A training device control method, apparatus, device, and storage medium
By acquiring user information and using a plan generation model to generate suitable training plans, the problem of existing training equipment being unable to formulate plans based on user status is solved, thereby improving training effectiveness and the accuracy of equipment control.
Patent Information
- Application Number
- CN202610333139.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-18
- Publication Date
- 2026-08-04
AI Technical Summary
Existing training equipment cannot develop suitable training plans based on the user's actual condition, resulting in poor training effectiveness.
By acquiring the user's training goals and physical information, the system analyzes and processes the completed training plan generation model to generate a training plan data table and description that matches the user's actual state. When training is scheduled to begin, the system controls the training device to perform operations and adjusts the training plan to meet the device system limitations.
This improves the training effectiveness of the training equipment, ensuring the accurate execution of training plans and enhancing the user experience.
Smart Images
Figure CN122499466A_ABST
Abstract
Description
Technical Field
[0001] This application relates to training equipment, and more particularly to a training equipment control method, apparatus, device, and storage medium. Background Technology
[0002] With the development of training equipment, the functions offered by these devices are becoming increasingly diverse. For example, treadmills and other training equipment can be set with different inclines and speeds to meet various training needs. Furthermore, corresponding training plans can be created based on the user's training requirements, and the equipment can be controlled to perform training operations according to these plans.
[0003] In related technologies, different training plans are usually pre-set in the training device, and users can choose one of the multiple training plans to train. However, this training control method cannot formulate a suitable training plan according to the user's actual situation, or the user has to manually set the training plan. However, most users do not have the professional knowledge related to training, and it is difficult to formulate a training plan that matches the user's actual situation, resulting in poor training effect of the training device. Summary of the Invention
[0004] This application provides a training device control method, apparatus, device, and storage medium to solve the technical problem in related technologies that it is difficult to formulate a training plan that conforms to the actual state of the user, resulting in poor training effect of the training device. The method can formulate a training plan according to the actual state of the user and improve the training effect of the training device.
[0005] In a first aspect, embodiments of this application provide a training device control method, comprising:
[0006] The system acquires user training objectives and user body information, sends the user training objectives and user body information to the trained plan generation model, and the trained plan generation model analyzes and processes the user training objectives and user body information to obtain a training plan data table and a training plan description. Initiate a training start query based on the training plan data table and the training plan description; Once training is initiated, the training equipment is controlled to perform training operations according to the training plan data table.
[0007] This application embodiment obtains the user's training goals and physical information, and uses a trained plan generation model to analyze and process the user's training goals and physical information to obtain a training plan data table and a training plan description. Based on the training plan data table and training plan description, a training start query is initiated, and when training is confirmed to start, the training device is controlled to perform training operations according to the training plan data table. By generating a more suitable and professional training plan based on the user's training goals and physical information, the training effect of the training device is effectively improved.
[0008] Furthermore, after obtaining the training plan data table and the training plan description, the process also includes: Determine whether the training parameters in the training plan data table meet the system limitation parameters of the training device; If the training parameters in the training plan data table do not meet the system limitation parameters of the training device, the user training objective and the user body information are sent to the training completed plan generation model to regenerate the training plan data table and training plan description, until the training parameters in the regenerated training plan data table meet the system limitation parameters of the training device.
[0009] As described above, by adjusting the training plan data table and training plan description according to the system limiting parameters of the training equipment, the training parameters in the training plan data table are made to conform to the system limiting parameters of the training equipment, ensuring correct control of the training equipment, accurate execution of the training plan, and guaranteeing the training effect of the training equipment.
[0010] Furthermore, the step of sending the user training objective and the user's physical information to the trained plan generation model, whereby the trained plan generation model analyzes and processes the user training objective and the user's physical information to obtain a training plan data table and a training plan description, including: The system limiting parameters of the training device are determined, and the system limiting parameters of the training device, the user training objective, and the user's physical information are sent to the training completed plan generation model. The training completed plan generation model analyzes and processes the user training objective and the user's physical information to obtain a training plan data table and a training plan description whose training parameters conform to the system limiting parameters of the training device.
[0011] As described above, by sending the system constraint parameters of the training device, the user's training objective, and the user's physical information to the trained plan generation model, a training plan data table and a training plan description with training parameters conforming to the system constraint parameters of the training device are generated. This ensures proper control of the training device, accurate execution of the training plan, and guarantees the training effect of the training device.
[0012] Furthermore, the step of initiating the training start query based on the training plan data table and the training plan description includes: Generate a training plan chart based on the training plan data table; The training start query is initiated based on the training plan diagram and the training plan description.
[0013] As described above, by generating a training plan chart based on the training plan data table, and initiating a training start prompt based on the training plan chart and training plan description, users can intuitively understand the training plan and improve the user experience.
[0014] Furthermore, generating the training plan chart based on the training plan data table includes: The training gradient and training speed at multiple training stages are determined based on the training plan data table. A training plan chart is generated based on the training gradient and training speed of the multiple training phases.
[0015] The above describes how training plan charts are generated based on the training gradient and speed of multiple training stages. The system then initiates a training start query based on the training plan charts and descriptions. By displaying the training gradient and speed in stages, the system makes it easier for users to understand the training plan intuitively and improves the user experience.
[0016] Furthermore, controlling the training device to perform training operations according to the training plan data table includes: Determine the current training stage corresponding to the current time, and control the training equipment to perform training operations based on the training slope and training speed corresponding to the current training stage.
[0017] Furthermore, determining the current training stage corresponding to the current time includes: Determine the length of time between the current time and the start time of training, and determine the current training stage among multiple training stages based on the time length.
[0018] As described above, by accurately determining the current training stage among multiple training stages based on the time elapsed since the start of training, training can be carried out accurately according to the training plan, ensuring the training effect of the training equipment.
[0019] The above-mentioned method, by controlling the training equipment according to the training incline and speed corresponding to the current training stage, helps users to accurately train according to the training plan and effectively improves the training effect of the training equipment.
[0020] In a second aspect, embodiments of this application provide a training device control apparatus, including an information acquisition module, a training query module, and a training execution module, wherein: The information acquisition module is used to acquire user training objectives and user body information, and send the user training objectives and user body information to the training completed plan generation model. The training completed plan generation model analyzes and processes the user training objectives and user body information to obtain a training plan data table and a training plan description. The training query module is used to initiate a training start query based on the training plan data table and the training plan description. The training execution module is used to control the training device to perform training operations according to the training plan data table when training is determined to start.
[0021] This application embodiment obtains the user's training goals and physical information, and uses a trained plan generation model to analyze and process the user's training goals and physical information to obtain a training plan data table and a training plan description. Based on the training plan data table and training plan description, a training start query is initiated, and when training is confirmed to start, the training device is controlled to perform training operations according to the training plan data table. By generating a more suitable and professional training plan based on the user's training goals and physical information, the training effect of the training device is effectively improved.
[0022] In a third aspect, embodiments of this application provide a training device control device, including: a memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the training device control method as described in the first aspect.
[0023] In a fourth aspect, embodiments of this application provide a storage medium for storing computer-executable instructions, which, when executed by a computer processor, are used to perform the training device control method as described in the first aspect. Attached Figure Description
[0024] Figure 1 This is a flowchart of a training device control method provided in an embodiment of this application; Figure 2 This is a flowchart of another training device control method provided in an embodiment of this application; Figure 3 This is a schematic diagram of a training start query interface provided in an embodiment of this application; Figure 4 This is a schematic diagram of a training progress interface provided in an embodiment of this application; Figure 5This is a schematic diagram of the structure of a training equipment control device provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a training equipment control device provided in an embodiment of this application. Detailed Implementation
[0025] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but additional steps not included in the drawings may also be present. The above processes can correspond to methods, functions, procedures, subroutines, subroutines, etc.
[0026] In existing training plan-based training device control schemes, different training plans are typically pre-set in the training device, or the user manually sets the training plan. With pre-set training plans, the user can choose one from multiple plans, but this method cannot tailor a suitable training plan based on the user's actual situation. As for manually setting training plans, most users lack the necessary training expertise to create a plan that matches their actual condition. Therefore, both pre-set and manual methods struggle to produce training plans that accurately reflect the user's situation, resulting in poor training effectiveness. To address these issues, this application provides a training device control method according to an embodiment of the present application.
[0027] Figure 1 A flowchart of a training equipment control method provided in an embodiment of this application is given. The training equipment control method provided in this embodiment of the application can be executed by a training equipment control device, which can be implemented by hardware and / or software and integrated into a training equipment control device (e.g., a treadmill).
[0028] The following description uses the example of a training equipment control device executing a training equipment control method. (Reference) Figure 1 The control method for this training equipment includes: S110: Obtain the user's training objectives and user's body information, and send the user's training objectives and user's body information to the trained plan generation model. The trained plan generation model analyzes and processes the user's training objectives and user's body information to obtain the training plan data table and training plan description.
[0029] For example, the user's training goal is obtained, wherein the user can provide the training goal through text input and / or voice input. After obtaining the user's training goal, the user's physical information is obtained, wherein the user's physical information may include the user's age, gender, height, weight, etc.
[0030] Optionally, input controls can be provided on the interactive interface of the training equipment control device. Users can input text or voice through the input controls, thereby determining the user's training goal based on the user's input. For example, if a user clicks the voice input button on the input control of the interactive interface and says "I want to improve my physical fitness," the training goal will be "improve physical fitness." Optionally, multiple selectable preset training goals can also be displayed on the interactive interface, and the user's training goal can be determined based on one or more preset training goals selected by the user.
[0031] In one embodiment, a user training goal can be a single training goal, such as "improving physical fitness," "aerobic training," "anaerobic training," "aerobic and anaerobic interval training," "incline training," "enhancing cardiopulmonary function," "strengthening lower limb muscle groups," or "burning fat." A user training goal can also include multiple training goals; for example, a user training goal could be "perform aerobic training first, then strengthen lower limb muscle groups." In one embodiment, the training duration corresponding to a user training goal can be a default training duration or a user-provided training duration. Optionally, a user training goal can also include a target training duration; for example, a user training goal could be "develop a 30-minute physical fitness training plan."
[0032] In one embodiment, after obtaining the user's training goals and physical information, a training plan data table and a training plan description can be generated based on these information. The training plan data table records training data suitable for the user's physical information and aimed at achieving the user's training goals. Taking a treadmill as an example of a training device control device, the training plan data table can record training parameters at different training stages. Training parameters can be understood as control parameters for the training device. For example, training parameters for a treadmill may include training incline and training speed. Training incline adjusts the tilt of the treadmill belt to simulate the user climbing an incline, and training speed adjusts the rotational speed of the treadmill belt to adjust the amplitude and frequency of the user's running on the treadmill.
[0033] The training plan description provided in this application is adapted to the training plan data table. The training plan description can be a natural language description of the training plan corresponding to the training plan data table. For example, the training plan description could be: "Hello! Based on your fitness level, I have designed this 30-minute interval training plan for you. We will start with a light warm-up, gradually increase the speed and incline to challenge your cardiovascular function, add a high-intensity phase in the middle to improve endurance, and finally finish smoothly with a cool-down phase. Please keep your core engaged throughout the entire process, pay attention to your breathing rhythm, and reduce the intensity immediately if you experience any discomfort."
[0034] Optionally, when generating the training plan data table and training plan description based on the user's training objectives and physical information, the training device control method provided in this application may send the user's training objectives and physical information to a trained plan generation model (e.g., a large language model), whereby the plan generation model analyzes and processes the user's training objectives and physical information to obtain the training plan data table and training plan description. Alternatively, the user's training objectives and physical information may be encapsulated into data in a preset format (e.g., JSON data) and pushed to the plan generation model, whereby the plan generation model generates the training plan data table and training plan description based on the user's training objectives and physical information.
[0035] In one embodiment, a prompt word can be generated based on the user's training objective and user's physical information, and sent to the plan generation model so that the plan generation model can output a corresponding training plan data table and training plan description based on the prompt word. Optionally, the prompt word could be "Please plan a training plan for the user based on the 'training objective' and 'user's physical information,' and provide a corresponding training plan data table and training plan description."
[0036] In one embodiment, various combinations of user training target samples and user body information samples, as well as training plan data table samples and training plan description samples corresponding to different combinations of user training target samples and user body information samples, can be collected. The user training target samples and user body information samples are used as input information for training, and the corresponding training plan data table samples and training plan description samples are used as output information for training the plan generation model. Optionally, the initial plan generation model can be a pre-trained neural network model, such as a pre-trained large language model.
[0037] During the training of the plan generation model, the loss value of the plan generation model can be determined by the deviation between the predicted training plan data table and the predicted training plan description output by the plan generation model based on the user training target sample and the user body information sample and the corresponding training plan data table sample and training plan description sample. The parameters of the plan generation model are then adjusted based on the loss value until the loss value of the plan generation model is less than the preset loss threshold, thus obtaining the trained plan generation model.
[0038] The training plan generation model can be deployed locally or on a server. This application generates training plan data tables and descriptions that conform to the user's training objectives and physical information through the trained training plan generation model. The generated training plan data tables and descriptions are more consistent with the user's actual state, effectively improving the training effect of the training equipment.
[0039] S120: Initiate a training start query based on the training plan data table and training plan description.
[0040] For example, after obtaining the training plan data table and training plan description, a training start prompt can be initiated on the interactive interface based on the training plan data table and training plan description. For instance, the training plan data table and training plan description can be displayed on the interactive interface. The display of the training plan data table can be the original training plan data table or a training plan chart generated based on the training plan data table; the display of the training plan description can be the text corresponding to the training plan description displayed on the interactive interface, or the training plan description can be played via voice.
[0041] In one embodiment, after initiating a training start query based on the training plan data table and training plan description, the system can wait for the user to confirm whether to proceed with training based on the training plan data table. Optionally, a "Start Training" button can be displayed on the interactive interface. Upon detecting that the user has clicked the "Start Training" button, training can be initiated. Alternatively, the user's voice data can be acquired, and training can be initiated based on the speech recognition results of the voice data. For example, upon detecting voice data indicating "Start Training," training can be initiated.
[0042] S130: Once training is initiated, control the training equipment to perform training operations based on the training plan data table.
[0043] For example, when training is initiated, the training device is controlled to perform training operations according to the training plan data table. Optionally, during the process of controlling the training device to perform training operations according to the training plan data table, the current training stage and the corresponding training plan data can be displayed on the interactive interface. For example, assuming the training device has slope adjustment and speed adjustment functions, the training slope and training speed corresponding to the current training stage can be displayed on the interactive interface.
[0044] In one embodiment, the training plan data table may record the training gradient and training speed of multiple training stages, wherein different training stages correspond to different combinations of training gradient and training speed, and different training stages correspond to different training time ranges. Accordingly, when controlling the training device to perform training operations according to the training plan data table, the current training stage corresponding to the current time may be determined, and the training device may be controlled to perform training operations according to the training gradient and training speed corresponding to the current training stage.
[0045] For example, the system determines the training time range matched by the current time, defines the training stage corresponding to this time range as the current training stage, and sets the slope and speed of the training equipment to match the current training stage, thereby controlling the equipment to perform training operations. This application helps users accurately train according to their training plan by controlling the equipment based on the training slope and speed corresponding to the current training stage, effectively improving the training effect of the equipment.
[0046] Optionally, determining the current training stage corresponding to the current time can be achieved by: determining the time elapsed between the current time and the training start time, and then determining the current training stage from among multiple training stages based on this time elapsed. For example, after determining the time elapsed between the current time and the training start time, the training time ranges corresponding to each training stage are sequentially accumulated according to the order of the multiple training stages in the training plan data table to obtain an accumulated time start point and an accumulated time end point until the current training stage is determined. Wherein, if the time elapsed between the current time and the training start time falls within the time range of the accumulated time start point and the accumulated time end point (e.g., the time range is: [accumulated time start point, accumulated time end point)), the training stage corresponding to the last accumulated training time range can be determined as the current training stage. Optionally, the training start time can be the time when training begins, or the time when the training device begins executing training operations according to the training plan data table. When accumulating the training time range corresponding to the training phase, the cumulative time end point corresponding to the previous training phase can be used as the cumulative time start point corresponding to the current training phase. The cumulative time end point corresponding to the previous training phase plus the duration of the training time range of the current training phase can be used as the cumulative time end point. The cumulative time start point corresponding to the first training phase is 0, and the cumulative time end point is the value corresponding to the duration of the training time range.
[0047] Assuming the generated training plan data table records three training phases, each lasting 5 minutes, including a warm-up phase, an improvement phase, and a cool-down phase, and the current time is 8 minutes from the start of training, we can first determine the starting and ending times for the warm-up phase as 0 minutes and 5 minutes respectively, corresponding to a time range of [0 minutes, 5 minutes). If the duration falls outside this range, we can then continue accumulating the training time for the improvement phase. At this point, the starting and ending times for the improvement phase are 5 minutes and 10 minutes respectively, corresponding to a time range of [5 minutes, 10 minutes]. If the duration falls within this range, we can then designate the improvement phase as the current training phase and end the accumulation of the training time range. This application accurately determines the current training phase among multiple training phases based on the time remaining from the start of training, ensuring accurate training according to the training plan and guaranteeing the training effectiveness of the training equipment.
[0048] The above describes a process where, by acquiring user training goals and physical information, a training plan data table and a training plan description are obtained using a trained plan generation model. Based on these data, a training start query is initiated. Upon confirmation of training start, the training device is controlled to perform training operations according to the training plan data table. By generating a more suitable and professional training plan based on the user's training goals and physical information, the training effect of the training device is effectively improved.
[0049] Based on the above embodiments, Figure 2 A flowchart of another training device control method provided in an embodiment of this application is given, which is a concretization of the above-described training device control method. (Reference) Figure 2 The control method for this training equipment includes: S210: Obtain the user's training objectives and user's body information, and send the user's training objectives and user's body information to the trained plan generation model. The trained plan generation model analyzes and processes the user's training objectives and user's body information to obtain the training plan data table and training plan description.
[0050] In one possible embodiment, the training device control method provided in this application, after sending the user's training objective and user's body information to the trained plan generation model, and having the trained plan generation model analyze and process the user's training objective and user's body information to obtain a training plan data table and a training plan description, further includes: determining whether the training parameters in the training plan data table meet the system limitation parameters of the training device; if the training parameters in the training plan data table do not meet the system limitation parameters of the training device, sending the user's training objective and user's body information to the trained plan generation model to regenerate the training plan data table and training plan description, until the training parameters in the regenerated training plan data table meet the system limitation parameters of the training device.
[0051] In one embodiment, various combinations of user training target samples and user body information samples, as well as training plan data table samples and training plan description samples corresponding to different combinations of training target samples and user body information samples, can be collected. The training target samples and user body information samples are used as input information for training, and the corresponding training plan data table samples and training plan description samples are used as output information to train the plan generation model. During the training process of the plan generation model, the loss value of the plan generation model can be determined based on the deviation between the predicted training plan data table and predicted training plan description output by the plan generation model based on the training target samples and user body information samples and the corresponding training plan data table samples and training plan description samples. The parameters of the plan generation model are then adjusted based on the loss value until the loss value of the plan generation model is less than a preset loss threshold, resulting in a trained plan generation model.
[0052] In one embodiment, the model can also collect various combinations of user training target samples, user body information samples, and system constraint parameter samples, as well as training plan data table samples and training plan description samples corresponding to different combinations of training target samples, user body information samples, and system constraint parameter samples. The training target samples, user body information samples, and system constraint parameter samples are used as input information for training, and the corresponding training plan data table samples and training plan description samples are used as output information to train the plan generation model. During the training process of the plan generation model, the loss value of the plan generation model can be determined based on the deviation between the predicted training plan data table and predicted training plan description output by the plan generation model based on the training target samples, user body information samples, and system constraint parameter samples, and the corresponding training plan data table samples and training plan description samples. The parameters of the plan generation model are then adjusted based on the loss value until the loss value of the plan generation model is less than a preset loss threshold, resulting in a trained plan generation model.
[0053] For example, after obtaining the training plan data table and the training plan description, it is determined whether the training parameters in the training plan data table conform to the system limitation parameters of the training device, that is, whether the training parameters in the training plan data table are within the limits of the system limitation parameters of the training device. In one embodiment, when the training parameters in the training plan data table are less than or equal to the system limitation parameters of the training device, it can be determined that the training parameters in the training plan data table conform to the system limitation parameters of the training device; while when the training parameters in the training plan data table are greater than the system limitation parameters of the training device, it can be determined that the training parameters in the training plan data table do not conform to the system limitation parameters of the training device.
[0054] Optionally, the system limiting parameters of the training device may include slope limiting parameters (i.e., the adjustable maximum slope) and / or speed limiting parameters (i.e., the adjustable maximum speed). The system limiting parameters of the training device may be recorded in the training device or determined according to the system limiting parameters set by the user (e.g., the user can manually adjust the maximum allowable slope and / or the maximum allowable speed of the training device).
[0055] In one embodiment, the combination of training gradient and training speed recorded in the training plan data table for each training stage can be used as training parameters, and the combination of gradient limitation parameters and speed limitation parameters of the training device can be used as system limitation parameters. Whether the combination of training gradient and training speed for each training stage conforms to the system limitation parameters of the training device is determined based on the comparison results. For example, for the combination of training gradient and training speed for a training stage, if the training gradient is less than or equal to the gradient limitation parameter and the training speed is less than or equal to the speed limitation parameter, it can be determined that the training parameters in the training plan data table conform to the system limitation parameters of the training device; while if the training gradient is greater than the gradient limitation parameter or the training speed is greater than the speed limitation parameter, it can be determined that the training parameters in the training plan data table do not conform to the system limitation parameters of the training device.
[0056] In one embodiment, when it is determined that the training parameters in the training plan data table do not meet the system limitation parameters of the training device, it is necessary to regenerate the training plan data table and training plan description based on the user's training objectives and user physical information until the training parameters in the regenerated training plan data table meet the system limitation parameters of the training device.
[0057] In one embodiment, when it is determined that the training parameters in the training plan data table do not conform to the system limitations of the training device, a prompt message can be sent to the plan generation model stating, "The training plan data table does not conform to the system limitations of the training device. Regenerate the training plan data table and training plan description according to the system limitations of the training device." This allows the plan generation model to regenerate a training plan data table and training plan description with training parameters conforming to the system limitations of the training device. This application ensures correct control of the training device, accurate execution of the training plan, and guaranteed training effectiveness by adjusting the training plan data table and training plan description according to the system limitations of the training device.
[0058] In one possible embodiment, the training device control method provided in this application generates a training plan data table and a training plan description based on the user's training objective and user's physical information. This may involve: determining the system limiting parameters of the training device; sending the system limiting parameters of the training device, the user's training objective, and the user's physical information to the training-completed plan generation model; and having the training-completed plan generation model analyze and process the user's training objective and user's physical information to obtain a training plan data table and a training plan description whose training parameters conform to the system limiting parameters of the training device.
[0059] For example, after obtaining the user's training objective and physical information, the system limiting parameters of the training device are determined. Based on the system limiting parameters, the user's training objective, and the user's physical information, a prompt message for the training plan is generated. For instance, the prompt message could be, "Please plan a training plan for the user based on the 'training objective' and 'user's physical information,' requiring the training gradient and speed to be limited within the range of the 'system limiting parameters of the training device,' and provide a corresponding training plan data table and training plan description." The prompt message is sent to the plan generation model so that the model can generate a training plan data table and training plan description with training parameters conforming to the system limiting parameters of the training device, based on the system limiting parameters, user's training objective, and user's physical information in the prompt message.
[0060] This application sends the system limitation parameters of the training device, the user's training objective, and the user's physical information to the trained plan generation model to generate a training plan data table and a training plan description whose training parameters conform to the system limitation parameters of the training device. This ensures proper control of the training device, accurate execution of the training plan, and guarantees the training effect of the training device.
[0061] S220: Generate a training plan chart based on the training plan data table.
[0062] S230: Initiate a training start query based on the training plan chart and training plan description.
[0063] For example, after obtaining the training plan data table and the training plan description, the training parameters corresponding to each training stage in the training plan data table are determined. A parameter line graph is generated based on the training parameters corresponding to each training stage, and a training plan chart is generated based on the parameter line graph. The parameter line graph reflects the changes in training parameters at different training stages.
[0064] Furthermore, the interactive interface displays a training plan chart and description to prompt the user to begin training. Users can use the line graph in the training plan chart to determine the changes in training parameters at different training stages, and adjust the training parameters for each stage according to their needs. This application generates a training plan chart based on the training plan data table and prompts the user to begin training based on the chart and description, making it easier for users to intuitively understand the training plan and improving the user experience.
[0065] In one embodiment, the training device control method provided in this application generates a training plan chart based on a training plan data table, which may involve: determining the training gradient and training speed in multiple training stages based on the training plan data table; and generating a training plan chart based on the training gradient and training speed in multiple training stages.
[0066] For example, the training gradient and training speed corresponding to each training stage in the training plan data table are determined. A gradient line chart and a speed line chart are generated based on the training gradient and training speed of each training stage. A training plan chart is then generated based on both the gradient and speed line charts. Alternatively, the gradient and speed line charts can be merged into a single chart to obtain the training plan chart. The gradient line chart reflects the changes in training gradient across different training stages, and the speed line chart reflects the changes in training speed across different training stages.
[0067] This application generates a training plan chart based on the training gradient and training speed of multiple training stages, and initiates a training start query based on the training plan chart and training plan description. By displaying the training gradient and training speed in a phased manner, it makes it easier for users to intuitively understand the training plan and improves the user experience.
[0068] S240: Once training is initiated, control the training equipment to perform training operations based on the training plan data table.
[0069] For example, suppose the generated training plan data table records 6 training phases, each with a duration of 5 minutes, including a warm-up phase, a first improvement phase, a second improvement phase, a high-intensity phase, a first cool-down phase, and a second cool-down phase. The training gradient and speed corresponding to the warm-up phase are 1° and 6 km / h, respectively; the training gradient and speed corresponding to the first improvement phase are 2° and 8 km / h, respectively; the training gradient and speed corresponding to the second improvement phase are 4° and 10 km / h, respectively; the training gradient and speed corresponding to the high-intensity phase are 6° and 12 km / h, respectively; the training gradient and speed corresponding to the first cool-down phase are 3° and 8 km / h, respectively; and the training gradient and speed corresponding to the second cool-down phase are 1° and 6 km / h, respectively. The training plan is described as follows: "Hello! Based on your fitness level, I have designed this 30-minute interval training plan for you. We will start with a gentle warm-up, gradually increase the speed and incline to challenge your cardiovascular system, add a high-intensity phase in the middle to improve endurance, and finish smoothly with a cool-down phase. Please keep your core engaged throughout, pay attention to your breathing rhythm, and reduce the intensity immediately if you experience any discomfort." Furthermore, a speed line graph can be generated based on the training plan data table to correspond to the training speed of each training stage. A training plan chart can then be generated based on the slope line graph and the speed line graph, and finally, the slope line graph and the speed line graph can be merged into a single chart to obtain the training plan chart. For example... Figure 3 The provided diagram shows a training start query interface. The interactive interface displays a training plan chart and a training plan description, and a start training button is added to the interactive interface. Users can intuitively understand the training plan based on the displayed training plan chart and training plan description, and can start training by clicking the start training button.
[0070] like Figure 4 As shown in the provided diagram of a training progress interface, after confirming the start of training, the interface jumps to a section displaying the training progress. At this point, the interface displays a training plan chart, as well as the current training gradient and speed. Optionally, the current training progress can also be displayed on the interface (in the diagram, the current training progress is indicated by the progress indicator S), allowing users to intuitively understand the current training progress.
[0071] As described above, by acquiring the user's training objectives and physical information, and using a trained plan generation model to analyze and process these, a training plan data table and a training plan description are obtained. Based on these data, a training start prompt is initiated. Upon confirmation of training start, the training device is controlled to execute training operations according to the training plan data table. By generating a more suitable and professional training plan based on the user's training objectives and physical information, the training device's training effectiveness is effectively improved. Furthermore, by generating a training plan chart from the data table and initiating a training start prompt based on the chart and description, the user can intuitively understand the training plan, enhancing the user experience.
[0072] Figure 5 A schematic diagram of a training equipment control device according to an embodiment of this application is provided. (Reference) Figure 5 The training equipment control device includes an information acquisition module 51, a training inquiry module 52, and a training execution module 53.
[0073] The information acquisition module 51 is used to acquire the user's training objectives and user's body information, and send the user's training objectives and user's body information to the trained plan generation model. The trained plan generation model analyzes and processes the user's training objectives and user's body information to obtain a training plan data table and a training plan description. The training query module 52 is used to initiate a training start query based on the training plan data table and the training plan description. The training execution module 53 is used to control the training device to perform training operations based on the training plan data table when training has started.
[0074] The above describes a process where, by acquiring user training goals and physical information, a training plan data table and a training plan description are obtained using a trained plan generation model. Based on these data, a training start query is initiated. Upon confirmation of training start, the training device is controlled to perform training operations according to the training plan data table. By generating a more suitable and professional training plan based on the user's training goals and physical information, the training effect of the training device is effectively improved.
[0075] In one possible embodiment, the information acquisition module 51 is further configured to: Determine whether the training parameters in the training plan data table meet the system limitations of the training equipment; If the training parameters in the training plan data table do not meet the system limitations of the training device, the user's training objective and user's physical information are sent to the completed plan generation model to regenerate the training plan data table and training plan description until the training parameters in the regenerated training plan data table meet the system limitations of the training device.
[0076] In one possible embodiment, the information acquisition module 51 sends the user's training objective and user's physical information to the trained plan generation model. The trained plan generation model analyzes and processes the user's training objective and user's physical information to obtain a training plan data table and a training plan description, including: The system limiting parameters of the training equipment are determined, and the system limiting parameters of the training equipment, the user's training objectives, and the user's physical information are sent to the training plan generation model. The training plan generation model analyzes and processes the user's training objectives and physical information to obtain a training plan data table and a training plan description that conform to the system limiting parameters of the training equipment.
[0077] In one possible embodiment, the training query module 52 initiates a training start query based on the training plan data table and the training plan description, including: Generate training plan charts based on the training plan data table; Initiate training based on the training plan chart and training plan description.
[0078] In one possible embodiment, the training query module 52 generates a training plan chart based on the training plan data table, including: The training gradient and speed at multiple training stages are determined based on the training plan data table. Training plan charts are generated based on the training gradient and training speed of multiple training phases.
[0079] In one possible embodiment, the training execution module 53 controls the training device to perform training operations according to the training plan data table, including: determining the current training stage corresponding to the current time, and controlling the training device to perform training operations according to the training slope and training speed corresponding to the current training stage.
[0080] In one possible embodiment, the training execution module 53 determines the current training stage corresponding to the current time, including: determining the time length between the current time and the training start time, and determining the current training stage among multiple training stages based on the time length.
[0081] It is worth noting that in the above-described embodiments of the training equipment control device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of this application.
[0082] This application also provides a training equipment control device, which can integrate the training equipment control device provided in this application. Figure 6 This is a schematic diagram of the structure of a training equipment control device provided in an embodiment of this application. (Reference) Figure 6 The training device control device includes: an input device 63, an output device 64, a memory 62, and one or more processors 61; the memory 62 is used to store one or more programs; when one or more programs are executed by one or more processors 61, the one or more processors 61 implement the training device control method provided in the above embodiments. The input device 63, output device 64, memory 62, and processors 61 can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.
[0083] The memory 62, as a computing device readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the training device control method provided in any embodiment of this application (e.g., information acquisition module 51, training query module 52, and training execution module 53 in the training device control apparatus). The memory 62 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device, etc. Furthermore, the memory 62 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 62 may further include memory remotely located relative to the processor 61, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0084] Input device 63 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. Output device 64 may include display devices such as a display screen.
[0085] The processor 61 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 62, thereby realizing the training device control method described above.
[0086] The training equipment control device, equipment, and computer provided above can be used to execute the training equipment control method provided in any of the above embodiments, and have corresponding functions and beneficial effects.
[0087] This application also provides a storage medium for storing computer-executable instructions. When executed by a computer processor, these computer-executable instructions are used to execute the training device control method provided in the above embodiments. The training device control method includes: acquiring user training objectives and user body information; sending the user training objectives and user body information to a training-completed plan generation model; having the training-completed plan generation model analyze and process the user training objectives and user body information to obtain a training plan data table and a training plan description; initiating a training start query based on the training plan data table and the training plan description; and, if training is determined to start, controlling the training device to perform training operations based on the training plan data table.
[0088] Storage medium – any type of memory device or storage device. The term “storage medium” is intended to include: mounting media, such as CD-ROMs, floppy disks, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (e.g., hard disks or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. Furthermore, storage media may reside in a first computer system in which a program is executed, or may reside in a different second computer system connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term “storage medium” can include two or more storage media that may reside in different locations (e.g., in different computer systems connected via a network). Storage media may store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.
[0089] Of course, the computer-executable instructions stored in the storage medium provided in the embodiments of this application are not limited to the training device control method provided above, but can also execute related operations in the training device control method provided in any embodiment of this application.
[0090] The training device control apparatus, device and storage medium provided in the above embodiments can execute the training device control method provided in any embodiment of this application. For technical details not described in detail in the above embodiments, please refer to the training device control method provided in any embodiment of this application.
[0091] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments provided herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of this application, the scope of which is determined by the scope of the claims.
Claims
1. A method for controlling a training device, characterized in that, include: The system acquires user training objectives and user body information, sends the user training objectives and user body information to the trained plan generation model, and the trained plan generation model analyzes and processes the user training objectives and user body information to obtain a training plan data table and a training plan description. Initiate a training start query based on the training plan data table and the training plan description; Once training is initiated, the training equipment is controlled to perform training operations according to the training plan data table.
2. The training equipment control method according to claim 1, characterized in that, After obtaining the training plan data table and the training plan description, the process also includes: Determine whether the training parameters in the training plan data table meet the system limitation parameters of the training device; If the training parameters in the training plan data table do not meet the system limitation parameters of the training device, the user training objective and the user body information are sent to the training completed plan generation model to regenerate the training plan data table and training plan description, until the training parameters in the regenerated training plan data table meet the system limitation parameters of the training device.
3. The training equipment control method according to claim 1, characterized in that, The step involves sending the user training objective and the user's physical information to the trained plan generation model. The trained plan generation model then analyzes and processes the user training objective and the user's physical information to obtain a training plan data table and a training plan description, including: The system limiting parameters of the training device are determined, and the system limiting parameters of the training device, the user training objective, and the user's physical information are sent to the training completed plan generation model. The training completed plan generation model analyzes and processes the user training objective and the user's physical information to obtain a training plan data table and a training plan description whose training parameters conform to the system limiting parameters of the training device.
4. The training equipment control method according to claim 1, characterized in that, The step of initiating a training start query based on the training plan data table and the training plan description includes: Generate a training plan chart based on the training plan data table; The training start query is initiated based on the training plan diagram and the training plan description.
5. The training equipment control method according to claim 4, characterized in that, The step of generating a training plan chart based on the training plan data table includes: The training gradient and training speed at multiple training stages are determined based on the training plan data table. A training plan chart is generated based on the training gradient and training speed of the multiple training phases.
6. The training equipment control method according to claim 1, characterized in that, The step of controlling the training device to perform training operations according to the training plan data table includes: Determine the current training stage corresponding to the current time, and control the training equipment to perform training operations based on the training slope and training speed corresponding to the current training stage.
7. The training equipment control method according to claim 6, characterized in that, Determining the current training phase corresponding to the current time includes: Determine the length of time between the current time and the start time of training, and determine the current training stage among multiple training stages based on the time length.
8. A training equipment control device, characterized in that, It includes an information acquisition module, a training query module, and a training execution module, among which: The information acquisition module is used to acquire user training objectives and user body information, and send the user training objectives and user body information to the training completed plan generation model. The training completed plan generation model analyzes and processes the user training objectives and user body information to obtain a training plan data table and a training plan description. The training query module is used to initiate a training start query based on the training plan data table and the training plan description. The training execution module is used to control the training device to perform training operations according to the training plan data table when training is determined to start.
9. A training equipment control device, characterized in that, include: Memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the training device control method as described in any one of claims 1-7.
10. A storage medium for storing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the training device control method as described in any one of claims 1-7.