WO2023025039A1 - 训练计划的生成方法、装置、电子设备及可读存储介质 - Google Patents

训练计划的生成方法、装置、电子设备及可读存储介质 Download PDF

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Publication number
WO2023025039A1
WO2023025039A1 PCT/CN2022/113395 CN2022113395W WO2023025039A1 WO 2023025039 A1 WO2023025039 A1 WO 2023025039A1 CN 2022113395 W CN2022113395 W CN 2022113395W WO 2023025039 A1 WO2023025039 A1 WO 2023025039A1
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Prior art keywords
training
plan
user
course
data
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PCT/CN2022/113395
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English (en)
French (fr)
Inventor
姜金
林骏豪
占堂海
刘亮
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华为技术有限公司
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Publication of WO2023025039A1 publication Critical patent/WO2023025039A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9035—Filtering based on additional data, e.g. user or group profiles

Definitions

  • the present application belongs to the technical field of data processing, and in particular relates to a training plan generation method, device, electronic equipment and readable storage medium.
  • the existing training plan generation technology generally pre-sets a fixed training plan template, establishes a mapping relationship between personal information and training plan templates, and then collects the user's personal information, such as height, weight, and age, based on the collected personal information. information and the mapping relationship to determine the corresponding training plan.
  • the prior art only determines the training plan according to the user's personal information and a fixed training plan template, and the method is single, which reduces the accuracy and effectiveness of the training plan.
  • the embodiment of the present application provides a training plan generation method, adjustment method, generation device, adjustment device, electronic equipment and readable storage medium, which can effectively improve the accuracy and effectiveness of the training plan.
  • the embodiment of the present application provides a wireless connection method, including:
  • a training direction of the user is determined based on the athlete type, and a training plan matching the training direction is generated.
  • the user's athlete type can be determined by acquiring the user's exercise data in the historical exercise process, and based on the athlete type identification, the corresponding training direction of the user during training can be obtained, and the training direction can be generated and trained.
  • a training plan matching the direction can generate a training plan adapted to the user's athletic ability.
  • the training plan generated based on individual parameters may not match the user's athletic ability, while the exercise data collected by the user in historical exercise activities can reflect the user's actual athletic ability , determine the user's athlete type based on the user's performance in historical sports, which can improve the matching degree between the training plan and the user's actual athletic ability, so that the generated training plan can guide the user to carry out sports training in a more targeted manner, improving the The accuracy of the generated training plan.
  • the acquired multiple motion data includes motion data of multiple sports items, and then determining the athlete type corresponding to the user based on the multiple motion data includes:
  • the athlete type of the user is determined based on the normalized parameters of the respective sports.
  • the determining the best sports performance corresponding to the sports item according to the sports data associated with each of the sports items includes:
  • the ideal heart rate is specifically the heart rate corresponding to the user's full exercise state
  • the best sports performance corresponding to the sports item is determined.
  • the acquisition of multiple motion data of the user includes:
  • the athletic data is obtained from the goal data source.
  • the method further includes:
  • a training report corresponding to the user is displayed; the training report includes the training plan and a descriptive paragraph about the athlete type and the training direction.
  • the determining the user's training direction based on the athlete type, and generating a training plan matching the training direction includes:
  • the training time is determined based on the period duration of the training phase
  • the training plan is generated according to the training courses corresponding to the training time of all the training stages.
  • the determining the course category associated with the training phase, and configuring a training course belonging to the course category for each training time in the training phase includes:
  • the training course framework is used to determine the training time included in the training stage and each of the The difficulty level of the course corresponding to the training time;
  • the determining the period duration of each pre-divided training phase in the preset plan template according to the training direction includes:
  • the plan template corresponding to the user's training purpose;
  • the training purpose is preset by the user;
  • the plan template includes a plurality of pre-divided training stages;
  • the stage cycle duration of the training stage is determined according to the duration ratio of the training stage and the preset total training duration.
  • the method before the acquisition of the plan template corresponding to the training purpose of the user, the method further includes:
  • the training purpose setting interface includes at least one purpose setting area for sports items;
  • the training purpose is obtained based on the target value of each of the sports items.
  • the method further includes:
  • the training plan is adjusted according to the subjective motion parameters to generate an adjusted training plan.
  • the method before generating the subjective parameter collection page if it is detected that any training course in the training plan has been completed, the method further includes:
  • the said training plan is adjusted according to said subjective motion parameters to generate an adjusted training plan, including:
  • the training plan is adjusted according to the training pressure value and the subjective exercise parameter to generate an adjusted training plan.
  • the obtaining the corresponding training pressure value when the user performs training based on any training course includes:
  • the training pressure value corresponding to the training course is determined based on the real-time data.
  • the adjusting the training plan according to the training pressure value and the subjective exercise parameter to generate an adjusted training plan includes:
  • the plan adjustment direction is determined based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment triggering moment;
  • the training course in the training plan after the adjustment trigger moment is adjusted to obtain the adjusted training plan.
  • the embodiment of the present application provides a device for generating a training plan, including:
  • a motion data acquisition unit configured to obtain multiple motion data of the user
  • an athlete type determining unit configured to determine an athlete type corresponding to the user based on a plurality of the exercise data
  • a training plan generating unit configured to determine the user's training direction based on the athlete type, and generate a training plan matching the training direction.
  • the plurality of acquired motion data includes motion data of multiple sports items
  • the player type determination unit includes:
  • a best sports performance determining unit configured to determine the best sports performance corresponding to the sports item according to the sports data associated with each of the sports items
  • a normalization parameter determination unit which imports the best sports performance into the normalization algorithm corresponding to the sports item, and determines the normalization parameter corresponding to the sports item;
  • An athlete type identification unit configured to determine the athlete type of the user based on the normalized parameters of each sport.
  • the unit for determining the best sports performance includes:
  • An ideal heart rate determination unit configured to determine the ideal heart rate corresponding to the exercise; the ideal heart rate is specifically the heart rate corresponding to the user's full exercise state;
  • An intensity coefficient determining unit configured to determine an intensity coefficient associated with the exercise data according to the actual heart rate and the ideal heart rate in the exercise data
  • the best sports performance calculation unit is configured to determine the best sports performance corresponding to the sports item according to the intensity coefficient and the actual sports performance.
  • the motion data acquisition unit includes:
  • a movement data authorization interface generating unit configured to generate a movement data authorization interface including at least one optional data source
  • a confirmation operation response unit configured to determine a target data source from the optional data sources in response to the user's confirmation operation based on the motion data authorization interface
  • a data acquisition unit configured to acquire the motion data from the target data source based on the authorization request.
  • the training plan generation device further includes:
  • the training report display unit is configured to display the training report corresponding to the user; the training report includes the training plan and descriptive paragraphs about the athlete type and the training direction.
  • the training plan generation unit includes:
  • a stage cycle duration determination unit configured to determine the stage cycle duration of each pre-divided training stage in the preset plan template according to the training direction;
  • a training course determination unit configured to determine the course category associated with the training phase, and configure a training course belonging to the course category for each training time in the training phase; the training time is based on the training period of the training phase The cycle duration of the above-mentioned stages is determined;
  • the training course packaging unit is configured to generate the training plan according to the training courses corresponding to the training time of all the training stages.
  • the training course determination unit includes:
  • a training category library configuration unit configured to configure a training category library for the training phase based on the course category associated with the training phase
  • the training course framework determination unit is used to determine the training course framework corresponding to the training stage according to the period duration of the training stage and the training category library; the training course framework is used to determine the training courses contained in the training stage.
  • the training course selection unit is configured to select the training course matching the difficulty level of the course for each training time from the training category library.
  • the phase cycle duration determination unit includes:
  • a plan template acquiring unit configured to acquire the plan template corresponding to the training purpose of the user; the training purpose is preset by the user; the plan template includes a plurality of pre-divided training stages;
  • a duration ratio determining unit configured to determine the duration ratio of each of the training stages based on the training direction
  • the total training duration allocation unit is configured to determine the period duration of the training phase according to the duration ratio of the training phase and the preset total training duration.
  • the training plan generation device further includes:
  • a setting interface display unit configured to generate a training purpose setting interface; the training purpose setting interface includes a purpose setting area for at least one sport item;
  • a setting operation response unit configured to determine the target value corresponding to each of the sports items in response to the user's setting operation in each of the target setting areas
  • the training purpose determining unit is configured to obtain the training purpose based on the target value of each of the sports items.
  • the device for generating a training plan further includes:
  • a subjective exercise parameter determination unit configured to generate a subjective parameter collection page if it is detected that any training course in the training plan has been completed, so as to determine according to the feedback operation initiated by the user on the subjective parameter collection page The user's subjective exercise parameters corresponding to any of the training courses;
  • a training plan adjustment unit configured to adjust the training plan according to the subjective motion parameters, and generate an adjusted training plan.
  • the device for generating a training plan further includes:
  • a training pressure value obtaining unit configured to obtain the corresponding training pressure value when the user performs training based on any training course in the training plan
  • the training plan adjustment unit is specifically configured to adjust the training plan according to the training pressure value and the subjective motion parameters, and generate an adjusted training plan.
  • the training pressure value acquisition unit includes:
  • a real-time data acquisition unit configured to acquire corresponding real-time data when the user performs training based on any training course in the training plan
  • a real-time data conversion unit configured to determine the training pressure value corresponding to the training course based on the real-time data.
  • the training plan adjustment unit includes:
  • a plan adjustment direction determination unit configured to determine a plan adjustment direction based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment trigger time when the preset adjustment trigger time is reached;
  • a training course adjustment unit configured to adjust the training course in the training plan after the adjustment trigger moment based on the plan adjustment direction, to obtain the adjusted training plan.
  • the embodiment of the present application provides a method for generating a training plan, including:
  • the training time is determined based on the period duration of the training phase
  • the training plan is generated according to the training courses corresponding to the training time of all the training stages.
  • the determining the course category associated with the training phase, and configuring a training course belonging to the course category for each training time in the training phase includes:
  • the training course framework is used to determine the training time included in the training stage and each of the The difficulty level of the course corresponding to the training time;
  • the determining the period duration of each pre-divided training phase in the preset plan template according to the training direction of the user includes:
  • the plan template corresponding to the user's training purpose;
  • the training purpose is preset by the user;
  • the plan template includes a plurality of pre-divided training stages;
  • the stage cycle duration of the training stage is determined according to the duration ratio of the training stage and the preset total training duration.
  • the method before the acquisition of the plan template corresponding to the training purpose of the user, the method further includes:
  • the training purpose setting interface includes at least one purpose setting area for sports items;
  • the training purpose is obtained based on the target value of each of the sports items.
  • the training plan is adjusted according to the subjective motion parameters to generate an adjusted training plan.
  • the method before generating the subjective parameter collection page if it is detected that any training course has been completed, the method further includes:
  • the said training plan is adjusted according to said subjective motion parameters to generate an adjusted training plan, including:
  • the training plan is adjusted according to the training pressure value and the subjective exercise parameter to generate an adjusted training plan.
  • the obtaining the corresponding training pressure value when the user performs training based on any training course includes:
  • the training pressure value corresponding to the training course is determined based on the real-time data.
  • the adjusting the training plan according to the training pressure value and the subjective exercise parameter to generate an adjusted training plan includes:
  • the plan adjustment direction is determined based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment triggering moment;
  • the training course in the training plan after the adjustment trigger moment is adjusted to obtain the adjusted training plan.
  • the embodiment of the present application provides a device for generating a training plan, including:
  • a stage cycle duration determination unit configured to determine the stage cycle duration of each pre-divided training stage in the preset plan template according to the user's training direction
  • a training course determination unit configured to determine the course category associated with the training phase, and configure a training course belonging to the course category for each training time in the training phase; the training time is based on the training period of the training phase The cycle duration of the above-mentioned stages is determined;
  • the training course packaging unit is configured to generate the training plan according to the training courses corresponding to the training time of all the training stages.
  • the training course determination unit includes:
  • a training category library configuration unit configured to configure a training category library for the training phase based on the course category associated with the training phase
  • the training course framework determination unit is used to determine the training course framework corresponding to the training stage according to the period duration of the training stage and the training category library; the training course framework is used to determine the training courses contained in the training stage.
  • the training course selection unit is configured to select the training course matching the difficulty level of the course for each training time from the training category library.
  • the phase cycle duration determination unit includes:
  • a plan template acquiring unit configured to acquire the plan template corresponding to the training purpose of the user; the training purpose is preset by the user; the plan template includes a plurality of pre-divided training stages;
  • a duration ratio determining unit configured to determine the duration ratio of each of the training stages based on the training direction
  • the total training duration allocation unit is configured to determine the period duration of the training phase according to the duration ratio of the training phase and the preset total training duration.
  • the training plan generation device further includes:
  • a setting interface display unit is used to generate a training purpose setting interface; the training purpose setting interface includes at least one purpose setting area for sports items;
  • a setting operation response unit configured to determine the target value corresponding to each of the sports items in response to the user's setting operation in each of the target setting areas
  • the training purpose determining unit is configured to obtain the training purpose based on the target value of each of the sports items.
  • the device for generating a training plan further includes:
  • a subjective exercise parameter determination unit configured to generate a subjective parameter collection page if it is detected that any training course in the training plan has been completed, so as to determine according to the feedback operation initiated by the user on the subjective parameter collection page The user's subjective exercise parameters corresponding to any of the training courses;
  • a training plan adjustment unit configured to adjust the training plan according to the subjective motion parameters, and generate an adjusted training plan.
  • the device for generating a training plan further includes:
  • a training pressure value obtaining unit configured to obtain the corresponding training pressure value when the user performs training based on any training course in the training plan
  • the training plan adjustment unit is specifically configured to adjust the training plan according to the training pressure value and the subjective motion parameters, and generate an adjusted training plan.
  • the training pressure value acquisition unit includes:
  • a real-time data acquisition unit configured to acquire corresponding real-time data when the user performs training based on any training course in the training plan
  • a real-time data conversion unit configured to determine the training pressure value corresponding to the training course based on the real-time data.
  • the training plan adjustment unit includes:
  • a plan adjustment direction determination unit configured to determine a plan adjustment direction based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment trigger time when the preset adjustment trigger time is reached;
  • the training course adjustment unit is configured to adjust the training course in the training plan after the adjustment trigger moment based on the plan adjustment direction to obtain the adjusted training plan.
  • the embodiment of the present application provides a method for adjusting a training plan, including:
  • a subjective parameter collection page is generated to determine the user's corresponding training course for the arbitrary training course according to the feedback operation initiated by the user in the subjective parameter collection page.
  • the training plan is adjusted according to the subjective motion parameters to generate an adjusted training plan.
  • the method before generating the subjective parameter collection page if it is detected that any training course in the training plan has been completed, the method further includes:
  • the said training plan is adjusted according to said subjective motion parameters to generate an adjusted training plan, including:
  • the training plan is adjusted according to the training pressure value and the subjective exercise parameter to generate an adjusted training plan.
  • the obtaining the corresponding training pressure value when the user performs training based on any training course includes:
  • the training pressure value corresponding to the training course is determined based on the real-time data.
  • the adjusting the training plan according to the training pressure value and the subjective exercise parameter to generate an adjusted training plan includes:
  • the plan adjustment direction is determined based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment triggering moment;
  • the training course in the training plan after the adjustment trigger moment is adjusted to obtain the adjusted training plan.
  • the embodiment of the present application provides a device for adjusting a training plan, including:
  • the subjective motion parameter determination unit is used to generate a subjective parameter collection page if it is detected that any training course in the training plan has been completed, so as to determine the user's preference for Subjective exercise parameters corresponding to any of the training courses;
  • a training plan adjustment unit configured to adjust the training plan according to the subjective motion parameters, and generate an adjusted training plan.
  • the device for adjusting the training plan further includes:
  • a training pressure value obtaining unit configured to obtain the corresponding training pressure value when the user performs training based on any training course in the training plan
  • the training plan adjustment unit is specifically configured to adjust the training plan according to the training pressure value and the subjective motion parameters, and generate an adjusted training plan.
  • the training pressure value acquisition unit includes:
  • a real-time data acquisition unit configured to acquire corresponding real-time data when the user performs training based on any training course in the training plan
  • a real-time data conversion unit configured to determine the training pressure value corresponding to the training course based on the real-time data.
  • the training plan adjustment unit includes:
  • a plan adjustment direction determination unit configured to determine a plan adjustment direction based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment trigger time when the preset adjustment trigger time is reached;
  • the training course adjustment unit is configured to adjust the training course in the training plan after the adjustment trigger moment based on the plan adjustment direction to obtain the adjusted training plan.
  • an embodiment of the present application provides an electronic device, a memory, a processor, and a computer program stored in the memory and operable on the processor, wherein the processor executes the The computer program realizes the method for generating the training plan described in any one of the first aspect or the third aspect above, or the method for adjusting the training plan described in any one of the fifth aspect.
  • an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and it is characterized in that, when the computer program is executed by a processor, the above-mentioned first or second aspect is implemented.
  • the embodiment of the present application provides a computer program product, which, when the computer program product is run on the electronic device, causes the electronic device to execute the training plan generation method described in any one of the first aspect or the third aspect , or the method for adjusting the training plan described in any one of the fifth aspect.
  • an embodiment of the present application provides a chip system, including a processor, the processor is coupled to a memory, and the processor executes a computer program stored in the memory, so as to implement any one of the first aspect or the third aspect.
  • Fig. 1 is a schematic diagram of existing training plan generation
  • Fig. 2 is the implementation flowchart of the generation method of the training program provided by an embodiment of the present application
  • Fig. 3 is a schematic diagram of acquisition of motion data provided by an embodiment of the present application.
  • Fig. 4 is a schematic diagram of an information input interface provided by an embodiment of the present application.
  • Fig. 5 is a schematic diagram of the authorization process of motion data provided by an embodiment of the present application.
  • Fig. 6 is a schematic diagram of a running scene provided by an embodiment of the present application.
  • Fig. 7 is a schematic diagram of merging motion data provided by an embodiment of the present application.
  • Fig. 8 is a schematic diagram of calculating the best sports performance provided by an embodiment of the present application.
  • FIG. 9 is a schematic diagram of a normalization algorithm provided by an embodiment of the present application.
  • Fig. 10 is a correspondence diagram of player types provided by an embodiment of the present application.
  • Fig. 11 is a schematic diagram of a training plan display process provided by an embodiment of the present application.
  • Fig. 12 is a schematic diagram of a training plan query provided by an embodiment of the present application.
  • Fig. 13 is an implementation flow chart of a method for generating a training plan provided by another embodiment of the present application.
  • Fig. 14 is a schematic diagram of division of the training phase provided by an embodiment of the present application.
  • Fig. 15 is a schematic diagram of setting the total training duration provided by an embodiment of the present application.
  • Fig. 16 is a schematic diagram of selection of training courses provided by an embodiment of the present application.
  • Fig. 17 is a schematic diagram of a training calendar interface provided by an embodiment of the present application.
  • Fig. 18 is an implementation flow chart of a method for adjusting a training plan provided by an embodiment of the present application.
  • Fig. 19 is a schematic diagram of a subjective parameter collection page provided by an embodiment of the present application.
  • Fig. 20 is a schematic diagram of the adjustment direction of the training plan provided by an embodiment of the present application.
  • Figure 21 is a schematic diagram of the adjustment of the training course provided by an embodiment of the present application.
  • Fig. 22 is a schematic diagram of the adjustment of the training plan provided by an embodiment of the present application.
  • Fig. 23 is a structural block diagram of a device for generating a training plan provided by an embodiment of the present application.
  • Fig. 24 is a structural block diagram of a device for generating a training plan provided by another embodiment of the present application.
  • Fig. 25 is a structural block diagram of a device for generating a training plan provided by an embodiment of the present application.
  • Fig. 26 is a structural block diagram of an adjustment device for a training plan provided by an embodiment of the present application.
  • Fig. 27 is a schematic diagram of the hardware structure of the electronic device provided by the embodiment of the present application.
  • Fig. 28 is a block diagram of the software structure of the electronic device according to the embodiment of the present application.
  • the term “if” may be construed, depending on the context, as “when” or “once” or “in response to determining” or “in response to detecting “.
  • the phrase “if determined” or “if [the described condition or event] is detected” may be construed, depending on the context, to mean “once determined” or “in response to the determination” or “once detected [the described condition or event] ]” or “in response to detection of [described condition or event]”.
  • references to "one embodiment” or “some embodiments” or the like in the specification of the present application means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application.
  • appearances of the phrases “in one embodiment,” “in some embodiments,” “in other embodiments,” “in other embodiments,” etc. in various places in this specification are not necessarily All refer to the same embodiment, but mean “one or more but not all embodiments” unless specifically stated otherwise.
  • the terms “including”, “comprising”, “having” and variations thereof mean “including but not limited to”, unless specifically stated otherwise.
  • Mode 1 generating a training plan by collecting individual parameters of the user.
  • the user can install the application program for generating the training plan on the user's smart phone, and by running the application program for generating the training plan, an input interface for inputting the user's individual parameters can be generated.
  • Fig. 1 shows a schematic diagram of an existing training plan generation. Referring to (a) in Figure 1, in the input interface for inputting individual parameters, the user needs to fill in the following parameter items, namely: age, height, weight, gender and body fat percentage, and based on the relevant data filled in by the user, select The training course corresponding to its physical quality generates a corresponding training plan, as shown in (b) in Fig. 1 .
  • this method only considers the user's individual parameters, that is, determines the corresponding training plan, and the accuracy of the generated training plan is low.
  • the difference in exercise ability between users is also related to multiple factors such as the user's willingness to exercise, exercise goals, and proficiency in related exercises.
  • the above method only considers the differences between individual parameters, and the factors for determining the training plan are too single, so that it cannot effectively and accurately guide the user to carry out training.
  • Mode 2 by collecting whether the user's biological sign indicators during exercise exceed the limit value of the human body, to determine whether the training plan needs to be adjusted.
  • Mode 2 is a further optimization of Mode 1.
  • the user can enter individual parameters on the smartphone, and generate a corresponding training plan through the relevant application program installed on the smartphone, and perform training based on the training plan.
  • the biometric parameters of the user during training based on the training plan can be obtained by wearing a smart watch or a smart bracelet. If it is detected that the user's biological sign parameters exceed the limit value of the human body, for example, during running training, it is detected that the user's heart rate exceeds the normal heart rate range of the human body. In this case, it will be determined that the training plan exceeds the user's tolerance range.
  • Already created training plans are adjusted. This method can optimize and adjust the training plan after an abnormal situation occurs during the training process of the user, so as to improve the matching degree between the training plan and the user.
  • the trigger condition for the adjustment is the user's biometric Adjustments are made only when the characteristic index exceeds the limit of the human body, and often when the biometric index of the user exceeds the limit of the human body, there is already a certain health risk. It can be seen that it is difficult to initiate the above-mentioned optimization adjustment. If the trigger threshold is set by When the threshold of the human body is reduced to a certain preset threshold, frequent adjustments to the training plan may also occur, which reduces the stability of the training plan and is not conducive to the user's arrangement of training exercises.
  • this application provides a method for generating a training plan, by determining the user's training focus, and then obtaining the training course matching the user's training focus from the course database , so as to generate the training plan used by the user to improve the accuracy of the training plan, and in the process of training the user based on the training plan, obtain the user's biometric index and the user's subjective feeling index during the exercise, so as to pass the above two
  • the type of parameters optimizes the training plan, improves the accuracy of the optimization operation, and can also reduce the occurrence of invalid optimization.
  • the execution subject of the process is an electronic device, which includes but is not limited to: computers, smart phones, notebook computers, tablet computers, wearable smart devices (such as smart necklaces, smart watches and smart bracelets) etc.), cloud servers and other devices capable of executing training plan generation tasks.
  • Fig. 2 shows the implementation flow chart of the generation method of the training plan provided by an embodiment of the present application, detailed description is as follows:
  • the electronic device acquires a plurality of motion data of a user.
  • the exercise data can be recorded with one or a combination of the following items: exercise type, exercise duration, peak heart rate, etc. If the exercise type of the exercise is running, the above exercise data may include the exercise distance, vertical climbing height, etc.; if the exercise type of the exercise is high jump, the above exercise data may include the maximum height, success ratio, etc.; if the exercise If the exercise type is cycling, the above exercise data may include: cycling distance, track type, and so on. Therefore, the parameter items included in the exercise data are determined according to the corresponding exercise items.
  • the user can obtain exercise data through the data collection device during exercise.
  • the above-mentioned data collection device for collecting the user's motion data may be the electronic device of this embodiment, or other devices other than the electronic device. In this case, the electronic device may obtain the user's motion data from other devices.
  • FIG. 3 shows a schematic diagram of acquiring exercise data provided by an embodiment of the present application.
  • the electronic device is specifically a user's smart phone.
  • the smart phone can be configured with a sports health application, and the user can record the relevant data of the user in the exercise process through the sports health application during the exercise process, and after the exercise is completed, the smart phone can generate information about this running exercise data.
  • the electronic device can also obtain the user's exercise data from other devices. For example, when a user wears a smart watch for exercise, the smart watch can also record the corresponding exercise data.
  • equipment such as treadmills, smart bracelets, smart necklaces, and heart rate belts can also collect the user's corresponding data when running.
  • the smart phone that is, the electronic device in this embodiment
  • the smart phone can establish a communication connection with the above-mentioned electronic device, and obtain the user's motion data from other electronic devices.
  • the electronic device can also obtain the user's motion data from other third-party devices, wherein the obtained motion data can generate a corresponding motion data list on the electronic device, and the motion data list contains the corresponding data of each motion data.
  • Data source exercise time, exercise items, exercise distance, exercise duration and other information.
  • an information input interface for collecting preset information of the user is generated; the preset information includes user information and training purpose.
  • the electronic device may first acquire preset information, and generate an information input interface for acquiring preset information.
  • the information input interface is specifically used to obtain two types of preset information of the user, namely user information and training purpose.
  • FIG. 4 shows a schematic diagram of an information input interface provided by an embodiment of the present application. (a) in FIG. 4 is used to collect user information of the user, which may include the user's age, height, gender, weight, training time;
  • the above S2001 may also include: generating a training goal setting interface; the training goal setting interface includes a goal setting area of at least one exercise item; The setting operation in the area determines the target value corresponding to each of the sports items; based on the target value of each of the sports items, the training purpose is obtained.
  • the interface of (b) in Figure 4 is used to collect the training purpose of the user.
  • the training purpose can be the sports performance corresponding to different training items, such as the target time of 5 kilometers running.
  • the user can drag the slide in the setting interface Controls to adjust the target value of the corresponding sport.
  • the training plan that the user needs to create is a training plan for running 5 kilometers. Of course, in other scenarios, different training plans can be created.
  • S2002 in response to the input operation based on the information input interface, determine the user information and training purpose of the user; the user information is used to determine the user's athlete type; the training purpose is used to determine the user's training plan.
  • the user can input corresponding user information and training purpose on the information input interface displayed by the electronic device, and determine the athlete type through the user information in subsequent operations.
  • the training purpose can be used to formulate the user's training plan.
  • the training purpose can include the sports performance corresponding to different training items. In this case, after the user sets the sports performance of one training project, the user can be prompted to input the sports performance of the next project. , as shown in (c) in FIG. 4 , until the sports scores of all sports items are set, the operation of the next step is performed.
  • S201 may specifically include the following steps:
  • a sports data authorization interface including at least one optional data source is generated.
  • the electronic device before the electronic device obtains motion data from other devices, it first needs to perform authorization authentication on the operation of obtaining motion data, so the electronic device can generate a motion data authorization interface, which contains information that can be obtained.
  • At least one optional data source for the user's athletic data can be other devices than the electronic device, or an application program installed in the electronic device.
  • an "exercise health" application program installed in the electronic device, which can Record the user's exercise data in real time, and encapsulate the exercise data in a preset format. Since motion data is a kind of private data of the user, obtaining the private data of the user generally requires the authorization of the user. Therefore, the electronic device can generate the above motion data authorization interface to prompt the user to perform authorization authentication for obtaining the motion data.
  • FIG. 5 shows a schematic diagram of an authorization process of motion data provided by an embodiment of the present application.
  • FIG. 5 it is a schematic diagram of a main interface displayed by an electronic device.
  • the user can click the application icon 500 corresponding to "Training Management" in the main interface to start the process of generating the training plan. Since the first step of generating a training plan is to obtain the user's exercise data, when the "Training Management" application is started for the first time, or when the "Training Management” application detects that no training plan has been generated, then A sports data authorization interface can be generated, as shown in (b) in FIG. 5 .
  • the sports data authorization interface contains a data source list 501, which is marked with at least one optional data source, such as “smart watch”, “smart bracelet”, “smart watch” shown in (b) of Figure 5 Treadmill” and "Sports Health” four optional data sources, among which, the first three optional data sources need to be obtained from other devices besides electronic devices, while "Sports Health” can be obtained from locally installed applications obtained from the database associated with the program.
  • the exercise data authorization interface also includes a "confirm authorization" control 502 and a "deny authorization” control 503 .
  • an electronic device may be configured with a wireless communication module.
  • the wireless communication module can be a wireless high-fidelity WIFI module, a Bluetooth module, or a low-power Bluetooth module.
  • the electronic device can search for wireless signals in the scene through the wireless communication module, analyze the connectable devices in the scene by analyzing the wireless signals, and add each connectable device to the above data source list.
  • the user is associated with a user account.
  • the user account has a plurality of optional devices recorded in the user account, and each optional device stores the user's exercise data.
  • the user can log in the same user account on the electronic device.
  • the electronic device can be based on the device information associated with the user account (that is, the information of other devices that have logged in to the user account), and in the above optional device list
  • Each associated optional device is displayed in , so that the user can select the target data source device from other associated devices.
  • the user if the user agrees that the electronic device obtains exercise data, he can select an authorized data source from the above-mentioned optional data sources, and after the selection is completed, confirm, and the electronic device can use the user-selectable data source. Select the data source as the target data source, that is, the user's exercise data can be obtained from the target data source.
  • the initial state of each optional data source is the state to be checked, and the user can select the data source that the electronic device can obtain from the optional data source, and Click the corresponding area of the optional data source in the above-mentioned exercise data authorization interface, the electronic device will recognize the above-mentioned click operation as a selection operation, and switch the state of the optional data source to the selected state, as shown in (c) in Figure 5 , for example the user selects all optional data sources as the target data source.
  • the electronic device detects that the user clicks on the "Confirm Authorization" control 502, it recognizes that the user initiates the above-mentioned confirmation operation, and determines the target data source based on the selection status of each optional data source when the confirmation operation is initiated.
  • each optional data source is the selected state, that is, the generated sports data authorization interface is as shown in (c) in FIG. 5 .
  • the user can select an optional data source that is not authorized to change its status from the selected status to the status to be checked, and click the "Confirm Authorization" control 502 after the selection is completed.
  • the motion data authorization interface can be configured with a maximum waiting time, and if the electronic device does not receive a confirmation operation initiated by the user within the maximum waiting time, it will identify the user's refusal to authorize the motion data acquisition.
  • the exercise data authorization interface can be configured with a maximum waiting time. If the electronic device does not receive a confirmation operation initiated by the user within the maximum waiting time, the target data source will be determined based on default settings, for example, all Optional data source as target data source. As shown in (d) in Figure 5, there is a remaining time displayed in the "confirm authorization" control 502, such as "9s", if no confirmation operation from the user is received within 9 seconds, then the identification user defaults to all optional data source as the target data source.
  • the electronic device may authenticate the identity of the user before generating an authorization request.
  • the electronic device may generate an authentication prompt message, as shown in (e) in FIG. 5 , requiring face authentication of the user, so as to determine that the user who initiated the confirmation operation is the user who belongs to the motion data. If the authentication is successful, a prompt message of successful authentication can be generated, as shown in (f) in Figure 5, to identify that the user agrees to authorize the acquisition of motion data from the target data source, and perform the operation of S2013.
  • the motion data is acquired from the target data source.
  • the electronic device may directly acquire the exercise data from the target data source after identifying that the user agrees to acquire the exercise data.
  • the electronic device may generate a corresponding authorization request, obtain the data acquisition permission of the target data source through the above authorization request, and then obtain the user's motion data from the target data source.
  • the electronic device can generate an acquisition progress prompt box, so that the user determines from which target data source obtains motion data currently, and this motion Data acquisition progress.
  • FIG. 6 shows a schematic diagram of a running exercise scene provided by an embodiment of the present application.
  • a user When a user is running, he can exercise on a treadmill. At this time, the user wears a smart watch on his hand. At this time, the user's Both the smart watch and the treadmill will record the exercise data of the running behavior.
  • the electronic device obtains the exercise data from the above two data sources, it will obtain two different exercise data, namely the exercise data 1 from the smart watch and the exercise data from the running Machine movement data2. At this time, the electronic device may combine the exercise data 1 and the exercise data 2 .
  • the specific merging method can be as follows: identify the start time and end time of each motion data, and determine the motion time period corresponding to the motion data; exercise data. For example, if the exercise time period of exercise data 1 includes the exercise time period of exercise data 2, keep exercise data 1 and delete exercise data 2; if the exercise time periods of the two exercise data partially overlap, merge the two exercise data The overlapping parts of the data, and the non-overlapping parts are spliced according to the sequence relationship between the overlapping parts, so as to obtain the combined motion data.
  • FIG. 7 shows a schematic diagram of merging motion data provided by an embodiment of the present application.
  • the exercise time period corresponding to the exercise data 1 obtained by the electronic device is 10:00 to 10:30, and the exercise time period corresponding to the exercise data 2 is 10:20 to 11:00. It can be seen that in the exercise period 10: From 20 to 10:30, motion data 1 and motion data 2 overlap.
  • the electronic device When the electronic device combines the above two motion data, it will :30) to obtain the combined data segment, and accordingly splicing the combined data segment and the remaining data segment to obtain the motion data 3.
  • the electronic device acquires exercise data of the target user in multiple different exercise events.
  • the electronic device can conduct a more accurate assessment of the user's overall exercise ability through the exercise data of multiple different sports events, so as to improve the accuracy of the user's athlete type identification.
  • the sports data of the above-mentioned sports items can specifically be sports data corresponding to different running distances, such as running data of 5 kilometers, running data of 10 kilometers, half marathon (21.09 kilometers) running data and full marathon (42.19 kilometers) running data.
  • running distances such as running data of 5 kilometers, running data of 10 kilometers, half marathon (21.09 kilometers) running data and full marathon (42.19 kilometers) running data.
  • the specific running distance can be set according to the actual situation, and the differences between sports events are not limited here.
  • different sports items can belong to the same sports type, as mentioned above, it can be sports data under different running distances; different sports items can belong to different sports types, for example, the required
  • the acquired sports are: long-distance running, swimming, high jump, long jump, etc.
  • Different sports can reflect the different abilities of the user, and can also determine the type of athlete mentioned by the user.
  • long-distance running events can determine the user's endurance, while high jump and long jump can determine the user's explosive power, etc. Therefore, different sports events can determine the user's corresponding athletic ability in different dimensions.
  • the electronic device may identify the player type corresponding to the user as a preset type, such as an entry-level type.
  • the user's exercise ability can be determined through the plurality of exercise data.
  • the user's multiple exercise data are all of the sprint type Sports data, and the average pace of each sprint is greater than the preset average, then it can be inferred that the user likes sprinting and is good at sprinting, and then it can be determined that the user's athlete type is a sprinting type. It can be seen that the electronic device can determine the type of athlete corresponding to the user through multiple sports data.
  • the above player types can be divided in different ways. For example, it can be divided according to the proficiency of sports, and can be divided into: novice type, balanced type, elite type, etc. It can also be divided into types according to the sports they are good at, such as: sprint type, long-distance running type, etc., or Divided into: running type, basketball type, football type, swimming type and so on.
  • the way the electronic device determines the type of athlete based on the multiple sports data may be: according to the sports item corresponding to the sports data, determine the performance dimension related to the sports performance associated with the sports data (such as muscular endurance, explosive power, skill, etc.) Sex, etc.), and determine the exercise time, heart rate value, etc. corresponding to the exercise data, and determine the dimension scores corresponding to each ability dimension.
  • the electronic device can take the highest value of each ability dimension as the user's final score in this ability dimension, or can be based on The average value of each sports data in the ability dimension is used as the user's final score in the ability dimension, and based on the final scores of all ability dimensions, the athlete type corresponding to the user is determined.
  • the step of determining the user's athlete type can be completed locally on the electronic device, or can be completed by a cloud server. If the step of determining the user's athlete type is completed by the cloud server, the electronic device can upload the acquired motion data to the cloud server, and the cloud server can determine the user's athlete type based on the motion data uploaded by the electronic device, that is, the recognition result, Then, the recognition result is fed back to the electronic device. After receiving the recognition result fed back by the cloud server, the electronic device can determine the user's athlete type and perform subsequent steps.
  • S202 can be specifically implemented in the following two ways:
  • Method 1 Determine the user's athlete type by determining the best score corresponding to each sport
  • the electronic device may divide all acquired exercise data into multiple data groups according to the exercise items to which the exercise data belongs, and each data group corresponds to the same exercise item.
  • the electronic device can determine the user's best sports performance for the sports item according to the multiple sports data contained in the data group associated with the sports item.
  • the above-mentioned sports data are running-type sports data, and different sports can be divided according to different running distances, such as: 5 kilometers running, 10 kilometers running, half marathon running and full marathon running, etc.
  • the electronic device can The running distance in each athletic data is identified to determine the data group to which the athletic data belongs.
  • the exercise data can be identified as belonging to the "5 kilometers running” exercise project.
  • the electronic device can also intercept the data segment of the first 5 kilometers from the exercise data, and add it to the data group corresponding to the exercise event of "5 kilometers running".
  • the method of determining the best sports performance may be: select a sports data with the best sports performance from the sports event, and determine the best sports performance based on the selected sports data with the best performance. score.
  • the method of determining the best sports performance may also include the following steps:
  • Step 1 Determine the ideal heart rate corresponding to the exercise item; the ideal heart rate is specifically the heart rate corresponding to the user's full exercise state.
  • the electronic device can determine the intensity coefficient corresponding to the current exercise according to the user's heart rate, and thus needs to determine a reference value, that is, the above-mentioned ideal heart rate.
  • the ideal heart rate is used to represent the heart rate corresponding to the user's full exercise state, that is, the peak value of the heart rate that the user will reach when completing the exercise with all his strength.
  • the individual information of the user is different, and the ideal heart rate corresponding to the same sports item may also be different.
  • the ideal heart rate of a 20-year-old user may be higher than that of a 30-year-old user; and the ideal heart rate of a male user may also be higher than that of a female user of the same age group.
  • the electronic device can acquire the ideal heart rate associated with the individual information according to the user's individual information.
  • the electronic device can obtain the user's static heart rate.
  • the electronic device is a smart watch.
  • the smart watch can not only record the dynamic heart rate of the user in the exercise state, but also obtain the user's resting heart rate.
  • the heart rate in the resting state that is, the resting heart rate. Since there is a relative relationship between the ideal heart rate of the human body and the resting heart rate, the electronic device can determine the corresponding ideal heart rate of the user through the resting heart rate of the user.
  • Step 2 Determine the intensity coefficient associated with the exercise data according to the actual heart rate and the ideal heart rate in the exercise data.
  • the actual heart rate of the user during the exercise is recorded in the exercise data, and the electronic device can determine the intensity system corresponding to this exercise by calculating the ratio between the actual heart rate and the ideal heart rate.
  • the ideal heart rate is the heart rate of the user in the state of full exercise
  • the actual heart rate of the user is closer to the ideal heart rate during exercise, the closer the user's exercise state is to the state of full exercise. It can be seen that by calculating the actual heart rate and ideal heart rate The ratio between them to determine the intensity coefficient corresponding to the user. Among them, the closer to the full power state, the higher the corresponding intensity coefficient.
  • Step 3 According to the intensity coefficient and the actual sports performance, determine the best sports performance corresponding to the sports item.
  • the electronic device can calculate the corresponding sports performance when the user is exercising at full strength, that is, the best sports performance, according to the intensity coefficient corresponding to the current exercise and the actual sports performance corresponding to the exercise data.
  • FIG. 8 shows a schematic diagram of calculating the best sports performance provided by an embodiment of the present application.
  • the electronic device can identify the running distance corresponding to the exercise data, determine the exercise item to which the exercise data belongs through the running distance, and determine the corresponding ideal heart rate based on the exercise item, that is, the user completes the exercise at full strength. The heart rate value corresponding to the running distance. Then, the electronic device can determine the actual heart rate corresponding to the user's current exercise process from the exercise data, calculate the ratio between the actual heart rate and the ideal heart rate, and determine the intensity coefficient corresponding to the current exercise data.
  • the sports performance is generally determined by the running time, it can be converted by the actual pace corresponding to the sports data.
  • the electronic device can calculate the ideal pace of the user in the state of full exercise according to the actual pace of this exercise and the above-mentioned intensity coefficient, and calculate the ideal pace according to the ratio between the running distance and the ideal pace
  • the optimal running time under ideal conditions is used as the best sports performance corresponding to the sport.
  • the sports items corresponding to different sports data may be inconsistent, for example, the time required for the user to run 5 kilometers is bound to be shorter than the time required for running 10 kilometers, so the two cannot pass the same
  • the time index of the user is used to determine the corresponding sports performance, that is, the user's sports ability.
  • the exercise indicators under different exercise distances are not necessarily linear. For example, the standard time-consuming for a normal user to run 5 kilometers is 30 minutes, while the standard time-consuming for a normal user to run 10 kilometers is not necessarily 30 minutes. *2 minutes is 1 hour, but it can be 1 hour and 10 minutes. Therefore, for different sports events, it is impossible to directly compare the sports performance through the distance relationship of different sports.
  • the electronic device can perform normalization processing on the best sports performance, so as to represent the performance of different sports through a unified dimension index, In order to improve the accuracy of subsequent identification of the user's athlete type.
  • the electronic device may store normalization algorithms corresponding to different sports items.
  • the electronic device can determine the sport item to which the exercise data belongs, and calculate a normalization parameter associated with the sport item through a normalization algorithm associated with the sport item.
  • the above-mentioned normalization algorithm may specifically be a list of corresponding relationships, or may be a conversion function, and the form of the above-mentioned normalization algorithm is not limited here.
  • the electronic device can import the above calculated best sports performance into the normalization algorithm of the corresponding sports event to obtain the normalization parameters of the sports event, so that the best sports performance of different sports events can be The best sports performance is converted to the same dimension for comparison.
  • FIG. 9 shows a schematic diagram of a normalization algorithm provided by an embodiment of the present application.
  • the abscissa in the coordinate system is used to determine the running distance and is used to distinguish different sports; the ordinate in the coordinate system is used to determine the best sports performance.
  • different parameter curves can be obtained. For example, if the value of the normalized parameter is 20, it corresponds to curve 1 in Figure 9; while the value of the normalized parameter is 35, it corresponds to Curve 2 in 9, that is, different curves correspond to different normalized values.
  • Table 1 shows a correspondence table of normalization parameters provided by an embodiment of the present application.
  • the electronic device can also determine the normalized parameters corresponding to the best athletic performances through the preset correspondence table. If a user’s best sports performance in the sport event of 5 km running is 25 minutes, it can be determined from Table 1 that the user’s normalized parameter for 5 km running is 40; The best sports performance corresponding to the sport of running is 43 minutes, which can also be determined from Table 1. The user’s normalized parameter for 10 km running is 50. For other sports, you can also refer to the above process, and query the corresponding The relational table obtains its corresponding normalization parameters.
  • the athlete type of the user is determined based on the normalized parameters of each sport item.
  • different sports items can reflect the user's corresponding sports ability in different sports evaluation dimensions, for example, a certain sports item can mainly reflect the user's explosive power, while another sports item can mainly reflect the user's endurance, etc.
  • the user's athletic ability can be evaluated more comprehensively through the normalized parameters of different sports, so the user's athlete type can then be determined through the normalized parameters corresponding to different sports.
  • FIG. 10 shows a correspondence relationship diagram of athlete types provided by an embodiment of the present application.
  • different athlete types correspond to different areas in the coordinate system.
  • the corresponding athlete curve is generated in the above coordinate system. Based on the position of the athlete curve Enter the area to determine the type of athlete corresponding to the user.
  • the types of athletes can be divided into: novice type (that is, the normalized parameters corresponding to each sport are at a relatively low level), balance (that is, the normalized parameters corresponding to each sport are at a low level).
  • the best sports performance corresponding to each sports event is determined respectively, and then the best sports performances of different sports events are normalized to obtain the normalized parameters of each sports event, and Determining the athlete type of the user according to the normalized parameters of all sports events can improve the accuracy of the process of identifying the athlete type to which the user belongs.
  • Method 2 Based on the normalized parameters corresponding to all sports data, determine the user's athlete type
  • the normalization algorithm associated with the sports data is determined, and the normalization parameter corresponding to the sports data is determined through the normalization algorithm.
  • different sports items may correspond to different normalization algorithms, so that the sports data corresponding to each sports item can be unified into the same dimension for comparison.
  • the electronic device can identify the sports item of the sports data, obtain the normalization algorithm corresponding to the sports item, and calculate the normalization parameter corresponding to the sports data through the normalization algorithm corresponding to the sports item.
  • the implementation process of calculating the normalization parameter can refer to the description of the previous method, such as calculating the normalization parameter through a corresponding relationship table or a related conversion function, etc., and will not be repeated here.
  • the athlete type of the user is determined based on the normalized parameters corresponding to all the exercise data.
  • the electronic device can obtain the normalized parameters corresponding to the acquired sports data, and determine the performance ability of the user in the sports event through the normalized parameters of multiple sports data in the sports event, for example, The average value of the normalized parameters of all sports data in a certain sport is used as the feature value corresponding to the user in the sport, and then the user's athlete type is determined according to the feature values corresponding to the user in all sports. Similar to the previous method, different sports can reflect the user's different sports abilities, such as endurance, explosive power, etc. Therefore, by determining the feature values of the corresponding sports through multiple sports data, it can be determined that the user is in multiple sports. For the performance ability of the sports event, the stability of the performance ability evaluation for a certain sport event is improved, and then the accuracy of athlete type identification is improved.
  • the electronic device does not determine the normalized parameters corresponding to the sports event from the best sports performance, but normalizes all the sports data, and can determine the user's performance in a certain sports event from multiple sports.
  • the performance ability in the game improves the stability of the performance ability evaluation for sports events.
  • the electronic device determines the user's athlete type
  • it can determine the user's training direction. Since the athlete type can determine the user's athletic ability in different dimensions, let's take running as an example. If the user's athlete type is a sprint type, it means that the user's explosive power is better, but the endurance is poor. In this case, the subsequent The training direction can be to improve the user's endurance and maintain the user's explosive power; if the user's athlete type is a novice type, it means that the user's explosive power and endurance are poor.
  • the follow-up training direction is to improve the user's endurance As well as explosive power, it can be seen that through the type of athlete, the direction that the user is good at and the direction to be improved can be determined, so that the corresponding training direction when guiding the user's training can also be called the training focus.
  • the electronic device may display a training report corresponding to the user; the training report includes the training plan and descriptions about the athlete type and the training direction part.
  • the training report specifically includes two parts, which are an analysis page for evaluating the user's overall exercise ability and a viewing page for the training plan.
  • the analysis page generated by the electronic device may include descriptions of the user's athlete type and training direction, so that the user can determine his own athletic ability through the analysis page.
  • FIG. 11 shows a schematic diagram of a training report provided by an embodiment of the present application.
  • the electronic device can determine the user's athlete type and training direction, Then an analysis page as shown in (a) in FIG. 11 is generated.
  • the analysis page shows the normalized parameters of different sports determined based on the collected sports data, that is, the chart area 01 of (a) in Figure 11, and then, it can also be generated to describe the user's athlete type and training
  • the analysis section 02 of the direction through which the user can determine his own athlete type 021 and the training direction 022 .
  • the electronic device may extract training courses matching the training direction from a preset training course library, thereby generating a training plan matching the training direction.
  • the above training plan may include a training period, a training time, and a training course corresponding to the training time.
  • the analysis page also includes a control 03 of "view training plan". If the electronic device detects that the user clicks on the control 03, the training plan corresponding to the user can be displayed , as shown in (b) in Figure 11, the training period is specifically used to indicate the duration of the training plan, such as from June 1 to June 20, and the training time is specifically used to indicate the triggering of each training course Time and course duration, such as training for 1 hour on June 1, the training course is specifically used to indicate the training content, for example, the training content corresponding to June 1 is squat jumping and running.
  • the above operation of determining the training plan can be completed locally on the electronic device, or can be completed on the cloud server. If the above-mentioned operation of determining the training plan is completed on the cloud server, then the above-mentioned training course library can be stored in the cloud server, and the cloud server determines the user's training direction according to the user's athlete type, and extracts the training direction that matches the training direction from the training course library. A training course is generated to generate a corresponding training plan, and the training plan is fed back to the electronic device.
  • the cloud server When the cloud server feeds back the training plan to the electronic device, it can send the user's complete training plan to the electronic device; the cloud server can also feed back the training courses in the training plan to the electronic device when it reaches the training prompt time, for example The cloud server sends the corresponding training course of the day to the electronic device; or the cloud server can receive the plan query request initiated by the user sent by the electronic device, and send the training course corresponding to the plan query request in the training plan to the electronic device.
  • FIG. 12 shows a schematic diagram of training plan query provided by an embodiment of the present application.
  • a training calendar can be displayed on the electronic device, and the dates with training courses in the training calendar can be marked in a preset manner, as shown in June 10th and 11th in the figure.
  • a date with a training course, and June 30 in the figure is a date without a training course.
  • the electronic device If the electronic device has a training course corresponding to the date stored locally, it can display the training course corresponding to the date; if the training course corresponding to the date is not stored locally, the electronic device can send the plan query request to the cloud server, The cloud server feeds back the training course corresponding to the date to the electronic device according to the training plan corresponding to the user, and the electronic device displays the training course corresponding to the date, as shown in (b) in FIG. 12 .
  • the above S203 specifically includes: determining the user's training direction according to the training purpose and the athlete type.
  • the electronic device can pre-set the training purpose through the user, determine the ability to be improved, and determine the user's current athletic ability based on the identified athlete type. Therefore, the electronic device can match the current athletic ability by identifying the ability required for the training purpose. , so as to determine the corresponding training direction, and generate the corresponding training plan for the determined training direction.
  • the user's training purpose is "to participate in a full marathon", and the identified athlete type of the user is a sprint type, in this case, it means that the user has excellent explosive power but lacks endurance.
  • the required ability is excellent endurance, but the user's current endurance does not match the training purpose.
  • the training direction can be determined to improve endurance, and a training plan for improving endurance can be generated. It can be seen from the above that a method for generating a training plan provided by the embodiment of the present application can determine the user's athlete type by acquiring the user's exercise data in the historical exercise process, and based on the athlete type identification, obtain the user's corresponding training plan.
  • the training direction and generate a training plan that matches the training direction, and can generate a training plan that is suitable for the user's athletic ability. Since the user's individual parameters cannot directly reflect the user's athletic ability, the training plan generated based on individual parameters may not match the user's athletic ability, while the exercise data collected by the user in historical exercise activities can reflect the user's actual athletic ability , determine the user's athlete type based on the user's performance in historical sports, which can improve the matching degree between the training plan and the user's actual athletic ability, so that the generated training plan can guide the user to carry out sports training in a more targeted manner, improving the The accuracy of the generated training plan.
  • the first embodiment mainly determines the user's athlete type based on the exercise data, and determines the corresponding training direction based on the athlete type, and then generates a training plan that matches the training direction.
  • the implementation process of how to generate a training plan based on the training direction is described in detail.
  • the user's training direction obtained by the electronic device in this embodiment can be obtained through the method of Embodiment 1, can also be obtained according to the method preset by the user, or can be obtained by receiving feedback from other devices.
  • the manner of obtaining the training direction is not limited here.
  • the execution subject of the process is an electronic device, which includes but is not limited to: computers, smart phones, notebook computers, tablet computers, wearable smart devices (such as smart necklaces, smart watches and smart bracelets) etc.), cloud servers and other devices capable of executing training plan generation tasks.
  • Fig. 13 shows the implementation flow chart of the method for generating a training plan provided by another embodiment of the present application, which is described in detail as follows:
  • the training direction in this embodiment can be determined through the method of Embodiment 1; optionally, the electronic device can also generate a training direction setting interface, and the user can fill in the training plan in the setting interface.
  • Targeted training direction so that the electronic device can also determine the training direction through the way set by the user; optionally, if the user has recognized his own training direction on other devices, in this case, the electronic device can receive feedback from other devices The user's training orientation.
  • the electronic device is a user terminal and other devices are cloud servers, the electronic device may have a client program corresponding to the cloud server installed locally, and the account associated with the user may be registered in the client program. If the training direction identified by the user is stored above, the training direction can be sent to each device that has logged in the account associated with the user, that is, the electronic device provided in this embodiment, so that the electronic device can obtain the user's training direction.
  • the electronic device may pre-store a plan template corresponding to the training plan.
  • the plan template is used to define a plurality of different training stages when the user is training. Each training stage will have a corresponding stage period length, which means the duration of the training stage. Different training stages will have different training emphases. Based on this, the electronic device can adjust accordingly after determining the user's training direction.
  • the phase cycle duration of each training phase in the training plan so that the training cycle duration of each training phase matches the training direction.
  • different training stages can be associated with one or more training focuses. If the training focus of the training stage matches the user's training direction, the period duration of the training stage can be extended; otherwise, if the training focus of the training stage If the focus does not match the user's training direction, the period of the training phase can be shortened.
  • FIG. 14 shows a schematic diagram of division of training stages provided by an embodiment of the present application.
  • a plan template contains four training stages, namely: basic adaptation stage, maximum oxygen uptake increase stage, lactate threshold improvement stage, and pre-competition adjustment stage.
  • the duration of the phase cycle corresponding to each training phase has not been limited.
  • the basic adaptation stage is specifically to let the user gradually enter the training state of continuous exercise, so the training focus of this stage is to improve the balance in all directions;
  • the maximum oxygen uptake promotion stage is mainly used to increase the user's maximum oxygen uptake, and the maximum The amount of oxygen is related to the user's running pace, that is, the training focus of this stage is to improve the user's running pace;
  • the lactate threshold improvement stage is mainly used to improve the user's ability to metabolize lactic acid, and lactic acid will be produced during long-distance running, and After long-distance running, there will be lactic acid accumulation, that is, the training focus of this stage is to improve the user's endurance;
  • the pre-race adjustment stage is specifically to allow the user to preserve physical strength and ensure a certain amount of exercise, that is, the training focus of this stage is ability maintenance.
  • the phase cycle duration of the training phase in the above-mentioned plan template can be 0, that is, in the training plan generated subsequently, some training phases in the plan template may not be included, as shown in (b ) shows that after determining the period duration of each training stage based on the training direction, the period duration assigned to the maximal oxygen uptake increase stage is 0, that is, this stage is not included, and only the other three stages are left.
  • the first situation is that the user already has a better performance in the corresponding training focus of this training stage. Therefore, there is no need to improve the corresponding sports ability through this training stage, such as the user's endurance. The performance is excellent, belonging to a very excellent level, but the speed is weak.
  • the training phases can be arranged periodically in the plan template, as shown in (c) in Figure 14, the phases of increasing the maximum oxygen uptake and the stages of improving the lactate threshold in the planning template are alternately arranged. There are multiple occurrences in the planning template.
  • the electronic device may respectively determine the period duration of each training phase corresponding to each period based on the user's training direction.
  • the electronic device can also determine the total duration of the training phase, and configure the corresponding phase cycle duration for each training cycle of the training phase according to the number of occurrences of the training phase in the plan template, as shown in (c) in Figure 14 As shown, the total duration of the VO2max raising phase is 28 days, which appears twice in the plan template, that is, there are two training cycles, and the electronic device can allocate For 13 days, allocate 15 days for the second training cycle of the VO2max raising phase.
  • the above S1301 may specifically include:
  • the electronic device may store different plan templates, and different plan templates are associated with corresponding training objectives. Based on this, before the electronic device generates the user's training plan, it can obtain the user's training purpose.
  • the method of obtaining the training purpose is as described above, and generates the information input interface shown in FIG. 4 to prompt the user to input the user's individual parameters and training purpose. And after obtaining the user's training purpose, select a matching plan template from the plan template library.
  • the number of training phases and training focus included in the plan templates corresponding to different training purposes may be different.
  • the corresponding plan template can be template 1, which can contain three training stages, namely: physical fitness recovery stage, physical fitness improvement stage, and physical fitness stabilization stage; user B
  • the purpose of the training is to see the marathon
  • the corresponding plan template can be template 2, which can include four training stages, namely: basic adaptation stage, maximum oxygen uptake promotion stage, lactate threshold improvement stage, and pre-race adjustment stage. Therefore, the training phase included in the plan template and the training emphasis corresponding to the training phase match the corresponding training purpose, so that the degree of adaptation between the generated training plan and the user can be improved.
  • the duration ratio of each training stage in the plan template can be preconfigured with a certain initial ratio, for example, the ratio between different training stages is 1:1, that is, the duration of each training stage is the same.
  • the electronic device determines the user's training direction (that is, the training focus), it can adjust the initial ratio between the training stages in the plan template. The adjustment is based on whether the training focus corresponding to the training stage matches the user's training direction.
  • the initial ratio corresponding to the training stage can be increased to obtain the above-mentioned duration ratio; if it does not match, the initial ratio of the training stage can be shortened to obtain The corresponding duration ratio can also keep the initial ratio unchanged, that is, the initial ratio in the training phase is used as the duration ratio.
  • FIG. 15 shows a schematic diagram of setting the total training duration provided by an embodiment of the present application.
  • the electronic device can generate an information input interface, which is similar to Figure 4, and can be used to input the user's personal parameters and training purposes.
  • the start date of the training plan is optional.
  • the electronic device may use the corresponding current date when the training plan is generated as an optional date of the training plan, and may also set it according to the needs of the user. As shown in (b) of FIG. 15 , the user can select the starting seven days and the ending date in the above training calendar.
  • the electronic device can obtain the stage cycle duration of each training stage by calculating the product of the duration ratio corresponding to each training stage and the total training duration corresponding to the user.
  • the duration ratio of a certain training stage is 25 %
  • the total training time is 60 days
  • other training periods can also be calculated by the above method.
  • the above-mentioned total training duration ranges from 28 days to 180 days, that is, the shortest total training duration of the training plan is one month, and the longest is 6 months. Since the total training time is too short, the user is close to the end of the training when cultivating exercise habits, and it is impossible to effectively improve the user's training direction; on the other hand, if the user's total training time is too long, the user's exercise ability will The degree of change is relatively large. Based on the determination of the training direction and the proportion of the training phase in the initial state, it may no longer be applicable to the user. Therefore, the accuracy of the training plan will be greatly reduced.
  • the electronic device can set a corresponding effective range for the total training time. If the total training time set by the user is outside the above-mentioned effective time range, a corresponding prompt message can be generated, as shown in Figure 15 ( As shown in c), the user is prompted that the total duration of this training is too short and needs to select a date after 28 days.
  • the accuracy of the period division process can be improved, and the The degree of adaptation between the subsequent training program and the user.
  • the electronic device can be divided into a plurality of training times according to the corresponding period of the training stage. For example, if the division is performed in units of days, each training time corresponds to a training date; For division, each training time corresponds to one training hour. Certainly, different training dates may be continuous or discontinuous, which shall be set according to the actual situation.
  • S1302 can be completed through an application program installed on the user terminal; if the electronic device is a cloud server, then S1302 can also determine the training courses for each training time on the cloud server. operate.
  • a training stage may correspond to one course category, or may correspond to more than two course categories, which shall be determined according to the actual situation.
  • the electronic device may pre-store multiple different training courses, and each training course may correspond to a course type. Since different training stages correspond to different training emphases, the electronic device can determine whether the course category is the course category associated with the training stage according to whether the course category matches the training emphases of the training stage, and store the course Category-associated training sessions are associated to individual training sessions. Wherein, one training time may correspond to one or more training courses, and the training courses between different training times may be the same or different.
  • the electronic device may record a table of correspondence between course categories and training stages, and by querying the above correspondence table, the course categories associated with each training stage may be determined.
  • the above S1302 may specifically include the following steps:
  • all the course categories corresponding to the training stage may be added to the same training category library.
  • the training category library includes at least one course category related to the training stage, and a course category may contain candidate courses of different course difficulty levels.
  • the training category library can include three course categories: high-intensity interval type, easy running type, and aerobic endurance running type, and based on Each of the above-mentioned course categories contains candidate courses with different course difficulty levels. For example, for the type of aerobic endurance running, the candidate courses with low difficulty are short in distance and require a low running pace, while the candidate courses with high difficulty are long in distance and require running. The pace is higher.
  • the electronic device can add candidate courses of different course difficulty levels in all course categories related to the training stage to the same training category library, so that the subsequent steps can determine the training courses corresponding to each training time.
  • the electronic device can divide the duration of the stage cycle to obtain multiple training times. As mentioned above, it can be divided in units of dates, and the duration of the stage cycle can be divided into multiple training dates. Each training date is for a training time.
  • the aforementioned training time may include a training date and a training duration corresponding to the training date.
  • the electronic device can configure corresponding course difficulty levels for different training dates, so as to generate a training course framework that meets the preset exercise intensity combination.
  • the early exercise intensity of the training phase is low, so the corresponding course difficulty The level is low; and in the later stage of the training phase, users have adapted to sports training, and the corresponding exercise intensity is relatively high, so the corresponding course difficulty level is relatively high.
  • the exercise intensity combinations corresponding to different training stages can be different. For example, for the stage of increasing the maximum oxygen uptake, the overall exercise intensity of this stage will be higher than that of the pre-competition adjustment stage, so the corresponding exercise intensity combinations will also be different, namely The difficulty level of the course will be different according to the training time.
  • the electronic equipment can realize the detailed configuration of the entire training stage, limit the structure, duration and difficulty combination of the training courses included in the training stage, and can take into account the difficulty of the courses required for different training periods
  • the relationship between levels instead of configuring the course difficulty level for the entire training phase as the same value, improves the rationality and accuracy of training course selection, thereby improving the accuracy of the training plan for user training guidance.
  • the electronic device may acquire the athlete type of the user, and determine the course difficulty level corresponding to each course category based on the user's athlete type.
  • the above training course framework is also used to determine the course category corresponding to each training time.
  • the electronic device after the electronic device generates the training course framework corresponding to the training phase, it can configure corresponding training courses for each training time in the training course framework. Since each training time is associated with a corresponding course difficulty level, Then the electronic device may extract a candidate course corresponding to the difficulty level of the course from the training category database as the training course for the training time.
  • FIG. 16 shows a schematic diagram of selecting a training course provided by an embodiment of the present application.
  • the electronic device determines the period duration of each training stage according to the training direction, and the period duration of each stage is configured with a corresponding training category library.
  • the training category library of stage 1 contains 3 course categories.
  • Each course category also contains candidate courses of different course difficulty levels, that is, courses 1.1 to 1.3.
  • the electronic device selects candidate courses corresponding to the course difficulty level from the course category according to the course difficulty level associated with the training time in the training stage.
  • the training course during this training period if the training time of June 10 corresponds to a course difficulty level of 2, then the candidate course with a course difficulty level of 2 in course category 1 is selected as its corresponding training course, that is, course 1.2 .
  • the corresponding training category library and training course framework are configured for each training stage, so as to determine the training courses corresponding to each training time in the training stage, and the differences between training courses configured between different training times can be considered. Correlation, which improves the accuracy of training programs.
  • the training plan is generated according to the training courses corresponding to the training time of all training stages.
  • the electronic device can integrate the training courses of each training time in each training stage, so as to obtain the user's training plan.
  • the electronic device can display all the training courses corresponding to the training time in the same interface, as shown in (b) in Figure 11; it can also generate a training calendar interface for the courses corresponding to each training time, as shown in Figure 17 Show.
  • Fig. 17 shows a schematic diagram of a training calendar interface provided by an embodiment of the present application. Referring to Fig.
  • the program name of the training program is displayed, such as "5 km running training program", the serial number corresponding to the current training time, when the training time is divided by day, the serial number It is the number of days of training, as shown in the figure, it is the 12th day. It can also display the total training time, that is, the above-mentioned 49 days, and the completion rate of the current training plan, that is, 5.1%.
  • the training calendar interface also shows Statistics can be made on the training time, exercise distance and cumulative consumption of the user to obtain corresponding values.
  • the training stage corresponding to the current training time is also displayed.
  • the "basic period" in the figure indicates the training stage corresponding to the training time.
  • the training calendar page can also display the stage number corresponding to the training stage and The total number of training stages.
  • the date corresponding to the training time can also be displayed, that is, the 31st, and the date with the training course (that is, the training time) is marked in a preset manner, such as the 31st, 2nd, and 4th and 6th etc.
  • the training time includes two training courses, namely "Aerobic Endurance Running” and "Lactate Threshold Interval Running", and displays the training time and completion status of the corresponding training courses. For the completed training courses, you can Change the control to "Completed", and for the training course to be completed, the control can be displayed as "Start training", so that the user can carry out the training course.
  • the training courses of each training time in the training plan can be displayed through the application program installed on the smart phone; If the electronic device is a cloud server, the cloud server can send the training course corresponding to each training time to the user terminal corresponding to the user, and display it through the smart phone; of course, if the user completes the training through the corresponding execution terminal during the training process, For example, with the help of a treadmill, smart watch or smart bracelet, etc., the received training courses can be forwarded to each execution terminal through the smart phone, so that the exercise data of the user during the training process can be collected through the execution terminal.
  • the generation method of a training plan can adjust the period duration of each training stage in the training plan according to the training direction of the user, and different training stages correspond to different training priorities. , so it can be associated with the corresponding course category, and the corresponding course category of the training stage, and configure the corresponding training course for each training time to generate a training plan that matches the user's training direction, so that the training plan can be targeted It is not based on the user's individual parameters to determine the training plan, improve the adaptability between the training plan and the user, and the pertinence of the training process.
  • Embodiment 1 and Embodiment 2 mainly describe how to generate a user's training plan. However, in this embodiment, how to adjust the training plan after the user's training plan is generated is described in detail.
  • the training plan that needs to be adjusted in this embodiment can be generated by the method of Embodiment 1, can also be generated by the method of Embodiment 2, or can be obtained by combining Embodiment 1 and Embodiment 2 (that is, the training direction in Embodiment 2 is determined based on the method in Embodiment 1, and then the user’s training plan is generated by the method in Embodiment 2), or it can be generated in other ways, and adjustments are not to be made here
  • the generation method of the training plan is limited.
  • the execution subject of the process is an electronic device, which includes but is not limited to: computers, smart phones, notebook computers, tablet computers, wearable smart devices (such as smart necklaces, smart watches and smart bracelets) etc.), cloud servers and other devices capable of executing training plan generation tasks.
  • Fig. 18 shows the implementation flowchart of the adjustment method of the training plan provided by an embodiment of the present application, which is described in detail as follows:
  • a subjective parameter collection page is generated to determine whether the user is interested in any of the training courses according to the feedback operation initiated by the user on the subjective parameter collection page. Subjective motion parameters corresponding to the training sessions.
  • FIG. 19 shows a schematic diagram of a subjective parameter collection page provided by an embodiment of the present application.
  • a prompt box 191 may pop up to prompt the end of the training, and a control 1911 for confirming the end of the course is displayed in the prompt box, as well as extending the exercise.
  • a page for collecting subjective motion parameters for this course training can be generated, that is, a subjective parameter collection page, as shown in Figure 19 ( b) as shown.
  • the subjective parameter collection page contains multiple optional controls corresponding to subjective motion parameters, namely "very easy”, “just right”, “challenging” and "too difficult”.
  • the above-mentioned subjective motion parameters correspond to The subjective exercise intensity increased in turn. Users can select the corresponding subjective exercise parameters according to their actual feelings about the training of this course, and initiate a feedback operation on the subjective parameter collection page. If a user feels that the exercise intensity of this training course is appropriate, he can click "Just Good” controls, electronic devices can operate based on user feedback to determine subjective motion parameters.
  • the above-mentioned subjective parameter collection page can be displayed on the display module of the electronic device, and can also be displayed on the display module of other devices.
  • the user is training on a treadmill, and the electronic device detects that the user has completed a certain After the course, the generated subjective parameter collection page can be sent to other electronic devices, or the corresponding page generation instructions can be sent to other electronic devices.
  • other electronic devices are treadmills, and the treadmill can be displayed on the local display module.
  • the subjective parameter collection page is displayed, the user can initiate a feedback operation on the display module of the treadmill, and the treadmill sends the subjective motion parameters corresponding to the feedback operation to the electronic device, so that the electronic device can obtain the user's subjective motion parameters.
  • the user can perform training according to the training plan.
  • the training plan can contain multiple training times, and each training time can be associated with one or more training courses, and the user can perform physical exercises according to the training content in the training courses.
  • Intensity can have a corresponding training pressure value, wherein, if the training pressure value is greater, it means that the exercise intensity corresponding to the training course is higher; on the contrary, if the training pressure value is smaller, it means that the exercise intensity corresponding to the training course is higher. lower.
  • the above-mentioned training pressure value can be determined according to the course difficulty level corresponding to the training course. For example, if the course difficulty level of a certain training course is 3, it can be determined that the user's training pressure value is 3.
  • the electronic device can also store The conversion relationship between the difficulty level of the course and the training pressure value, through which the corresponding training pressure value of the training course is calculated; Sure.
  • S1801 may specifically include the following steps:
  • the training pressure value corresponding to the training course is determined based on the real-time data.
  • the user in the process of exercising, can obtain the corresponding real-time exercise data when the user is training based on the training course, that is, the above-mentioned real-time data, through electronic devices or other data collection devices.
  • the real-time data may include heart rate values and exercise duration during exercise.
  • the above-mentioned real-time data includes heart rate values corresponding to multiple collection moments.
  • the electronic device or other data collection equipment can acquire the user's heart rate value during the exercise at a preset time interval.
  • Each heart rate value may correspond to a collection moment.
  • the electronic device determines the training pressure value of the user during the training course, it may first determine the exercise intensity corresponding to each moment according to the heart rate value corresponding to each collection moment, wherein the calculation method of the exercise intensity may specifically be based on the actual heart rate of the user The ratio between the value and the ideal heart rate value corresponding to the sport item is determined.
  • the electronic device After the electronic device calculates the exercise intensity corresponding to each acquisition time, it can mark the coordinate points corresponding to each acquired heart rate value on the preset coordinate system, wherein the ordinate of the coordinate point can be the exercise intensity, and the abscissa can be It may be the corresponding collection time, and then the electronic device may connect each coordinate point according to the sequence of the collection time to obtain the exercise intensity curve corresponding to the real-time data.
  • the electronic device may integrate the exercise intensity curve in the time dimension, and use the integrated value as the training pressure value corresponding to the training course.
  • the electronic device may calculate the training pressure value as follows: the electronic device determines the user's average exercise intensity according to the heart rate values at multiple collection moments in the real-time data, and calculates the average exercise intensity based on the exercise duration and the average exercise intensity. The product between them is used to obtain the training pressure value corresponding to the training course.
  • the training plan is adjusted according to the subjective exercise parameters, and an adjusted training plan is generated.
  • the electronic device can adjust the training plan according to the user's subjective motion parameters. For example, if the subjective motion parameters indicate that it is difficult for the user to complete the above training plan, the difficulty of the training courses in the training plan can be reduced; The exercise parameter indicates that it is easier for the user to complete the training plan, and the difficulty of the training courses in the training plan can be increased, so as to ensure that the training plan is consistent with the training experience of the user.
  • the above S1803 may specifically be: adjust the training plan according to the training pressure value and subjective motion parameters, and generate an adjusted training plan .
  • the electronic device can compare the training pressure value of the same training course with the subjective exercise parameters to determine whether the actual exercise intensity of the training course is consistent with the user's subjective feeling. Due to the individual differences in the feelings of each person during the exercise process, the difficulty level of the training courses is set according to the common indicators, such as determining the difficulty level of the courses based on the feedback from a large number of users, and the common indicators may be related to the individual feelings of the users. There will be a mismatch. In order to improve the fitness between the training plan and the user, increase the user's training enthusiasm, and cultivate the user's habit of continuous exercise, the electronic device can compare the objectively collected training pressure value with the subjective exercise parameters. The training plan is adjusted to obtain the adjusted training plan, so as to improve the rationality of the follow-up training course arrangement and the fit between the user.
  • S1803 may specifically include:
  • the plan adjustment direction is determined based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment trigger time.
  • the electronic device may store the obtained training pressure value and subjective exercise parameters in the memory before the adjustment trigger time is reached, and the training plan will not be adjusted immediately after the training course is completed.
  • a corresponding prompt message "Training experience will be used to adjust the next week's plan" can be displayed, that is, it is not available at this time.
  • the subsequent training courses will be adjusted immediately, but the training plan will be adjusted when the user reaches the next week (that is, the preset adjustment trigger time).
  • the electronic device may preset an adjustment period for the training plan, and multiple adjustment triggering moments may be determined based on the period length of the adjustment period. For example, if the above-mentioned adjustment period is one week (7 days), then 0:00 every Sunday can be set as the adjustment trigger time, and the training pressure value and subjective exercise parameters corresponding to the training courses completed this week can be used for the training after the next week. Courses are adjusted.
  • the electronic device can determine the adjustment direction for the training plan according to the training pressure value corresponding to each training course that the user has completed and the subjective movement parameters.
  • the adjustment direction includes: increasing the training difficulty, reducing the training difficulty and maintaining training difficulty.
  • FIG. 20 shows a schematic diagram of an adjustment direction of a training plan provided by an embodiment of the present application.
  • the electronic device can determine the coordinate points of the training course on the above-mentioned control coordinate system according to the training pressure value of the training course and the subjective movement parameters, wherein the above-mentioned coordinate points are specifically Can fall into three different areas, namely:
  • the electronic device can mark the coordinate points of each training course on the above-mentioned comparison coordinate system, in addition to being able to determine the adjustment direction of the training plan
  • the adjustment range can also be determined; if multiple training courses fall into the area of increasing training difficulty, it means that the training courses in the training plan have a low degree of difficulty level, and the low range is relatively large, and the courses will be adjusted later
  • you can increase the difficulty level of the matching course on the contrary, if part of the training courses fall into the area of maintaining the training difficulty or even reducing the training difficulty, while the other part of the training courses fall into the area of increasing the training difficulty, it means that the course The difficulty level is low, but the degree of lowness is small.
  • the difficulty level of the training course can be slightly increased. If the difficulty level of some training courses is increased, the difficulty level of some training courses can be maintained.
  • each training course corresponds to a course category
  • the electronic device can determine that the course category corresponds to direction of adjustment.
  • the electronic device may adjust subsequent training courses in the training plan according to the plan adjustment direction, for example, increasing the course difficulty level of the subsequent training course, or decreasing the course difficulty level of the training course.
  • the training category library contains one or more course categories corresponding to the training stage, and a course category can contain different courses Difficulty level training courses, therefore, if the course difficulty level of a certain training course does not match the user, you can select a training course with another course difficulty level from the course category corresponding to the training course to replace the course category in the training plan training courses.
  • FIG. 21 shows a schematic diagram of adjusting a training course provided by an embodiment of the present application.
  • the training course on June 10 was course 1.2, that is, the difficulty level of the course was 2. It is necessary to reduce the course difficulty of the training course on the subsequent date.
  • the course category of the training course on June 10 is course category 1, and course category 1 contains training courses with 3 course difficulty levels, and the course difficulty level is less than
  • the training course for 2 is course 1.1.
  • course 1.1 will replace the training course arranged on June 10, and the training courses for each training time will be adjusted in the above way, and the adjusted training course will be obtained.
  • FIG. 22 shows a schematic diagram of adjusting a training plan provided by an embodiment of the present application.
  • the electronic device can be configured with a menu control 221 in the query interface of the training course. If it is detected that the user clicks on the above-mentioned menu control 221, a corresponding menu pop-up window 222 can be generated.
  • the pop-up window 222 includes a plurality of options, namely: modifying the training day, modifying the training course, training reminder and terminating the plan.
  • a page for adjusting the training day will be generated, as shown in (b) in Figure 22.
  • the user can set the training date corresponding to different training items , such as the training date of running events and the training date of strength events, users can choose the appropriate date according to their own conditions.
  • the adjustment of the training day can take effect in the next week, and of course, it can also take effect immediately.
  • the electronic device detects that the user clicks on the option to modify the training course, and can generate a training course adjustment page, as shown in (c) in Figure 22.
  • each training course can display the current difficulty level of the course, and the user can adjust it according to their own According to the situation, adjust the course difficulty level corresponding to each training course, and the electronic device can select the training course corresponding to the course difficulty level from the course category corresponding to the training course to replace.
  • the above adjustments can be adjusted to the training plan at the next adjustment trigger moment, or can take effect immediately.
  • Fig. 23 shows a structural block diagram of a device for generating a training plan provided by an embodiment of the present application , for ease of description, only the parts related to the embodiment of the present application are shown.
  • the generation device of this training plan comprises:
  • An athlete type determining unit 232 configured to determine an athlete type corresponding to the user based on a plurality of the exercise data
  • a training plan generating unit 233 configured to determine the user's training direction based on the athlete type, and generate a training plan matching the training direction.
  • the plurality of acquired motion data includes motion data of a plurality of sports items
  • the player type determination unit 232 includes:
  • the best sports performance determination unit 2321 is configured to determine the best sports performance corresponding to the sports item according to the sports data associated with each of the sports items;
  • the normalization parameter determination unit 2322 imports the best sports performance into the normalization algorithm corresponding to the sports item, and determines the normalization parameter corresponding to the sports item;
  • the athlete type identification unit 2323 is configured to determine the athlete type of the user based on the normalized parameters of each sport.
  • the best sports performance determination unit 2321 includes:
  • An ideal heart rate determination unit configured to determine the ideal heart rate corresponding to the exercise; the ideal heart rate is specifically the heart rate corresponding to the user's full exercise state;
  • An intensity coefficient determining unit configured to determine an intensity coefficient associated with the exercise data according to the actual heart rate and the ideal heart rate in the exercise data
  • the best sports performance calculation unit is configured to determine the best sports performance corresponding to the sports item according to the intensity coefficient and the actual sports performance.
  • the motion data acquisition unit 231 includes:
  • a movement data authorization interface generation unit 2311 configured to generate a movement data authorization interface including at least one optional data source
  • a confirmation operation response unit 2312 configured to determine a target data source from the optional data sources in response to the user's confirmation operation based on the sports data authorization interface;
  • a data acquisition and sending unit 2313 configured to acquire the exercise data from the source of the target data.
  • the generating device of the training plan also includes:
  • the training report display unit is configured to display the training report corresponding to the user; the training report includes the training plan and descriptive paragraphs about the athlete type and the training direction.
  • the training plan generating unit 233 includes:
  • the stage cycle duration determination unit 2331 is used to determine the stage cycle duration of each pre-divided training stage in the preset plan template according to the training direction;
  • the training course determination unit 2332 is configured to determine the course category associated with the training phase, and configure a training course belonging to the course category for each training time in the training phase; the training time is based on the training period The duration of the stage cycle is determined;
  • the training course encapsulation unit 2333 is configured to generate the training plan according to the training courses corresponding to the training time of all the training stages.
  • the training course determination unit 2332 includes:
  • a training category library configuration unit configured to configure a training category library for the training phase based on the course category associated with the training phase
  • the training course framework determination unit is used to determine the training course framework corresponding to the training stage according to the period duration of the training stage and the training category library; the training course framework is used to determine the training courses contained in the training stage.
  • the training course selection unit is configured to select the training course matching the difficulty level of the course for each training time from the training category library.
  • the stage cycle duration determining unit 2331 includes:
  • a plan template acquiring unit configured to acquire the plan template corresponding to the training purpose of the user; the training purpose is preset by the user; the plan template includes a plurality of pre-divided training stages;
  • a duration ratio determining unit configured to determine the duration ratio of each of the training stages based on the training direction
  • the total training duration allocation unit is configured to determine the period duration of the training phase according to the duration ratio of the training phase and the preset total training duration.
  • the generating device of the training plan also includes:
  • a setting interface display unit configured to generate a training purpose setting interface; the training purpose setting interface includes a purpose setting area for at least one sport item;
  • a setting operation response unit configured to determine the target value corresponding to each of the sports items in response to the user's setting operation in each of the target setting areas
  • the training purpose determining unit is configured to obtain the training purpose based on the target value of each of the sports items.
  • the generating device of the training plan also includes:
  • the subjective exercise parameter determination unit 235 is configured to generate a subjective parameter collection page if it is detected that any training course in the training plan has been completed, so as to perform a feedback operation initiated by the user on the subjective parameter collection page, Determining the user's subjective exercise parameters corresponding to any of the training courses;
  • the training plan adjustment unit 236 is configured to adjust the training plan with the subjective motion parameters to generate an adjusted training plan.
  • the generating device of the training plan also includes:
  • the training plan adjustment unit 236 is specifically configured to adjust the training plan according to the training pressure value and the subjective exercise parameters, and generate an adjusted training plan.
  • the training pressure value acquisition unit 234 includes:
  • the real-time data acquisition unit 2341 is used to acquire the corresponding real-time data when the user performs training based on any training course in the training plan;
  • the real-time data conversion unit 2342 is configured to determine the training pressure value corresponding to the training course based on the real-time data.
  • the training plan adjustment unit 236 includes:
  • the plan adjustment direction determination unit 2361 is configured to determine the plan adjustment direction based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment trigger time when the preset adjustment trigger time is reached ;
  • the training course adjustment unit 2362 is configured to adjust the training course in the training plan after the adjustment trigger moment based on the plan adjustment direction to obtain the adjusted training plan.
  • the training program generation device provided by the embodiment of the present application also determines the user's athlete type by acquiring the user's exercise data during the historical exercise process, and based on the athlete type identification, obtains the corresponding training direction of the user when training, and Generate a training plan that matches the training direction, and can generate a training plan that is compatible with the user's athletic ability.
  • the training plan generated based on individual parameters may not match the user's athletic ability, while the exercise data collected by the user in historical exercise activities can reflect the user's actual athletic ability , determine the user's athlete type based on the user's performance in historical sports, which can improve the matching degree between the training plan and the user's actual athletic ability, so that the generated training plan can guide the user to carry out sports training in a more targeted manner, improving the The accuracy of the generated training plan.
  • FIG. 24 shows a structural block diagram of an apparatus for generating a training plan provided in another embodiment of the present application.
  • the training plan generation device may specifically include a training plan generation unit 241 , a course execution unit 242 and a plan adjustment unit 243 .
  • the training plan generation unit 241 is used to execute the generation method of the training plan provided by the first embodiment and the second embodiment, that is, to determine the training direction according to the user's motion data, and to determine the phase cycle duration of each training phase in the plan template based on the training direction .
  • the training plan generating unit 241 may also include a course extractor, after determining the duration of each training period corresponding to each training stage, the course extractor may select a corresponding training course for each training stage to generate a training plan.
  • the training plan generation unit 242 can be located in the smart phone on the user side, or can be located in the cloud server.
  • the above-mentioned course execution unit 242 can receive each training course issued by the training plan generating unit 241, and output each training course through the course execution unit 242, for example, reminding the user to execute the training course, or displaying the guidance corresponding to the training course through the display module video. Then, the course execution unit 242 may also acquire the corresponding training pressure value and subjective exercise parameters when the user executes the training course.
  • the course execution unit 242 may be located on a smart phone, a smart watch, a treadmill, a smart bracelet, etc. on the user side.
  • the plan adjustment unit 243 is specifically configured to adjust the training plan according to the training pressure value and subjective exercise parameters fed back by the course execution unit 242 , and feed back the adjusted training plan to the training plan generation unit 241 .
  • the plan adjustment unit 243 may be located in the smart phone on the user side, or may be located in the cloud server.
  • Fig. 25 shows a structural block diagram of the device for generating the training plan provided by the embodiment of the present application, for the convenience of explanation , only shows the part related to the embodiment of the present application.
  • the generation device of this training plan comprises:
  • the stage cycle duration determination unit 251 is used to determine the stage cycle duration of each pre-divided training stage in the preset plan template according to the user's training direction;
  • the training course determination unit 252 is configured to determine the course category associated with the training phase, and configure a training course belonging to the course category for each training time in the training phase; the training time is based on the training period of the training phase The duration of the stage cycle is determined;
  • the training plan packaging unit 253 is configured to generate the training plan according to the training courses corresponding to the training time of all the training stages.
  • the training course determination unit 252 includes:
  • a training category library configuration unit 2521 configured to configure a training category library for the training phase based on the course category associated with the training phase
  • the training course framework determination unit 2522 is configured to determine the training course framework corresponding to the training stage according to the period duration of the training stage and the training category library; the training course framework is used to determine the The training time and the course difficulty level corresponding to each training time;
  • the training course selection unit 2523 is configured to select the training course matching the difficulty level of the course for each training time from the training category library.
  • phase cycle duration determination unit 251 includes:
  • a plan template acquiring unit 2511 configured to acquire the plan template corresponding to the training purpose of the user; the training purpose is preset by the user; the plan template includes a plurality of pre-divided training stages;
  • a duration ratio determination unit 2512 configured to determine the duration ratio of each of the training stages based on the training direction
  • the total training duration allocation unit 2513 is configured to determine the period duration of the training phase according to the duration ratio of the training phase and the preset total training duration.
  • the generating device of the training plan also includes:
  • a setting interface display unit configured to generate a training purpose setting interface; the training purpose setting interface includes a purpose setting area for at least one sport item;
  • a setting operation response unit configured to determine the target value corresponding to each of the sports items in response to the user's setting operation in each of the target setting areas
  • the training purpose determining unit is configured to obtain the training purpose based on the target value of each of the sports items.
  • the generating device of the training plan also includes:
  • the subjective exercise parameter determination unit 255 is configured to generate a subjective parameter collection page if it is detected that any training course in the training plan has been completed, so as to generate a subjective parameter collection page according to the feedback operation initiated by the user in the subjective parameter collection page, Determining the user's subjective exercise parameters corresponding to any of the training courses;
  • the training plan adjustment unit 256 is configured to adjust the training plan with the subjective motion parameters to generate an adjusted training plan.
  • the generating device of the training plan also includes:
  • a training pressure value acquisition unit 254 configured to acquire the corresponding training pressure value when the user performs training based on any training course in the training plan;
  • the training plan adjustment unit 256 is specifically configured to adjust the training plan according to the training pressure value and the subjective exercise parameters, and generate an adjusted training plan.
  • the training pressure value acquisition unit 254 includes:
  • the real-time data acquisition unit 2541 is used to acquire the corresponding real-time data when the user performs training based on any training course in the training plan;
  • the real-time data conversion unit 2542 is configured to determine the training pressure value corresponding to the training course based on the real-time data.
  • the training plan adjustment unit 256 includes:
  • the plan adjustment direction determination unit 2561 is configured to determine the plan adjustment direction based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment trigger time when the preset adjustment trigger time is reached ;
  • the training course adjustment unit 2562 is configured to adjust the training course in the training plan after the adjustment trigger moment based on the plan adjustment direction to obtain the adjusted training plan.
  • the training plan generating device can also adjust the period duration of each training stage in the training plan according to the training direction of the user.
  • Different training stages correspond to different training priorities, so it can be associated with The corresponding course category, and the corresponding course category of the training stage, configure the corresponding training course for each training time to generate a training plan that matches the user's training direction, so that the training plan can improve the user's training direction in a targeted manner It is not based on the user's individual parameters to determine the training plan, improve the fitness between the training plan and the user, and the pertinence of the training process.
  • Fig. 26 shows a structural block diagram of the device for adjusting the training plan provided by the embodiment of the present application. part.
  • the adjusting device of this training plan comprises:
  • Subjective exercise parameter determination unit 262 configured to generate a subjective parameter collection page if it is detected that any training course in the training plan has been completed, so as to determine the user's Subjective exercise parameters corresponding to any of the training courses;
  • the training plan adjustment unit 263 is configured to adjust the training plan according to the subjective exercise parameters, and generate an adjusted training plan.
  • the adjustment device of the training plan also includes:
  • the training pressure value obtaining unit 261 is used to obtain the corresponding training pressure value when the user performs training based on any training course in the training plan;
  • the training plan adjustment unit 263 is specifically configured to adjust the training plan according to the training pressure value and the subjective exercise parameters, and generate an adjusted training plan.
  • the training pressure value acquisition unit 261 includes:
  • the real-time data acquisition unit 2611 is used to acquire the corresponding real-time data when the user performs training based on any training course in the training plan;
  • the real-time data conversion unit 2612 is configured to determine the training pressure value corresponding to the training course based on the real-time data.
  • the training plan adjustment unit 263 includes:
  • the plan adjustment direction determination unit 2631 is configured to determine the plan adjustment direction based on the training pressure values and the subjective exercise parameters corresponding to all training courses completed before the adjustment trigger time when the preset adjustment trigger time is reached ;
  • the training course adjustment unit 2632 is configured to adjust the training course in the training plan after the adjustment trigger moment based on the plan adjustment direction to obtain the adjusted training plan.
  • the training plan adjustment device provided by the embodiment of the present application can also obtain the user's subjective exercise parameters for this training course after the training course is over, in addition to obtaining the user's training pressure value during the exercise process, and based on The objective training pressure value and the subjective motion parameters related to the user's subjective feelings are used to adjust the training plan, so as to improve the accuracy of the training plan adjustment and further improve the user's requirements for the personalized setting of the training plan.
  • the method for generating the training plan provided in the embodiment of the present application can be applied to mobile phones, tablet computers, wearable devices, vehicle-mounted devices, augmented reality (augmented reality, AR)/virtual reality (virtual reality, VR) equipment, notebook computers, super mobile On personal computers (ultra-mobile personal computer, UMPC), netbooks, personal digital assistants (personal digital assistant, PDA), smart watches, smart bracelets, servers and other electronic devices, the embodiments of this application do not make any specific types of electronic devices. limit.
  • the electronic device may be a station (STATION, ST) in a WLAN, may be a cellular phone, a cordless phone, a Session Initiation Protocol (Session Initiation Protocol, SIP) phone, a wireless local loop (Wireless Local Loop, WLL) station , Personal Digital Assistant (PDA) equipment, handheld devices with wireless communication capabilities, computing devices or other processing devices connected to wireless modems, computers, laptop computers, handheld communication devices, handheld computing devices, And/or other devices used to communicate on wireless systems and next-generation communication systems, for example, mobile terminals in 5G networks or mobile terminals in future evolved Public Land Mobile Network (Public Land Mobile Network, PLMN) networks, etc. .
  • PLMN Public Land Mobile Network
  • the wearable device can also be a general term for wearable devices that are intelligently designed for daily wear and developed by applying wearable technology, such as glasses, gloves, Watches, clothing and shoes, etc.
  • a wearable device is a portable device that is directly worn on the body, or integrated into the user's clothing or accessories, and collects the user's biometric data, such as the user's heart rate, by attaching to the user's body.
  • Wearable devices are not only a hardware device, but also achieve powerful functions through software support, data interaction, and cloud interaction.
  • Generalized wearable smart devices include full-featured, large-sized, complete or partial functions without relying on smart phones, such as smart watches or smart glasses, etc., and only focus on a certain type of application functions, and need to be used in conjunction with other devices such as smart phones , such as various smart bracelets and smart jewelry with unlockable touch screens.
  • FIG. 27 shows a schematic structural diagram of the electronic device 100 .
  • the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (universal serial bus, USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, and an antenna 2 , mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, earphone jack 170D, sensor module 180, button 190, motor 191, indicator 192, camera 193, display screen 194, and A subscriber identification module (subscriber identification module, SIM) card interface 195 and the like.
  • SIM subscriber identification module
  • the sensor module 180 may include a motion sensor, wherein the motion sensor may include a pressure sensor 180A, a gyroscope sensor 180B, and an acceleration sensor 180E.
  • the sensor module 180 may also include an air pressure sensor 180C, a magnetic sensor 180D, a distance sensor 180F, and a proximity light sensor. 180G, fingerprint sensor 180H, temperature sensor 180J, touch sensor 180K, ambient light sensor 180L, bone conduction sensor 180M, etc.
  • the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the electronic device 100 .
  • the electronic device 100 may include more or fewer components than shown in the figure, or combine certain components, or separate certain components, or arrange different components.
  • the illustrated components can be realized in hardware, software or a combination of software and hardware.
  • the processor 110 may include one or more processing units, for example: the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processing unit (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), controller, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural network processor (neural-network processing unit, NPU), etc. Wherein, different processing units may be independent devices, or may be integrated in one or more processors.
  • application processor application processor, AP
  • modem processor graphics processing unit
  • GPU graphics processing unit
  • image signal processor image signal processor
  • ISP image signal processor
  • controller video codec
  • digital signal processor digital signal processor
  • baseband processor baseband processor
  • neural network processor neural-network processing unit
  • the processor can be used to execute the operations of S202 and S203, the operations of S2021 ⁇ S2023, the operations of S2021' ⁇ S2022' in the first embodiment, and can also be used to execute the operations of S1301 ⁇ S1303 in the second embodiment,
  • the operations of S1301.1-S1301.3 and the operations of S1302.1-S1302.3 may also be used to execute the operations of S1803 and S1803.1-S1803.2 in the third embodiment.
  • the controller can generate an operation control signal according to the instruction opcode and timing signal, and complete the control of fetching and executing the instruction.
  • a memory may also be provided in the processor 110 for storing instructions and data, such as user's exercise data, a generated training plan, a created training course library, and the like.
  • the memory in processor 110 is a cache memory.
  • the memory may hold instructions or data that the processor 110 has just used or recycled. If the processor 110 needs to use the instruction or data again, it can be called directly from the memory. Repeated access is avoided, and the waiting time of the processor 110 is reduced, thereby improving the efficiency of the system.
  • processor 110 may include one or more interfaces.
  • the interface may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous transmitter (universal asynchronous receiver/transmitter, UART) interface, mobile industry processor interface (mobile industry processor interface, MIPI), general-purpose input and output (general-purpose input/output, GPIO) interface, subscriber identity module (subscriber identity module, SIM) interface, and /or universal serial bus (universal serial bus, USB) interface, etc.
  • I2C integrated circuit
  • I2S integrated circuit built-in audio
  • PCM pulse code modulation
  • PCM pulse code modulation
  • UART universal asynchronous transmitter
  • MIPI mobile industry processor interface
  • GPIO general-purpose input and output
  • subscriber identity module subscriber identity module
  • SIM subscriber identity module
  • USB universal serial bus
  • the I2C interface is a bidirectional synchronous serial bus, including a serial data line (serial data line, SDA) and a serial clock line (derail clock line, SCL).
  • processor 110 may include multiple sets of I2C buses.
  • the processor 110 can be respectively coupled to the touch sensor 180K, the charger, the flashlight, the camera 193 and the like through different I2C bus interfaces.
  • the processor 110 may be coupled to the touch sensor 180K through the I2C interface, so that the processor 110 and the touch sensor 180K communicate through the I2C bus interface to realize the touch function of the electronic device 100 .
  • the PCM interface can also be used for audio communication, sampling, quantizing and encoding the analog signal.
  • the audio module 170 and the wireless communication module 160 may be coupled through a PCM bus interface.
  • the audio module 170 can also transmit audio signals to the wireless communication module 160 through the PCM interface, so as to realize the function of answering calls through the Bluetooth headset. Both the I2S interface and the PCM interface can be used for audio communication.
  • the UART interface is a universal serial data bus used for asynchronous communication.
  • the bus can be a bidirectional communication bus. It converts the data to be transmitted between serial communication and parallel communication.
  • a UART interface is generally used to connect the processor 110 and the wireless communication module 160 .
  • the processor 110 communicates with the Bluetooth module in the wireless communication module 160 through the UART interface to realize the Bluetooth function.
  • the audio module 170 can transmit audio signals to the wireless communication module 160 through the UART interface, so as to realize the function of playing music through the Bluetooth headset.
  • the GPIO interface can be configured by software.
  • the GPIO interface can be configured as a control signal or as a data signal.
  • the GPIO interface can be used to connect the processor 110 with the camera 193 , the display screen 194 , the wireless communication module 160 , the audio module 170 , the sensor module 180 and so on.
  • the GPIO interface can also be configured as an I2C interface, I2S interface, UART interface, MIPI interface, etc.
  • the interface connection relationship between the modules shown in the embodiment of the present application is only a schematic illustration, and does not constitute a structural limitation of the electronic device 100 .
  • the electronic device 100 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.
  • the wireless communication function of the electronic device 100 can be realized by the antenna 1 , the antenna 2 , the mobile communication module 150 , the wireless communication module 160 , a modem processor, a baseband processor, and the like.
  • the wireless communication module 160 can provide wireless local area networks (wireless local area networks, WLAN) (such as wireless fidelity (Wireless Fidelity, Wi-Fi) network), bluetooth (bluetooth, BT), global navigation satellite, etc. applied on the electronic device 100.
  • System global navigation satellite system, GNSS
  • frequency modulation frequency modulation, FM
  • near field communication technology near field communication, NFC
  • infrared technology infrared, IR
  • the wireless communication module 160 may be one or more devices integrating at least one communication processing module.
  • the wireless communication module 160 receives electromagnetic waves via the antenna 2 , frequency-modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110 .
  • the wireless communication module 160 can also receive the signal to be sent from the processor 110 , frequency-modulate it, amplify it, and convert it into electromagnetic waves through the antenna 2 for radiation.
  • the antenna 1 of the electronic device 100 is coupled to the mobile communication module 150, and the antenna 2 is coupled to the wireless communication module 160, so that the electronic device 100 can communicate with the network and other devices through wireless communication technology.
  • the wireless communication technology may include global system for mobile communications (GSM), general packet radio service (general packet radio service, GPRS), code division multiple access (code division multiple access, CDMA), broadband Code division multiple access (wideband code division multiple access, WCDMA), time division code division multiple access (time-division code division multiple access, TD-SCDMA), long term evolution (long term evolution, LTE), BT, GNSS, WLAN, NFC , FM, and/or IR techniques, etc.
  • GSM global system for mobile communications
  • GPRS general packet radio service
  • code division multiple access code division multiple access
  • CDMA broadband Code division multiple access
  • WCDMA wideband code division multiple access
  • time division code division multiple access time-division code division multiple access
  • TD-SCDMA time-division code division multiple access
  • the GNSS may include a global positioning system (global positioning system, GPS), a global navigation satellite system (global navigation satellite system, GLONASS), a Beidou navigation satellite system (beidou navigation satellite system, BDS), a quasi-zenith satellite system (quasi -zenith satellite system (QZSS) and/or satellite based augmentation systems (SBAS).
  • GPS global positioning system
  • GLONASS global navigation satellite system
  • Beidou navigation satellite system beidou navigation satellite system
  • BDS Beidou navigation satellite system
  • QZSS quasi-zenith satellite system
  • SBAS satellite based augmentation systems
  • the internal memory 121 may be used to store computer-executable program codes including instructions.
  • the internal memory 121 may include an area for storing programs and an area for storing data.
  • the storage program area can store the operating system, at least one application program required by the function (such as the wireless connection function, the vibration wave generation function, the adjustment program of the training plan provided by the embodiment of the present application, the generation program of the training plan, etc.) and the like.
  • the storage data area can store data created during the use of the electronic device 100 (such as audio data, phone book, and can also store motion data obtained from target data sources, generated training plans, plan templates, etc. as in the embodiment of the application. training course framework, training category library, training courses, user information input by the user, subjective exercise parameters fed back, etc.) etc.
  • the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, universal flash storage (universal flash storage, UFS) and the like.
  • the processor 110 executes various functional applications and data processing of the electronic device 100 by executing instructions stored in the internal memory 121 and/or instructions stored in a memory provided in the processor.
  • the pressure sensor 180A is used to sense the pressure signal and convert the pressure signal into an electrical signal.
  • pressure sensor 180A may be disposed on display screen 194 .
  • pressure sensors 180A such as resistive pressure sensors, inductive pressure sensors, and capacitive pressure sensors.
  • a capacitive pressure sensor may be comprised of at least two parallel plates with conductive material.
  • the electronic device 100 determines the intensity of pressure according to the change in capacitance.
  • the electronic device 100 detects the intensity of the touch operation according to the pressure sensor 180A.
  • the electronic device 100 may also calculate the touched position according to the detection signal of the pressure sensor 180A.
  • touch operations acting on the same touch position but with different touch operation intensities may correspond to different operation instructions. For example: when a touch operation with a touch operation intensity less than the first pressure threshold acts on the short message application icon, execute the instruction of viewing the short message. When a touch operation whose intensity is greater than or equal to the first pressure threshold acts on the icon of the short message application, the instruction of creating a new short message is executed.
  • the gyro sensor 180B can be used to determine the motion posture of the electronic device 100 .
  • the angular velocity of the electronic device 100 around three axes may be determined by the gyro sensor 180B.
  • the gyro sensor 180B can be used for image stabilization. Exemplarily, when the shutter is pressed, the gyro sensor 180B detects the shaking angle of the electronic device 100, calculates the distance that the lens module needs to compensate according to the angle, and allows the lens to counteract the shaking of the electronic device 100 through reverse movement to achieve anti-shake.
  • the gyro sensor 180B can also be used for navigation and somatosensory game scenes.
  • the acceleration sensor 180E can detect the acceleration of the electronic device 100 in various directions (generally three axes). When the electronic device 100 is stationary, the magnitude and direction of gravity can be detected. It can also be used to identify the posture of electronic devices, and can be used in applications such as horizontal and vertical screen switching, pedometers, etc.
  • the distance sensor 180F is used to measure the distance.
  • the electronic device 100 may measure the distance by infrared or laser. In some embodiments, when shooting a scene, the electronic device 100 may use the distance sensor 180F for distance measurement to achieve fast focusing.
  • the keys 190 include a power key, a volume key and the like.
  • the key 190 may be a mechanical key. It can also be a touch button.
  • the electronic device 100 can receive key input and generate key signal input related to user settings and function control of the electronic device 100 .
  • the motor 191 can generate a vibration prompt, such as a vibration signal in this application.
  • the motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback.
  • touch operations applied to different applications may correspond to different vibration feedback effects.
  • the motor 191 may also correspond to different vibration feedback effects for touch operations acting on different areas of the display screen 194 .
  • Different application scenarios for example: time reminder, receiving information, alarm clock, games, etc.
  • the touch vibration feedback effect can also support customization.
  • the software system of the electronic device 100 may adopt a layered architecture, an event-driven architecture, a micro-kernel architecture, a micro-service architecture, or a cloud architecture.
  • the embodiment of the present application takes the Android system with a layered architecture as an example to illustrate the software structure of the electronic device 100 .
  • FIG. 28 is a block diagram of the software structure of the electronic device 100 according to the embodiment of the present application.
  • the layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Layers communicate through software interfaces.
  • the Android system is divided into four layers, which are respectively the application program layer, the application program framework layer, the Android runtime (Android runtime) and the system library, and the kernel layer from top to bottom.
  • the application layer can consist of a series of application packages.
  • the application package can include applications such as camera, calendar, map, mailbox, WLAN, Bluetooth, music, video, short message, WeChat, WPS, etc. Further, the above application package can also include The training management program provided by the example is used to generate a training plan and adjust the training plan through the training management program.
  • the application framework layer provides an application programming interface (application programming interface, API) and a programming framework for applications in the application layer.
  • the application framework layer includes some predefined functions.
  • the application framework layer can include window manager, content provider, view system, phone manager, resource manager, notification manager, etc.
  • a window manager is used to manage window programs.
  • the window manager can obtain the size of the display screen, determine whether there is a status bar, lock the screen, capture the screen, etc.
  • Content providers are used to store and retrieve data and make it accessible to applications.
  • Said data may include video, images, audio, calls made and received, browsing history and bookmarks, phonebook, etc.
  • the view system includes visual controls, such as controls for displaying text, controls for displaying pictures, and so on.
  • the view system can be used to build applications.
  • a display interface can consist of one or more views.
  • the display interface that includes a text message notification icon may include a view for displaying text and a view for displaying pictures, and may also include a sports data authorization interface, a training purpose setting interface, a subjective parameter collection page, and a training report as provided in the embodiments of the present application. interface etc.
  • the phone manager is used to provide communication functions of the electronic device 100 . For example, the management of call status (including connected, hung up, etc.).
  • the resource manager provides various resources to the application, such as localized strings, icons, images, layout files, video files, motion data obtained from target data sources, and so on.
  • the notification manager enables the application to display notification information in the status bar, which can be used to convey notification-type messages, and can automatically disappear after a short stay without user interaction.
  • the notification manager is used to notify the download completion, message reminder, authorization information of sports data, etc.
  • the notification manager can also be a notification that appears on the top status bar of the system in the form of a chart or scroll bar text, such as a notification of an application running in the background, or a notification that appears on the screen in the form of a dialog window.
  • prompting text information in the status bar issuing a prompt sound, vibrating the electronic device, and flashing the indicator light, etc.
  • the Android Runtime includes core library and virtual machine. The Android runtime is responsible for the scheduling and management of the Android system.
  • the core library consists of two parts: one part is the function function that the java language needs to call, and the other part is the core library of Android.
  • the application layer and the application framework layer run in virtual machines.
  • the virtual machine executes the java files of the application program layer and the application program framework layer as binary files.
  • the virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.
  • a system library can include multiple function modules. For example: surface manager (surface manager), media library (Media Libraries), 3D graphics processing library (eg: OpenGL ES), 2D graphics engine (eg: SGL), etc.
  • the surface manager is used to manage the display subsystem and provides the fusion of 2D and 3D layers for multiple applications.
  • the media library supports playback and recording of various commonly used audio and video formats, as well as still image files, etc.
  • the media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.
  • the 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing and layer processing, etc.
  • 2D graphics engine is a drawing engine for 2D drawing.
  • the kernel layer is the layer between hardware and software.
  • the kernel layer includes at least a display driver, a camera driver, an audio driver, and a sensor driver.
  • a corresponding hardware interrupt is sent to the kernel layer.
  • the kernel layer processes touch operations into original input events (including touch coordinates, time stamps of touch operations, and other information).
  • Raw input events are stored at the kernel level.
  • the application framework layer obtains the original input event from the kernel layer, and identifies the control corresponding to the input event.
  • the training management application calls the application
  • the interface of the frame layer starts the bluetooth communication module, and then starts the bluetooth driver in the wireless communication module 160 by calling the kernel layer, establishes a wireless connection with the smart watch through the bluetooth in the wireless communication module 160, and obtains motion data from the smart watch, and
  • the I2C interface between the wireless communication module 160 and the processor 110 the exercise data is transmitted to the processor 110, and the processor 110 can generate a user's training plan according to the received exercise data.
  • the embodiment of the present application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and operable on the at least one processor, and the processor executes The computer program implements the steps in any of the above method embodiments.
  • the embodiment of the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in each of the foregoing method embodiments can be realized.
  • An embodiment of the present application provides a computer program product.
  • the computer program product When the computer program product is run on a mobile terminal, the mobile terminal can implement the steps in the foregoing method embodiments when executed.
  • the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the procedures in the methods of the above embodiments in the present application can be completed by instructing related hardware through computer programs, and the computer programs can be stored in a computer-readable storage medium.
  • the computer program When executed by a processor, the steps in the above-mentioned various method embodiments can be realized.
  • the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form.
  • the computer-readable medium may at least include: any entity or device capable of carrying computer program codes to the photographing device/electronic device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium.
  • ROM read-only memory
  • RAM random access memory
  • electrical carrier signal telecommunication signal and software distribution medium.
  • U disk mobile hard disk
  • magnetic disk or optical disk etc.
  • computer readable media may not be electrical carrier signals and telecommunication signals under legislation and patent practice.
  • the disclosed device/network device and method may be implemented in other ways.
  • the device/network device embodiments described above are only illustrative.
  • the division of the modules or units is only a logical function division.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Abstract

本申请适用于数据处理技术领域，提供了训练计划的生成方法、装置、电子设备及可读存储介质，该方法包括：获取用户的多个运动数据；基于多个所述运动数据确定所述用户对应的运动员类型；基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划。本申请提供的技术方案可以通过获取用户在历史运动过程中的运动数据，确定用户的运动员类型，并基于该运动员类型识别得到用户在进行训练时对应的训练方向，并生成与训练方向相匹配的训练计划，能够生成与用户的运动能力相适应的训练计划，提高了生成的训练计划的准确性。

Description

训练计划的生成方法、装置、电子设备及可读存储介质
本申请要求于2021年08月23日提交国家知识产权局、申请号为202110972020.5、申请名称为“训练计划的生成方法、装置、电子设备及可读存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请属于数据处理技术领域，尤其涉及一种训练计划的生成方法、装置、电子设备以及可读存储介质。
背景技术
随着人们生活水平的提高，人们越来越重视身体健康，人们自发性的运动行为也随之增加。为了健康、有效地提高身体素质，用户可以通过聘请私人教练或参加健身机构开展的训练课程等方式开展训练活动。然而，上述方式要求用户去到指定的训练场所才能够进行相关的训练，灵活性较低。为了满足人们随时随运动的需求，并且能够实现健康系统地进行训练，与运动训练相关的智能应用也随之涌现。
现有训练计划的生成技术，一般是预先设置好固定的训练计划模板，并建立个人信息与训练计划模板的映射关系，然后采集用户的个人信息，如身高、体重以及年龄等，基于采集的个人信息以及所述映射关系，确定对应的训练计划。现有技术只是按照用户的个人信息和固定的训练计划模板来确定训练计划，方式单一，降低了训练计划的准确性和有效性。
发明内容
本申请实施例提供了一种训练计划的生成方法、调整方法、生成装置、调整装置、电子设备以及可读存储介质，可以有效提高训练计划的准确性和有效性。
第一方面，本申请实施例提供了一种无线连接的方法，包括：
获取用户的多个运动数据；
基于多个所述运动数据确定所述用户对应的运动员类型；
基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划。
实施本申请实施例具有以下有益效果：可以通过获取用户在历史运动过程中的运动数据，确定用户的运动员类型，并基于该运动员类型识别得到用户在进行训练时对应的训练方向，并生成与训练方向相匹配的训练计划，能够生成与用户的运动能力相适应的训练计划。由于用户的个体参数无法直接体现用户的运动能力，在基于个体参数生成的训练计划可能与用户的运动能力不匹配，而用户在历史的运动活动中采集的运动数据，能够体现用户实际的运动能力，基于用户在历史运动中的表现确定用户的运动员类型，能够提高训练计划与用户的实际运动能力之间的匹配程度，使得生成的训练计划能够更加有针对性地指导用户开展运动训练，提高了生成的训练计划的准确性。
在第一方面的一种可能实现方式中，获取的多个所述运动数据包含多个运动项目 的运动数据，则所述基于多个所述运动数据确定所述用户对应的运动员类型，包括：
分别根据各个所述运动项目关联的所述运动数据，确定所述运动项目对应的最佳运动成绩；
将所述最佳运动成绩导入到所述运动项目对应的归一化算法，确定所述运动项目对应的归一化参量；
基于各个运动项目的归一化参量，确定所述用户的所述运动员类型。
在第一方面的一种可能实现方式中，所述分别根据各个所述运动项目关联的所述运动数据，确定所述运动项目对应的最佳运动成绩，包括：
确定所述运动项目对应的理想心率；所述理想心率具体是用户在全力运动状态下对应的心率；
根据所述运动数据中的实际心率以及所述理想心率，确定所述运动数据关联的强度系数；
根据所述强度系数以及所述实际运动成绩，确定所述运动项目对应的所述最佳运动成绩。
在第一方面的一种可能实现方式中，所述获取用户的多个运动数据，包括：
生成包含至少一个可选数据来源的运动数据授权界面；
响应于用户基于所述运动数据授权界面的确认操作，从所述可选数据来源中确定目标数据来源；
从所述目标数据来源获取所述运动数据。
在第一方面的一种可能实现方式中，在所述基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划之后，还包括：
显示所述用户对应的训练报告；所述训练报告包含所述训练计划以及关于所述运动员类型以及所述训练方向的描述语段。
在第一方面的一种可能实现方式中，所述基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划，包括：
根据所述训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
在第一方面的一种可能实现方式中，所述确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程，包括：
基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
在第一方面的一种可能实现方式中，所述根据所述训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长，包括：
获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
基于所述训练方向，确定各个所述训练阶段的时长比例；
根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
在第一方面的一种可能实现方式中，在所述获取与所述用户的训练目的对应的所述计划模板之前，还包括：
生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；
响应于所述用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；
基于各个所述运动项目的所述目标值，得到所述训练目的。
在第一方面的一种可能实现方式中，在所述基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划之后，还包括：
若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第一方面的一种可能实现方式中，在所述若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面之前，还包括：
获取所述用户基于所述任一训练课程进行训练时对应的训练压力值；
对应地，所述根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第一方面的一种可能实现方式中，所述获取所述用户基于所述任一训练课程进行训练时对应的训练压力值，包括：
获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
基于所述实时数据确定所述训练课程对应的所述训练压力值。
在第一方面的一种可能实现方式中，所述根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
第二方面，本申请实施例提供了一种训练计划的生成装置，包括：
运动数据获取单元，用于获取用户的多个运动数据；
运动员类型确定单元，用于基于多个所述运动数据确定所述用户对应的运动员类型；
训练计划生成单元，用于基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划。
在第二方面的一种可能实现方式中，获取的多个所述运动数据包含多个运动项目的运动数据，所述运动员类型确定单元，包括：
最佳运动成绩确定单元，用于分别根据各个所述运动项目关联的所述运动数据，确定所述运动项目对应的最佳运动成绩；
归一化参量确定单元，将所述最佳运动成绩导入到所述运动项目对应的归一化算法，确定所述运动项目对应的归一化参量；
运动员类型识别单元，用于基于各个运动项目的归一化参量，确定所述用户的所述运动员类型。
在第二方面的一种可能实现方式中，所述最佳运动成绩确定单元，包括：
理想心率确定单元，用于确定所述运动项目对应的理想心率；所述理想心率具体是用户在全力运动状态下对应的心率；
强度系数确定单元，用于根据所述运动数据中的实际心率以及所述理想心率，确定所述运动数据关联的强度系数；
最佳运动成绩计算单元，用于根据所述强度系数以及所述实际运动成绩，确定所述运动项目对应的所述最佳运动成绩。
在第二方面的一种可能实现方式中，所述运动数据获取单元，包括：
运动数据授权界面生成单元，用于生成包含至少一个可选数据来源的运动数据授权界面；
确认操作响应单元，用于响应于用户基于所述运动数据授权界面的确认操作，从所述可选数据来源中确定目标数据来源；
数据获取单元，用于基于所述授权请求从所述目标数据来源获取所述运动数据。
在第二方面的一种可能实现方式中，所述训练计划的生成装置还包括：
训练报告显示单元，用于显示所述用户对应的训练报告；所述训练报告包含所述训练计划以及关于所述运动员类型以及所述训练方向的描述语段。
在第二方面的一种可能实现方式中，所述训练计划生成单元，包括：
阶段周期时长确定单元，用于根据所述训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
训练课程确定单元，用于确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
训练课程封装单元，用于根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
在第二方面的一种可能实现方式中，所述训练课程确定单元，包括：
训练类别库配置单元，用于基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
训练课程框架确定单元，用于根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
训练课程选取单元，用于从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
在第二方面的一种可能实现方式中，所述阶段周期时长确定单元，包括：
计划模板获取单元，用于获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
时长比例确定单元，用于基于所述训练方向，确定各个所述训练阶段的时长比例；
训练总时长分配单元，用于根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
在第二方面的一种可能实现方式中，所述训练计划的生成装置还包括：
设置界面显示单元，用于生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；
设置操作响应单元，用于响应于所述用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；
训练目的确定单元，用于基于各个所述运动项目的所述目标值，得到所述训练目的。
在第二方面的一种可能实现方式中，所述训练计划的生成装置，还包括：
主观运动参数确定单元，用于若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
训练计划调整单元，用于根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第二方面的一种可能实现方式中，所述训练计划的生成装置，还包括：
训练压力值获取单元，用于获取所述用户基于所述训练计划中任一训练课程进行训练时对应的训练压力值；
训练计划调整单元具体用于，根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第二方面的一种可能实现方式中，所述训练压力值获取单元，包括：
实时数据获取单元，用于获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
实时数据转换单元，用于基于所述实时数据确定所述训练课程对应的所述训练压力值。
在第二方面的一种可能实现方式中，所述训练计划调整单元，包括：
计划调整方向确定单元，用于若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
训练课程调整单元，用于基于所述计划调整方向对所述训练计划中在所述调整触 发时刻后的训练课程进行调整，得到所述调整后的训练计划。
第三方面，本申请实施例提供了一种训练计划的生成方法，包括：
根据用户的训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
在第三方面的一种可能实现方式中，所述确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程，包括：
基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
在第三方面的一种可能实现方式中，所述根据用户的训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长，包括：
获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
基于所述训练方向，确定各个所述训练阶段的时长比例；
根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
在第三方面的一种可能实现方式中，在所述获取与所述用户的训练目的对应的所述计划模板之前，还包括：
生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；
响应于所述用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；
基于各个所述运动项目的所述目标值，得到所述训练目的。
在第三方面的一种可能实现方式中，在所述根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划之后，还包括：
若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第三方面的一种可能实现方式中，在所述若检测到任一训练课程已完成，则生成主观参数采集页面之前，还包括：
获取所述用户基于所述任一训练课程进行训练时对应的训练压力值；
对应地，所述根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第三方面的一种可能实现方式中，所述获取所述用户基于所述任一训练课程进行训练时对应的训练压力值，包括：
获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
基于所述实时数据确定所述训练课程对应的所述训练压力值。
在第三方面的一种可能实现方式中，所述根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
第四方面，本申请实施例提供了一种训练计划的生成装置，包括：
阶段周期时长确定单元，用于根据用户的训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
训练课程确定单元，用于确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
训练课程封装单元，用于根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
在第四方面的一种可能实现方式中，所述训练课程确定单元，包括：
训练类别库配置单元，用于基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
训练课程框架确定单元，用于根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
训练课程选取单元，用于从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
在第四方面的一种可能实现方式中，所述阶段周期时长确定单元，包括：
计划模板获取单元，用于获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
时长比例确定单元，用于基于所述训练方向，确定各个所述训练阶段的时长比例；
训练总时长分配单元，用于根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
在第四方面的一种可能实现方式中，所述训练计划的生成装置还包括：
设置界面显示单元，用于生成训练目的设置界面；所述训练目的设置界面内包含 至少一个运动项目的目的设置区域；
设置操作响应单元，用于响应于所述用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；
训练目的确定单元，用于基于各个所述运动项目的所述目标值，得到所述训练目的。
在第四方面的一种可能实现方式中，所述训练计划的生成装置，还包括：
主观运动参数确定单元，用于若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
训练计划调整单元，用于根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第四方面的一种可能实现方式中，所述训练计划的生成装置，还包括：
训练压力值获取单元，用于获取所述用户基于所述训练计划中任一训练课程进行训练时对应的训练压力值；
训练计划调整单元具体用于，根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第四方面的一种可能实现方式中，所述训练压力值获取单元，包括：
实时数据获取单元，用于获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
实时数据转换单元，用于基于所述实时数据确定所述训练课程对应的所述训练压力值。
在第四方面的一种可能实现方式中，所述训练计划调整单元，包括：
计划调整方向确定单元，用于若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
训练课程调整单元，用于基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
第五方面，本申请实施例提供了一种训练计划的调整方法，包括：
若检测到训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第五方面的一种可能实现方式中，在所述若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面之前，还包括：
获取所述用户基于所述任一训练课程进行训练时对应的训练压力值；
对应地，所述根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整 后的训练计划。
在第五方面的一种可能实现方式中，所述获取所述用户基于所述任一训练课程进行训练时对应的训练压力值，包括：
获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
基于所述实时数据确定所述训练课程对应的所述训练压力值。
在第五方面的一种可能实现方式中，所述根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
第六方面，本申请实施例提供了一种训练计划的调整装置，包括：
主观运动参数确定单元，用于若检测到训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
训练计划调整单元，用于根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第六方面的一种可能实现方式中，所述训练计划的调整装置还包括：
训练压力值获取单元，用于获取所述用户基于所述训练计划中任一训练课程进行训练时对应的训练压力值；
训练计划调整单元具体用于，根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在第六方面的一种可能实现方式中，所述训练压力值获取单元，包括：
实时数据获取单元，用于获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
实时数据转换单元，用于基于所述实时数据确定所述训练课程对应的所述训练压力值。
在第六方面的一种可能实现方式中，所述训练计划调整单元，包括：
计划调整方向确定单元，用于若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
训练课程调整单元，用于基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
第七方面，本申请实施例提供了一种电子设备，存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现上述第一方面或第三方面中任一项所述训练计划的生成方法，或第五方面中任一项所述训练计划的调整方法。
第八方面，本申请实施例提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现上述第一 方面或第三方面中任一项所述训练计划的生成方法，或第五方面中任一项所述训练计划的调整方法。
第九方面，本申请实施例提供了一种计算机程序产品，当计算机程序产品在电子设备上运行时，使得电子设备执行上述第一方面或第三方面中任一项所述训练计划的生成方法，或第五方面中任一项所述训练计划的调整方法。
第十方面，本申请实施例提供一种芯片系统，包括处理器，处理器与存储器耦合，所述处理器执行存储器中存储的计算机程序，以实现如上述第一方面或第三方面中任一项所述训练计划的生成方法，或第五方面中任一项所述训练计划的调整方法。
可以理解的是，上述第二方面至第十方面的有益效果可以参见上述第一方面中的相关描述，在此不再赘述。
附图说明
图1是现有的训练计划生成的示意图；
图2是本申请一实施例提供的训练计划的生成方法的实现流程图；
图3是本申请一实施例提供的运动数据的获取示意图；
图4是本申请一实施例提供的信息输入界面的示意图；
图5是本申请一实施例提供的运动数据的授权过程示意图；
图6是本申请一实施例提供的跑步运动场景的示意图；
图7是本申请一实施例提供的运动数据的合并示意图；
图8是本申请一实施例提供的最佳运动成绩的计算示意图；
图9是本申请一实施例提供的归一化算法的示意图；
图10是本申请一实施例提供的运动员类型的对应关系图；
图11是本申请一实施例提供的训练计划显示过程的示意图；
图12是本申请一实施例提供的训练计划查询的示意图；
图13是本申请另一实施例提供的训练计划的生成方法的实现流程图；
图14是本申请一实施例提供的训练阶段的划分示意图；
图15是本申请一实施例提供的训练总时长的设置示意图；
图16是本申请一实施例提供的训练课程的选取示意图；
图17是本申请一实施例提供的训练日历界面的示意图；
图18是本申请一实施例提供的训练计划的调整方法的实现流程图；
图19是本申请一实施例提供的主观参数采集页面的示意图；
图20是本申请一实施例提供的训练计划的调整方向的示意图；
图21是本申请一实施例提供的训练课程的调整示意图；
图22是本申请一实施例提供的训练计划的调整示意图；
图23是本申请实施例提供的训练计划的生成装置的结构框图；
图24是本申请另一实施例提供的训练计划的生成装置的结构框图；
图25是本申请实施例提供的训练计划的生成装置的结构框图；
图26是本申请实施例提供的训练计划的调整装置的结构框图；
图27是本申请实施例提供的电子设备的硬件结构示意图；
图28是本申请实施例的电子设备的软件结构框图。
具体实施方式
以下描述中，为了说明而不是为了限定，提出了诸如特定系统结构、技术之类的具体细节，以便透彻理解本申请实施例。然而，本领域的技术人员应当清楚，在没有这些具体细节的其它实施例中也可以实现本申请。在其它情况中，省略对众所周知的系统、装置、电路以及方法的详细说明，以免不必要的细节妨碍本申请的描述。
应当理解，当在本申请说明书和所附权利要求书中使用时，术语“包括”指示所描述特征、整体、步骤、操作、元素和/或组件的存在，但并不排除一个或多个其它特征、整体、步骤、操作、元素、组件和/或其集合的存在或添加。
还应当理解，在本申请说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
如在本申请说明书和所附权利要求书中所使用的那样，术语“如果”可以依据上下文被解释为“当...时”或“一旦”或“响应于确定”或“响应于检测到”。类似地，短语“如果确定”或“如果检测到[所描述条件或事件]”可以依据上下文被解释为意指“一旦确定”或“响应于确定”或“一旦检测到[所描述条件或事件]”或“响应于检测到[所描述条件或事件]”。
另外，在本申请说明书和所附权利要求书的描述中，术语“第一”、“第二”、“第三”等仅用于区分描述，而不能理解为指示或暗示相对重要性。
在本申请说明书中描述的参考“一个实施例”或“一些实施例”等意味着在本申请的一个或多个实施例中包括结合该实施例描述的特定特征、结构或特点。由此，在本说明书中的不同之处出现的语句“在一个实施例中”、“在一些实施例中”、“在其他一些实施例中”、“在另外一些实施例中”等不是必然都参考相同的实施例，而是意味着“一个或多个但不是所有的实施例”，除非是以其他方式另外特别强调。术语“包括”、“包含”、“具有”及它们的变形都意味着“包括但不限于”，除非是以其他方式另外特别强调。
随着人们对于身体健康的重视程度不断提高，如何能够有效系统地开展训练运动则成为了亟需解决的问题之一。特别全民体育的概念不断普及，运动领域中的业余选手与专业选手之间的界限越来越模糊，人们在训练时，不仅限于强身健体，还希望能够参与运动相关的比赛，而上述目标的实现，更离不开专业系统的训练计划的指定。以马拉松运动为例，由于马拉松具有距离长、体能消耗大、持续时间长等特点，对于未曾接触长跑的用户而言，具有一定的风险，属于一个入门门槛较高的运动。若用户计划参加一个马拉松比赛，则需要提前一定的时间进行针对性训练，此时，用户则需要一个可靠且便捷的方式对其进行训练指导，安排相应的训练计划。
现有的训练计划的生成技术，主要可以包括以下两种：
方式1，通过采集用户的个体参数生成训练计划。用户可以将生成训练计划的应用程序安装于用户的智能手机上，通过运行该生成训练计划的应用程序，可以生成一个用于输入用户的个体参数的输入界面。示例性地，图1示出了现有的训练计划生成的示意图。参见图1中的(a)所示，输入个体参数的输入界面内，需要用户填写以下参数项，分别为：年龄、身高、体重、性别以及体脂率，并基于用户填写的相关数据，选取与其身体素质相对应的训练课程，生成对应的训练计划，如图1中的(b)所示。 由此可见，通过用户的个体参数生成训练计划，只需采集不同的年龄、身高、体重以及性别等的个体参数，并进行有限的排列组合，并为不同的组合关联对应的训练课程，即可生成对应的训练计划。
然而该方式，只是考虑用户的个体参数，即确定对应的训练计划，生成的训练计划的准确率较低。由于决定用户间运动能力的差异，除了与用户的个体参数相关外，还与用户的运动意愿、运动目标以及与相关运动的熟练程度等多个因素相关。上述方式只是考虑个体参数间的差异，确定训练计划的因素过于单一，从而无法有效准确地指导用户开展训练。
方式2，通过采集用户运动过程中的生物体征指标是否超过人体极限值，以确定是否需要对训练计划进行调整。该方式2是对方式1的进一步优化。用户可以在智能手机上录入个体参数，并通过智能手机上安装的相关应用程序生成对应的训练计划，并基于训练计划进行训练。在用户训练的过程中，可以通过佩戴智能手表或智能手环的方式，获取用户在基于训练计划进行训练时的生物体征参数。若检测到用户的生物体征参数超过了人体极限值，如在进行跑步训练时，检测用户的心率超过人体的正常心率范围，在该情况下，则会判定该训练计划超出用户的承受范围，对已经创建的训练计划进行调整。该方式能够在用户训练过程中出现异常情况后，对训练计划进行优化调整，以提高训练计划与用户之间的匹配程度。
虽然该方式能够采集用户在运动过程中的生物特征指标，实现对已经生成的训练计划进行调整优化的目的，以提高训练计划与用户之间的契合度，但是调整的触发条件是在用户的生物特征指标超过人体极限的情况下才进行调整，而往往用户的生物特征指标超过人体极限时，已经具有一定的健康风险，由此可见，上述优化调整的发起难度较大，若将触发的阈值由人体阈值降低到某一预设阈值，也可能会出现频繁对训练计划调整的情况，降低了训练计划的稳定性，不利于用户对训练运动进行安排。
由此可见，现有的训练计划的生成技术，训练计划与用户之间的契合度较低，训练计划的准确性较低，并且对于训练计划的调整以及优化手段，无法兼顾优化及时性以及计划稳定性两个方面。因此，为了解决上述训练计划的准确性低缺陷，本申请提供一种训练计划的生成方法，通过确定用户的训练侧重点，继而从课程数据库内，获取与用户的训练侧重点相匹配的训练课程，从而生成用户使用的训练计划，以提高训练计划的准确性，并且在用户基于训练计划开展训练的过程中，获取用户的生物特征指标以及用户在运动过程中的主观感受指标，以通过上述两类型的参数对训练计划进行优化，提高了优化操作的准确性，也能够减少无效优化的情况发生。
实施例一：
在本申请实施例中，流程的执行主体为电子设备，该电子设备包括但不限于：计算机、智能手机、笔记本电脑、平板电脑、可穿戴的智能设备(如智能项链、智能手表以及智能手环等)、云端服务器等能够执行训练计划的生成任务的设备。图2示出了本申请一实施例提供的训练计划的生成方法的实现流程图，详述如下：
在S201中，电子设备获取用户的多个运动数据。
在本实施例中，用户在完成一次运动后，可以生成关于与本次运动相关的运动数据。该运动数据可以记录有以下一项或多项的组合：运动类型、运动时长、心率峰值 等。若该运动的运动类型为跑步，则上述运动数据内可以包含运动距离、垂直攀升高度等；若该运动的运动类型为跳高，则上述运动数据内可以包含最大高度、成功比例等；若该运动的运动类型为骑行类型，则上述运动数据可以包括：骑行距离、赛道类型等等。因此，运动数据包含的参数项是根据所对应的运动项目确定的。
在本实施例中，用户在运动过程中，可以通过数据采集装置获取运动数据。上述采集用户的运动数据的数据采集装置可以为本实施例的电子设备，也可以为电子设备外的其他设备，在该情况下，电子设备可以从其他设备处获取用户的运动数据。
以跑步这一项运动为例进行说明，示例性地，图3示出了本申请一实施例提供的运动数据的获取示意图。参见图3所示，该电子设备具体为用户的智能手机。该智能手机内可以配置有运动健康的应用程序，用户可以通过在运动过程中，通过运动健康的应用程序记录用户在运动过程的相关数据，并在运动完成后，智能手机可以生成关于本次跑步的运动数据。电子设备还可以从其他设备处获取用户的运动数据。例如，用户在佩戴了智能手表进行运动时，智能手表也可以记录下相应的运动数据，同样地，跑步机、智能手环、智能项链、心率带等设备，也可以采集用户在进行跑步时相应的运动数据。在该情况下，智能手机(即本实施例中的电子设备)可以与上述电子设备建立通信连接，并从其他电子设备获取用户的运动数据。当然，电子设备还可以从其他第三方的设备处获取用户的运动数据，其中，获取得到的运动数据可以在电子设备上生成对应的运动数据列表，该运动数据列表中包含有各个运动数据对应的数据来源、运动时间、运动项目、运动距离、运动时长等等信息。
进一步地，作为本申请的另一实施例，在S201之前，还可以包括以下步骤：
在S2001中，生成用于采集用户的预设信息的信息输入界面；该预设信息包括用户信息以及训练目的。
在本实施例中，电子设备在获取运动数据之前，可以先获取预设信息，并生成用于采集预设信息的信息输入界面。该信息输入界面具体用于获取用户的两类预设信息，分别为用户信息，以及训练目的。示例性地，图4示出了本申请一实施例提供的信息输入界面的示意图，图4中的(a)用于采集用户的用户信息，该用户信息可以包含用户的年龄、身高、性别、体重，训练时长；
进一步地，作为本申请的另一实施例，上述S2001还可以包括：生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；响应于用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；基于各个所述运动项目的所述目标值，得到所述训练目的。如图4中的(b)的界面，用于采集用户的训练目的，该训练目的可以为不同训练项目对应的运动成绩，如5公里跑步的目标时间，用户可以拖动该设置界面内的滑动控件，以调整对应运动项目的目标值。需要说明的是，在该例子中，该用户所需创建的训练计划为5公里跑步的训练计划，当然，在其他场景下，可以创建不同的训练计划。
在S2002中，响应基于所述信息输入界面的输入操作，确定所述用户的用户信息以及训练目的；所述用户信息用于确定所述用户的运动员类型；所述训练目的用于确定用户的训练计划。
在本实施例中，用户可以在电子设备显示的信息输入界面上输入对应的用户信息 以及训练目的，并在后续操作中通过用户信息确定运动员类型。而训练目的可以用于制定用户的训练计划。其中，在一种可能的实现方式中，训练目的可以包含不同的训练项目对应的运动成绩，在该情况下，用户设置完成一个训练项目的运动成绩后，可以提示用户输入下一项目的运动成绩，如图4中的(c)，直到所有运动项目的运动成绩被设置完成，则执行下一步骤的操作。
进一步地，作为本申请另一实施例中，电子设备从其他设备处获取运动数据时，需要得到用户的授权确认，才能够从数据来源获取得到运动数据。在该情况下，S201具体可以包括以下步骤：
在S2011中，生成包含至少一个可选数据来源的运动数据授权界面。
在本实施例中，电子设备从其他设备获取运动数据之前，首先需要对获取运动数据这一操作进行授权认证，因此电子设备可以生成一个运动数据授权界面，该运动数据授权界面内包含有可以获取用户的运动数据的至少一个可选数据来源。该可选数据来源可以为除电子设备外的其他设备，还可以是安装于该电子设备中的应用程序，例如，电子设备中安装有一“运动健康”的应用程序，该应用程序可以在用户运动时记录用户的运动数据，并通过预设的格式对运动数据进行封装。由于运动数据属于用户的隐私数据的一种，获取用户的隐私数据，一般情况下需要用户的授权许可，因此，电子设备可以生成上述运动数据授权界面，以提示用户对获取运动数据进行授权认证。
示例性地，图5示出了本申请一实施例提供的运动数据的授权过程示意图。参见图5中的(a)所示，为一电子设备显示的主界面的示意图。用户可以通过点击该主界面中的“训练管理”对应的应用图标500，以启动训练计划的生成流程。由于生成训练计划的第一步是需要获取用户的运动数据，因此，在首次启动“训练管理”的应用程序时，又或者“训练管理”的应用程序检测到并未生成任何训练计划时，则可以生成运动数据授权界面，如图5中的(b)所示。该运动数据授权界面中包含有一数据来源列表501，该数据来源列表501中标记有至少一个可选数据来源，如图5的(b)中显示的“智能手表”、“智能手环”、“跑步机”以及“运动健康”四种可选数据来源，其中，前三种的可选数据来源需要从除电子设备外的其他设备处获取，而“运动健康”则可以从安装于本地的应用程序关联的数据库中获取得到。该运动数据授权界面中除了显示有可选数据来源对应的数据来源列表501，还包含有“确认授权”控件502，以及“拒绝授权”控件503。
在一种可能的实现方式中，电子设备可以配置有无线通信模块。该无线通信模块可以为无线高保真WIFI模块，也可以是蓝牙模块，也可以是低功耗蓝牙模块等。电子设备可以通过无线通信模块搜索场景下的无线信号，并通过对无线信号进行解析场景中可连接的设备，并将各个可连接设备添加到上述数据来源列表中。
在一种可能的实现方式中，用户关联有一用户账户。该用户账户，该用户账户记录有多个可选设备，每个可选设备存储有用户的运动数据。用户可在电子设备上登录同样的用户账户，在该情况下，电子设备可以基于用户账户关联的设备信息(即记录了登录了该用户账户的其他设备的信息)，并在上述可选设备列表中显示有各个关联的可选设备，以便用户从关联的其他设备中选取目标数据来源的设备。
在S2012中，响应于用户基于所述运动数据授权界面的确认操作，从所述可选数 据来源中确定目标数据来源。
在本实施例中，若用户同意电子设备获取运动数据，则可以从上述的可选数据来源中，选择可以授权的数据来源，并在选取完毕后，进行确认，电子设备可以将用户选择的可选数据来源作为目标数据来源，即可以从目标数据来源处获取用户的运动数据。
参见图5中的(b)所示，该运动数据授权界面中，各个可选数据来源的初始状态为待勾选状态，用户可以从可选数据来源中选取电子设备可以获取的数据来源，并点击可选数据来源在上述运动数据授权界面中相应的区域，电子设备将上述点击操作识别为选取操作，并将该可选数据来源的状态切换为已选状态，如图5中的(c)所示，例如用户选择所有可选数据来源作为目标数据来源。若电子设备检测到用户点击“确认授权”控件502时，则识别用户发起了上述的确认操作，并基于发起确认操作时，各个可选数据来源的选择状态，确定目标数据来源。
在一种可能的实现方式中，各个可选数据来源的初始状态为已选状态，即生成的运动数据授权界面为如图5中的(c)所示。用户可以通过选取不授权的可选数据来源，将其状态由已选状态变更为待勾选状态，并在选择完成后，点击“确认授权”控件502。
在一种可能的实现方式中，该运动数据授权界面可以配置有最大等待时长，若电子设备在最大等待时长内没有接收到用户发起的确认操作，则识别用户拒绝授权获取运动数据。
在一种可能的实现方式中，该运动数据授权界面可以配置有最大等待时长，若电子设备在最大等待时长内没有接收到用户发起的确认操作，则基于默认设置确定目标数据来源，例如将所有可选数据来源作为目标数据来源。如图5中的(d)所示，该“确认授权”控件502中显示有一剩余时间，如“9s”，若在9秒内没有接收到用户的确认操作，则识别用户默认将所有可选数据来源作为目标数据来源。
在一种可能的实现方式中，电子设备在接收到用户发起的确认操作之后，在生成授权请求之前，可以对用户的身份进行认证。示例性地，电子设备可以生成一个认证提示信息，如图5中的(e)所示，要求对用户的人脸认证，以确定发起本次确认操作的用户为运动数据的所属用户。若认证成功，则可以生成认证成功的提示信息，如图5中的(f)所示，识别用户同意授权从目标数据来源获取运动数据，并执行S2013的操作。
在S2013中，从所述目标数据来源获取所述运动数据。
在本实施例中，电子设备可以在识别得到用户同意获取运动数据后，可以直接从目标数据来源获取运动数据。可选地，电子设备在接收到用户发起的确认操作后，可以生成对应的授权请求，通过上述授权请求获取目标数据来源的数据获取权限，继而从目标数据来源获取用户的运动数据。继续参见图5中的(g)所示，电子设备从目标数据来源获取运动数据的过程中，可以生成一个获取进度提示框，以便用户确定当前从哪一目标数据来源获取运动数据，以及该运动数据的获取进度。
在一种可能的实现方式中，电子设备从各个目标数据来源获取到运动数据后，可以对运动数据进行整理以及合并，将属于同一次运动的运动数据进行合并。例如，图6示出了本申请一实施例提供的跑步运动场景的示意图，用户在进行跑步运动时，可 以在跑步机上进行运动，此时，用户手上佩戴着智能手表，此时，用户的智能手表以及跑步机均会记录该次跑步行为的运动数据，电子设备从上述两个数据来源获取运动数据时，会获取获得两个不同的运动数据，即来自智能手表的运动数据1以及来自跑步机的运动数据2。此时，电子设备可以对运动数据1与运动数据2进行合并。具体合并的方式可以为：识别每个运动数据的起始时间以及结束时间，确定运动数据对应的运动时间段；若两个运动数据间对应的运动时间段存在重合的时间段，则合并上述两个运动数据。例如，若运动数据1的运动时间段包含运动数据2的运动时间段，则保留运动数据1，删除运动数据2；若两个运动数据的运动时间段为部分重合，则合并两个运动数据中的重合部分，非重合部分根据与重合部分之间的先后关系进行拼接，从而得到合并后的运动数据。
示例性，图7示出了本申请一实施例提供的运动数据的合并示意图。电子设备获取得到的运动数据1对应的运动时间段为10:00至10:30，而运动数据2对应的运动时间段为10:20至11:00，由此可见，在运动时间段10:20至10:30，运动数据1与运动数据2存在重合的情况，电子设备在对上述两个运动数据合并时，会根据运动数据1与运动数据2在重合时间段的(10:20至10:30)的运动数据均值，得到合并数据段，并依此拼接合并数据段与剩余数据段，得到运动数据3。
在一种可能的实现方式中，电子设备获取目标用户在多个不同的运动项目的运动数据。电子设备可以通过多个不同运动项目的运动数据，以对用户的整体运动能力进行一个更为准确评估，以提高用户的运动员类型识别的准确性。
示例性地，若用户需要生成跑步类的训练计划，则上述运动项目的运动数据，具体可以为不同跑步距离所对应的运动数据，如5公里的跑步数据、10公里的跑步数据、半程马拉松(21.09公里)的跑步数据以及全程马拉松(42.19公里)的跑步数据，当然，具体的跑步距离可以根据实际情况进行设置，在此不对运动项目之间的差异进行限定。
在一种可能的实现方式中，不同的运动项目可以属于相同的运动类型，如上所述的，可以是不同跑步距离下的运动数据；不同的运动项目可以属于不同的运动类型，例如，所需获取的运动项目为：长跑项目、游泳项目、跳高项目、跳远项目等等，不同的运动项目可以体现用户的不同能力，也能够确定用户所述的运动员类型。例如，长跑项目可以确定用户的耐力，而跳高以及跳远则可以确定用户的爆发力等，因此，通过不同运动项目确定用户在不同维度对应的运动能力。
在一种可能的实现方式中，电子设备若没有获取到用户的运动数据，即用户在生成训练计划之前并没有通过电子设备或其他设备记录运动数据，即不存在对应的数据来源，在该情况下，电子设备可以识别用户对应的运动员类型为预设类型，如入门类型。
在S202中，基于多个所述运动数据确定所述用户对应的运动员类型。
在本实施例中，电子设备在获取了用户的多个运动数据后，可以通过多个运动数据确定用户的运动能力，以跑步运动为例进行说明，若用户的多个运动数据均为短跑类型的运动数据，并且每次短跑的平均配速均大于预设的均值，则可以推断该用户是喜爱短跑且擅长短跑，则可以确定该用户的运动员类型为短跑类型。由此可见，电子 设备可以通过多个运动数据，确定用户对应的运动员类型。
在本实施例中，上述运动员类型可以根据不同的方式进行划分。例如，可以根据运动的熟练程度进行划分，分为：新手型、均衡型、精英型等等，也可以根据擅长的运动项目进行划分为，例如分为：短跑型、长跑型等等，又或者分为：跑步型、篮球运动类型、足球运动类型、游泳型等等。
在本实施例中，电子设备基于多个运动数据确定运动员类型的方式可以为：根据运动数据对应的运动项目，确定该运动数据关联的与运动能力相关的能力维度(如肌耐力、爆发力、技巧性等)，并确定该运动数据对应的运动时间、心率值等，确定在各个能力维度对应的维度分值。对所有运动数据均进行上述的处理，确定了各个运动数据在各个能力维度的维度分值；继而电子设备可以取各个能力维度的最高值作为该用户在该能力维度的最终得分，又或者可以基于各个运动数据在能力维度的均值作为该用户在该能力维度的最终得分，基于所有能力维度的最终的得分，确定该用户对应的运动员类型。
需要说明的是，确定用户的运动员类型的步骤可以在电子设备本地完成，也可以由云端服务器完成。若确定用户的运动员类型的步骤是由云端服务器完成的情况下，电子设备可以将获取的运动数据上传给云端服务器，云端服务器可以基于电子设备上传的运动数据确定用户的运动员类型，即识别结果，然后将识别结果反馈给电子设备，电子设备在接收到云端服务器反馈的识别结果后，可以确定该用户的运动员类型，并执行后续的步骤。
进一步地，作为本申请的另一实施例，若上述获取的运动数据包含多个运动项目，则S202具体可以通过以下两个方式实现：
方式一：通过确定每个运动项目对应的最佳成绩，确定用户的运动者类型
在S2021中，分别根据各个所述运动项目关联的运动数据，确定所述运动项目对应的最佳运动成绩。
在本实施例中，电子设备可以根据运动数据所属的运动项目，将所有获取的运动数据划分为多个数据组，每个数据组对应相同的运动项目。电子设备可以根据运动项目关联的数据组中包含的多个运动数据，确定用户对于该运动项目的最佳运动成绩。例如，该上述运动数据均为跑步类型的运动数据，根据跑步距离的不同，可以划分不同的运动项目，如：5公里跑步、10公里跑步、半程马拉松跑步以及全程马拉松跑步等，电子设备可以识别各个运动数据中的跑步距离，以确定该运动数据所属的数据组。例如，某一运动数据对应的跑步距离为5.5公里，该跑步距离大于在“5公里跑步”，而小于“10公里跑步”，则可以将该运动数据识别为属于“5公里跑步”这一运动项目。当然，电子设备也可以从运动数据中，截取前5公里的数据段，添加到“5公里跑步”的运动项目对应的数据组内。
在一种可能的实现方式中，确定最佳运动成绩的方式可以为：从该运动项目中选取运动成绩最好的一个运动数据，并基于该选取得到的成绩最好的运动数据确定最佳运动成绩。
进一步地，作为本申请的另一实施例，确定最佳运动成绩的方式还可以包括以下步骤：
步骤1：确定所述运动项目对应的理想心率；所述理想心率具体是用户在全力运动状态下对应的心率。
在本实施例中，由于用户在进行运动训练时，未必以全力运动状态进行运动，即可能对实力有所保留，因此，采集得到的运动数据中并不能直接体现用户的最佳运动成绩。在该情况下，可以根据已采集的运动数据，推算用户的最佳运动成绩。其中，电子设备可以根据用户的心率，确定本次运动对应的强度系数，因而需要确定一个基准值，即上述理想心率。该理想心率用于表示用户在全力运动状态下对应的心率，即用户尽全力完成该项运动项目时，心率会达到的峰值。
其中，用户的个体信息不同，对于同一运动项目对应的理想心率也可以存在差异。例如，20岁用户的理想心率可能会高于30岁用户的理想心率；而男性用户的理想心率也可以高于同年龄段女性用户的理想心率。在该情况下，电子设备可以根据用户的个性信息，获取与该个体信息关联的理想心率。
在一种可能的实现方式中，电子设备可以获取用户的静态心率，例如，该电子设备为一智能手表，该智能手表处理可以记录用户在运动状态下的动态心率外，还可以获取用户在静息状态下的心率，即静态心率。由于人体的理想心率往往与静态心率之间存在一个相对关系，因此，电子设备可以通过用户的静态心率，以确定该用户对应的理想心率。
步骤2：根据所述运动数据中的实际心率以及所述理想心率，确定所述运动数据关联的强度系数。
在本实施例中，运动数据中记录有用户在运动过程中的实际心率，电子设备可以通过计算实际心率与理想心率之间的比值，确定本次运动对应的强度系统。由于理想心率是用户在全力运动状态下的心率，因此，若用户运动时的实际心率与理想心率越接近，则用户的运动状态越接近全力运动状态，由此可见，通过计算实际心率与理想心率之间的比值，以确定用户对应的强度系数。其中，越接近全力状态对应的强度系数越高。
步骤3：根据所述强度系数以及所述实际运动成绩，确定所述运动项目对应的最佳运动成绩。
在本实施例中，电子设备可以根据本次运动对应的强度系数，以及该运动数据对应的实际运动成绩，能够计算得到用户以全力状态下运动时对应的运动成绩，即最佳运动成绩。例如，计算最佳运动成绩的方式可以为：最佳运动成绩＝实际运动成绩/强度系数＝实际运动成绩/(实际心率/理想心率)。
示例性地，以跑步为例说明最佳运动成绩进行说明，图8示出了本申请一实施例提供的最佳运动成绩的计算示意图。参见图8所示，电子设备可以识别运动数据对应的跑步距离，通过跑步距离确定该运动数据所属的运动项目，并基于该运动项目确定与之对应的理想心率，即用户在全力状态下完成该跑步距离时对应的心率值。然后，电子设备可以从运动数据中确定用户在本次运动过程中对应的实际心率，计算实际心率与理想心率之间的比值，确定该本次运动数据对应的强度系数。由于对于跑步运动而言，运动成绩一般是通过跑步时长确定的，可以通过运动数据对应的实际配速进行转换。在该情况下，电子设备可以根据本次运动的实际配速以及上述的强度系数，计 算得到用户在全力运动状态下的理想配速，并根据跑步距离与理想配速之间的比值，计算得到理想状态下最佳的跑步时长，作为该运动项目对应的最佳运动成绩。
在S2022中，将所述最佳运动成绩导入到所述运动项目对应的归一化算法，确定所述运动项目对应的归一化参量。
在本实施例中，由于不同的运动数据对应的运动项目可以不一致，例如，用户跑步5公里所需的耗时，必然会比跑步10公里所需的耗时短，因此，两者无法通过同一的时间指标来确定对应的运动成绩，即用户的运动能力。另一方面，不同的运动距离下的运动指标也并不一定是线性关系，例如，正常用户跑步5公里的标准耗时为30分钟，而正常用户跑步10公里的标准耗时并不一定是30*2分钟，即1小时，而可以是1小时10分钟。因此，对于不同的运动项目，也无法直接通过不同的项目的距离关系来对运动成绩进行比较。基于此，为了能够更好地确定用户的运动能力，以确定其对应的运动员类型，电子设备可以对最佳运动成绩进行归一化处理，从而通过统一的维度指标来表示不同运动项目的成绩，以提高后续识别用户的运动员类型的准确性。
在一种可能的实现方式中，电子设备可以存储有不同运动项目对应的归一化算法。电子设备可以确定运动数据所属的运动项目，并通过与该运动项目关联的归一化算法计算该运动项目关联的归一化参量。其中，上述归一化算法具体可以为一个对应关系列表，也可以为一个转换函数，在此不对上述归一化算法的形式进行限定。
在本实施例中，电子设备可以将上述计算得到的最佳运动成绩导入到与其对应的运动项目的归一化算法中，得到该运动项目的归一化参量，从而可以将不同运动项目的最佳运动成绩转换到同一的维度进行比较。
示例性地，以跑步运动为例，图9示出了本申请一实施例提供的归一化算法的示意图。参见图9所示，该坐标系中的横坐标用于确定跑步距离，用于区分不同的运动项目；该坐标系中的纵坐标用于确定最佳运动成绩。根据归一化参量的数值不同，可以得到不同的参量曲线，例如，对于归一化参量的数值为20，则对应图9中的曲线1；而归一化参量的数值为35，则对应图9中的曲线2，即不同的曲线对应不同的归一化数值。
示例性地，继续以跑步运动为例，表1示出了本申请一实施例提供的归一化参量的对应关系表。参见表1所示，电子设备还可以通过预设的对应关系表，确定各个最佳运动成绩对应的归一化参量。若某一用户在5公里跑步这一运动项目对应的最佳运动成绩为25分钟，则通过表1可以确定，该用户对于5公里跑步的归一化参量为40；若该用户的在10公里跑步这一运动项目对应的最佳运动成绩为43分钟，则通过表1也可以确定，该用户对于10公里跑步的归一化参量为50，对于其他运动项目也可以参照上述过程，通过查询对应关系表得到与其对应的归一化参量。
表1
Figure PCTCN2022113395-appb-000001
Figure PCTCN2022113395-appb-000002
在S2023中，基于各个运动项目的归一化参量，确定所述用户的所述运动员类型。
在本实施例中，由于不同的运动项目可以体现用户在不同运动评价维度对应的运动能力，例如某一运动项目可以主要体现用户的爆发力，而另一运动项目则主要体现用户的耐力等等，通过不同的运动项目的归一化参量能够对用户的运动能力有一个较为全面的评价，因而可以继而可以通过不同运动项目对应的归一化参量，确定用户的运动员类型。
示例性地，以跑步运动为例进行说明，图10示出了本申请一实施例提供的运动员类型的对应关系图。参见图10所示，不同的运动员类型在坐标系中对应不同的区域，根据用户在不同的运动项目对应的归一化参量，在上述坐标系中生成对应的运动员曲线，基于该运动员曲线所落入的区域，确定该用户对应的运动员类型。其中，通过图10可以确定，运动员类型可以分为：新手型(即在各个运动项目对应的归一化参量均处于较低水平)、均衡性(即在各个运动项目对应的归一化参量均处于中等水平)、精英型(即在各个运动项目对应的归一化参量均处于较高水平)、耐力型(在短距离的运动项目对应的归一化参量较小，而在远距离的运动项目对应的归一化参量较大)以及速度型(在短距离的运动项目对应的归一化参量较大，而在远距离的运动项目对应的归一化参量较小)。
在本申请实施例中，根据所有运动数据分别确定各个运动项目对应的最佳运动成绩，然后将不同运动项目的最佳运动成绩进行归一化处理，得到各个运动项目的归一化参量，并根据所有运动项目的归一化参量确定用户的运动员类型，能够提高识别用户所属的运动员类型过程的准确性。
方式二：基于所有运动数据对应的归一化参量，确定用户的运动员类型
在S2021’中，根据所述运动数据对应的运动项目，确定所述运动数据关联的归一化算法，并通过所述归一化算法确定所述运动数据对应的归一化参量。
在本实施例中，与上一实现方式相似，不同的运动项目可以对应不同的归一化算法，从而能够使得将各个运动项目对应的运动数据统一到同一维度进行比较。基于此，电子设备可以识别运动数据的运动项目，并获取与运动项目对应的归一化算法，并通过与运动项目对应的归一化算法计算该运动数据对应的归一化参量。其中，计算归一化参量的实现过程可以参见上一方式的描述，如通过对应关系表或相关的转换函数计算归一化参量等方式实现，在此不再赘述。
在S2022’中，基于所有运动数据对应的归一化参量，确定所述用户的所述运动员类型。
在本实施例中，电子设备可以得到以获取的各个运动数据对应的归一化参量，通 过运动项目中多个运动数据的归一化参量，确定用户在该运动项目中的表现能力，例如可以将某一运动项目中所有运动数据的归一化参量的均值，作为该用户在该运动项目对应的特征值，然后根据用户在所有运动项目对应的特征值，确定用户的运动员类型。与上一方式相似，不同的运动项目可以体现用户的不同运动能力，如耐力、爆发力等，因此，通过多个运动数据确定在对应的运动项目的特征值，能够确定用户在多次运动中，对于该运动项目的表现能力，即提高了对于某一运动项目的表现能力评价的稳定性，继而提高运动员类型识别的准确性。
在本申请实施例中，电子设备并非从最佳运动成绩确定运动项目对应的归一化参量，而是将所有运动数据进行归一化处理，能够从多次运动中确定用户在某一运动项目中的表现能力，提高了对于运动项目的表现能力评价的稳定性。
在S203中，基于所述运动员类型，确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划。
在本实施例中，电子设备在确定了用户的运动员类型后，可以确定用户的训练方向。由于运动员类型可以确定用户在不同维度上的运动能力，以跑步为例进行说明，若用户的运动员类型为短跑类型，则表示用户的爆发力较好，而耐力较差，在该情况下，后续的训练方向可以为提升用户的耐力，而保持用户的爆发力；若用户的运动员类型为新手类型，则表示用户的爆发力与耐力等均较差，在该情况下，后续的训练方向为提升用户的耐力以及爆发力，由此可见，通过运动员类型，可以确定用户擅长的方向以及待提升的方向，从而在对用户的训练进行指导时对应的训练方向，也可以称之为训练侧重点。
在一种可能的实现方式中，电子设备在生成训练计划后，可以显示所述用户对应的训练报告；所述训练报告包含所述训练计划以及关于所述运动员类型以及所述训练方向的描述语段。其中，该训练报告具体包含两个部分，分别为对于用户整体运动能力评价的分析页面，以及训练计划的查看页面。其中，电子设备生成的分析页面中可以包含用户的运动员类型以及训练方向的描述语段，以便用户可以通过该分析页面确定自身的运动能力。示例性地，图11示出了本申请一实施例提供的训练报告的示意图。参见图11中的(a)所示，电子设备在获取得到用户的运动数据后，即如图5中的(f)在获取得到用户的运动数据后，可以确定用户的运动员类型以及训练方向，继而生成如图11中的(a)的分析页面。该分析页面中显示有基于采集的运动数据确定的不同运动项目的归一化参量，即如图11中的(a)的图表区域01，然后，还可以生成用于描述用户的运动员类型以及训练方向的分析段落02，用户可以通过该分析段落确定自身的运动员类型021以及训练方向022。
在本实施例中，电子设备在确定了用户的训练方向后，可以从预设的训练课程库中，提取与上述训练方向相匹配的训练课程，从而生成与上述训练方向相匹配的训练计划。
在一种可能的实现方式中，上述训练计划可以包括训练周期、训练时间以及该训练时间对应的训练课程。示例性地，参见图11中的(a)所示，该分析页面中还包括有“查看训练计划”的控件03，若电子设备检测到用户点击该控件03，则可以显示用 户对应的训练计划，如图11中的(b)所示，该训练周期具体用于指示该训练计划持续的时间，如6月1日至6月20日，而训练时间具体用于指示每个训练课程的触发时间以及课程持续时间，如6月1日训练1小时，训练课程具体用于指示训练内容，如6月1日对应的训练内容为深蹲跳和跑步。
需要说明的是，上述确定训练计划的操作可以在电子设备本地完成，也可以在云端服务器完成。若上述确定训练计划的操作在云端服务器完成，则上述的训练课程库可以存储于云端服务器，云端服务器根据用户的运动员类型确定用户的训练方向，并从训练课程库中提取与训练方向相匹配的训练课程，从而生成与之对应的训练计划，并将训练计划反馈给电子设备。云端服务器在向电子设备反馈训练计划时，可以将用户的完整的训练计划一并发送给电子设备；云端服务器还可以在到达训练提示时刻时，将训练计划中的训练课程反馈给电子设备，例如云端服务器将当天对应的训练课程发送给电子设备；又或者云端服务器可以接收电子设备发送的用户发起的计划查询请求，将训练计划中计划查询请求对应的训练课程发送给电子设备。
示例性地，图12示出了本申请一实施例提供的训练计划查询的示意图。参见图12中的(a)所示，电子设备上可以显示有一训练月历，该训练月历中具有训练课程的日期可以通过预设的方式进行标记，如图中的6月10日以及11日为具有训练课程的日期，图中的6月30日则为没有训练课程的日期。用户在需要查询训练计划中某个日期的训练课程时，可以点击在训练月历中对应日期的控件，即发起一个计划查询请求。电子设备若在本地存储有该日期对应的训练课程，则可以显示该日期对应的训练课程；若本地未存储有该日期对应的训练课程，则电子设备可以将该计划查询请求发送给云端服务器，云端服务器根据该用户对应的训练计划，将该日期对应的训练课程反馈给电子设备，电子设备显示该日期对应的训练课程，如图12中的(b)所示。
在一种可能的实现方式中，若获取了用户的训练目的，则上述S203具体为：根据所述训练目的以及所述运动员类型，确定所述用户的训练方向。电子设备可以通过用户预先设置训练目的，确定所需提高的能力，并基于识别得到的运动员类型确定用户当前的运动能力，因此，电子设备通过识别训练目的所需的能力与当前的运动能力是否匹配，从而确定对应的训练方向，并确定的训练方向生成与之对应的训练计划。
以跑步运动为例进行说明，若用户的训练目的为“参加全程马拉松比赛”，且识别得到的用户的运动员类型为短跑类型，在该情况下，则表示用户的爆发力优秀，而耐力较为缺乏，而基于上述训练目的，所需的能力为优秀的耐力，而用户当前的耐力与训练目的不匹配，此时，可以确定训练方向为提升耐力，并生成提升耐力的训练计划。以上可以看出，本申请实施例提供的一种训练计划的生成方法可以通过获取用户在历史运动过程中的运动数据，确定用户的运动员类型，并基于该运动员类型识别得到用户在进行训练时对应的训练方向，并生成与训练方向相匹配的训练计划，能够生成与用户的运动能力相适应的训练计划。由于用户的个体参数无法直接体现用户的运动能力，在基于个体参数生成的训练计划可能与用户的运动能力不匹配，而用户在历史的运动活动中采集的运动数据，能够体现用户实际的运动能力，基于用户在历史运动中的表现确定用户的运动员类型，能够提高训练计划与用户的实际运动能力之间的匹配程度，使得生成的训练计划能够更加有针对性地指导用户开展运动训练，提高了 生成的训练计划的准确性。
实施例二：
实施例一主要是基于运动数据确定用户的运动员类型，并基于运动员类型确定对应的训练方向，继而生成与训练方向相匹配的训练计划。而本实施例中具体阐述如何基于训练方向生成训练计划的实现过程。与上一实施例相比，本实施例中电子设备获取的用户的训练方向，可以通过实施例一的方式获取，也可以根据用户预先设置的方式获取，还可以接收其他设备反馈的方式获取，在此不对训练方向的获取方式进行限定。
在本申请实施例中，流程的执行主体为电子设备，该电子设备包括但不限于：计算机、智能手机、笔记本电脑、平板电脑、可穿戴的智能设备(如智能项链、智能手表以及智能手环等)、云端服务器等能够执行训练计划的生成任务的设备。图13示出了本申请另一实施例提供的训练计划的生成方法的实现流程图，详述如下：
在S1301中，根据用户的训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长。
如上所述，在本实施例中的训练方向，可以通过实施例一的方式确定；可选地，电子设备还可以生成一个训练方向的设置界面，用户可以在该设置界面中填写该训练计划所针对的训练方向，从而电子设备也能够通过用户设置的方式确定训练方向；可选地，若用户在其他设备上已经识别得到自身的训练方向，在该情况下，电子设备可以接收其他设备反馈的用户的训练方向。若该电子设备为用户终端，而其他设备为云端服务器的情况下，则电子设备可以在本地安装有云端服务器对应的客户端程序，并在该客户端程序中登录了用户关联的账号，云端服务器上若存储有用户已经识别得到的训练方向，则可以将训练方向下发给各个登录了用户关联的账户的设备，即本实施例提供的电子设备，从而电子设备能够获取得到用户的训练方向。
在本实施例中，电子设备可以预先存储有训练计划对应的计划模板。该计划模板用于限定用户在训练时的多个不同的训练阶段。各个训练阶段会有相应的阶段周期时长，即表示该训练阶段的持续时间，不同的训练阶段所对应的训练侧重点会不同，基于此，电子设备在确定了用户的训练方向后，可以对应调整训练计划中各个训练阶段的阶段周期时长，以使各个训练阶段的训练周期时长与训练方向相匹配。具体地，不同的训练阶段可以关联有一个或多个训练重点，若训练阶段的训练重点与用户的训练方向相匹配，则可以延长该训练阶段的阶段周期时长；反之，若该训练阶段的训练重点与用户的训练方向不匹配，则可以缩短该训练阶段的阶段周期时长。
示例性地，以跑步运动为例进行说明，图14示出了本申请一实施例提供的训练阶段的划分示意图。参见图14中的(a)所示，某一计划模板内包含有4个训练阶段，分别为：基础适应阶段、最大摄氧量提升阶段、乳酸阈改善阶段以及赛前调整阶段，在计划模板内，尚未限定各个训练阶段对应的阶段周期时长。其中，基础适应阶段具体是让用户逐渐进入持续运动的训练状态，因此该阶段的训练重点为各方向均衡提高；最大摄氧量提升阶段主要是用于提升用户的最大摄氧量，而最大摄氧量与用户跑步的配速相关，即该阶段的训练重点为提升用户的跑步配速；乳酸阈改善阶段主要是用于 提升用户的对于乳酸代谢的能力，而长跑过程中会产生乳酸，以及在长跑后会出现乳酸堆积的情况，即该阶段的训练重点为提升用户的耐力；而赛前调整阶段具体是让用户保存体力且保证有一定的运动量，即该阶段的训练重点是能力维持。由此可见，不同的训练阶段对应的训练重点不同，若某一用户的运动员类型为新手类型，则对应的训练方向为均衡提高，通过上述各阶段的训练重点可以确定，该用户的训练方向与基础适应阶段相匹配，此时，可以延长该阶段对应的阶段周期时长，如图14中的(a)所示，基础适应阶段的阶段周期时长会大于另外三个阶段的阶段周期时长，其他阶段的阶段周期时长可以也可以基于训练方向配置为匹配的数值。
在一种可能的实现方式中，上述计划模板中的训练阶段的阶段周期时长可以为0，即后续生成的训练计划中，可以不包含计划模板中的部分训练阶段，如图14中的(b)所示，基于训练方向确定了各个训练阶段的阶段周期时长后，最大摄氧量提升阶段分配的阶段周期时长为0，即不包含该阶段，只剩下其他三个阶段。出现上述情况的可能性有两种，第一种情况是，用户在该训练阶段对应的训练重点已经具有较优的表现，因此，无需通过该训练阶段来提升对应的运动能力，例如用户的耐力表现极好，属于十分优秀的水平，而速度较弱，此时，可以无需进行乳酸阈改善阶段，而是可以增加最大摄氧量提升阶段；另一种情况是用户的训练总时长较短，在该情况下，无法为所有训练阶段分配合适的训练周期时长，因此可以删减部分的训练阶段，即将某一训练阶段的训练周期时长设置为0。
在一种可能的实现方式中，训练阶段在计划模板中可以周期排列，如图14中的(c)所示，该计划模板中的最大摄氧量提升阶段与乳酸阈改善阶段交替排列，在计划模板中出现了多次，在该情况下，电子设备可以基于用户的训练方向，分别确定每个训练阶段在各个周期对应的阶段周期时长。当然，电子设备也可以确定该训练阶段的总时长，并根据该训练阶段在计划模板中的出现次数，为该训练阶段的各个训练周期配置对应的阶段周期时长，如图14中的(c)所示，该最大摄氧量提升阶段的总时长为28天，在计划模板中出现了两次，即存在两个训练周期，电子设备可以为最大摄氧量提升阶段的第一个训练周期分配13天，为最大摄氧量提升阶段的第二个训练周期分配15天。
进一步地，作为本申请另一实施例，上述S1301具体可以包括：
在S1301.1中，获取与用户的训练目的对应的所述计划模板。
在本实施例中，电子设备可以存储有不同的计划模板，不同的计划模板关联对应的训练目的。基于此，电子设备在生成用户的训练计划之前，可以获取用户的训练目的，获取训练目的方式如上所述，生成图4所示的信息输入界面，以提示用户输入用户的个体参数以及训练目的，并在获取得到用户的训练目的后，从计划模板库中选取与之匹配的计划模板。
需要说明的是，不同训练目的对应的计划模板内包含的训练阶段的个数以及训练重点可以不同。例如，用户A的训练目的是提高身体素质，则对应的计划模板可以为模板1，该模板1内可以包含三个训练阶段，分别为：体能恢复阶段、体能提升阶段以及体能稳定阶段；用户B的训练目的是参见马拉松比赛，则对应的计划模板可以为模板2，该模板2可以包含四个训练阶段，分别为：基础适应阶段、最大摄氧量提升 阶段、乳酸阈改善阶段以及赛前调整阶段。因此，计划模板中包含的训练阶段，以及该训练阶段对应的训练重点，是与其对应的训练目的相匹配的，从而能够提高生成的训练计划与用户之间的适配程度。
在S1301.2中，基于所述训练方向，确定各个所述训练阶段的时长比例。
在本实施例中，计划模板中各个训练阶段的时长比例可以预先配置一定的初始比例，例如不同的训练阶段之间的比例为1:1，即各个训练阶段的时长一致。电子设备在确定了用户的训练方向(即训练侧重点)后，可以对计划模板中训练阶段之间的初始比例进行调整，调整的依据是基于训练阶段对应的训练重点与用户的训练方向是否匹配；若某一训练阶段对应的训练重点与用户的训练方向相匹配，则可以增加该训练阶段对应的初始比例，得到上述的时长比例；若不匹配，则可以缩短该训练阶段的初始比例，得到对应的时长比例，也可以保持该初始比例不变，即将训练阶段的初始比例作为时长比例。
在S1301.3中，根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
在本实施例中，用户在需要生成训练计划时，可以在电子设备上输入本次训练计划的训练总时长，如通过图4所示的信息输入界面，上述除了包含有用户输入的个体参数以及训练目的外，还可以输入对应的训练总时长，如图4中的“90天”，在设置训练总时长时，还可以通过点击对应的训练结束日期的方式，来确定训练总时长。示例性地，图15示出了本申请一实施例提供的训练总时长的设置示意图。参见图15中的(a)所示，电子设备可以生成一个信息输入界面，该信息输入界面如图4相似，可以用于输入用户的个人参数以及训练目的，除此之外，还配置有一个用于填写“预计训练结束日期”的控件1501，电子设备在检测到用户点击上述控件1501时，会生成一个训练日历，如图15中的(b)所示，电子设备可以根据用户的选择操作，确定用户选择的训练结束日期，如6月30日，电子设备根据当前日期以及训练结束日期之间的差值，确定训练总时长，并在上述训练日历中显示，以提示用户本次训练计划的训练总时长，若检测到用户点击确认控件1502，则将用户选择的日期作为预计训练结束的日期，从而确定训练总时长。
在一种可能的实现方式中，训练计划的起始日期为可选。电子设备可以将生成训练计划时对应的当日日期作为该训练计划的可选日期，也可以根据用户的需求进行设置。如图15中的(b)所示，用户可以在上述训练日历中选择起始七日以及结束日期。
在本实施例中，电子设备可以通过计算各个训练阶段对应的时长比例与用户对应的训练总时长之间的乘积，得到各个训练阶段的阶段周期时长，例如，某一训练阶段的时长比例为25％，训练总时长为60天，则该训练阶段对应的阶段周期时长为25％*60天＝15天，同样地，对于其他训练周期也可以通过上述方式进行计算。
在一种可能的实现方式中，若上述的时长比例是各个训练阶段之间的比例，例如某一计划模板中包含有4个训练阶段，四个训练阶段之间的时长比例为：阶段1：阶段2：阶段3：阶段4＝1:1:2:2，则可以确定阶段1和阶段2占训练总时长的六分之一，而阶段3和阶段4占训练总时长的三分之一，继而可以通过计算训练总时长与该训练阶段所占的比例，计算得到该训练阶段的阶段周期时长。
在一种可能的实现方式中，上述训练总时长的时长范围为28天～180天之间，即训练计划最短的训练总时长为一个月，最长为6个月。由于训练总时长过短，则用户在培养运动习惯时，已经接近训练结束，无法有效地对用户的训练方向进行针对性提高；另一方面，若用户训练总时长过长，用户的运动能力的变化程度较大，基于初始状态下确定训练方向以及训练阶段的比例，可能对于用户而言不再适用，因此，会大大降低了训练计划的准确性，因此，为了兼顾训练计划的准确性以及执行的可行性两个方面，电子设备可以对训练总时长设置对应的有效范围，若用户设置的训练总时长在上述的有效的时长范围外，则可以生成对应的提示信息，如图15中的(c)所示，提示用户本次训练总时长过短，需要选取28天后的某个日期。
在本申请实施例中，通过识别用户训练目的，并获取与该训练目的相匹配的计划模板，并基于训练总时长确定各个训练阶段的阶段周期时长，能够提高周期划分过程的准确性，提高了后续训练计划与用户之间的适配程度。
在S1302中，确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的。
在本实施例中，电子设备可以根据训练阶段对应的阶段周期时长，划分为多个训练时间，例如，若以日为单位进行划分，则每个训练时间对应一个训练日期；若以小时为单位进行划分，则每个训练时间对应一个训练小时。当然，不同的训练日期之间可以是连续的，也可以是不连续的，具体根据实际情况进行设置。其中，若电子设备为用户侧的用户终端，则可以S1302可以在通过用户终端上安装的应用程序完成；若电子设备为云端服务器，则S1302还可以在云端服务器上确定各个训练时间的训练课程的操作。
需要说明的是，一个训练阶段可以对应一个课程类别，还可以对应两个以上的课程类别，具体根据实际情况进行确定。
在本实施例中，电子设备可以预先存储有多个不同的训练课程，各个训练课程可以对应一个课程类型。由于不同的训练阶段对应不同的训练重点，因此电子设备可以根据该课程类别与该训练阶段的训练重点之间是否匹配，以确定该课程类别是否为该训练阶段关联的课程类别，并将该课程类别关联的训练课程关联到各个训练时间。其中，一个训练时间可以对应一个或多个训练课程，并且不同训练时间之间的训练课程可以相同，也可以不同。
在一种可能的实现方式中，电子设备可以记录有课程类别与训练阶段的对应关系表，通过查询上述对应关系表，则可以确定各个训练阶段关联的课程类别。
在一种可能的实现方式中，上述S1302具体可以包括以下步骤：
在S1302.1中，基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库。
在本实施例中，电子设备在确定了训练阶段对应的课程类别后，可以将该训练阶段对应的所有课程类别均添加到同一训练类别库。该训练类别库内包含有与该训练阶段相关的至少一个课程类别，一个课程类别中可以包含有不同课程难度等级的候选课程。
以跑步运动为例进行说明，若某一训练阶段为最大摄氧量提升阶段，则该训练类别库可以包括：高强度间歇类型、轻松跑类型、有氧耐力跑类型三个课程类别，并基于上述各个课程类别包含有不同课程难度等级的候选课程，例如对于有氧耐力跑类型，低难度的候选课程距离短、要求的跑步配速较低，而高难度的候选课程距离长、要求的跑步配速较高。电子设备可以将与该训练阶段相关的所有课程类别中不同课程难度等级的候选课程，添加到同一训练类别库中，以便后续步骤确定每个训练时间对应的训练课程。
在S1302.2中，根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级。
在本实施例中，电子设备可以对阶段周期时长进行划分，得到多个训练时间，如上所述，可以以日期为单位进行划分，将阶段周期时长划分为多个训练日期，每个训练日期即为一个训练时间。上述训练时间可以包括有训练日期以及该训练日期对应的训练时长。
在本实施例中，电子设备可以为不同的训练日期配置对应的课程难度等级，从而生成满足预设的运动强度组合的训练课程框架，例如训练阶段的前期运动强度较低，因此对应的课程难度等级较低；而训练阶段的后期用户已经适应了运动训练，对应的运动强度较高，因此对应的课程难度等级较高。不同的训练阶段对应的运动强度组合可以不同，例如对于最大摄氧量提升阶段，该阶段整体的运动强度会高于赛前调整阶段的运动强度，因此对应的运动强度组合也会存在差异，即不同训练时间的课程难度等级会不同。电子设备通过配置训练课程框架，能够实现对整个训练阶段进行细化配置，对该训练阶段内包含的训练课程的结构、时长以及难度的组合进行限定，能够兼顾不同训练时间所需配置的课程难度等级之间的关系，而并非整个训练阶段的课程难度等级配置为同一数值，提高了训练课程选取的合理性以及准确性，进而提高了训练计划对于用户训练指导的准确性。
在一种可能的实现方式中，电子设备可以获取用户的运动员类型，基于该用户的运动员类型确定各个课程类别对应的课程难度等级。
在一种可能的实现方式中，上述训练课程框架还用于确定各个训练时间对应的课程类别。
在S1302.3中，从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
在本实施例中，电子设备在生成了训练阶段对应的训练课程框架后，可以对该训练课程框架中的各个训练时间配置对应的训练课程，由于每个训练时间关联有对应的课程难度等级，则电子设备可以从训练类别库中，提取与该课程难度等级对应的候选课程，作为该训练时间的训练课程。
示例性地，图16示出了本申请一实施例提供的训练课程的选取示意图。参见图16所示，电子设备根据训练方向确定了各个训练阶段的阶段周期时长，每个阶段周期时长配置有对应的训练类别库，如阶段1的训练类别库中则包含3个课程类别，每个课程类别下又包含不同课程难度等级的候选课程，即课程1.1～课程1.3，电子设备根据 训练阶段内的训练时间关联的课程难度等级，从该课程类别下选取对应课程难度等级的候选课程，作为该训练时期的训练课程，如将6月10日这一训练时间对应的课程难度等级为2，则课程类别1中选课程难度等级为2的候选课程，作为其对应的训练课程，即课程1.2。
在本申请实施例中，为各个训练阶段配置对应的训练类别库以及训练课程框架，从而确定该训练阶段内各个训练时间对应的训练课程，能够考虑不同训练时间之间配置的训练课程之间的关联性，提高了训练计划的准确性。
在S1303中，根据所有训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
在本实施例中，电子设备可以将各个训练阶段内各个训练时间的训练课程进行整合，从而得到该用户的训练计划。其中，电子设备可以在同一界面中显示所有训练时间对应的训练课程，如图11中的(b)所示；也可以将每个训练时间对应的课程，生成一个训练日历界面，如图17所示。图17示出了本申请一实施例提供的训练日历界面的示意图。参见图17所示，该训练日历界面中，显示该训练计划的计划名，如“5公里跑步的训练计划”，当前的训练时间对应的序号，以日为单位划分的训练时间时，该序号即为训练的天数，如图中所示的为第12天，还可以显示有训练总时长，即上述的49天，以及当前的训练计划的完成比例，即5.1％，该训练日历界面中还可以对用户已经训练的时长、运动距离以及累计消耗进行统计，得到对应的数值。在该训练日历页面中，还显示有当前的训练时间对应的训练阶段，如图中的“基础期”，即表示该训练时间对应的训练阶段，还可以显示有该训练阶段对应的阶段序号以及总的训练阶段个数。该训练日历页面中，还可以显示有该训练时间所对应的日期，即31日，并且具有训练课程的日期(即训练时间)通过预设的方式进行标记，如31日、2日、4日以及6日等。该训练时间中包含有两个训练课程，分别为“有氧耐力跑”以及“乳酸阈值间歇跑”，并显示有对应的训练课程的训练时间，以及完成状态，对于完成了的训练课程，可以将控件变更为“已完成”，对于待完成的训练课程，可以将控件显示为“开始训练”，以便用户开展该项训练课程。
在本实施例中，在确定了用户的训练计划后，若该电子设备为用户侧的智能手机，则可以通过智能手机上安装的应用程序显示该训练计划中各个训练时间的训练课程；若该电子设备为云端服务器，则云端服务器可以将各个训练时间对应的训练课程发送给用户对应的用户终端，通过智能手机进行显示；当然，若用户在训练的过程中，通过对应的执行终端完成训练，例如需要借助跑步机、智能手表或智能手环等，则可以通过智能手机将接收到的训练课程转发给各个执行终端，以便通过执行终端采集用户训练过程中的运动数据。
以上可以看出，本申请实施例提供的一种训练计划的生成方法，可以根据用户的训练方向，对训练计划中的各个训练阶段的阶段周期时长进行调整，不同的训练阶段对应不同的训练重点，因此可以关联有对应的课程类别，并该训练阶段对应的课程类别，为每个训练时间配置对应的训练课程，以生成与用户的训练方向相匹配的训练计划，从而使得训练计划能够针对性地提高用户训练方向的能力，并非根据用户的个体参数来确定训练计划，提高训练计划与用户之间的适配度，以及训练过程的针对性。
实施例三：
实施例一以及实施例二主要是阐述的是如何生成用户的训练计划。而本实施例中具体阐述生成了用户的训练计划后，如何对训练计划进行调整。与上两个实施例相比，本实施例中需要调整的训练计划，可以通过实施例一的方式生成，也可以通过实施例二的方式生成，也可以通过实施例一和实施例二结合得到的方式生成(即实施例二中的训练方向，是基于实施例一的方式确定的，然后在通过实施例二的方式生成用户的训练计划)，也可以通过其他方式生成，在此不对待调整的训练计划的生成方式进行限定。
在本申请实施例中，流程的执行主体为电子设备，该电子设备包括但不限于：计算机、智能手机、笔记本电脑、平板电脑、可穿戴的智能设备(如智能项链、智能手表以及智能手环等)、云端服务器等能够执行训练计划的生成任务的设备。图18示出了本申请一实施例提供的训练计划的调整方法的实现流程图，详述如下：
在S1802中，若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数。
在本实施例中，电子设备在检测到用户完成一个训练课程后，可以生成一个主观参数采集页面。示例性地，图19示出了本申请一实施例提供的主观参数采集页面的示意图。参见图19中的(a)所示，电子设备在检测到用户完成一个训练课程时，可以弹出一个提示训练结束的提示框191，该提示框中显示有确认结束课程的控件1911，以及延长运动的控件1912，若检测到用户点击控件1911，则识别本次训练课程已结束，可以生成用于采集对于本次课程训练的主观运动参数的页面，即主观参数采集页面，如图19中的(b)所示。该主观参数采集页面中包含有多个可选的主观运动参数对应的控件，分别为“很轻松”、“刚刚好”、“有挑战”以及“太难了”，其中上述各个主观运动参数对应的主观运动强度依次增高。用户可以根据对于本次课程训练的实际感受，选择对应的主观运动参数，并在该主观参数采集页面中发起反馈操作，若某一用户觉得本次训练课程的运动强度合适，则可以点击“刚刚好”的控件，电子设备可以根据用户的反馈操作，确定主观运动参数。
需要说明的是，上述主观参数采集页面可以在电子设备的显示模块上显示，还可以在其他设备的显示模块上显示，例如，用户在跑步机上进行课程训练，电子设备检测到用户完成某一训练课程后，可以将生成的主观参数采集页面发送给其他电子设备，或将对应的页面生成指令发送给其他电子设备，在该例子中其他电子设备为跑步机，跑步机可以在本地的显示模块上显示该主观参数采集页面，用户可以在跑步机的显示模块上发起反馈操作，跑步机将反馈操作对应的主观运动参数发送给电子设备，从而电子设备能够获取得到用户的主观运动参数。
进一步地，作为本申请的另一实施例，在S1802之前，还可以包括：
在S1801中，获取用户基于训练计划中任一训练课程进行训练时对应的训练压力值。
在本实施例中，电子设备在生成训练计划后，用户可以根据该训练计划进行训练。 该训练计划中可以包含有多个训练时间，每个训练时间可以关联有一个或多个训练课程，用户可以按照训练课程中的训练内容进行体育锻炼，用户在进行体育锻炼的过程中，根据运动强度可以有对应的训练压力值，其中，若该训练压力值越大，则表示该训练课程对应的运动强度越高；反之，若该训练压力值越小，则表示该训练课程对应的运动强度越低。
其中，上述训练压力值可以根据训练课程对应的课程难度等级确定，例如，某一训练课程的课程难度等级为3级，则可以确定该用户的训练压力值为3，当然电子设备还可以存储有课程难度等级与训练压力值之间的转换关系，通过该转换关系计算得到该训练课程对应的训练压力值；电子设备还可以根据用户在开展该训练运动时对应的实时数据(即实时运动数据)确定。
若电子设备根据用户的实时数据确定训练压力值，则S1801具体可以包括以下步骤：
在S1801.1中，获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
在S1801.2中，基于所述实时数据确定所述训练课程对应的所述训练压力值。
在本实施例中，用户在进行运动的过程中，可以通过电子设备或其他数据采集设备获取自身在基于训练课程进行训练时对应的实时运动数据，即上述的实时数据。该实时数据可以包括有运动过程中的心率值以及运动时长。
在本实施例中，上述实时数据中包含多个采集时刻对应的心率值，用户在运动过程中，电子设备或其他数据采集设备可以以预设的时间间隔获取用户在运动过程中的心率值，每个心率值可以对应一个采集时刻。电子设备在确定用户在训练课程过程中的训练压力值时，可以首先根据各个采集时刻对应的心率值，确定各个时刻对应的运动强度，其中，运动强度的计算方式具体可以为根据用户的实际心率值与该运动项目对应的理想心率值之间的比值确定。电子设备在计算得到各个采集时刻对应的运动强度后，可以在预设的坐标系上标记出各个采集得到的心率值对应的坐标点，其中，该坐标点的纵坐标可以为运动强度，横坐标可以为对应的采集时刻，然后电子设备可以根据采集时刻的先后次序，连接各个坐标点，得到该实时数据对应的运动强度曲线。电子设备可以对该运动强度曲线在时间维度上进行积分，将积分得到的数值作为该训练课程对应的训练压力值。
在一种可能的实现方式中，电子设备计算训练压力值的方式还可以为：电子设备根据实时数据中多个采集时刻的心率值，确定用户的平均运动强度，并根据运动时长与平均运动强度之间的乘积，得到该训练课程对应的训练压力值。
在S1803中，根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在本实施例中，电子设备可以根据用户的主观运动参数对训练计划进行调整，例如主观运动参数表示用户较难完成上述训练计划，则可以降低训练计划中的训练课程的难度；反之，若主观运动参数表示用户较容易完成上述训练计划，则可以提高训练计划中的训练课程的难度，从而能够保证训练计划与用户的训练体验一致。
进一步地，若电子设备还获取了用户在进行训练计划时对应的训练压力值，则上 述S1803具体可以为：根据训练压力值以及主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
在本实施例中，电子设备可以根据同一训练课程的训练压力值与主观运动参数进行比对，确定该训练课程实际的运动强度，与用户的主观感受是否一致。由于每个人在运动过程中的感受存在个性化的差异，训练课程的课程难度等级是根据共性指标设置的，例如根据大量用户的反馈情况确定课程难度等级，而该共性指标与用户的个性感受可能会存在不匹配的情况，为了提高训练计划与用户自身的适配度，提高用户的训练积极性，以培养用户的持续运动的习惯，电子设备可以根据客观采集到的训练压力值与主观运动参数对训练计划进行调整，从而得到调整后的训练计划，以提高后续训练课程安排的合理性以及与用户之间的契合度。
进一步地，作为本申请的另一实施例，S1803具体可以包括：
在S1803.1中，若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向。
在本实施例中，电子设备在未到达调整触发时刻时，可以将获取得到的训练压力值以及主观运动参数存储于存储器内，在完成训练课程后并不会立即对训练计划进行调整。如图19中的(b)所示，在用户完成训练课程后生成的主观参数采集页面中，可以显示有对应的提示信息“训练感受将用于下周计划的调整”，即此时并不会立即对后续的训练课程进行调整，而是在用户到达下一周时(即预设的调整触发时刻)，才会对训练计划进行调整。
在本实施例中，电子设备可以预先设置对于训练计划的调整周期，基于该调整周期的周期时长，可以确定多个调整触发时刻。例如，上述调整周期为一周(7天)，则可以将每周日的0点设置为调整触发时刻，将本周完成的训练课程对应的训练压力值以及主观运动参数，对下一周后的训练课程进行调整。
在本实施例中，电子设备可以根据用户已经完成的各个训练课程对应的训练压力值以及主观运动参数确定对于训练计划的调整方向，该调整方向包括有：提高训练难度、降低训练难度以及保持训练难度。
示例性地，图20示出了本申请一实施例提供的训练计划的调整方向的示意图。参见图20，为本实施例提供的调整方向的对照坐标系，电子设备可以根据训练课程的训练压力值以及主观运动参数在上述对照坐标系上确定训练课程的坐标点，其中，上述坐标点具体可以落入三种不同的区域，分别为：
情况1：对于同一训练课程，若其对应的训练压力值与对应的主观运动参数基本相似，即训练课程的实际运动强度与用户的主观感受基本吻合，此时，训练课程对应的坐标点会落入到保持训练难度对应的区域，即无需对训练计划进行调整。
情况2：对于同一训练课程，若其对应的训练压力值较大，而用户反馈的主观运动参数较小，即训练课程的实际运动强度较高，但用户却觉得较为轻松完成该训练课程，即表示用户具有完成更高难度的训练课程，此时，训练课程对应的坐标点会落入到提升难度对应的区域，即需要提高训练计划中训练课程的课程难度等级。
情况3：对于同一训练课程，若其对应的训练压力值较小，而用户反馈的主观运动参数较大，即训练课程的实际运动强度较低，但用户依然觉得较难完成该训练课 程，即表示用户完成该训练课程较为吃力，训练课程对于用户而言属于难度偏高的课程，此时，训练课程对应的坐标点会落入到降低难度对应的区域，即需要降低训练计划中的训练课程的课程难度等级。
在一种可能的实现方式中，由于在满足调整触发时刻时，用户可以完成多个训练课程，电子设备可以在上述对照坐标系上标记各个训练课程的坐标点，除了能够确定训练计划的调整方向外，还可以确定调整幅度；若多个训练课程均落入到提升训练难度的区域，则表示训练计划中的训练课程的课程难度等级偏低，且偏低幅度较大，后续对课程进行调整时，可以提高与之匹配的课程难度等级；反之，若一部分的训练课程落入到保持训练难度甚至降低训练难度的区域，而另一部分的训练课程落入到提高训练难度的区域，则表示课程难度等级偏低，但偏低程度较小，后续对课程进行调整时，可以小幅提高训练课程的课程难度等级，若提高一部分的训练课程的课程难度等级，而保持部分训练课程的课程难度等级。
在一种可能的实现方式中，每个训练课程对应一个课程类别，在进行调整时，电子设备可以根据课程类别对应的已完成的训练课程的训练压力值以及主观运动参数，确定该课程类别对应的调整方向。
在S1803.2中，基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
在本实施例中，电子设备可以根据计划调整方向对训练计划中后续的训练课程进行调整，例如提高后续训练课程的课程难度等级，或降低训练课程的课程难度等级。
由于电子设备在生成训练计划时，可以为不同的训练阶段创建对应的训练类别库，该训练类别库内包含有与训练阶段对应的一个或多个课程类别，一个课程类别中可以包含有不同课程难度等级的训练课程，因此，若某一训练课程的课程难度等级与用户不匹配，则可以从该训练课程对应的课程类别中，选取其他课程难度等级的训练课程来替换训练计划中该课程类别的训练课程。
示例性地，图21示出了本申请一实施例提供的训练课程的调整示意图。参见图21所示，在调整前，6月10日的训练课程为课程1.2，即课程难度等级为2，若电子设备在6月3日确定需要降低后续训练课程的课程难度等级，则电子设备需要降低后续日期的训练课程的课程难度，识别得到6月10日的训练课程所属的课程类别为课程类别1，而课程类别1中包含有3个课程难度等级的训练课程，而课程难度等级小于2的训练课程即为课程1.1，此时，会将课程1.1替换6月10日中已经安排的训练课程，对各个训练时间的训练课程均通过上述方式完成调整，则得到调整后的训练课程。
在一种可能的实现方式中，除了可以通过上述方式自动对训练计划进行调整外，电子设备还可以接收用户的主动修改请求，对训练计划进行调整。示例性地，图22示出了本申请一实施例提供的训练计划的调整示意图。参见图22中的(a)所示，电子设备在训练课程的查询界面中可以配置有一个菜单控件221，若检测到用户点击上述菜单控件221，则可以生成对应的菜单弹窗222，该菜单弹窗222中包含有多个选项，分别为：修改训练日、修改训练课程、训练提醒以及终止计划。其中，电子设备检测到用户点击修改训练日的选项，则会生成训练日调整的页面，如图22中的(b)所示，该训练日调整页面中用户可以设置不同训练项目对应的训练日期，如跑步项目的训练 日期，以及力量项目的训练日期，用户可以根据自身的情况选择合适的日期。其中，为了提高训练计划的稳定性，对于训练日的调整可以在下一周生效，当然，还可以立即生效。
电子设备检测到用户点击修改训练课程的选项，可以生成一个训练课程调整页面，如图22中的(c)，具体地，每个训练课程可以显示有当前的课程难度等级，用户可以根据自己的情况，调整各个训练课程对应的课程难度等级，电子设备可以从该训练课程对应的课程类别中选取对应课程难度等级的训练课程进行替换。同样地，上述调整可以在下一个调整触发时刻对训练计划进行调整，也可以立即生效。
以上可以看出，本申请实施例提供的一种训练计划的调整方法，可以在运动过程中除了获取用户的训练压力值外，还可以在训练课程结束后，获取用户对于本次训练课程的主观运动参数，并基于客观的训练压力值以及与用户主观感受相关的主观运动参数，来对训练计划进行调整，从而能够提高训练计划调整的准确性，进一步提高用户对于训练计划的个性化设置的要求。
应理解，上述实施例中各步骤的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
实施例四：
结合上文实施例一和二所述的训练计划的生成方法以及上文实施例三所述的训练计划的调整方法，图23示出了本申请实施例提供的训练计划的生成装置的结构框图，为了便于说明，仅示出了与本申请实施例相关的部分。
参照图23，该训练计划的生成装置包括：
运动数据获取单元231，用于获取用户的多个运动数据；
运动员类型确定单元232，用于基于多个所述运动数据确定所述用户对应的运动员类型；
训练计划生成单元233，用于基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划。
可选地，获取的多个所述运动数据包含多个运动项目的运动数据，所述运动员类型确定单元232，包括：
最佳运动成绩确定单元2321，用于分别根据各个所述运动项目关联的所述运动数据，确定所述运动项目对应的最佳运动成绩；
归一化参量确定单元2322，将所述最佳运动成绩导入到所述运动项目对应的归一化算法，确定所述运动项目对应的归一化参量；
运动员类型识别单元2323，用于基于各个运动项目的归一化参量，确定所述用户的所述运动员类型。
可选地，所述最佳运动成绩确定单元2321，包括：
理想心率确定单元，用于确定所述运动项目对应的理想心率；所述理想心率具体是用户在全力运动状态下对应的心率；
强度系数确定单元，用于根据所述运动数据中的实际心率以及所述理想心率，确定所述运动数据关联的强度系数；
最佳运动成绩计算单元，用于根据所述强度系数以及所述实际运动成绩，确定所述运动项目对应的所述最佳运动成绩。
可选地，所述运动数据获取单元231，包括：
运动数据授权界面生成单元2311，用于生成包含至少一个可选数据来源的运动数据授权界面；
确认操作响应单元2312，用于响应于用户基于所述运动数据授权界面的确认操作，从所述可选数据来源中确定目标数据来源；
数据获取发送单元2313，用于从所述目标数据来源获取所述运动数据。
可选地，所述训练计划的生成装置还包括：
训练报告显示单元，用于显示所述用户对应的训练报告；所述训练报告包含所述训练计划以及关于所述运动员类型以及所述训练方向的描述语段。
可选地，所述训练计划生成单元233，包括：
阶段周期时长确定单元2331，用于根据所述训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
训练课程确定单元2332，用于确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
训练课程封装单元2333，用于根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
可选地，所述训练课程确定单元2332，包括：
训练类别库配置单元，用于基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
训练课程框架确定单元，用于根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
训练课程选取单元，用于从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
可选地，所述阶段周期时长确定单元2331，包括：
计划模板获取单元，用于获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
时长比例确定单元，用于基于所述训练方向，确定各个所述训练阶段的时长比例；
训练总时长分配单元，用于根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
可选地，所述训练计划的生成装置还包括：
设置界面显示单元，用于生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；
设置操作响应单元，用于响应于所述用户在各个所述目的设置区域内的设置操作， 确定各个所述运动项目对应的目标值；
训练目的确定单元，用于基于各个所述运动项目的所述目标值，得到所述训练目的。
可选地，所述训练计划的生成装置，还包括：
主观运动参数确定单元235，用于若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
训练计划调整单元236，用于所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
可选地，所述训练计划的生成装置，还包括：
训练压力值获取单元234，用于获取所述用户基于所述训练计划中任一训练课程进行训练时对应的训练压力值；
训练计划调整单元236，具体用于根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
可选地，所述训练压力值获取单元234，包括：
实时数据获取单元2341，用于获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
实时数据转换单元2342，用于基于所述实时数据确定所述训练课程对应的所述训练压力值。
可选地，所述训练计划调整单元236，包括：
计划调整方向确定单元2361，用于若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
训练课程调整单元2362，用于基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
因此，本申请实施例提供的训练计划的生成装置同样通过获取用户在历史运动过程中的运动数据，确定用户的运动员类型，并基于该运动员类型识别得到用户在进行训练时对应的训练方向，并生成与训练方向相匹配的训练计划，能够生成与用户的运动能力相适应的训练计划。由于用户的个体参数无法直接体现用户的运动能力，在基于个体参数生成的训练计划可能与用户的运动能力不匹配，而用户在历史的运动活动中采集的运动数据，能够体现用户实际的运动能力，基于用户在历史运动中的表现确定用户的运动员类型，能够提高训练计划与用户的实际运动能力之间的匹配程度，使得生成的训练计划能够更加有针对性地指导用户开展运动训练，提高了生成的训练计划的准确性。
继续结合实施例一、实施例二的训练计划的生成方法以及实施例三提供的方案训练计划的调整方法，图24示出了本申请另一实施例提供的训练计划的生成装置的结构框图。参见图24所示，该训练计划的生成装置具体可以包括训练计划生成单元241，课程执行单元242以及计划调整单元243。
其中，训练计划生成单元241用于执行实施例一以及实施例二提供的训练计划的 生成方法，即根据用户的运动数据确定训练方向，并基于训练方向确定计划模板中各个训练阶段的阶段周期时长。其中，该训练计划生成单元241还可以包含课程提取器，在确定了各个训练阶段对应的阶段周期时长后，可以通过该课程提取器为各个训练阶段选取对应的训练课程，生成训练计划。其中，该训练计划生成单元242可以位于用户侧的智能手机，也可以位于云端的服务器。
上述课程执行单元242可以接收训练计划生成单元241下发的各个训练课程，并通过课程执行单元242输出各个训练课程，例如提醒的方式提示用户执行训练课程，或者通过显示模块显示训练课程对应的指导视频。然后，课程执行单元242还可以获取用户在执行训练课程时对应的训练压力值以及主观运动参数。其中，该课程执行单元242可以位于用户侧的智能手机、智能手表、跑步机、智能手环等。
上述计划调整单元243具体用于根据课程执行单元242反馈的训练压力值以及主观运动参数对训练计划进行调整，并将调整后的训练计划反馈给训练计划生成单元241。其中，该计划调整单元243可以位于用户侧的智能手机，也可以位于云端的服务器。
实施例五：
结合上文二所述的训练计划的生成方法以及上文实施例三所述的训练计划的调整方法，图25示出了本申请实施例提供的训练计划的生成装置的结构框图，为了便于说明，仅示出了与本申请实施例相关的部分。
参照图25，该训练计划的生成装置包括：
阶段周期时长确定单元251，用于根据用户的训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
训练课程确定单元252，用于确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
训练计划封装单元253，用于根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
可选地，所述训练课程确定单元252，包括：
训练类别库配置单元2521，用于基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
训练课程框架确定单元2522，用于根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
训练课程选取单元2523，用于从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
可选地，所述阶段周期时长确定单元251，包括：
计划模板获取单元2511，用于获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
时长比例确定单元2512，用于基于所述训练方向，确定各个所述训练阶段的时长比例；
训练总时长分配单元2513，用于根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
可选地，所述训练计划的生成装置还包括：
设置界面显示单元，用于生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；
设置操作响应单元，用于响应于所述用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；
训练目的确定单元，用于基于各个所述运动项目的所述目标值，得到所述训练目的。
可选地，所述训练计划的生成装置，还包括：
主观运动参数确定单元255，用于若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
训练计划调整单元256，用于所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
可选地，所述训练计划的生成装置，还包括：
训练压力值获取单元254，用于获取所述用户基于所述训练计划中任一训练课程进行训练时对应的训练压力值；
训练计划调整单元256，具体用于根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
可选地，所述训练压力值获取单元254，包括：
实时数据获取单元2541，用于获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
实时数据转换单元2542，用于基于所述实时数据确定所述训练课程对应的所述训练压力值。
可选地，所述训练计划调整单元256，包括：
计划调整方向确定单元2561，用于若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
训练课程调整单元2562，用于基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
因此，本申请实施例提供的训练计划的生成装置同样可以根据用户的训练方向，对训练计划中的各个训练阶段的阶段周期时长进行调整，不同的训练阶段对应不同的训练重点，因此可以关联有对应的课程类别，并该训练阶段对应的课程类别，为每个训练时间配置对应的训练课程，以生成与用户的训练方向相匹配的训练计划，从而使得训练计划能够针对性地提高用户训练方向的能力，并非根据用户的个体参数来确定训练计划，提高训练计划与用户之间的适配度，以及训练过程的针对性。
实施例六：
对应于上文实施例三所述的训练计划的调整方法，图26示出了本申请实施例提供的训练计划的调整装置的结构框图，为了便于说明，仅示出了与本申请实施例相关的部分。
参照图26，该训练计划的调整装置包括：
主观运动参数确定单元262，用于若检测到训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
训练计划调整单元263，用于根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
可选地，所述训练计划的调整装置，还包括：
训练压力值获取单元261，用于获取用户基于训练计划中任一训练课程进行训练时对应的训练压力值；
训练计划调整单元263，具体用于根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
可选地，所述训练压力值获取单元261，包括：
实时数据获取单元2611，用于获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
实时数据转换单元2612，用于基于所述实时数据确定所述训练课程对应的所述训练压力值。
可选地，所述训练计划调整单元263，包括：
计划调整方向确定单元2631，用于若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
训练课程调整单元2632，用于基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
因此，本申请实施例提供的训练计划的调整装置同样可以在运动过程中除了获取用户的训练压力值外，还可以在训练课程结束后，获取用户对于本次训练课程的主观运动参数，并基于客观的训练压力值以及与用户主观感受相关的主观运动参数，来对训练计划进行调整，从而能够提高训练计划调整的准确性，进一步提高用户对于训练计划的个性化设置的要求。
本申请实施例提供的训练计划的生成方法可以应用于手机、平板电脑、可穿戴设备、车载设备、增强现实(augmented reality，AR)/虚拟现实(virtual reality，VR)设备、笔记本电脑、超级移动个人计算机(ultra-mobile personal computer，UMPC)、上网本、个人数字助理(personal digital assistant，PDA)、智能手表、智能手环、服务器等电子设备上，本申请实施例对电子设备的具体类型不作任何限制。
例如，所述电子设备可以是WLAN中的站点(STATION，ST)，可以是蜂窝电话、 无绳电话、会话启动协议(Session Initiation Protocol，SIP)电话、无线本地环路(Wireless Local Loop，WLL)站、个人数字处理(Personal Digital Assistant，PDA)设备、具有无线通信功能的手持设备、计算设备或连接到无线调制解调器的其它处理设备、电脑、膝上型计算机、手持式通信设备、手持式计算设备、和/或用于在无线系统上进行通信的其它设备以及下一代通信系统，例如，5G网络中的移动终端或者未来演进的公共陆地移动网络(Public Land Mobile Network，PLMN)网络中的移动终端等。
作为示例而非限定，当所述电子设备为可穿戴设备时，该可穿戴设备还可以是应用穿戴式技术对日常穿戴进行智能化设计、开发出可以穿戴的设备的总称，如眼镜、手套、手表、服饰及鞋等。可穿戴设备即直接穿在身上，或是整合到用户的衣服或配件的一种便携式设备，通过附着与用户身上，采集用户的生物特征数据，如用户的心率值。可穿戴设备不仅仅是一种硬件设备，更是通过软件支持以及数据交互、云端交互来实现强大的功能。广义穿戴式智能设备包括功能全、尺寸大、可不依赖智能手机实现完整或者部分的功能，如智能手表或智能眼镜等，以及只专注于某一类应用功能，需要和其它设备如智能手机配合使用，如各类包含可解锁的触控屏的智能手环、智能首饰等。
图27示出了电子设备100的结构示意图。
电子设备100可以包括处理器110，外部存储器接口120，内部存储器121，通用串行总线(universal serial bus，USB)接口130，充电管理模块140，电源管理模块141，电池142，天线1，天线2，移动通信模块150，无线通信模块160，音频模块170，扬声器170A，受话器170B，麦克风170C，耳机接口170D，传感器模块180，按键190，马达191，指示器192，摄像头193，显示屏194，以及用户标识模块(subscriber identification module，SIM)卡接口195等。其中传感器模块180可以包括运动传感器，其中该运动传感器可以包括压力传感器180A，陀螺仪传感器180B以及加速度传感器180E，该传感器模块180还可以包括气压传感器180C，磁传感器180D，距离传感器180F，接近光传感器180G，指纹传感器180H，温度传感器180J，触摸传感器180K，环境光传感器180L，骨传导传感器180M等。
可以理解的是，本申请实施例示意的结构并不构成对电子设备100的具体限定。在本申请另一些实施例中，电子设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。
处理器110可以包括一个或多个处理单元，例如：处理器110可以包括应用处理器(application processor，AP)，调制解调处理器，图形处理器(graphics processing unit，GPU)，图像信号处理器(image signal processor，ISP)，控制器，视频编解码器，数字信号处理器(digital signal processor，DSP)，基带处理器，和/或神经网络处理器(neural-network processing unit，NPU)等。其中，不同的处理单元可以是独立的器件，也可以集成在一个或多个处理器中。其中，该处理器可以用于执行实施例一中的S202以及S203的操作、S2021～S2023的操作、S2021’～S2022’的操作，还可以用于执行实施例二中的S1301～S1303的操作、S1301.1～S1301.3的操作、S1302.1～S1302.3的操作，还可以用于执行实施例三中的S1803的操作，以及S1803.1～S1803.2的操作。
控制器可以根据指令操作码和时序信号，产生操作控制信号，完成取指令和执行指令的控制。
处理器110中还可以设置存储器，用于存储指令和数据，例如用户的运动数据，生成的训练计划，创建的训练课程库等。在一些实施例中，处理器110中的存储器为高速缓冲存储器。该存储器可以保存处理器110刚用过或循环使用的指令或数据。如果处理器110需要再次使用该指令或数据，可从所述存储器中直接调用。避免了重复存取，减少了处理器110的等待时间，因而提高了系统的效率。
在一些实施例中，处理器110可以包括一个或多个接口。接口可以包括集成电路(inter-integrated circuit，I2C)接口，集成电路内置音频(inter-integrated circuit sound，I2S)接口，脉冲编码调制(pulse code modulation，PCM)接口，通用异步收发传输器(universal asynchronous receiver/transmitter，UART)接口，移动产业处理器接口(mobile industry processor interface，MIPI)，通用输入输出(general-purpose input/output，GPIO)接口，用户标识模块(subscriber identity module，SIM)接口，和/或通用串行总线(universal serial bus，USB)接口等。
I2C接口是一种双向同步串行总线，包括一根串行数据线(serial data line，SDA)和一根串行时钟线(derail clock line，SCL)。在一些实施例中，处理器110可以包含多组I2C总线。处理器110可以通过不同的I2C总线接口分别耦合触摸传感器180K，充电器，闪光灯，摄像头193等。例如：处理器110可以通过I2C接口耦合触摸传感器180K，使处理器110与触摸传感器180K通过I2C总线接口通信，实现电子设备100的触摸功能。
PCM接口也可以用于音频通信，将模拟信号抽样，量化和编码。在一些实施例中，音频模块170与无线通信模块160可以通过PCM总线接口耦合。在一些实施例中，音频模块170也可以通过PCM接口向无线通信模块160传递音频信号，实现通过蓝牙耳机接听电话的功能。所述I2S接口和所述PCM接口都可以用于音频通信。
UART接口是一种通用串行数据总线，用于异步通信。该总线可以为双向通信总线。它将要传输的数据在串行通信与并行通信之间转换。在一些实施例中，UART接口通常被用于连接处理器110与无线通信模块160。例如：处理器110通过UART接口与无线通信模块160中的蓝牙模块通信，实现蓝牙功能。在一些实施例中，音频模块170可以通过UART接口向无线通信模块160传递音频信号，实现通过蓝牙耳机播放音乐的功能。
GPIO接口可以通过软件配置。GPIO接口可以被配置为控制信号，也可被配置为数据信号。在一些实施例中，GPIO接口可以用于连接处理器110与摄像头193，显示屏194，无线通信模块160，音频模块170，传感器模块180等。GPIO接口还可以被配置为I2C接口，I2S接口，UART接口，MIPI接口等。
可以理解的是，本申请实施例示意的各模块间的接口连接关系，只是示意性说明，并不构成对电子设备100的结构限定。在本申请另一些实施例中，电子设备100也可以采用上述实施例中不同的接口连接方式，或多种接口连接方式的组合。
电子设备100的无线通信功能可以通过天线1，天线2，移动通信模块150，无线通信模块160，调制解调处理器以及基带处理器等实现。
无线通信模块160可以提供应用在电子设备100上的包括无线局域网(wireless local area networks，WLAN)(如无线保真(wireless fidelity，Wi-Fi)网络)，蓝牙(bluetooth，BT)，全球导航卫星系统(global navigation satellite system，GNSS)，调频(frequency modulation，FM)，近距离无线通信技术(near field communication，NFC)，红外技术(infrared，IR)等无线通信的解决方案。无线通信模块160可以是集成至少一个通信处理模块的一个或多个器件。无线通信模块160经由天线2接收电磁波，将电磁波信号调频以及滤波处理，将处理后的信号发送到处理器110。无线通信模块160还可以从处理器110接收待发送的信号，对其进行调频，放大，经天线2转为电磁波辐射出去。
在一些实施例中，电子设备100的天线1和移动通信模块150耦合，天线2和无线通信模块160耦合，使得电子设备100可以通过无线通信技术与网络以及其他设备通信。所述无线通信技术可以包括全球移动通讯系统(global system for mobile communications，GSM)，通用分组无线服务(general packet radio service，GPRS)，码分多址接入(code division multiple access，CDMA)，宽带码分多址(wideband code division multiple access，WCDMA)，时分码分多址(time-division code division multiple access，TD-SCDMA)，长期演进(long term evolution，LTE)，BT，GNSS，WLAN，NFC，FM，和/或IR技术等。所述GNSS可以包括全球卫星定位系统(global positioning system，GPS)，全球导航卫星系统(global navigation satellite system，GLONASS)，北斗卫星导航系统(beidou navigation satellite system，BDS)，准天顶卫星系统(quasi-zenith satellite system，QZSS)和/或星基增强系统(satellite based augmentation systems，SBAS)。
内部存储器121可以用于存储计算机可执行程序代码，所述可执行程序代码包括指令。内部存储器121可以包括存储程序区和存储数据区。其中，存储程序区可存储操作系统，至少一个功能所需的应用程序(比如无线连接功能，振动波生成功能以及本申请实施例提供的训练计划的调整程序、训练计划的生成程序等)等。存储数据区可存储电子设备100使用过程中所创建的数据(比如音频数据，电话本，还可以存储如本申请实施例中的从目标数据来源获取的运动数据、生成的训练计划、计划模板、训练课程框架、训练类别库、训练课程、用户输入的用户信息、反馈的主观运动参量等)等。此外，内部存储器121可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件，闪存器件，通用闪存存储器(universal flash storage，UFS)等。处理器110通过运行存储在内部存储器121的指令，和/或存储在设置于处理器中的存储器的指令，执行电子设备100的各种功能应用以及数据处理。
压力传感器180A用于感受压力信号，可以将压力信号转换成电信号。在一些实施例中，压力传感器180A可以设置于显示屏194。压力传感器180A的种类很多，如电阻式压力传感器，电感式压力传感器，电容式压力传感器等。电容式压力传感器可以是包括至少两个具有导电材料的平行板。当有力作用于压力传感器180A，电极之间的电容改变。电子设备100根据电容的变化确定压力的强度。当有触摸操作作用于显示屏194，电子设备100根据压力传感器180A检测所述触摸操作强度。电子设备100也可以根据压力传感器180A的检测信号计算触摸的位置。在一些实施例中，作用于相同触摸位置，但不同触摸操作强度的触摸操作，可以对应不同的操作指令。例如：当有触摸操作强度小于第一压力阈值的触摸操作作用于短消息应用图标时，执行查看 短消息的指令。当有触摸操作强度大于或等于第一压力阈值的触摸操作作用于短消息应用图标时，执行新建短消息的指令。
陀螺仪传感器180B可以用于确定电子设备100的运动姿态。在一些实施例中，可以通过陀螺仪传感器180B确定电子设备100围绕三个轴(即，x，y和z轴)的角速度。陀螺仪传感器180B可以用于拍摄防抖。示例性的，当按下快门，陀螺仪传感器180B检测电子设备100抖动的角度，根据角度计算出镜头模组需要补偿的距离，让镜头通过反向运动抵消电子设备100的抖动，实现防抖。陀螺仪传感器180B还可以用于导航，体感游戏场景。
加速度传感器180E可检测电子设备100在各个方向上(一般为三轴)加速度的大小。当电子设备100静止时可检测出重力的大小及方向。还可以用于识别电子设备姿态，应用于横竖屏切换，计步器等应用。
距离传感器180F，用于测量距离。电子设备100可以通过红外或激光测量距离。在一些实施例中，拍摄场景，电子设备100可以利用距离传感器180F测距以实现快速对焦。
按键190包括开机键，音量键等。按键190可以是机械按键。也可以是触摸式按键。电子设备100可以接收按键输入，产生与电子设备100的用户设置以及功能控制有关的键信号输入。
马达191可以产生振动提示，例如本申请中的振动信号。马达191可以用于来电振动提示，也可以用于触摸振动反馈。例如，作用于不同应用(例如拍照，音频播放等)的触摸操作，可以对应不同的振动反馈效果。作用于显示屏194不同区域的触摸操作，马达191也可对应不同的振动反馈效果。不同的应用场景(例如：时间提醒，接收信息，闹钟，游戏等)也可以对应不同的振动反馈效果。触摸振动反馈效果还可以支持自定义。
电子设备100的软件系统可以采用分层架构，事件驱动架构，微核架构，微服务架构，或云架构。本申请实施例以分层架构的Android系统为例，示例性说明电子设备100的软件结构。
图28是本申请实施例的电子设备100的软件结构框图。
分层架构将软件分成若干个层，每一层都有清晰的角色和分工。层与层之间通过软件接口通信。在一些实施例中，将Android系统分为四层，从上至下分别为应用程序层，应用程序框架层，安卓运行时(Android runtime)和系统库，以及内核层。
应用程序层可以包括一系列应用程序包。
如图28所示，应用程序包可以包括相机，日历，地图，邮箱，WLAN，蓝牙，音乐，视频，短信息、微信、WPS等应用程序，进一步地，上述应用程序包还可以包括本申请实施例提供的训练管理程序，通过训练管理程序生成训练计划以及对训练计划进行调整。
应用程序框架层为应用程序层的应用程序提供应用编程接口(application programming interface，API)和编程框架。应用程序框架层包括一些预先定义的函数。
如图28所示，应用程序框架层可以包括窗口管理器，内容提供器，视图系统，电话管理器，资源管理器，通知管理器等。
窗口管理器用于管理窗口程序。窗口管理器可以获取显示屏大小，判断是否有状 态栏，锁定屏幕，截取屏幕等。
内容提供器用来存放和获取数据，并使这些数据可以被应用程序访问。所述数据可以包括视频，图像，音频，拨打和接听的电话，浏览历史和书签，电话簿等。
视图系统包括可视控件，例如显示文字的控件，显示图片的控件等。视图系统可用于构建应用程序。显示界面可以由一个或多个视图组成的。例如，包括短信通知图标的显示界面，可以包括显示文字的视图以及显示图片的视图，还可以包括如本申请实施例提供的运动数据授权界面、训练目的设置界面、主观参数采集页面、训练报告的界面等。
电话管理器用于提供电子设备100的通信功能。例如通话状态的管理(包括接通，挂断等)。
资源管理器为应用程序提供各种资源，比如本地化字符串，图标，图片，布局文件，视频文件、从目标数据来源获取的运动数据等等。
通知管理器使应用程序可以在状态栏中显示通知信息，可以用于传达告知类型的消息，可以短暂停留后自动消失，无需用户交互。比如通知管理器被用于告知下载完成，消息提醒、运动数据的授权信息等。通知管理器还可以是以图表或者滚动条文本形式出现在系统顶部状态栏的通知，例如后台运行的应用程序的通知，还可以是以对话窗口形式出现在屏幕上的通知。例如在状态栏提示文本信息，发出提示音，电子设备振动，指示灯闪烁等。
Android Runtime包括核心库和虚拟机。Android runtime负责安卓系统的调度和管理。
核心库包含两部分：一部分是java语言需要调用的功能函数，另一部分是安卓的核心库。
应用程序层和应用程序框架层运行在虚拟机中。虚拟机将应用程序层和应用程序框架层的java文件执行为二进制文件。虚拟机用于执行对象生命周期的管理，堆栈管理，线程管理，安全和异常的管理，以及垃圾回收等功能。
系统库可以包括多个功能模块。例如：表面管理器(surface manager)，媒体库(Media Libraries)，三维图形处理库(例如：OpenGL ES)，2D图形引擎(例如：SGL)等。
表面管理器用于对显示子系统进行管理，并且为多个应用程序提供了2D和3D图层的融合。
媒体库支持多种常用的音频，视频格式回放和录制，以及静态图像文件等。媒体库可以支持多种音视频编码格式，例如:MPEG4，H.264，MP3，AAC，AMR，JPG，PNG等。
三维图形处理库用于实现三维图形绘图，图像渲染，合成和图层处理等。
2D图形引擎是2D绘图的绘图引擎。
内核层是硬件和软件之间的层。内核层至少包含显示驱动，摄像头驱动，音频驱动，传感器驱动。
下面结合从目标数据来源获取运动数据的场景，示例性说明电子设备100软件以及硬件的工作流程。
当触摸传感器180K接收到触摸操作，相应的硬件中断被发给内核层。内核层将 触摸操作加工成原始输入事件(包括触摸坐标，触摸操作的时间戳等信息)。原始输入事件被存储在内核层。应用程序框架层从内核层获取原始输入事件，识别该输入事件所对应的控件。以该触摸操作是触摸单击操作，该单击操作所对应的控件为运动数据授权界面中的“确定”的控件502为例(其中选取的目标数据来源为智能手表)，训练管理应用调用应用框架层的接口，启动蓝牙通信模块，进而通过调用内核层启动无线通信模块160中的蓝牙驱动，通过无线通信模块160中的蓝牙与智能手表建立无线连接，并从智能手表中获取运动数据，并通过无线通信模块160与处理器110之间的I2C接口，将运动数据传输给处理器110，处理器110可以根据上述接收到的运动数据，生成用户的训练计划。
需要说明的是，上述装置/单元之间的信息交互、执行过程等内容，由于与本申请方法实施例基于同一构思，其具体功能及带来的技术效果，具体可参见方法实施例部分，此处不再赘述。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，仅以上述各功能单元、模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能单元、模块完成，即将所述装置的内部结构划分成不同的功能单元或模块，以完成以上描述的全部或者部分功能。实施例中的各功能单元、模块可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中，上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。另外，各功能单元、模块的具体名称也只是为了便于相互区分，并不用于限制本申请的保护范围。上述系统中单元、模块的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
本申请实施例还提供了一种网络设备，该网络设备包括：至少一个处理器、存储器以及存储在所述存储器中并可在所述至少一个处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现上述任意各个方法实施例中的步骤。
本申请实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时实现可实现上述各个方法实施例中的步骤。
本申请实施例提供了一种计算机程序产品，当计算机程序产品在移动终端上运行时，使得移动终端执行时实现可实现上述各个方法实施例中的步骤。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请实现上述实施例方法中的全部或部分流程，可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一计算机可读存储介质中，该计算机程序在被处理器执行时，可实现上述各个方法实施例的步骤。其中，所述计算机程序包括计算机程序代码，所述计算机程序代码可以为源代码形式、对象代码形式、可执行文件或某些中间形式等。所述计算机可读介质至少可以包括：能够将计算机程序代码携带到拍照装置/电子设备的任何实体或装置、记录介质、计算机存储器、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、电载波信号、电信信号以及软件 分发介质。例如U盘、移动硬盘、磁碟或者光盘等。在某些司法管辖区，根据立法和专利实践，计算机可读介质不可以是电载波信号和电信信号。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详述或记载的部分，可以参见其它实施例的相关描述。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的实施例中，应该理解到，所揭露的装置/网络设备和方法，可以通过其它的方式实现。例如，以上所描述的装置/网络设备实施例仅仅是示意性的，例如，所述模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通讯连接可以是通过一些接口，装置或单元的间接耦合或通讯连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
以上所述实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围，均应包含在本申请的保护范围之内。

Claims (27)

  1. 一种训练计划的生成方法，其特征在于，包括：
    获取用户的多个运动数据；
    基于多个所述运动数据确定所述用户对应的运动员类型；
    基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划。
  2. 根据权利要求1所述的生成方法，其特征在于，获取的多个所述运动数据包含多个运动项目的运动数据，则所述基于多个所述运动数据确定所述用户对应的运动员类型，包括：
    分别根据各个所述运动项目关联的所述运动数据，确定所述运动项目对应的最佳运动成绩；
    将所述最佳运动成绩导入到所述运动项目对应的归一化算法，确定所述运动项目对应的归一化参量；
    基于各个运动项目的归一化参量，确定所述用户的所述运动员类型。
  3. 根据权利要求2所述的生成方法，其特征在于，所述分别根据各个所述运动项目关联的所述运动数据，确定所述运动项目对应的最佳运动成绩，包括：
    确定所述运动项目对应的理想心率；所述理想心率具体是用户在全力运动状态下对应的心率；
    根据所述运动数据中的实际心率以及所述理想心率，确定所述运动数据关联的强度系数；
    根据所述强度系数以及所述实际运动成绩，确定所述运动项目对应的所述最佳运动成绩。
  4. 根据权利要求1所述的生成方法，其特征在于，所述获取用户的多个运动数据，包括：
    生成包含至少一个可选数据来源的运动数据授权界面；
    响应于用户基于所述运动数据授权界面的确认操作，从所述可选数据来源中确定目标数据来源；
    从所述目标数据来源获取所述运动数据。
  5. 根据权利要求1所述的生成方法，其特征在于，在所述基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划之后，还包括：
    显示所述用户对应的训练报告；所述训练报告包含所述训练计划以及关于所述运动员类型以及所述训练方向的描述语段。
  6. 根据权利要求1-5任一项所述的生成方法，其特征在于，所述基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划，包括：
    根据所述训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
    确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
    根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
  7. 根据权利要求6所述的生成方法，其特征在于，所述确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程，包括：
    基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
    根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
    从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
  8. 根据权利要求6所述的生成方法，其特征在于，所述根据所述训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长，包括：
    获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
    基于所述训练方向，确定各个所述训练阶段的时长比例；
    根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
  9. 根据权利要求8所述的生成方法，其特征在于，在所述获取与所述用户的训练目的对应的所述计划模板之前，还包括：
    生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；
    响应于所述用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；
    基于各个所述运动项目的所述目标值，得到所述训练目的。
  10. 根据权利要求1-9任一项所述的生成方法，其特征在于，在所述基于所述运动员类型确定所述用户的训练方向，并生成与所述训练方向匹配的训练计划之后，还包括：
    若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
    根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
  11. 根据权利要求10所述的生成方法，其特征在于，在所述若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面之前，还包括：
    获取所述用户基于所述任一训练课程进行训练时对应的训练压力值；
    对应地，所述根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
    根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
  12. 根据权利要求11所述的生成方法，其特征在于，所述获取所述用户基于所述 任一训练课程进行训练时对应的训练压力值，包括：
    获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
    基于所述实时数据确定所述训练课程对应的所述训练压力值。
  13. 根据权利要求11所述的生成方法，其特征在于，所述根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
    若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
    基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
  14. 一种训练计划的生成方法，其特征在于，包括：
    根据用户的训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长；
    确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程；所述训练时间是基于所述训练阶段的所述阶段周期时长确定的；
    根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划。
  15. 根据权利要求14所述的生成方法，其特征在于，所述确定所述训练阶段关联的课程类别，并为所述训练阶段中的各个训练时间配置属于所述课程类别的训练课程，包括：
    基于所述训练阶段关联的所述课程类别，为所述训练阶段配置训练类别库；
    根据所述训练阶段的阶段周期时长以及所述训练类别库，确定所述训练阶段对应的训练课程框架；所述训练课程框架用于确定所述训练阶段内包含的所述训练时间以及各个所述训练时间对应的课程难度等级；
    从所述训练类别库中，为各个所述训练时间选取与所述课程难度等级匹配的所述训练课程。
  16. 根据权利要求15所述的生成方法，其特征在于，所述根据用户的训练方向，确定预设的计划模板中各个预先划分的训练阶段的阶段周期时长，包括：
    获取与所述用户的训练目的对应的所述计划模板；所述训练目的是所述用户预先设置的；所述计划模板包含预先划分的多个所述训练阶段；
    基于所述训练方向，确定各个所述训练阶段的时长比例；
    根据所述训练阶段的所述时长比例以及预设的训练总时长，确定所述训练阶段的阶段周期时长。
  17. 根据权利要求16所述的生成方法，其特征在于，在所述获取与所述用户的训练目的对应的所述计划模板之前，还包括：
    生成训练目的设置界面；所述训练目的设置界面内包含至少一个运动项目的目的设置区域；
    响应于所述用户在各个所述目的设置区域内的设置操作，确定各个所述运动项目对应的目标值；
    基于各个所述运动项目的所述目标值，得到所述训练目的。
  18. 根据权利要求14-17任一项所述的生成方法，其特征在于，在所述根据所有所述训练阶段的所述训练时间对应的所述训练课程，生成所述训练计划之后，还包括：
    若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据所述用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
    根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
  19. 根据权利要求18所述的生成方法，其特征在于，在所述若检测到所述训练计划中的任一训练课程已完成，则生成主观参数采集页面之前，还包括：
    获取所述用户基于所述任一训练课程进行训练时对应的训练压力值；
    对应地，所述根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
    根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
  20. 根据权利要求19所述的生成方法，其特征在于，所述获取所述用户基于所述任一训练课程进行训练时对应的训练压力值，包括：
    获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
    基于所述实时数据确定所述训练课程对应的所述训练压力值。
  21. 根据权利要求19所述的生成方法，其特征在于，所述根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
    若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
    基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
  22. 一种训练计划的调整方法，其特征在于，包括：
    若检测到训练计划中的任一训练课程已完成，则生成主观参数采集页面，以根据用户在所述主观参数采集页面中发起的反馈操作，确定用户对于所述任一训练课程对应的主观运动参数；
    根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
  23. 根据权利要求22所述的调整方法，其特征在于，在所述若检测到训练计划中的任一训练课程已完成，则生成主观参数采集页面之前，还包括：
    获取所述用户基于所述任一训练课程进行训练时对应的训练压力值；
    对应地，所述根据所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
    根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划。
  24. 根据权利要求23所述的调整方法，其特征在于，所述获取所述用户基于所述任一训练课程进行训练时对应的训练压力值，包括：
    获取用户基于训练计划中任一训练课程进行训练时对应的实时数据；
    基于所述实时数据确定所述训练课程对应的所述训练压力值。
  25. 根据权利要求23或24所述的调整方法，其特征在于，所述根据所述训练压力值以及所述主观运动参数对所述训练计划进行调整，生成调整后的训练计划，包括：
    若到达预设的调整触发时刻，则基于在所述调整触发时刻前完成的所有训练课程对应的所述训练压力值以及所述主观运动参数，确定计划调整方向；
    基于所述计划调整方向对所述训练计划中在所述调整触发时刻后的训练课程进行调整，得到所述调整后的训练计划。
  26. 一种电子设备，包括存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述计算机程序时实现如权利要求1至25任一项所述的方法。
  27. 一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，其特征在于，所述计算机程序被处理器执行时，使得计算机实现如权利要求1至25任一项所述的方法。
PCT/CN2022/113395 2021-08-23 2022-08-18 训练计划的生成方法、装置、电子设备及可读存储介质 WO2023025039A1 (zh)

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