigue level, further ensuring that the determined fatigue level can better reflect the user's actual fatigue level, which is conducive to providing appropriate exercise guidance before exercise.

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

[0051] In this way, when other indicators with higher priority than sleep data cannot determine the fatigue level, sleep data is used to determine the fatigue level. Furthermore, if sleep data cannot determine the fatigue level, the user is assumed to be at the lowest fatigue level. This ensures that a fatigue level can be determined before the user exercises, regardless of the situation, and thus appropriate exercise guidance can be provided.

[0052] According to the first aspect, or any implementation of the first aspect above, the fatigue level is calculated based on sleep data, including: if the sleep data meets preset conditions, displaying a second questionnaire, which includes multiple sleep quality assessment options, with different sleep quality assessment options corresponding to different scores; and determining the fatigue level based on the score corresponding to the sleep quality option selected by the user in the second questionnaire.

[0053] The second questionnaire, for example Figure 14 The sleep quality questionnaire shown in (2) is as follows.

[0054] According to the first aspect, or any of the above implementations of the first aspect, the preset conditions are met, including: the sleep duration is less than the first preset duration; and / or, the number of nighttime 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 than the second preset duration.

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

[0056] The preset number of times is, for example, 3 times.

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

[0058] According to the first aspect, or any implementation of the first aspect above, the fatigue level is calculated based on the morning resting heart rate data, including: if the fluctuation of the morning resting heart rate data compared to the average morning resting heart rate of the previous week is within N1 bpm, the fatigue level is determined to be the lowest level; if the morning resting heart rate data exceeds the average morning resting heart rate of the previous week (N1 bpm to N2 bpm), a third questionnaire is displayed, which includes multiple fatigue assessment options, each corresponding to a different score; the fatigue level is determined based on the score corresponding to the fatigue assessment option selected by the user in the third questionnaire; if both the morning resting heart rate data and yesterday's morning resting heart rate data exceed the average morning resting heart rate of the previous week (N1 bpm to N2 bpm), the fatigue level is determined to be between the highest and lowest levels; if the morning resting heart rate data, yesterday's morning resting heart rate data, and the morning resting heart rate data from the day before yesterday all exceed the average morning resting heart rate of the previous week (N1 bpm to N2 bpm), the fatigue level is determined to be between the highest and lowest levels; if the morning resting heart rate data, yesterday's morning resting heart rate data, and the morning resting heart rate data from the day before yesterday all exceed the average morning resting heart rate of the previous week (N1 bpm to N2 bpm), the fatigue level is determined to be between the highest and lowest levels. At a rate of 0 bpm, the fatigue level is determined to be the highest level; when the morning resting heart rate exceeds the previous week's average morning resting heart rate by 3 bpm, the fatigue level is determined to be the highest level; where 0 <N1<N2<N3。

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

[0060] For specific details on calculating fatigue levels based on morning resting heart rate data, please refer to [link to relevant documentation]. Figure 13 and Figure 14 The description of the illustrated embodiment will not be repeated here.

[0061] According to the first aspect, or any implementation of the first aspect above, the fatigue level is calculated based on HRV data, including: determining the fatigue level based on the RMSSD and LF / HF ratio in the HRV data, where RMSSD refers to the root mean square of the difference 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] For specific details on calculating fatigue level based on HRV data, please refer to [link / reference]. Figure 15 The description of the illustrated embodiment will not be repeated here.

[0063] According to the first aspect, or any implementation of the first aspect above, the Acute / Chronic Load Ratio (ACWR) data is calculated based on the heart rate data during the exercise phase and the training duration of the currently completed training course. This includes: determining the heart rate interval in which the heart rate data during the exercise phase falls; wherein, starting from 50% of the maximum heart rate and ending at 100% of the maximum heart rate, each 10% increase constitutes a heart rate interval, and each heart rate interval corresponds to an intensity level; determining the intensity level based on the determined heart rate interval; calculating the user's current training load based on the intensity level and training duration; and calculating the user's current ACWR data based on the training load, historical ACWR data, and a parameter indicating the degree of decay of the training load over time. The historical ACWR data is the ACWR data corresponding to the user's last completed training session, and the parameter indicating the degree of decay of the training load over time takes a value between 0 and 1.

[0064] For details on determining ACWR data based on heart rate data during exercise provided by wearable devices, and then calculating fatigue levels, please refer to [link to relevant documentation]. Figure 16 The description of the illustrated embodiment will not be repeated here.

[0065] Secondly, this application provides an electronic device. The electronic device includes: a memory and a processor, the memory and the processor being coupled; the memory stores program instructions, which, when executed by the processor, cause the electronic device to perform the methods of the first aspect or any possible implementation thereof.

[0066] Thirdly, this application provides a computer-readable medium for storing a computer program including instructions for performing the methods in the first aspect or any possible implementation thereof.

[0067] Fourthly, this application provides a computer program including instructions for performing the method in the first aspect or any possible implementation thereof.

[0068] Fifthly, this application provides a chip including a processing circuit and transceiver pins. The transceiver pins and the processing circuit communicate with each other via an internal connection path. 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 signals and to control the transmitting pin to transmit signals. Attached Figure Description

[0069] Figure 1 This is an illustrative diagram illustrating a scenario for adjusting an exercise plan.

[0070] Figure 2 This is a schematic diagram of the hardware structure of an electronic device for implementing exercise plan adjustment, as exemplarily shown.

[0071] Figure 3 As shown in the example Figure 2 A schematic diagram of the software structure of the electronic device shown.

[0072] Figure 4 This is a schematic diagram of the hardware structure of another electronic device for implementing exercise plan adjustment, as exemplarily shown.

[0073] Figure 5 As shown in the example Figure 4 A schematic diagram of the software structure of the electronic device shown.

[0074] Figure 6 This is a schematic diagram illustrating an exemplary system architecture for implementing exercise plan adjustments;

[0075] Figure 7 and Figure 8 This is an example illustration of the user interface involved in launching a fitness app to view an exercise plan;

[0076] Figure 9 This is an illustrative diagram showing course identifiers for different times and intensities;

[0077] Figure 10 This is an example of a window displaying only information related to core training days and regular training days;

[0078] Figure 11 This is an example diagram of a user interface that provides prompts based on different fatigue levels.

[0079] Figure 12 This is a schematic diagram illustrating the process of determining the fatigue level in a short-cycle fatigue adjustment scheme, as exemplarily shown.

[0080] Figure 13 This is an illustrative diagram showing how fatigue levels are determined based on morning resting heart rate data.

[0081] Figure 14 This is an example of a user interface diagram showing the questionnaire feedback displayed when the case is determined to be case 1b based on morning resting heart rate data;

[0082] Figure 15 This is an illustrative diagram showing how fatigue levels are determined based on heart rate variability data.

[0083] Figure 16 This is an illustrative diagram showing how to determine ACWR and thus fatigue level;

[0084] Figure 17This is an illustrative diagram illustrating yet another method of determining ACWR and subsequently determining the fatigue level;

[0085] Figure 18 For example, the target Figure 17 A user interface diagram showing the pop-up course feedback in a scenario;

[0086] Figure 19 This is an illustrative diagram illustrating the determination of fatigue levels based on sleep data.

[0087] Figure 20 The diagram illustrates a window and user interface for a better course as an example.

[0088] Figure 21 This is a schematic diagram of a training sequence reminder window, as exemplarily shown.

[0089] Figure 22 and Figure 23 A schematic diagram illustrating the user interface and related windows for setting the menstrual cycle;

[0090] Figure 24 This is a schematic diagram illustrating the logic of providing exercise guidance suggestions based on the menstrual cycle stage.

[0091] Figure 25 This is a schematic diagram illustrating exercise guidance suggestions for different stages of the menstrual cycle;

[0092] Figure 26 This is an example of a logic diagram illustrating how to provide exercise guidance suggestions based on weather conditions;

[0093] Figure 27 A schematic diagram illustrating exercise guidance suggestions for different weather conditions;

[0094] Figure 28 This is a flowchart illustrating an exemplary scheme for improving and adjusting large-cycle motion capabilities.

[0095] Figure 29 This is an example of a window display showing exercise guidance suggestions given after an improvement in athletic ability;

[0096] Figure 30 This is a flowchart illustrating an example of a large-cycle execution rate mismatch adjustment plan;

[0097] Figure 31 This is an example of a window display showing exercise guidance suggestions given after a failure to meet the performance target.

[0098] Figure 32This is a schematic diagram of various exercise guidance suggestions involved in the exercise adjustment scheme provided in an embodiment of this application, which is an exemplary illustration. Detailed Implementation

[0099] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

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

[0101] The terms "first" and "second," etc., used in the specification and claims of this application are used to distinguish different objects, not to describe a specific order of objects. For example, "first target object" and "second target object," etc., are used to distinguish different target objects, not to describe a specific order of target objects.

[0102] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0103] In the description of the embodiments in this application, unless otherwise stated, "multiple" means two or more. For example, multiple processing units means two or more processing units; multiple systems means two or more systems.

[0104] In the description of the embodiments of this application, the user interface may also be referred to as an interface. The icons, controls, names, etc., included in the various interfaces shown in the examples can be replaced with other names according to the actual scenario.

[0105] With increasing pressure from modern life, people are paying more and more attention to their health. Currently, more and more people are improving their physical fitness through exercise. However, most people cannot afford a personal trainer. Therefore, their exercise plans may be unreasonable and unable to be adjusted appropriately based on their actual exercise situation.

[0106] Alternatively, with the gradual expansion of the mobile internet industry, one possible implementation is that users can use fitness applications (APPs) to create exercise plans and then exercise according to those plans to improve their physical fitness. However, in practice, various factors may influence users to the point that they do not strictly adhere to the exercise plan. Therefore, continuing to exercise according to the previous plan will not only fail to achieve the desired results, but may even cause injury to the user's body due to improper exercise.

[0107] In view of this, the embodiments of this application provide a more comprehensive and multi-dimensional method for adjusting exercise plans, which aims to reasonably adjust the user's exercise plan so that the user can exercise more effectively.

[0108] For example, in some possible implementations, the exercise plan adjustment method provided in this application embodiment can be applied to an electronic device. This electronic device can be any of a mobile phone, tablet computer, wearable device (such as a smartwatch, bracelet, etc.), or other portable device.

[0109] For example, in some other possible implementations, the exercise plan adjustment method provided in this application embodiment can also be applied to a variety of portable devices, such as mobile phones and smartwatches (hereinafter referred to as: watches), so that the user's exercise plan can be adjusted more reasonably through the cooperation of these two devices.

[0110] In this embodiment of the application, a communication connection is established between a mobile phone 100 and a watch 200 to perform data interaction, such as... Figure 1 The scenario shown provides a detailed explanation of how to adjust the exercise plan.

[0111] See Figure 2 The diagram illustrates the structure of a mobile phone 100. Figure 2 As 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, buttons 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] Antennas 1 and 2 are used to transmit and receive electromagnetic wave signals. Each antenna in mobile phone 100 can be used to cover one or more communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other implementations, the antennas can be used in conjunction with a tuning switch.

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

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

[0115] Specifically, in the technical solution provided in this application embodiment, the mobile phone 100 can communicate with the watch 200 through the wireless communication module 160 and the antenna.

[0116] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. In some implementations, the mobile phone 100 may include one or N display screens 194, where N is a positive integer greater than 1. Specifically, in this embodiment, user interaction and prompts can be implemented through the display screen.

[0117] Furthermore, it should be noted that in some possible implementations, the processor 110 may include one or more processing units, such as 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., which will not be listed here, and this application does not impose any limitations on them.

[0118] Alternatively, these processing units can be independent devices, meaning that each processing unit can be viewed as a processor.

[0119] Alternatively, these processing units can be integrated into one or more processors.

[0120] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0121] Specifically, in this embodiment of the application, the mobile phone 100 can use the application processor to provide guidance to the user before exercise and adjust the exercise plan based on multi-dimensional indicator data.

[0122] Optionally, multi-dimensional indicator data may include, for example, data used to determine user fatigue levels, weather data, physiological cycle data, exercise capacity data, execution rate data, etc.

[0123] Data used to determine fatigue levels may include, for example, morning resting heart rate data, heart rate variability data, acute / chronic load ratio data, and sleep data.

[0124] That concludes the introduction to the hardware structure of the Mobile 100. It should be understood that... Figure 2 The mobile phone 100 shown is merely an example. In a specific implementation, the mobile phone 100 may have more or fewer components than 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 3The diagram illustrates a software structure of a mobile phone 100. Before describing the software structure of the mobile phone 100, the architecture that the software system of the mobile phone 100 can adopt will be explained first.

[0126] Alternatively, the software system of Mobile 100 can adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture.

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

[0128] For ease of explanation, this application uses the layered architecture of the Android system as an example to illustrate the software structure of the mobile phone 100.

[0129] like Figure 3 As shown, the layered architecture of the mobile phone 100 divides the software into several layers, each with a clear role and division of labor. Layers communicate with each other through software interfaces. In some implementations, the Android system of the mobile phone 100 is divided into five layers, from top to bottom: 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 can include a series of application packages.

[0131] like Figure 3 As shown, the application package may include applications such as Health, Settings, Music, Bluetooth, and Gallery, which will not be listed here, and this application does not impose any restrictions on them.

[0132] The sports and health application provided in this embodiment is an app that can be used with wearable and health devices (such as watch 200) to achieve scientific exercise monitoring and health management, and provides professional data and a rich activity experience. Users can create exercise plans through the sports and health app, making it easy to exercise according to the plan.

[0133] Optionally, the exercise plan adjustment method provided in this application embodiment can reasonably adjust the exercise plan formulated by the user using a sports and health APP. Specific implementation details are detailed in the following embodiments and will not be elaborated here.

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

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

[0136] The notification manager allows applications to display notification information in the status bar. It can be used to convey informational messages and can disappear automatically after a short time without user interaction.

[0137] Specifically, in this embodiment of the application, an exercise guidance prompt message can be pushed by the notification manager an hour before the user's usual start time for exercising.

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

[0139] Content providers are used to store and retrieve data, and make that data accessible to applications.

[0140] A view system includes visual controls, such as controls that display text and controls that display images.

[0141] The resource manager provides various resources for applications, such as the layout and content 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 screen size, determine if a status bar is present, lock the screen, and determine the currently displayed interface (e.g., whether it is in the state described in the following embodiments). Figure 8 The interface shown in (2) is 10d, etc.

[0143] The system library and runtime layer includes the system libraries and the Android Runtime. The Android Runtime includes the core libraries 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 functionalities that need to be called by the Java language, and the other part is the Android core library.

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

[0146] System libraries can include multiple functional modules. For example: surface manager, media libraries, 3D graphics processing libraries (e.g., OpenGL ES), 2D graphics engines (e.g., SGL), etc.

[0147] The Surface Manager is used to manage the display subsystem and provides the blending of 2D and 3D layers for multiple applications.

[0148] The media library supports playback and recording of various common audio and video formats, as well as still image files. It supports multiple audio and video encoding formats, such as MPEG4, H.264, MP3, AAC, AMR, JPG, and PNG.

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

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

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

[0152] The kernel layer is the layer between hardware and software. At a minimum, the kernel layer includes sensor drivers, display drivers, camera drivers, power management drivers, etc. For example, a sensor driver can be used to output detection signals from a sensor (such as a touch sensor) to the view system, so that the view system responds to the detection signals and displays the corresponding application interface.

[0153] That concludes the introduction to the software structure of the mobile phone 100. It is understandable that... Figure 3 The layers in the illustrated software structure and the components contained in each layer do not constitute a specific limitation on the mobile phone 100. In other embodiments of this application, the mobile phone 100 may include more or fewer layers than illustrated, and each layer may include more or fewer components; this application does not impose any limitations.

[0154] See Figure 4 The example illustrates the hardware structure of a watch 200. For instance... Figure 4As shown, the watch 200 may include: processor 210, sensor 220, memory 230, antenna 240, etc.

[0155] The processor 210 can serve as the central nervous system and command center of the watch 200. The processor 210 can generate operation control signals based on the instruction opcode and timing signals to control instruction fetching and execution. The processor 210 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 210 is a cache memory.

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

[0157] Furthermore, the processor 210 can be configured to communicate with the memory 230 and execute a series of instructions stored in the memory 230 on the watch 200. Specifically, the processor 210 executes various functions and data processing of the watch 200 by running computer program instructions stored in the memory 230.

[0158] The sensor 220 may include, for example, a sensor for monitoring sleep, a sensor for monitoring heart rate, or other sensors capable of motion and health monitoring. These sensors can collect data on several dimensions, including sleep, morning resting heart rate, and heart rate variability (HRV), and transmit this data to the mobile phone 100. The mobile phone's health and fitness app can then determine the user's current fatigue level based on these multiple parameters and provide appropriate reminders.

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

[0160] That concludes the introduction to the hardware structure of Watch 200. It should be understood that... Figure 4 The watch 200 shown is merely an example. In a real implementation, the watch 200 may have more or fewer parts than shown in the figure, may combine two or more parts, or may have different part configurations. Figure 4 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.

[0161] See Figure 5 This example illustrates a software architecture for a watch 200. Understandably, the software architecture of the watch 200 can also employ a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture. The software system includes, but is not limited to, Android and iOS systems.

[0162] For ease of explanation, this application uses the layered architecture of the Android system as an example to illustrate the software structure of the watch 200.

[0163] like Figure 3 As shown, the layered architecture of the Watch200 divides the software into several layers, each with a clear role and division of labor. Layers communicate with each other through software interfaces. In some implementations, the Android system of the Watch200 is divided into four layers, from top to bottom: the Application (APP) layer, the Application Framework (FWK) layer, the algorithm and internal libraries layer, and the kernel layer.

[0164] like Figure 5 As shown, the application package for Watch 200 may include map applications, communication applications, music players, etc.

[0165] Understandably, the communication applications mentioned above include, for example, messaging applications, call log applications, contact applications, and call applications.

[0166] See also Figure 5 For example, the application framework layer of 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 user's fatigue level from multiple dimensions such as morning resting heart rate, heart rate variability, acute-chronic workload ratio (ACWR), and sleep, the logic control service may include various logic control services such as sleep data acquisition, morning resting heart rate calculation, and heart rate variability calculation.

[0168] The communication protocol can be a pre-agreed protocol with the watch 100, which facilitates data exchange between the two according to the agreed communication protocol.

[0169] 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 libraries, barcode libraries, payment libraries, and protocol stacks provided by chip manufacturers, such as traditional Bluetooth protocol stacks and low-power protocol stacks.

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

[0171] That concludes the introduction to the software structure of Watch 200. It is understandable that... Figure 5 The layers in the illustrated software structure and the components contained in each layer do not constitute a specific limitation on the watch 200. In other embodiments of this application, the watch 200 may include more or fewer layers than illustrated, and each layer may include more or fewer components; this application does not impose any limitations.

[0172] To better understand the exercise plan adjustment method provided in the embodiments of this application, in Figure 3 The software structure shown is for mobile phone 100 and Figure 5 Based on the software structure of the watch 200 shown, combined with Figure 6 A system for implementing the exercise plan adjustment method provided in the embodiments of this application will be described.

[0173] See Figure 6 For example, a system for implementing an exercise plan adjustment method may include a mobile phone 100 and a watch 200.

[0174] Specifically, in this embodiment, a sports and health app is installed on the mobile phone 100. Optionally, the sports and health app may integrate the logic provided in this embodiment for intelligently adjusting exercise plans based on five major scenarios.

[0175] Optionally, five scenarios are included, such as fatigue, menstrual cycle, weather, improved physical ability, and inconsistent execution rate.

[0176] See also Figure 6 For example, the processing of integrated functions in a sports and health app can be implemented by a separate sports platform kit (tool). This application does not limit the specific implementation of the sports platform kit.

[0177] Furthermore, it should be noted that the mobile phone 100 also needs to include a software development kit (SDK) for interconnecting with the watch 200. In this embodiment, it is referred to as the Interconnection SDK, but in practical applications, it can be named as needed. In this way, the mobile phone 100, through the Interconnection SDK and using the same account, can achieve interconnected management of multiple devices, and multiple devices under the same account can also synchronize data.

[0178] See also Figure 6 For example, mobile phone 100 also needs to have a communication protocol. Mobile phone 100 and watch 200 can establish a communication connection between them based on their respective communication protocols.

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

[0180] In addition, the display screen of the watch 200 can be used to display prompts related to the adjustment of the exercise plan made by the phone 100 according to five scenarios, as well as course reminders in the exercise plan.

[0181] In addition, among some possible implementations, the system used to implement the exercise plan adjustment method may also include sports and health data cloud platforms and big data cloud platforms.

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

[0183] Optionally, the mobile phone can also interact with the big data cloud platform to send fault or operational data to the big data cloud platform, so that technicians can locate the anomalies in the sports and health APP based on the data and perform updates, maintenance and other processing on the sports and health APP.

[0184] Based on the above system, when a user exercises using a sports and health app, the exercise plan adjustment method provided in this application embodiment can provide short-term scientific guidance and suggestions in scenarios such as fatigue, menstrual cycle, and weather. It can also provide long-term exercise plan adjustments in scenarios such as discrepancies between the user's improved athletic ability and execution rate, thereby ensuring more scientific training, avoiding injuries and overtraining, and ultimately achieving the user's exercise goals. Examples of running goals include maintaining health, completing a 3km race, completing a 5km race, improving 5km performance, improving 10km performance, improving half-marathon performance, and improving full-marathon performance.

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

[0186] For ease of explanation, this application uses a 7-day (1-week) cycle as a small cycle and a 41-day (6-week) cycle as a large cycle as an example.

[0187] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the small cycle and the large cycle can be set according to the actual situation, and this application does not impose any restrictions on this.

[0188] The following sections will describe the exercise plan adjustment method provided in this application embodiment, focusing on both short-cycle and long-cycle exercise plan adjustments.

[0189] Optionally, adjustments to exercise plans over shorter periods primarily involve providing scientific guidance and suggestions before the user begins exercising. Adjustments over longer periods, on the other hand, involve creating a new exercise plan based on the current progress of the existing plan and changes in the user's capabilities.

[0190] The following are the scenarios involved in adjusting short-cycle exercise plans:

[0191] Scenario 1: Short-cycle fatigue adjustment plan

[0192] See Figure 7 In example (1), the interface 10a of the mobile phone 100 displays icons of some or all of the currently installed applications. These icons include the icon 10a-1 of the Sports & Health APP.

[0193] Optionally, when the user clicks icon 10a-1, the mobile phone 100 responds to the operation by launching the Sports & Health APP. After the Sports & Health APP launches, the interface displayed on the screen will change from... Figure 7 The interface 10a shown in (1) is switched to Figure 7 Interface 10b is shown in (2).

[0194] Interface 10b can be the default interface displayed after the sports and health app is launched. Optionally, interface 10b can be, for example, the interface corresponding to the "Health" option, that is, the "Health" option shown in the bottom taskbar of interface 10b (including the "Health" option, "Exercise" option, "Device" option, and "My" option) is selected (in the selected state). Figure 7 When the style shown in (2) is displayed, the corresponding interface is displayed.

[0195] See also Figure 7 In section (2), for example, interface 10b may include various health-related function options, information, etc. For example, information related to today's steps, information related to moderate to high intensity activities, information related to activity consumption, and corresponding graphs. Also, for example, function options and information related 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 recent walking steps. Also, for example, the "Menstrual Cycle" option, the "Weight" option, etc.

[0196] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, users can edit the tabs displayed on the interface 10b according to their usage habits, such as adjusting the display position of each tab, and specifying which tabs need to be shown or hidden on the interface 10b. This application does not impose any restrictions on this.

[0197] See also Figure 7 In example (2), when a user clicks the "Sports" option in interface 10b, the mobile phone 100 responds to the operation by switching from interface 10b to the interface corresponding to the "Sports" option, such as... Figure 8 The interface 10c shown in (1) indicates that the "Motion" option is selected, as indicated by the style of the "Motion" option displayed in the bottom taskbar of the interface 10c.

[0198] See Figure 8 In example (1), interface 10c may include various sports-related options, information, etc. For example, the user's accumulated mileage from outdoor running, various sports options (such as outdoor running, indoor running, walking, cycling, etc.). Also, for example, cards corresponding to the formulated exercise plan, such as... Figure 8 The “XX Running Plan” card shown in (1) is another example. Other examples include the “All Courses” option to view all fitness classes and the “All Plans” option to view all exercise plans.

[0199] Understandably, in the embodiments of this application, "XX Running Plan" is only an illustrative example. In actual applications, it can be named as other names as needed.

[0200] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, other cards may also be displayed in the interface 10c, such as course ranking cards, plan recommendation cards, etc., and this application does not impose any limitations on this.

[0201] Taking a user-defined exercise plan as an example, specifically a running plan, see below. Figure 8 In example (1), the “XX Running Plan” card can display the total duration of the running plan (31 days as shown in the figure), the current progress (2 days as shown in the figure), and the course schedule for this week.

[0202] See also Figure 8 In example (1), in the "XX Running Plan" card, the weekly schedule section can be identified by different icons. For instance, a dumbbell icon can be used for core courses, which are high-intensity courses. A circle icon can be used for regular courses, which are relatively low-intensity courses.

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

[0204] In scenarios with only core courses, where the user's goal is to maintain health, the core training days (i.e. days with core courses) available for the user to train each week in the exercise plan could be, for example, 2 days.

[0205] In scenarios with only core courses, where the user's goal is to become a beginner, the core training days available for the user each week in the exercise plan could be, for example, 2 or 3 days.

[0206] In scenarios with only core courses, where the user's goal is to improve performance, the exercise plan could include, for example, 3 core training days per week.

[0207] For scenarios that include both core and regular courses, and where the user's goal is to become a beginner, the number of training days (including core training days and regular training days) available for selection per week in the exercise plan can be, for example, 3 days or more. Optionally, if the number of training days is 3, for example, 2 core training days and 1 regular training day.

[0208] For scenarios that include both core and regular courses, and where the user's goal is to become a beginner, the number of training days available for the user to choose from each week in the exercise plan can be, for example, more than 3 days.

[0209] In scenarios where there are both core courses and regular courses, and the user's goal is to improve their grades, the number of training days available to the user each week in the exercise plan can be, for example, more than 3 days.

[0210] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the number of training days available to the user per week in the exercise plan can be reasonably adjusted according to the user's physical condition, and this application does not impose any restrictions on this.

[0211] Furthermore, since the "XX Running Plan" card displays a weekly schedule, different colors and styles can be used to distinguish between past, current, and future courses. Regarding the styles of past, current, and future course identifiers, as well as core past, current, and future course identifiers, some possible implementations could be as follows: Figure 9 As shown.

[0212] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, other styles of icons can also be used to identify courses with different times and training intensities, and this application does not impose any restrictions on this.

[0213] by Figure 9 Taking the style shown as an example, Figure 8 The specific schedule for this week in the “XX Running Plan” card shown in (1) is as follows: Monday (11th) was a regular course, today (Wednesday, 13th) was a regular course, and Friday (15th) was a core course.

[0214] For example, when a user wants to exercise, they can click the "XX Running Plan" card. In response to this action, mobile phone 100 will redirect from interface 10c to the corresponding interface for the XX Running Plan, such as... Figure 8 Interface 10d is shown in (2).

[0215] See Figure 8 In the middle (2), for example, the interface 10d may include multiple cards, such as the daily course completion card 10d-1, the weekly course schedule card 10d-2, the card for all courses included in the selected date, such as the card corresponding to the pre-run warm-up exercise course 10d-3 and the card corresponding to the enjoyable experience run course 10d-4, and the icon 10d-0 for opening the introduction to core training days and ordinary training days.

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

[0217] See Figure 10 For example, window 10d-01 displays introductory information about core training days and regular training days. When the user clicks the "OK" option displayed in window 10d-01, the mobile phone 100 responds by closing window 10d-01, and the user interface returns to normal. Figure 8 Interface 10d is shown in (2).

[0218] In addition, it should be noted that in short-cycle fatigue adjustment scenarios, the phone displays 100%. Figure 8In the case of interface 10d shown in (2), mobile phone 100 can determine the current fatigue level of the user based on the indicator data provided by the watch 200 worn by the user to determine the fatigue level, or the user evaluation data collected by mobile phone 100 through the displayed questionnaire feedback form. Then, based on the user's fatigue level, a prompt information window (hereinafter referred to as: window) pops up in interface 10d to provide exercise guidance to the user, that is, to achieve small-cycle fatigue adjustment.

[0219] Optionally, in this embodiment of the application, the user's state is divided into non-fatigue and fatigued. Fatigue can be divided into multiple levels as needed, such as level 1 (hereinafter referred to as: level 1 fatigue), level 2 (hereinafter referred to as: level 2 fatigue), and level 3 (hereinafter referred to as: level 3 fatigue), and non-fatigue can also be represented as level 0 fatigue.

[0220] The reminder strategies (exercise guidance) to be followed for different user states can be shown in Table 1.

[0221] Table 1 Exercise guidance for different user states

[0222] Fatigue level Exercise guidance Level 0 fatigue No reminder Level 1 fatigue Users are reminded to pay attention to their physical condition during the course and ensure they get enough rest. Level 2 fatigue It is recommended that users do not train today or engage in a low-intensity, regular course. Level 3 fatigue Users are advised not to perform any training today.

[0223] Optionally, at level 0 fatigue, i.e., when there is no fatigue, the interface can remain as described in point 10d since no additional reminders are needed to the user. Figure 8 The style shown in (2) is as follows.

[0224] Optionally, in the case of Level 1 fatigue, a pop-up window in interface 10d can remind the user to pay attention to their physical condition during the course and ensure sufficient rest. This can be, for example... Figure 11 As shown in (1). That is, in this case, the style of the window displayed in interface 10d is Figure 11 The window 10d-51 shown in (1) is shown in the middle.

[0225] Optionally, in the case of Level 1 fatigue, the pop-up window in interface 10d may contain content suggesting that the user should not train today or should engage in a low-intensity, regular course. This content could be as follows: Figure 11 As shown in (2). That is, in this case, the style of the window displayed in interface 10d is Figure 11 The window 10d-52 shown in (2) is shown in the middle.

[0226] Optionally, in the case of Level 1 fatigue, a pop-up window in interface 10d may display content suggesting that the user should not perform any training today. This content could include, for example... Figure 11 As shown in (3). That is, in this case, the style of the window displayed in interface 10d is Figure 11 The window 10d-53 shown in (3) is shown in the middle.

[0227] It should be noted that when the user clicks Figure 11 The "OK" option in window 10d-51 shown in (1), or Figure 11 The "OK" option in window 10d-52 shown in (2) or Figure 11 After the “OK” option in window 10d-53 shown in (3), the mobile phone 100 can close window 10d-51, or window 10d-52, or window 10d-53 displayed in interface 10d in response to the operation.

[0228] In addition, it should be noted that, Figure 11 The courses shown in window 10d-52 in (2) are the courses for ordinary training days, i.e., training days with ordinary courses; the courses with high training intensity are the training days with core courses.

[0229] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0230] Furthermore, it should be noted that when the mobile phone 100 and the watch 200 are interconnected, and a pop-up window 10d-51, 10d-52, or 10d-53 appears on interface 10d, and the watch 200 is enabled to receive notification messages from the sports and health app, the watch 200 will display the prompt information in window 10d-51, 10d-52, or 10d-53. The corresponding interface effects are not limited in this embodiment and will not be described here.

[0231] Optionally, during 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 follows: Figure 12 As shown.

[0232] S101, Mobile Phone 100 determines whether at least one of the fatigue levels, determined by morning resting heart rate, HRV, or ACWR, is level 3 fatigue.

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

[0234] Here, HRV refers to the minute differences that exist between successive heartbeats. In this embodiment, the fatigue level is determined based on the RMSSD (the square root of the average of the sum of squares of the differences between adjacent normal RR intervals) determined by HRV data, and the ratio of low frequency (LF) to high frequency (HF) (LF / HF).

[0235] The RR interval typically refers to the time interval between two heartbeats.

[0236] ACWR refers to the ratio of the amount of training completed in one week (acute workload or acute load) to the average amount of training completed in four weeks (average chronic workload or chronic load).

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

[0238] Accordingly, if the user's current fatigue level is determined to be level 3 fatigue, a pop-up message can be displayed in the interface 10d. Figure 11 The window shown in (3) is 10d-53.

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

[0240] Optionally, once a specific fatigue level, such as level 0, level 1, or level 2 fatigue, is determined based on high-priority data, the phone 100 can stop determining the fatigue level based on low-priority data. This eliminates the need to calculate the fatigue level based on data from every dimension, reducing computational load.

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

[0242] Optionally, in scenarios where the fatigue level determined based on the morning resting heart rate data is level 0, 1, or 2, the user's current fatigue level can be determined to be the same as that determined based on the morning resting heart rate data. Otherwise, if the fatigue level cannot be determined based on the morning resting heart rate data, the fatigue level can be determined based on HRV data, which has a lower priority than the morning resting heart rate, i.e., step S103 can be executed.

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

[0244] Optionally, in scenarios where the fatigue level determined based on HRV data is level 0, level 1, or level 2 fatigue, the user's current fatigue level can be determined to be the fatigue level determined based on the HRV data. Otherwise, if the fatigue level cannot be determined based on HRV data, the fatigue level can be determined based on ACWR data, which has a lower priority than HRV, i.e., step S104 is executed.

[0245] S104, Mobile Phone 100 determines whether the fatigue level determined based on ACWR data is Level 1 fatigue or Level 2 fatigue.

[0246] Optionally, in scenarios where the fatigue level determined based on ACWR data is level 0, level 1, or level 2 fatigue, the user's current fatigue level can be determined to be the fatigue level determined based on the ACWR data. Otherwise, if the fatigue level cannot be determined based on ACWR data, the fatigue level can be determined based on sleep data with a lower priority than HRV, i.e., step S104 is executed.

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

[0248] Optionally, in scenarios where the fatigue level determined based on sleep data is level 0, 1, or 2, the user's current fatigue level can be determined to be the same as the fatigue level determined by the sleep data. Otherwise, if the fatigue level cannot be determined based on sleep data, the user can be assumed to be not fatigued, i.e., the fatigue level is level 0.

[0249] In addition, it should be noted that in some possible implementations, when executing steps S102, S103, S104, and 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 rules governing the validity of morning resting heart rate data, HRV data, ACWR data, and sleep data, please refer to the corresponding standards; they will not be elaborated here.

[0251] Therefore, based on multi-dimensional data and prioritizing resting heart rate > HRV > ACWR > sleep, the Phone100 determines the user's current fatigue level. This allows for accurate detection of fatigue while minimizing unnecessary calculations. Once the user's fatigue level is determined, the Phone100 can perform short-cycle fatigue adjustments. Specifically, it can provide appropriate guidance before the user exercises, thus minimizing the risk of injury from excessive exercise.

[0252] The following, in conjunction with the accompanying diagrams, explains the specific logic behind determining fatigue levels based on morning resting heart rate data, HRV data, ACWR data, and sleep data.

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

[0254] See Figure 13 For example, if a user wears watch 200 while sleeping at night, watch 200 will determine the user's morning resting heart rate, i.e., the average resting heart rate 2 hours before sleep, based on the morning resting heart rate calculation logic and heart rate algorithm.

[0255] Optionally, the user's sleep and wake times can be determined based on sleep data collected by the watch 200 over a period of time.

[0256] In addition, to distinguish whether the morning resting heart rate is from the first day or the second day, one possible approach is to use 8 p.m. as the dividing line. That is, if the sleep time is earlier than 8 p.m., the obtained morning resting heart rate is determined to be from the first day (the previous day); if the sleep time is later than 8 p.m., the obtained morning resting heart rate is determined to be from the second day.

[0257] In addition, it should be noted that during the user's sleep, the watch 200 can periodically record resting heart rate data, such as once per minute. This allows the average resting heart rate from the two hours prior to waking to be used as the morning resting heart rate.

[0258] In addition, it should be noted that, in order to ensure the validity of the data, for cases where the total sleep duration is less than 2 hours, the morning resting heart rate can be calculated based on the actual sleep duration.

[0259] See also Figure 13 For example, after obtaining the user's morning resting heart rate data, the watch 200 will send the user's morning resting heart rate data to the mobile phone 100 when a communication connection is established between the watch 200 and the mobile phone 100.

[0260] See also Figure 13 For example, after receiving the morning resting heart rate data sent by the watch 200, the mobile phone 100 can determine the user's heart rate fluctuation range based on the morning resting heart rate data, and then determine the user's fatigue level for the day based on the heart rate fluctuation range.

[0261] It should be noted that in practical applications, users may sleep and rest multiple times a day. For situations involving multiple sleep periods within a day, when a user opens the fitness app to view their exercise plan, as shown on the phone's 100 display interface... Figure 8 When the interface 10d shown in (2) is used, in one possible implementation, the resting heart rate data of the morning pulse during the longest sleep period in multiple sleep cycles can be selected to determine the range of heart rate fluctuations of the user.

[0262] Optionally, the heart rate fluctuation range may include Figure 13 The five cases shown are as follows.

[0263] See also Figure 13 For example, if a user's heart rate today fluctuates within N1 bpm (beats per minute) compared to the average heart rate of last week, i.e., case 1a, it can be determined that the user is not fatigued today, i.e., the fatigue level is 0.

[0264] See also Figure 13 For example, in the case of a user whose heart rate today exceeds the average of last week's N1-N2 bpm (including the two endpoints) (the heart rate before today did not exceed this), i.e., case 1b, to avoid special circumstances causing temporary fluctuations in heart rate exceeding the average of last week's N1-N2 bpm, which could lead to inaccurate determination of the fatigue level, one possible implementation is to pop up a Borg questionnaire on the user interface of mobile phone 100 so that the user can conduct a self-assessment, and then determine the user's fatigue level for today based on the assessment.

[0265] It should be noted that the logic for determining fatigue level provided in this application embodiment also includes determining fatigue level based on sleep data. When sleep data meets preset conditions, user intervention is still required to perform a self-assessment. Therefore, when the Borg questionnaire pops up, a sleep quality questionnaire can also pop up simultaneously, allowing users to complete the assessment together and avoiding the need to pop up the questionnaire again later when sleep data is required to determine fatigue level.

[0266] For example, when the heart rate fluctuation range determined based on morning resting heart rate data falls under case 1b, when the user opens the Sports & Health app and enters... Figure 8 When the interface 10d shown in (2) is displayed, the mobile phone 100 can directly jump to the following: Figure 14 The questionnaire feedback interface (interface 10e) is shown in (1).

[0267] See Figure 14 In example (1), interface 10e includes two questionnaires, such as questionnaire 10e-1 and questionnaire 10e-2. Questionnaire 10e-1 is used to determine the user's current level of fatigue, i.e., the aforementioned Borg questionnaire; questionnaire 10e-2 is used to determine the user's sleep quality last night, i.e., the aforementioned sleep quality questionnaire. The Borg questionnaire includes 11 levels of fatigue corresponding to different scores (0 to 10). Figure 14 Swiping up on interface 10e shown in (1) will display the complete sleep quality questionnaire. Figure 14 As shown in (2), the sleep quality questionnaire includes four options.

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

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

[0270] Table 2 shows the relationship between user self-assessment scores obtained from the Borg questionnaire and fatigue levels.

[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] Therefore, in case 1b, based on the user's self-assessment score obtained from the Borg questionnaire and Table 2, Mobile Phone 100 can quickly determine the user's current fatigue level.

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

[0274] See also Figure 13 For example, if a user's heart rate exceeds the average of last week's N1 to N2 bpm for two consecutive days today and yesterday (i.e., case 1c), there is no need to pop up interface 10e. That is, there is no need to determine based on the user's self-assessment score. The user's fatigue level for today is directly determined to be level 2 fatigue.

[0275] See also Figure 13 For example, if a user's heart rate exceeds the average of last week's N1 to N2 bpm for three consecutive days today, yesterday, and the day before yesterday (i.e., case 1d), there is no need to pop up interface 10e. That is, there is no need to determine based on the user's self-assessment score. The user's fatigue level for today is directly determined to be level 3 fatigue.

[0276] See also Figure 13 For example, if a user's signaling exceeds the average of last week N3 bpm or more, it indicates that today's heart rate fluctuation is not caused by special circumstances. In this case, there is no need to pop up the interface 10e, that is, there is no need to determine based on the user's self-assessment score. The user's fatigue level today is directly determined to be level 3 fatigue.

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

[0278] Optionally, in some possible implementations, 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 merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the specific values ​​of N1, N2, and N3 can be adaptively adjusted according to the user's actual situation, and this application does not impose any restrictions on this.

[0280] This allows for the determination of fatigue levels based on morning resting heart rate data.

[0281] The following is the content for determining fatigue level based on HRV data:

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

[0283] See also Figure 14 For example, after receiving heart rate variability data sent by watch 200, mobile phone 100 can determine the user's current fatigue level based on the heart rate variability data.

[0284] Optionally, the mobile phone 100 can determine the user's current fatigue level based on the RMSSD and LF / HF ratio determined from heart rate variability data.

[0285] RMSSD refers to the root mean square of the difference between adjacent normal cardiac cycles. It is an important indicator of heart rate variability, used to reflect the activity of the body's parasympathetic nervous system.

[0286] The LF / HF ratio refers to the ratio of low-frequency heart rate variability to high-frequency heart rate variability. Generally, a smaller LF / HF ratio indicates better autonomic nervous system function and better heart health.

[0287] The calculation of RMSSD and LF / HF ratio can be found in relevant literature on 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 RMSSD, LF, HF, RR intervals and other data obtained during sleep need to be consistent with the HRV change trend.

[0289] Optionally, it can be stipulated that consistency reaches 80%.

[0290] Based on the two heart rate variability indicators, RMSSD and LF / HF ratio, several situations can be distinguished, such as... Figure 15 The five cases shown are 2a to 2e.

[0291] See also Figure 14 For example, if the RMSSD is higher than a milliseconds and the LF / HF ratio is lower than x, i.e., case 2a, it can be determined that the user is not fatigued today, i.e., the fatigue level is level 0 fatigue.

[0292] See also Figure 14 For example, in the case where the RMSSD is between b and a milliseconds (inclusive of the endpoint value) and the LF / HF ratio is between x and y (inclusive of the endpoint value), i.e., case 2b, it can be determined that the user is fatigued today and the fatigue level is level 1 fatigue.

[0293] See also Figure 14 For example, if the RMSSD is between c and b milliseconds (inclusive of the endpoint value) and the LF / HF ratio is between y and z (inclusive of the endpoint value), i.e. case 2c, it can be determined that the user is fatigued today and the fatigue level is level 2 fatigue.

[0294] See also Figure 14 For example, if the RMSSD is less than c milliseconds and the LF / HF ratio is greater than z, i.e. case 2d, it can be determined that the user is fatigued today and the fatigue level is level 3 fatigue.

[0295] See also Figure 14 For example, if the RMSSD and LF / HF ratios do not fall under case 2a, case 2b, case 2c, or case 2d, it can be determined that the user is not fatigued today, i.e., the fatigue level is 0.

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

[0297] Optionally, in some possible implementations, 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] Furthermore, it should be noted that the above x, y, and z satisfy the following relationship: 0 <x<y<z。

[0299] Optionally, in some possible implementations, 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 merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the specific values ​​of a, b, and c, as well as x, y, and z, can be adaptively adjusted according to the user's actual situation, and this application does not impose any restrictions on this.

[0301] This enabled the determination of fatigue levels based on HRV data.

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

[0303] The determination of fatigue level based on ACWR data can be divided into two scenarios: Scenario 1.1, where the user wears Watch 200 and calculates ACWR based on the heart rate data provided by Watch 200; and Scenario 2.2, where the phone 100 does not interact with Watch 200 and calculates ACWR based on the RPE value and training duration obtained from course feedback. The following will explain each scenario in conjunction with... Figure 16 and Figure 17 The following will explain scenarios 1.1 and 1.2.

[0304] Scenario 1.1:

[0305] See Figure 16 For example, when a user is wearing watch 200, watch 200 will acquire the user's heart rate data at the end of each training session based on the heart rate data acquisition logic and heart rate algorithm, and send the acquired heart rate data to mobile phone 100.

[0306] See also Figure 16 For example, after receiving heart rate data sent by watch 200, mobile phone 100 will calculate ACWR based on the heart rate data, and then determine the fatigue level based on ACWR.

[0307] In essence, ACWR refers to the ratio of the amount of training completed in one week (acute workload or acute load) to the average amount of training completed in four weeks (average chronic workload or chronic load). That is, ACWR = the ratio of the user's acute load completed in one week to the average chronic load completed in four weeks.

[0308] Optionally, in some implementations, ACWR can be calculated using an Exponentially Weighted Moving-Average (EWMA). Specifically, the user's current ACWR can be determined according to the following formula (1).

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

[0310] Here, λa represents the degree to which the training load decays over time, and its specific value is between 0 and 1.

[0311] Furthermore, the degree to which the training load, represented by λa, decays over time satisfies the following formula (2).

[0312] λa=2 / (N+1) Formula (2)

[0313] Where N is the time decay constant, which is usually the time window for acute load and chronic load. The time window for acute load is 7 days, or 1 week; the time window for chronic load is 28 days, or 4 weeks.

[0314] For example, if a user's acute load in the most recent week is 4, and the acute loads in the previous 1, 2, and 3 weeks are 1, 2, and 3 respectively, then the chronic load coupling over 4 weeks = 1 + 2 + 3 + 4 = 10, and the average chronic load = 10 / 4 = 2.5.

[0315] The training load in formula (1) can be determined based on the pre-defined intensity level and training duration (min), specifically according to the following formula (3).

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

[0317] Optionally, intensity levels can be divided according to heart rate zones. Specifically, heart rate data from all training sessions (such as running + strength training) is aggregated and averaged. Using the training zone stimulation method, an individual's heart rate can be divided into five levels based on their maximum heart rate, with each zone increasing by 10% from 50% of their maximum heart rate.

[0318] Optionally, the intensity level can be divided into 5 heart rate zones, as shown in Table 3.

[0319] Table 3 Relationship between Heart Rate and Intensity Level

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

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

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

[0323] Accordingly, after determining the training load, the user's current ACWR can be quickly determined based on yesterday's ACWR (ACWR_yesterday, or the ACWR corresponding to the last training course) and formulas (1) and (2).

[0324] Optionally, ACWR can be divided into 4 intervals, which can be viewed as 4 specific cases, such as Figure 16The examples shown are cases 3a, 3b, 3c, and 3d. These four intervals can each correspond to different fatigue levels.

[0325] The relationship between ACWR and fatigue level is shown in Table 4.

[0326] Table 4 Relationship between ACWR and Fatigue Grade

[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] Therefore, based on the calculated ACWR value and Table 4, Mobile Phone 100 can quickly determine the user's current fatigue level.

[0329] Optionally, Table 4 can be pre-stored in the local storage medium of the mobile phone 100, such as 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 implementations, 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 merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the specific values ​​of d, e, and f can be adaptively adjusted according to the user's actual situation, and this application does not impose any restrictions on this.

[0333] Thus, when the mobile phone 100 interacts with the watch 200, the ACWR is calculated based on the heart rate data provided by the watch 200, thereby determining the fatigue level.

[0334] Scene 1.2:

[0335] See Figure 17 For example, if the user is not wearing the watch 200, or if there is no communication connection between the watch 200 and the mobile phone 100, the mobile phone 100 can pop up a course feedback form, such as the rating of perceived exertion (REP), after each training session. Then, based on the RPE value selected by the user in the RPE table and the training duration (min), the ACWR is calculated, and the fatigue level is determined based on the ACWR.

[0336] Optionally, the RPE table can be displayed in a way that, for example, is the interface corresponding to the end of the training course. Figure 18 A pop-up window 10f-1 appears in the interface 10f shown.

[0337] Optionally, window 10f-1 provides a space for users to perform a self-assessment. The selected RPE value can include 11 scores from 0 to 10, with each score corresponding to a description... Figure 11 The descriptions corresponding to the same score in the Borg questionnaire shown in (1) are similar, and will not be repeated here.

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

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

[0340] Therefore, without the interaction between the mobile phone 100 and the watch 200, the user's current ACWR can be quickly determined based on yesterday's ACWR (ACWR_yesterday, or the ACWR corresponding to the last training course) and the formulas (1) and (2) given in scenario 1.1.

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

[0342] This allows for the calculation of ACWR based on the RPE value obtained from course feedback and training duration, thereby determining the fatigue level.

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

[0344] See Figure 19 For example, if a user wears watch 200 while sleeping, watch 200 will acquire the user's sleep data during sleep based on sleep data acquisition logic and sleep algorithms.

[0345] Optionally, the watch 200 can send sleep data to the mobile phone 100 with which it has established a communication connection, either on a timer or after detecting that the user has woken up.

[0346] See also Figure 19 For example, after receiving sleep data sent by watch 200, mobile phone 100 will determine whether the user's sleep meets any one or more of the following three conditions based on the received sleep data.

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

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

[0349] Condition 3: The average wake-up time of the previous week is earlier than the second preset time.

[0350] Optional, 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.

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

[0354] It should be understood that the priority of using sleep data to determine fatigue level is lower than that of using morning resting heart rate data. Therefore, if situation 1b occurs during the stage of determining fatigue level using morning resting heart rate data, where the sleep quality questionnaire pops up along with the borg questionnaire, meaning both questionnaires are displayed simultaneously on interface 10e, then when entering the stage of determining fatigue level based on sleep data, there is no need to jump back to interface 10e. Instead, the fatigue level can be determined directly based on the user's selection in the sleep quality questionnaire on interface 10e, as in situation 1b.

[0355] pass Figure 11 As shown in the interface 10e in (2), the sleep quality questionnaire includes four options. In practical applications, these four options can be mapped to four 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 four situations can correspond to different scores, and different scores can correspond to different fatigue levels.

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

[0357] Table 5 shows the scores for each option in the sleep quality questionnaire, and the relationship between different scores and fatigue levels.

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

[0359] Therefore, if 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, Mobile Phone 100 can quickly determine the user's current fatigue level.

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

[0361] This allows for the determination of fatigue levels based on sleep data.

[0362] In the small-cycle fatigue adjustment scheme provided in this application embodiment, health-related data such as morning resting heart rate data, HRV data, heart rate data (for ACWR calculation), and sleep data collected by smart wearable devices, such as the watch 200 mentioned in the above embodiment, are combined with self-evaluation results collected from various subjective evaluation questionnaires displayed on the user's smart devices, such as mobile phone 100. The four specific fatigue level determination methods—morning resting heart rate data, HRV data, ACWR data, and sleep data—complement each other. The fatigue level is selected from these four dimensions according to the priority order: morning resting heart rate is higher than HRV, HRV is higher than ACWR, and ACWR is higher than sleep. This makes the final determined fatigue level more reasonable and accurate, thereby providing appropriate guidance (i.e., a reasonable adjustment plan) before the user exercises, avoiding damage to the body caused by excessive exercise.

[0363] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, other methods can also be used to determine the user's fatigue level, and then appropriate exercise guidance suggestions can be made based on the fatigue level.

[0364] Furthermore, it should be noted that in some possible implementations, the above-mentioned process for determining the fatigue level can also occur when the user opens the fitness app, or opens... Figure 8 The interface shown in (2) was determined 10 days ago. In this case, that is, when the user interface is switched to... Figure 8 When the interface shown in (2) is 10d, the mobile phone 100 can directly display exercise guidance suggestions suitable for the current fatigue level on this interface based on the determined fatigue level, such as Figure 11 The window 10d-51, or window 10d-52, or window 10 shown in (1), or (2), or (3).

[0365] Furthermore, it should be noted that there are not courses every day of the week, nor is it that users have already completed today's course. To avoid users opening the app when there are no courses available or when they have already completed the course, [further details are needed]. Figure 8 In the case of interface 10d shown in (2), mobile phone 100 displays on this interface. Figure 11Window 10d-51, or window 10d-52, or window 10 are shown in (1), (2), or (3). Before making exercise guidance recommendations based on the determined fatigue level, it can be further determined whether there is a class today, or whether today's class has already been trained. If there is no class today, or today's class has already been trained, exercise guidance recommendations may not be made based on the determined fatigue level. Conversely, if there is a class today, and today's class has not yet been trained, exercise guidance recommendations should be made based on the determined fatigue level.

[0366] Furthermore, it's important to note that to prevent users from overtraining and causing physical harm, one possible implementation is to configure the system so that users can only train on core courses for two consecutive days, or if their weekly load already meets the load standard for core courses, and today's course is also a core course. Figure 8 In the interface shown in (2), a pop-up window reminds the user that they can choose to rest or practice the week's regular courses today. That is, in this case, the user's current fatigue level can be disregarded.

[0367] Optionally, for windows that pop up in interface 10d under overload conditions, such as Figure 20 The window 10d-54 is shown in (1).

[0368] It should be noted that the suggestion to contact the regular courses for this week requires that there are still regular courses available for training this week. Specifically, if there are still regular courses available for training this week, in addition to the "OK" and "Rest Today" options, window 10d-54 will also display the "Change Course" option.

[0369] Specifically, when a user clicks the "OK" or "Rest Today" option, the phone 100 will respond to this action by closing window 10d-54. When a user clicks the "Change Course" option, the phone 100 will respond to this action by closing window 10d-54 and displaying a window saying "Adjusting your plan..." on the 10d interface. Figure 20 As shown in (2).

[0370] For example, in Figure 20 If the interface shown in Figure (2) 10d displays today's trainable courses including the core courses, and the user clicks the "Change Course" option to adjust the plan, the following will be displayed: Figure 20 The interface shown in (3) 10d indicates that the courses available for training today will be adjusted to regular courses.

[0371] This avoids users from undergoing high-intensity training courses for several consecutive days, ensuring that users' bodies are not injured.

[0372] Furthermore, it's important to note that in practical applications, users may not follow the pre-programmed order of exercises in their workout plan. This could not only affect training effectiveness but also potentially lead to injury. For example, a warm-up is usually required before starting a regular or core workout, but users might skip this step and directly select the regular or core workout. In such cases, a pop-up window can be displayed on the interface. Figure 21 Window 10d-55 in the middle.

[0373] For example, when the user clicks the "Cancel" option in window 10d-55, the mobile phone 100 responds to the operation and can exit the selected normal course or training course, that is, return to interface 10d. When the user clicks the "Continue Training" option in window 10d-55, the mobile phone 100 responds to the operation and can start the normal course or training course.

[0374] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0375] Scenario 2: Short-cycle menstrual cycle adjustment plan (This scenario is mainly for female users)

[0376] Before explaining this scenario, we must first explain the prerequisite for realizing this scenario, namely, setting a physiological cycle.

[0377] Alternatively, in one possible implementation, the user can actively click on, such as... Figure 7 The “Menstrual Cycle” option is displayed in interface 10b shown in Figure (2). In response to this operation, mobile phone 100 can jump from interface 10b to the Menstrual Cycle interface, as shown below. Figure 22 Interface 10e is shown in (1).

[0378] See Figure 22 In (1), for example, the interface 10e may include more options 10e-1, switches 10e-2, etc.

[0379] When the user clicks on the "More Options" 10e-1, the phone 100 responds to this operation and displays the following on the interface 10e: Figure 22 The window 10e-3 shown in (2) is shown.

[0380] When a user clicks switch 10e-2, the phone 100 will respond by setting today as the start date of the menstrual period. Furthermore, it will display a menstrual period indicator and a fertile period indicator for the corresponding date in the recording area.

[0381] When a user clicks the "Settings" option in window 10e-3, the phone 100 responds to this operation and jumps from interface 10e to the menstrual cycle settings interface, such as... Figure 23 Interface 10f is shown in (1).

[0382] Optionally, the interface 10f can display two options: "menstrual period length" and "cycle length".

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

[0384] Alternatively, in some other possible implementations, the user can click the "Menstrual Period Length" option, and the phone 100 will respond to this operation by displaying a pop-up window on the interface 10f. Figure 23 The menstrual period length setting window 10f-1 is shown in (2). In this way, the user can select a suitable menstrual period length by sliding up and down the selectable number of days, and save the setting after clicking the "Confirm" option.

[0385] Alternatively, in some other possible implementations, the user can click the "cycle length" option, and the phone 100, in response to this operation, can display a pop-up window on the interface 10f. Figure 23 The cycle length setting window 10f-2 is shown in (3). In this way, the user can select a cycle length that suits them by sliding the selectable number of days up and down, and save the setting after clicking the "Confirm" option.

[0386] Alternatively, in another possible implementation, for example, if the user does not open interface 10e from the "Menstrual Cycle" option entry in interface 10b, but instead opens interface 10f through the "Settings" option in window 10e-3, and completes the menstrual cycle settings through the menstrual period length setting window 10f-1 and cycle length setting window 10f-2, then when the user opens... Figure 8 In the case of interface 10d shown in (2), a pop-up window can be displayed in interface 10d as follows: Figure 23 The window 10d-6 shown in (4) is used to remind the user to set their menstrual cycle.

[0387] For example, when a user clicks the "Go to Settings" option in window 10d-6, in one possible implementation, phone 100 responds to the operation and can jump to... Figure 22 The interface 10e shown in (1) allows users to complete the physiological cycle settings according to the above-described setup process. In another possible implementation, users can also directly jump to... Figure 23 The interface 10f shown in (1) is used to complete the setting of the menstrual cycle according to the above setting process.

[0388] This completes the setting of the menstrual cycle.

[0389] After setting the menstrual cycle, the phone 100 will periodically (e.g., once a day) retrieve the recorded menstrual cycle data. Based on the set menstrual cycle (menstrual period length, cycle length, etc.) and the recorded menstrual cycle data (which can be the predicted start time of menstruation based on the set menstrual cycle, or data generated after the user turns on switch 10e-2), it will determine the current stage. This allows it to provide reasonable exercise guidance and suggestions, i.e., adjust the exercise plan accordingly.

[0390] Optionally, in some possible implementations, five phases (five cases) can be divided based on the menstrual cycle and the recorded menstrual cycle data.

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

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

[0393] Optionally, in some possible implementations, 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 merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the specific values ​​of D1, D2, D3, D4, D5, D6, D7, D8, D9, and D10 can be adaptively adjusted according to the user's actual settings for menstrual period length and cycle length, etc., and this application does not impose any limitations on this.

[0395] See also Figure 24For example, in case 5a, since menstruation has just begun, a suggestion could be given such as "During this period when women experience frequent menstrual cramps, it is recommended that users refrain from any exercise." In practical applications, this suggestion could be displayed... Figure 8 In the interface 10d shown in (2), as displayed in interface 10d Figure 25 The window 10d-72 shown in (2) is shown in the middle.

[0396] See also Figure 24 For example, in scenario 5b, since menstruation has been underway for several days and is about to end, a suggestion like "Core workouts are not recommended; rest or regular workouts are advised" could be given. In practical applications, this suggestion could be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 25 The window 10d-73 shown in (3) is shown.

[0397] See also Figure 24 For example, for cases 5c and 5d, since menstruation has ended at this stage, no special adjustments are needed, and no prompt is given to the user. That is, no prompt is displayed to the user in interface 10d.

[0398] See also Figure 24 For example, in scenario 5e, where menstruation is approaching, a suggestion could be given such as, "Remind the user that menstruation is approaching, so they can prepare accordingly and adjust their training intensity based on their physical condition during menstruation." In practical applications, this suggestion could be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 25 The window 10d-71 shown in (1) is shown in the middle.

[0399] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0400] Furthermore, it should be noted that in some possible implementations, the process of determining the current stage described above could also occur when the user opens the Health & Fitness app, or opens... Figure 8 The interface shown in (2) was determined 10 days ago. In this case, that is, when the user interface is switched to... Figure 8 When the interface shown in (2) is 10d, the mobile phone 100 can directly display exercise guidance suggestions suitable for the current menstrual stage based on the determined menstrual stage, such as Figure 25 The window 10d-71 shown in (1) or Figure 25The window shown in (2) is 10d-72, or Figure 25 The window 10d-73 shown in (3) is shown.

[0401] Furthermore, it should be noted that there are not courses every day of the week, nor is it that users have already completed today's course. To avoid users opening the app when there are no courses available or when they have already completed the course, [further details are needed]. Figure 8 In the case of interface 10d shown in (2), mobile phone 100 displays on this interface. Figure 25 The window 10d-71 shown in (1) or Figure 25 The window shown in (2) is 10d-72, or Figure 25 Window 10d-73 is shown in (3). Before providing exercise guidance based on the determined menstrual cycle, it is possible to further determine whether there is a class today, or whether today's class has already been trained. If there is no class today, or today's class has already been trained, exercise guidance may not be provided based on the determined menstrual cycle. Conversely, if there is a class today, and today's class has not yet been trained, exercise guidance may be provided based on the determined menstrual cycle.

[0402] Furthermore, it's worth noting that the phone can also determine the user's preferred start time for training based on their daily workout schedule. This means that, if the user has enabled notification permissions for the fitness app, the app can send a notification message based on the user's preferred training time, such as one hour before their scheduled start time, according to their menstrual cycle. Figure 25 The contents of window 10d-71 shown in (1), or Figure 25 The contents of window 10d-72 shown in (2), or Figure 25 The contents of window 10d-73 shown in (3) provide advance guidance on exercise, enabling users to schedule their time more reasonably.

[0403] Therefore, for female users, reasonable exercise guidance suggestions can be made based on their menstrual cycle to avoid improper exercise during the menstrual cycle, which could cause injury to their body.

[0404] Scenario 3: Short-term weather adjustment plan (mainly for outdoor sports)

[0405] Understandably, weather conditions affecting outdoor sports can be categorized into abnormal weather such as rain, snow, and storms; abnormal temperature weather such as high or low temperatures; and air pollution. Specifically, in this embodiment, when the mobile phone 100 makes adjustments (makes sports guidance suggestions) based on weather data, such as the daily weather data obtained by the installed weather application, it can start from these three types of weather.

[0406] See Figure 26 For example, if the temperature is too high or too low today, corresponding exercise guidance suggestions can be given based on the specific temperature. For instance, in case 6a, where the temperature is greater than or equal to tem1°C, exercise guidance suggestions such as "High temperature risk warning; it is recommended that the user not train today or switch to indoor training" can be given. In practical applications, this suggestion can be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 27 The window 10d-81 shown in (1) is shown in the middle.

[0407] See also Figure 26 For example, in case 6b, where the temperature is greater than or equal to tem2°C but less than tem1°C, a suggestion similar to "It is recommended that the user rest today, practice a regular class, or switch to indoor training" can be given. In practical applications, this suggestion can be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 27 The window 10d-82 shown in (2) is shown in the middle.

[0408] See also Figure 26 For example, in case 6c, where the temperature is greater than tem4°C and less than or equal to tem3°C, exercise guidance suggestions such as "inform the user of the risk of injury, emphasize adequate warm-up or switch to indoor training" can be given. In practical applications, this suggestion can be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 27 The window 10d-83 shown in (3) is shown in the middle.

[0409] See also Figure 26 For example, in scenario 6d, where the temperature is less than or equal to tem3°C, exercise guidance suggestions could be given such as "inform the user of the risk of injury, emphasize adequate warm-up, and suggest resting today or switching to indoor training." In practical applications, this suggestion could be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 27 The window 10d-84 is shown in (4).

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

[0411] Optionally, in some possible implementations, 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 merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the specific values ​​of tem1, tem2, tem3, and tem4 can be determined according to the classification standards corresponding to high-temperature weather and local weather, and this application does not impose any restrictions on this.

[0413] See also Figure 26 For example, air quality can be categorized based on the Air Quality Index (AQI). For instance, in case 7a, where today's AQI falls between AQI1 and AQI2 (inclusive), the air quality can be considered excellent or good. In this case, users can proceed with their outdoor exercise plans normally, and therefore no reminder is needed. Figure 8 The interface shown in (2) 10d displays the window corresponding to the coach's suggestions.

[0414] See also Figure 26 For example, in scenario 7b, where today's AQI falls between AQI3 and AQI4 (inclusive), the air quality can be considered poor, belonging to light or moderate pollution. In this case, to protect user health, exercise guidance suggestions such as "inform the user of the air quality risk and suggest rest or indoor training" can be provided. In practical applications, this suggestion can be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 27 The window 10d-85 is shown in (5).

[0415] See also Figure 26 For example, in scenario 7c, where today's AQI is between AQI 5 and AQI 6 (inclusive), the air quality can be considered very poor, falling into the category of heavy or severe pollution. In this situation, to protect user health, exercise guidance suggestions such as "inform the user of the air quality risk and suggest rest or indoor training" can be provided. In practical applications, this suggestion can be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 27 The window 10d-85 is shown in (5).

[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 implementations, 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 merely an example provided to better understand the technical solution of this embodiment, and is not intended to be the sole limitation of this embodiment. In practical applications, the specific values ​​of aqi1, aqi2, aqi3, aqi4, aqi5, and aqi6 can be determined based on the air quality index and the corresponding classification criteria, and this application does not impose any restrictions on this.

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

[0420] See also Figure 26 For example, if today's weather is abnormal, such as rain, snow, or a storm, and outdoor exercise is not possible, a suggestion could be given such as "Indoor training is recommended." In practical applications, this suggestion could be displayed... Figure 8 In the interface 10d shown in (2), the following is displayed in the interface 10d: Figure 27 The window 10d-86 is shown in (6).

[0421] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0422] Furthermore, it should be noted that in some possible implementations, the above-mentioned process of determining weather conditions can also occur when the user opens the fitness and health app, or opens... Figure 8 The interface shown in (2) was determined 10 days ago. In this case, that is, when the user interface is switched to... Figure 8 When the interface shown in (2) is 10d, the mobile phone 100 can directly display suitable exercise guidance suggestions based on the determined weather conditions on this interface, such as Figure 27 The window shown in (1) is 10d-81, or Figure 27 The window shown in (2) is 10d-82, or Figure 27 The window shown in (3) is 10d-83, or Figure 27 The window shown in (4) is 10d-84, or Figure 27 The window shown in (5) is 10d-85, or Figure 27 The window 10d-86 is shown in (6).

[0423] Furthermore, it should be noted that there are not courses every day of the week, nor is it that users have already completed today's course. To avoid users opening the app when there are no courses available or when they have already completed the course, [further details are needed]. Figure 8 In the case of interface 10d shown in (2), mobile phone 100 displays on this interface. Figure 27 The window shown in (1) is 10d-81, or Figure 27 The window shown in (2) is 10d-82, or Figure 27 The window shown in (3) is 10d-83, or Figure 27 The window shown in (4) is 10d-84, or Figure 27 The window shown in (5) is 10d-85, or Figure 27 Window 10d-86 is shown in (6). Before making exercise guidance recommendations based on the determined weather conditions, it can be further determined whether there is a class today, or whether today's class has already been trained. If there is no class today, or today's class has already been trained, exercise guidance recommendations may not be made based on the determined weather conditions. Conversely, if there is a class today, and today's class has not yet been trained, exercise guidance recommendations should be made based on the determined weather conditions.

[0424] Furthermore, it's worth noting that the phone can also determine the user's preferred start time for training based on their daily workout schedule. This means that, if the user has enabled notification permissions for the Health app, the app can send a notification message based on the day's weather conditions, such as an hour before the user's preferred training time. Figure 27 The contents of window 10d-81 shown in (1), or Figure 27 The contents of window 10d-82 shown in (2), or Figure 27 The contents of window 10d-83 shown in (3), or Figure 27 The contents of window 10d-84 shown in (4), or Figure 27 The contents of window 10d-85 shown in (5), or Figure 27 The contents of window 10d-86 shown in (6) provide advance guidance on exercise, enabling users to schedule their time more reasonably.

[0425] Furthermore, it should be noted that in some possible implementations, the various weather conditions listed above, such as rain, snow, storms, high / low temperatures, and air pollution, may coexist. Since users are advised to switch from outdoor to indoor activities under these weather conditions, it is only necessary to prioritize and... Figure 8In the interface shown in (2), the prompt window corresponding to the coach's suggestion will pop up once.

[0426] Optionally, the various weather conditions listed above can be prioritized as follows: rain, snow, storm > temperature (high or low) > air quality (light, moderate, heavy, or severe pollution).

[0427] For example, today is a rainy day, and the temperature is between... Figure 26 In scenario 6a shown, where the air quality falls under scenario 7b, a pop-up message will appear on interface 10d when the user opens the Sports & Health app. Figure 27 The window 10d-86 is shown in (6). Alternatively, a coaching suggestion can be pushed to window 10d-86 via the notification manager an hour before the user's usual exercise session.

[0428] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0429] Therefore, it can provide reasonable exercise guidance suggestions based on the weather conditions of the day, avoiding users from exercising in situations unsuitable for outdoor activities and causing injury to their bodies.

[0430] Furthermore, it should be noted that in some possible implementations, scenarios 1, 2, and 3 involved in the aforementioned small-cycle motion plan adjustments may also exist concurrently. To avoid... Figure 8 In the interface shown in (2), multiple prompt windows corresponding to coach suggestions pop up continuously, affecting the user experience. These three small-cycle scenarios can also be configured so that only one prompt window corresponding to the coach suggestion pops up at a time, according to the set priority.

[0431] Optionally, Scenario 1 (fatigue), Scenario 2 (physiological cycle), and Scenario 3 (weather) can satisfy the following priority: fatigue reminder for Scenario 1 > physiological cycle reminder for Scenario 2 > weather reminder for Scenario 3.

[0432] For example, in a scenario where the user's current physical condition is at level 3 fatigue, their current menstrual cycle is in the proliferative phase, and the weather is condition 6b, a pop-up message can appear on screen 10d when the user opens the sports and health app. Figure 11 The window shown in (3) is 10d-53. Alternatively, a notification can be pushed an hour before the user's usual activity. Figure 11 The coaching advice in window 10d-53 shown in (3) is as follows.

[0433] For example, in a scenario where the user's current physical condition is at level 0 fatigue, their current menstrual cycle is in the proliferative phase, and the weather is in condition 6b, since no reminders are needed for level 0 fatigue and the proliferative phase, a pop-up message can appear on the screen when the user opens the Health app. Figure 27 The window 10d-82 shown in (3) is an example. Alternatively, a notification can be pushed an hour before the user's usual activity. Figure 27 The coaching advice in window 10d-82 shown in (3) is as follows.

[0434] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0435] This enables adjustments to the exercise plan when multiple short-cycle scenarios occur concurrently, resulting in more reasonable exercise guidance and ensuring a better user experience.

[0436] The following are the scenarios involved in adjusting a long-term exercise plan:

[0437] Scenario 4: Adjustment Plan for Enhancing Large-Cycle Motion Capabilities

[0438] Taking running as an example, the improvement in long-term exercise capacity is primarily in running ability. (See [link to relevant documentation]). Figure 28 For example, the running ability improvement and adjustment scheme implemented by mobile phone 100 may include steps S201 to S203.

[0439] S201 determines whether the user's maximum oxygen uptake should be increased to level S.

[0440] Among them, maximum oxygen uptake (VO2 max) refers to the maximum amount of oxygen that the human body can take in per minute under maximum load. It is one of the important indicators for measuring the human body's aerobic exercise capacity.

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

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

[0443] Optionally, in some possible implementations, S is 2. That is, if the user's VO2 max increases by 2 levels, the user's exercise capacity is considered to have improved, thus excluding the possibility of an accidental increase of 1 level.

[0444] See also Figure 28 For example, if the user's VO2 max improves by level S, such as level 2, then step S202 can be executed. Otherwise, the current exercise capacity improvement detection can be exited, and step S201 can be executed again when the conditions for the next detection are met.

[0445] Optionally, the frequency at which the mobile phone 100 performs step S201, i.e., the operation of detecting whether the user's maximum oxygen uptake has increased to level S, can be once a day.

[0446] Furthermore, it should be noted that, typically, the number of times a user's exercise capacity improves within the corresponding cycle of a single exercise plan is limited; that is, situations where VO2 max increases by level S are not frequent. Therefore, in some possible implementations, the phone could be configured to stop detecting VO2 max increases after only one instance of level S improvement.

[0447] S202 calculates pace grading based on an individual's best running performance over the past N months.

[0448] Optionally, personal best running times over N months can be obtained through the sports and health app.

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

[0450] Optionally, in some possible implementations, N is 1. That is, the pace class is calculated based on the user's best personal running performance in the most recent month.

[0451] It should be noted that VO2 max varies among users of different genders and ages. Therefore, when calculating pace levels based on a user's best running performance within the past month, the user's pace level can be determined by considering their gender and age, in conjunction with the VO2 max reference table. This application does not provide specific details about the VO2 max reference table.

[0452] S203 updates users' running plans based on the latest pace classifications.

[0453] Optionally, the user's running plan will not be updated if the latest pace rating does not improve. That is, a pop-up window will not appear on the interface. Figure 29 The window shown is 10d-9.

[0454] Optionally, if the latest pace ratings have been improved, a pop-up window can appear on the 10d interface. Figure 29 The window shown is 10d-9. When the user clicks the "Close" option in window 10d-9, the mobile phone 100 will respond to the operation by closing window 10d-9 without adjusting the current exercise plan; that is, the user will continue training according to the existing exercise plan. When the user clicks the "Adjust Plan" option, the mobile phone 100 will respond to the operation by closing window 10d-9 and adjusting the exercise plan corresponding to the remaining cycle according to the latest pace classification.

[0455] Optionally, the adjusted exercise plan will take effect next week, meaning that the classes starting next week will be updated to correspond to the adjusted exercise plan.

[0456] Furthermore, it should be noted that for adjustments to the exercise plan triggered by improved athletic ability, the original cycle of the exercise plan remains unchanged. For example, if the user's initial exercise plan corresponds to a 6-week cycle, and adjustments are made midway due to improved athletic ability, the overall cycle of the exercise plan remains 6 weeks. That is, the end time of the adjusted exercise plan is the same as the end time of the original exercise plan; only the courses between the adjusted and the end time have changed, such as changes in exercise intensity.

[0457] Considering the adjustment of the exercise plan triggered by improved athletic ability, the total training period remains unchanged. Therefore, in some possible implementations, if the latest pace classification has improved, it can be further determined whether the remaining training period is greater than or equal to W weeks.

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

[0459] Optionally, in one possible implementation, W is 2. That is, only when the remaining training period is greater than or equal to 2 weeks will a pop-up window 10d-9 appear in interface 10d to remind the user that their athletic ability has improved and provide an "Adjust Plan" option to allow for adjustments to the training plan. Otherwise, if the remaining training period is less than 2 weeks (the remaining time is too short for adjusting the training plan to significantly improve subsequent abilities), the pop-up window in interface 10d will only remind the user that their athletic ability has improved, but will not provide an "Adjust Plan" option.

[0460] Therefore, it is possible to adjust the exercise plan midway based on the changes in the user's exercise ability within the corresponding cycle of the exercise plan, and to provide exercise guidance and 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 use running, an aerobic exercise, as an example. In practical applications, the large-cycle exercise capacity improvement and adjustment plan is also applicable to other types of exercise, such as strength training (e.g., weight training). For example, for strength training, strength tests can be conducted regularly. If the strength level corresponding to the strength test results shows an improvement, the exercise plan can be adjusted according to the latest strength level, changing the remaining time of the class. Otherwise, no adjustment is made.

[0462] Scenario 5: Adjustment plan for discrepancies in large-cycle execution rates

[0463] Taking running as an example, see Figure 30For example, the adjustment scheme for the large cycle execution rate of mobile phone 100 may include steps S301 to S306.

[0464] S301: Is the user currently maintaining health, or starting out / improving performance?

[0465] Specifically, if the user's initial exercise plan is for maintaining health, the mobile phone 100 can execute step S302. If the user's initial exercise plan is for beginners / performance improvement, the mobile phone 100 can execute step S306.

[0466] S302, In the most recent week W1, were there any courses with a core training day or more that did not meet the target?

[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 implementations, W1 is 2 and W2 is also 2. The specific value can be determined based on the user's motion goals.

[0470] Understandably, in an exercise plan, the core curriculum has a greater impact on athletic ability. Therefore, when judging whether the execution rate is not up to standard, that is, whether the training on the core training day has met the standard, the judgment is made.

[0471] Core training days are those days when core courses are scheduled.

[0472] In this context, "course training meeting the standard" means that the ratio of the actual training load generated by the user to the training load required by the course is greater than or equal to a preset threshold, such as 50%. Therefore, "course training not meeting the standard" means that the ratio of the actual training load generated by the user to the training load required by the course is less than the preset threshold (such as 50%).

[0473] Alternatively, in some possible implementations, the reason for the training course failing to meet the standards may be due to absences.

[0474] Alternatively, in some possible implementations, a user's failure to complete the core course training or inadequate training can be considered as absence from class.

[0475] Optionally, in some possible implementations, reminders can be issued from two perspectives regarding absences: a short-term (daily detection, with no further detection for the week after one absence) and a long-term (weekly detection).

[0476] Scenario 1.1 (Missing classes due to failure to take core courses during a short period):

[0477] Optionally, if a user misses one core course for the first time this week, a pop-up window can be displayed on the interface to prompt the user with exercise guidance suggestions such as "Complete the make-up training this week; failure to do so may delay the exercise plan or risk the achievement of the goal."

[0478] Scenario 1.2 (Core course training was conducted within a short period, but the training did not meet the standards):

[0479] Optionally, in one possible implementation, after the completion of this core course training, the recorded training data can be used to determine whether the training has met the standards. If not, a pop-up window on the interface can prompt the user with a message such as "This training did not meet the standards. In the next training session, please pay attention to strictly following the course requirements, otherwise it may cause delays in the exercise plan or risk to achieving the goal."

[0480] Scenario 2.1 (Training for week W1-1 has been completed)

[0481] Taking W1 as an example, optionally, if a week of training has already been completed and no issues of situation 1.1 or 1.2 occurred during that week, no prompt will be displayed. If issues of situation 1.1 or 1.2 occur during that week, a prompt may appear on interface 10d. Figure 31 The window shown is 10d-10.

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

[0483] Optionally, when the user clicks the "Adjust Plan" option in window 10d-10, the mobile phone 100 responds to the operation and regenerates the exercise plan. Specifically, the exercise plan can be regenerated when the total number of untrained weeks is greater than or equal to W5 weeks. For example, in this case, the end time of the generated exercise plan can be the same as the initial exercise plan.

[0484] Alternatively, in another possible implementation, when the number of untrained full weeks is less than W5 weeks, the "Adjust Plan" option may not be provided in window 10d-10. That is, training will still proceed according to the initial exercise plan.

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

[0486] Case 2.2 (Training of W1 weeks or more has been completed)

[0487] Taking W1 as an example, optionally, if the currently completed training course is greater than or equal to 2 weeks, and no issues in situation 1.1 or 1.2 occur during these 2 weeks, no prompt will be displayed. If issues in situation 1.1 or 1.2 occur during these 2 weeks, a prompt will appear on interface 10d, for example... Figure 31 The window shown is 10d-10.

[0488] Optionally, if the user clicks the "Postpone" option in window 10d-10, the mobile phone 100 will respond to the operation and postpone the course starting from the week in which the first core course was missed.

[0489] Optionally, when the user clicks the "Adjust Plan" option in window 10d-10, the mobile phone 100 responds to the operation and adjusts the exercise plan according to the adjustment plan logic in situation 2.1.

[0490] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0491] S303: Will the user confirm the postponement or adjust the plan?

[0492] Optionally, if the user clicks the "Postpone" option in window 10d-10, step S304 is executed, and the mobile phone 100 responds to the operation by postponing the course starting from the week in which the first core course was missed. That is, the course content remains the same after the postponement, but the corresponding cycle of the exercise plan becomes longer.

[0493] Optionally, if the user clicks the "Adjust Plan" option in window 10d-10, step S305 is executed, and the mobile phone 100 responds to this operation by regenerating the exercise plan. For details on regenerating the exercise plan, please refer to cases 2.1 and 2.2 above, which will not be repeated here.

[0494] S304, the extension will begin from the week in which the first core training day was not met.

[0495] S305, regenerate the subsequent running plan.

[0496] S306, in the last 3 weeks, have you had at least 4 core training days that did not meet the training target?

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

[0498] Understandably, the values ​​of W3 and W4 can be the same or different.

[0499] Optionally, in some possible implementations, W3 is 2 and W4 is also 3. The volume can be determined based on the user's motion goals.

[0500] See also Figure 30 For example, if there are at least four core training days in the most recent W3 weeks that have not met the training target, a pop-up window can be displayed in interface 10d to provide corresponding exercise guidance suggestions, following the logic of situation 1.1, 1.2, 2.1, or 2.2 described above. This embodiment of the application still uses a pop-up window in interface 10d as an example... Figure 31 The window shown is 10d-10 as an example.

[0501] Therefore, the system can adjust the exercise plan midway through the cycle based on the user's execution rate, and provide exercise guidance and suggestions, enabling users to exercise more effectively.

[0502] Furthermore, it should be noted that in some possible implementations, scenarios 1, 2, and 3 related to the aforementioned short-cycle exercise plan adjustments, as well as scenarios 4 and 5 related to the long-cycle exercise plan adjustments, may coexist. The absence reminders, performance improvement reminders, training overload reminders, non-compliance rate reminders, various questionnaire feedback pop-ups, and the three short-cycle scenarios (scenario 1, scenario 2, and scenario 3) that appear in these five scenarios can be displayed as pop-up reminders according to a set priority.

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

[0504] The priority of the three small-cycle scenarios is as follows, according to the above embodiment: fatigue reminder for scenario 1 > physiological cycle reminder for scenario 2 > weather and environment reminder for scenario 3, and only one scenario is reminded.

[0505] This enables adjustments to exercise plans when multiple scenarios occur concurrently, resulting in more reasonable exercise guidance and recommendations, and ensuring a better user experience.

[0506] Furthermore, it should be noted that in the exercise plan adjustment method provided in this application embodiment, users can randomly select from all the courses displayed in the interface 10d for training as needed.

[0507] For example, if today is the 13th and there are courses on the 15th, users can choose to train on the course on the 15th instead of the course on the 13th.

[0508] Accordingly, when a user completes the training for day 15 on day 13, the training for day 15 can be displayed as completed (checked in).

[0509] Accordingly, if a user does not complete the training session on the 13th, they can make up for the 14th session on the 14th (when there are no scheduled sessions), or at another time during the week. After completing the make-up session for the 13th, the session for the 13th will also show as completed.

[0510] In other words, users can make up for missed lessons at any time during the week, or complete other lessons that were not practiced this week in advance.

[0511] Understandably, to prevent users from over-exercising, the courses for next week and last week can be set so that users cannot select them, thus preventing users from over-exercising within a week.

[0512] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0513] In addition, it should be noted that, in order to better improve the user experience, the exercise plan mentioned in this application embodiment can have the following termination methods.

[0514] Method 1: The exercise plan will automatically end on the last day.

[0515] Method 2: After the user completes the last training session of the final training week, a pop-up window provides an option to close the program, allowing the user to choose to end it. This way, the user can end the exercise plan early without having to wait until the last day.

[0516] Method 3: An entry to terminate the exercise plan can be provided in the menu list, which allows users to easily end the exercise plan at any stage.

[0517] It should be understood that the above description is merely an example provided to better understand the technical solution of this embodiment, and is not intended as the only limitation on this embodiment.

[0518] Furthermore, it should be noted that the embodiments of this application mainly take the running scenario as an example. In practical applications, the exercise plan adjustment method provided by the embodiments of this application can also be applied to other sports scenarios, such as cycling, swimming, mountain climbing, etc., and this application does not limit them.

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

[0520] Furthermore, it is understood that, in order to achieve the aforementioned functions, the electronic device includes hardware and / or software modules corresponding to the execution of each function. Based on the algorithmic steps of the various examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in a hardware-driven or software-driven manner 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 conjunction with the embodiments, but such implementation should not be considered beyond the scope of this application.

[0521] Furthermore, it should be noted that, in practical application scenarios, the motion plan adjustment methods provided in the above embodiments, implemented by electronic devices, can also be executed by a chip system included in the electronic device. This chip system may include a processor. The chip system can be coupled to a memory, enabling it to call computer programs stored in the memory during runtime to implement the steps executed by the electronic device. The processor in this chip system can be an application processor or a non-application processor.

[0522] In addition, this application embodiment also provides a computer-readable storage medium storing computer instructions. When the computer instructions are executed on an electronic device, the electronic device performs the above-mentioned related method steps to implement the exercise plan adjustment method in the above embodiment.

[0523] In addition, this application also provides a computer program product that, when run on an electronic device, causes the electronic device to perform the above-mentioned related steps to implement the exercise plan adjustment method in the above embodiments.

[0524] In addition, embodiments of this application also provide a chip (which may also be a component or module), which may include one or more processing circuits and one or more transceiver pins; wherein the transceiver pins and the processing circuits communicate with each other through internal connection paths, and the processing circuits execute the above-mentioned related method steps to implement the motion plan adjustment method in the above embodiments, so as to control the receiving pin to receive signals and control the transmitting pin to transmit signals.

[0525] Furthermore, as can be seen from the above description, the electronic devices, computer-readable storage media, computer program products, or chips provided in the embodiments of this application are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0526] To illustrate the beneficial effects of the exercise plan adjustment method provided in the embodiments of this application in detail, a comparison with related technologies is provided below.

[0527] Compared to current practices where exercise plans cannot be adjusted once formulated, the exercise plan adjustment method provided in this application not only offers guidance on extending and / or adjusting exercise plans from a long-term perspective, allowing for extensions or adjustments to the initial plan based on user choices, but also provides reasonable exercise guidance before the user begins exercise from a short-term perspective, preventing injuries caused by physical conditions or weather. In other words, it can achieve... Figure 32 The various exercise guidance suggestions shown in the document enable users to exercise more reasonably according to their exercise plans, thereby achieving their desired goals.

[0528] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for adjusting an exercise plan, characterized in that, Applied to electronic devices, the method includes: Obtain the user's first exercise plan, which is the 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 high training intensity. For each training cycle, if there are any absences in the core courses during the training cycle, a first exercise guidance suggestion is made. The first exercise guidance suggestion does not include the option corresponding to the postponement suggestion or the option corresponding to the adjustment of the exercise plan. For the first exercise plan including multiple training cycles, if N training cycles have been completed and there are any absences in the completed N training cycles, a second exercise guidance suggestion is made. 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 the adjustment of the exercise plan, where N is an integer greater than 0. When the second exercise guidance suggestion includes the option corresponding to the postponement suggestion and the option corresponding to the adjustment of the exercise plan, the second exercise plan is generated when the user clicks the option corresponding to the adjustment of the exercise plan. Acquire indicator data, physiological cycle data, and weather data used to calculate fatigue levels; During the user's training according to the first exercise plan or the second exercise plan, a fourth exercise guidance suggestion is made based on the fatigue level, the physiological cycle data, and the weather data. The fourth exercise guidance suggestion is an exercise guidance suggestion corresponding to the fatigue level, or an exercise guidance suggestion corresponding to the physiological cycle data, or an exercise guidance suggestion corresponding to the weather data. Specifically, the exercise guidance suggestion with the highest priority is selected as the fourth exercise guidance suggestion, following the order that the exercise guidance suggestion corresponding to the fatigue level has a higher priority than the exercise guidance suggestion corresponding to the physiological cycle data, and the exercise guidance suggestion corresponding to the physiological cycle data has a higher priority than the exercise guidance suggestion corresponding to the weather data.

2. The method according to claim 1, characterized in that, For each training cycle, if there are absences in the core course within the training cycle, a first exercise guidance suggestion is made, including: For each training cycle, the system checks daily to determine if there are any missed sessions. Upon first detection of absence, the first exercise guidance suggestion is made, and absence detection for the training cycle is stopped.

3. The method according to claim 1 or 2, characterized in that, The absences mentioned include: The core courses were not trained during the training period; or, The core courses were trained during the training period, but the training did not meet the required standards.

4. The method according to claim 3, characterized in that, If the core course is not trained during the training cycle, the first exercise guidance suggestion is used to prompt the user to make up for the untrained core course. If the core curriculum has been trained within the training cycle, but the training results are not met, the first exercise guidance suggestion is used to remind the user to strictly follow the requirements for the core curriculum that has not yet started training within the training cycle.

5. The method according to claim 1, characterized in that, Regarding the multiple training cycles included in the first exercise plan, if N training cycles have been completed, and there are any absences in the completed N training cycles, a second exercise guidance suggestion is made, including: For the first exercise plan including multiple training cycles, if N training cycles have been completed and there are any missed training cycles, determine the number of remaining training cycles of the first exercise plan. If the number of remaining training cycles is greater than or equal to the first threshold, a second exercise guidance suggestion is made, including the option corresponding to the postponement suggestion and the option corresponding to the adjustment of the exercise plan; If the remaining number of training cycles is less than the first threshold, a second exercise guidance suggestion is made, which includes the option corresponding to the postponement suggestion but does not include the option corresponding to the adjustment of 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, when the user clicks the option corresponding to the postponement suggestion, the first exercise plan will be postponed by 1 training cycle. When N is greater than 1, when the user clicks the option corresponding to the postponement suggestion, the training cycle will be postponed starting from the first missed class.

7. The method according to claim 1 or 5, characterized in that, The second exercise plan is an adjusted exercise plan, which includes training cycles that were not conducted in the first exercise plan, and the training courses for each untrained training cycle have been adjusted.

8. The method according to claim 7, characterized in that, The first exercise plan or the second exercise plan is an exercise plan for running; The method further includes: During the user's training according to the first exercise plan or the second exercise plan, the user's maximum oxygen uptake is obtained; When the maximum oxygen uptake is increased to level S, the pace grade is calculated based on the user's best personal running performance in the most recent M months, where S is an integer greater than 1 and M is an integer greater than 0. Based on the calculated pace level, a third exercise guidance suggestion is made, which may include the option corresponding to the postponement suggestion, or the third exercise guidance suggestion may include the option corresponding to the postponement suggestion and the option corresponding to the adjustment of the exercise plan.

9. The method according to claim 8, characterized in that, If the third exercise guidance suggestion includes options corresponding to the postponement suggestion and options corresponding to the adjustment of the exercise plan, the method further includes: When the user clicks the option corresponding to the adjustment exercise plan, a third exercise plan is generated. The third exercise plan is the adjusted exercise plan. The third exercise plan includes the training cycles that were not trained in the first exercise plan / second exercise plan. The training courses of each training cycle that was not trained have been adjusted.

10. The method according to claim 9, characterized in that, The method further includes: Acquire indicator data, physiological cycle data, and weather data used to calculate fatigue levels; During the user's training according to the third exercise plan, a fourth exercise guidance suggestion is made based on the fatigue level, the physiological cycle data, and the weather data. The fourth exercise guidance suggestion is an exercise guidance suggestion corresponding to the fatigue level, or an exercise guidance suggestion corresponding to the physiological cycle data, or an exercise guidance suggestion corresponding to the weather data.

11. 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, which, when executed by the processor, cause the electronic device to perform the exercise plan adjustment method as described in any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that, The method includes a computer program that, when run on an electronic device, causes the electronic device to perform the exercise plan adjustment method as described in any one of claims 1 to 10.

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