A method for generating fitness guidance information, terminal device and storage medium

Abstract

The present application is applicable to the field of data processing technology, and provides a method for generating fitness guidance information, a terminal device, and a computer-readable storage medium, the method comprising: obtaining the user's body shape data, physical measurement data, and fitness preference information; generating the user's fitness guidance information based on the body shape data, physical measurement data, fitness preference information, and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities. In the method provided by the present application, the terminal device can determine the specific fitness needs of different users through the acquired user's body shape data, physical measurement data, and fitness preference information, and can also enrich the generated fitness guidance information content of the user through the fitness knowledge graph, thereby improving the accuracy of the generated fitness guidance information.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and in particular, relates to a method for generating fitness guidance information, a terminal device, and a computer-readable storage medium. Background Art

[0002] With the improvement of living standards, more and more people are starting to exercise. Scientific and reasonable exercise can improve physical quality and increase physical fitness, while blind and excessive exercise will cause damage to the body. Therefore, scientific and reasonable fitness guidance information is essential.

[0003] However, the prior art simply generates the user's fitness guidance information based on the user's body data and fitness purpose, and the accuracy of the generated fitness guidance information is low. Summary of the invention

[0004] The embodiments of the present application provide a method for generating fitness guidance information, a terminal device, and a computer-readable storage medium, which can improve the accuracy of the generated fitness guidance information.

[0005] In a first aspect, an embodiment of the present application provides a method for generating fitness guidance information, comprising:

[0006] Obtain the user's body shape data, physical measurement data, and fitness preference information;

[0007] Generate fitness guidance information for the user based on the body shape data, the physical measurement data, the fitness preference information and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationships between the entities.

[0008] Optionally, generating the user's fitness guidance information according to the body shape data, the physical measurement data, the fitness preference information and a pre-constructed fitness knowledge graph includes:

[0009] Determining a target training part of the user according to the fitness preference information;

[0010] Determining a first training action of the user according to the body shape data, the physical measurement data, the fitness preference information, the target training part, and the fitness knowledge graph;

[0011] Determining a first training parameter corresponding to the first training action according to the body shape data, the physical measurement data and the fitness preference information;

[0012] The fitness guidance information is generated according to the first training action and the first training parameter.

[0013] Optionally, the fitness element includes a training action and a training part; and determining the first training action of the user according to the body shape data, the physical measurement data, the fitness preference information, the target training part and the fitness knowledge graph includes:

[0014] Searching for a set of body part training actions associated with the target training body part from the fitness knowledge graph;

[0015] The first training action is selected from the body part training action set according to the body shape data, the body measurement data and the fitness preference information.

[0016] Optionally, before selecting the first training action from the body part training action set according to the body shape data, the physical measurement data and the fitness preference information, the method further includes:

[0017] For each training action in the part training action set, scoring the training action according to the action type of the training action and a preset action scoring rule;

[0018] The training actions in the part training action set whose scores are less than a first threshold are deleted.

[0019] Optionally, each training action in the part training action set corresponds to a sport type; before selecting the first training action from the part training action set according to the body shape data, the physical measurement data and the fitness preference information, the method further includes:

[0020] Determining the desired exercise type of the user according to the fitness preference information;

[0021] In the part training action set, the training actions whose corresponding exercise types are different from the expected exercise type are deleted.

[0022] Optionally, the fitness element includes training actions and body shape data; the body shape data includes target body shape data and human body index data; and determining the first training action of the user according to the body shape data, the physical measurement data, the fitness preference information, the target training part and the fitness knowledge graph includes:

[0023] Searching for a set of posture training actions associated with the target posture data from the fitness knowledge graph;

[0024] The first training action is selected from the body training action set according to the human body index data, the physical measurement data, the target training part and the fitness preference information.

[0025] Optionally, generating the user's fitness guidance information according to the body shape data, the physical measurement data, the fitness preference information and a pre-constructed fitness knowledge graph includes:

[0026] Obtaining the training stage of the user;

[0027] Calculating the body fat percentage of the user according to the body shape data;

[0028] Determining a training theme for the user from the fitness knowledge graph according to the body fat percentage;

[0029] Determining a second training action of the user from the fitness knowledge graph according to the training theme, the training stage, the physical measurement data, and the fitness preference information;

[0030] Determining a second training parameter corresponding to the second training action according to the body shape data, the physical measurement data and the fitness preference information;

[0031] The fitness guidance information is generated according to the second training action and the second training parameter.

[0032] Optionally, after generating the user's fitness guidance information according to the body shape data, the physical measurement data, the fitness preference information and the pre-constructed fitness knowledge graph, the method further includes:

[0033] Acquire first training result data obtained by the user through training based on the fitness guidance information, and second training result data obtained by the user without training based on the fitness guidance information;

[0034] The fitness guidance information is adjusted according to the first training achievement data and the second training achievement data.

[0035] In a second aspect, an embodiment of the present application provides a device for generating fitness guidance information, including:

[0036] A first acquisition unit, used to acquire the user's body shape data, physical measurement data and fitness preference information;

[0037] The first generating unit is used to generate fitness guidance information for the user according to the body shape data, the physical measurement data, the fitness preference information and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities.

[0038] In a third aspect, an embodiment of the present application provides a terminal device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for generating fitness guidance information as described in any one of the first aspects above are implemented.

[0039] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for generating fitness guidance information as described in any one of the first aspects above are implemented.

[0040] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device can execute the method for generating fitness guidance information described in any one of the first aspects above.

[0041] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0042] The embodiment of the present application provides a method for generating fitness guidance information, which obtains the user's body shape data, physical measurement data and fitness preference information; generates the user's fitness guidance information based on the body shape data, physical measurement data, fitness preference information and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities. In the method provided by the present application, the terminal device can determine the specific fitness needs of different users through the acquired user's body shape data, physical measurement data and fitness preference information, and can also enrich the generated user's fitness guidance information content through the fitness knowledge graph, thereby improving the accuracy of the generated fitness guidance information. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 is a flowchart of a method for generating fitness guidance information provided by an embodiment of the present application;

[0045] Figure 2 is a flowchart of a method for generating fitness guidance information provided by another embodiment of the present application;

[0046] Figure 3is a flowchart of a method for generating fitness guidance information provided in yet another embodiment of the present application;

[0047] Figure 4 is a flowchart of a method for generating fitness guidance information provided by another embodiment of the present application;

[0048] Figure 5 is a flowchart of a method for generating fitness guidance information provided by another embodiment of the present application;

[0049] Figure 6 is a flowchart of a method for generating fitness guidance information provided by another embodiment of the present application;

[0050] Figure 7 is a flowchart of a method for generating fitness guidance information provided by another embodiment of the present application;

[0051] Figure 8 is a flowchart of a method for generating fitness guidance information provided by another embodiment of the present application;

[0052] Fig. 9 It is a structural schematic diagram of a device for generating fitness guidance information provided by an embodiment of the present application;

[0053] Fig.10 It is a structural diagram of a terminal device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0054] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0055] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0056] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0057] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0058] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0059] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0060] See also Figure 1 , Figure 1 1 is a flowchart of a method for generating fitness guidance information provided by an embodiment of the present application. In the embodiment of the present application, the execution subject of the method for generating fitness guidance information is a terminal device. The terminal device may be a notebook, a desktop computer, a smart phone or other device.

[0061] like Figure 1 As shown, the method for generating fitness guidance information provided in an embodiment of the present application may include S101 to S102, which are described in detail as follows:

[0062] In S101, the user's body shape data, physical measurement data, and fitness preference information are obtained.

[0063] In actual applications, when a user needs to obtain fitness guidance information related to himself, he can send a fitness guidance information generation request to the terminal device, wherein the fitness guidance information refers to a fitness plan.

[0064] In the embodiment of the present application, the terminal device detects that the fitness guidance information generation request is: detecting that the user triggers a preset operation for the terminal device. The preset operation can be determined according to actual needs and is not limited here. Exemplarily, the preset operation can be clicking a preset control, that is, if the terminal device detects that the user clicks the preset control, it is considered that the preset operation is triggered, that is, it is considered that the fitness guidance information generation request sent by the user is detected.

[0065] After receiving the request to generate fitness guidance information, the terminal device can obtain the user's body shape data, physical measurement data and fitness preference information.

[0066] The user's body shape data includes but is not limited to the user's human body index data and target body shape data.

[0067] Human index data includes basic data and body composition data. Basic data includes but is not limited to height, weight, age and gender. Body composition data refers to the content of various components in the body (such as muscle, bone, fat, water and minerals, etc.), which is usually expressed by the composition and proportion of various substances in the body.

[0068] The target body shape data is used to describe the user's shape, that is, the user's body shape problems, such as round shoulders, hunchback, hunched chest and forward head (i.e. upper crossed syndrome), pelvic tilt, lumbar lordosis and knee hyperextension (i.e. lower crossed syndrome), O-shaped legs, uneven shoulders and long and short legs.

[0069] Physical fitness data refers to physical fitness data, which is used to describe the user's comprehensive athletic function, including but not limited to cardiopulmonary endurance, muscle endurance and muscle explosiveness.

[0070] The fitness preference information is used to describe the user's training preferences, including but not limited to the user's preferred body parts, preferred training duration, and preferred training frequency when exercising.

[0071] In one implementation of the embodiment of the present application, the terminal device can obtain the user's human body index data through a body data testing device that is wirelessly connected to it.

[0072] In another implementation of the embodiment of the present application, the terminal device can obtain the target body posture data of the user through a body posture tester wirelessly connected to it.

[0073] In another implementation of the embodiment of the present application, the terminal device can obtain the user's physical measurement data through a physical fitness tester that is wirelessly connected to the terminal device.

[0074] In another implementation of the embodiment of the present application, a plurality of preset buttons are provided on the display interface of the terminal device, and each preset button may correspond to a training preference. Exemplarily, the preset buttons may include but are not limited to a first preset button, a second preset button, and a third preset button. The terminal device may set the training preference corresponding to the first preset button to the preferred training part, set the training preference corresponding to the second preset button to the preferred training duration, and set the training preference corresponding to the third preset button to the preferred training frequency.

[0075] In this embodiment, after detecting that the user clicks a preset button on the display interface of the terminal device, the terminal device may display preference sub-information of the training preference corresponding to the preset button (such as specific preset preferred training parts, specific preset preferred training duration, and specific preset preferred training frequency, etc.). For example, assuming that the user clicks the first preset button on the display interface of the terminal device, the terminal device may display multiple preset preferred parts on its display interface, such as arms, chest, etc.

[0076] Based on this, the user can select his / her preferred training part, preferred training duration and preferred training frequency from the above preference sub-information, that is, the terminal device obtains the user's fitness preference information.

[0077] In S102, fitness guidance information for the user is generated based on the body shape data, the physical measurement data, the fitness preference information and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities.

[0078] It should be noted that the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities. Among them, fitness elements include but are not limited to training movements, muscles, parts, postures, joints, etc.

[0079] In an embodiment of the present application, after obtaining the user's body shape data, physical measurement data, and fitness preference information, the terminal device can select multiple training movements that suit the user from a pre-built fitness knowledge graph based on the body shape data, physical measurement data, and fitness preference information, and generate fitness guidance information for the user based on the multiple training movements.

[0080] In one embodiment of the present application, in order to prevent users from straining when performing training movements, complete fitness guidance information includes multiple training links, such as warm-up links, exercise links, and relaxation links, etc. Therefore, the terminal device can determine at least one training movement corresponding to each training link based on the user's body shape data, physical measurement data, fitness preference information, and a pre-built fitness knowledge graph, and generate fitness guidance information based on at least one training movement corresponding to each training link.

[0081] In another embodiment of the present application, since fitness needs to be carried out for a long time to achieve results, the fitness elements in the fitness knowledge graph can also include training courses consisting of at least one training action and the training frequency of each training action. Therefore, the fitness knowledge graph can pre-set the correspondence between different training actions and training courses.

[0082] Based on this, in this embodiment, after the terminal device selects multiple training movements that suit the user from a pre-built fitness knowledge graph based on body shape data, physical measurement data, and fitness preference information, it can also determine the target training course based on the correspondence between different pre-set training movements and training courses, and generate user fitness guidance information based on the training course.

[0083] It should be noted that each training course includes multiple training sessions mentioned above.

[0084] From the above, it can be seen that a method for generating fitness guidance information provided in an embodiment of the present application obtains the user's body shape data, physical measurement data, and fitness preference information; generates the user's fitness guidance information based on the body shape data, physical measurement data, fitness preference information, and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities. In the method provided in the present application, the terminal device can determine the specific fitness needs of different users through the acquired user's body shape data, physical measurement data, and fitness preference information, and can also enrich the generated user's fitness guidance information content through the fitness knowledge graph, thereby improving the accuracy of the generated fitness guidance information.

[0085] See also Figure 2 , Figure 2 This is a method for generating fitness guidance information provided by another embodiment of the present application. Figure 1 Corresponding to the embodiment, the method for generating fitness guidance information provided in this embodiment, step S102 may specifically include S201 to S204, which are described in detail as follows:

[0086] In S201, the target training part of the user is determined according to the fitness preference information.

[0087] In this embodiment, since the user's fitness preference information includes the user's preferred training parts, in order to meet the user's specific fitness needs, the terminal device can determine the user's target training parts according to the preferred training parts in the fitness preference information.

[0088] In S202, a first training action of the user is determined according to the body shape data, the physical measurement data, the fitness preference information, the target training part and the fitness knowledge graph.

[0089] In this embodiment, in order to generate standard fitness guidance information, and the fitness guidance information needs to be consistent with the user's physical condition, and each training action is within the user's tolerance range, the terminal device can specifically determine the user's first training action through the user's body shape data, physical measurement data, fitness preference information, target training parts and fitness knowledge graph.

[0090] It should be noted that the first training action includes multiple training actions.

[0091] In one embodiment of the present application, since the fitness elements include training movements and training parts, the terminal device can specifically perform the following steps: Figure 3 S301 to S302 shown determine the first training action of the user, which is described in detail as follows:

[0092] In S301, a part training action set associated with the target training part is searched from the fitness knowledge graph.

[0093] It should be noted that the fitness knowledge graph pre-sets the correspondence between different training parts and training actions, wherein each training part can correspond to at least one training action.

[0094] Based on this, in this embodiment, the terminal device can search for a set of part training actions associated with the target training part from the fitness knowledge graph through the user's target training part and the correspondence between different training parts and training actions pre-set in the fitness knowledge graph.

[0095] In S302, the first training action is selected from the body part training action set according to the body shape data, the body measurement data and the fitness preference information.

[0096] In this embodiment, since the difficulty and requirements of each training movement are different, and the user's fitness preference information can also include the user's preferred training movements, in order to meet the user's specific fitness needs while ensuring the user's safety and avoiding physical injuries, the terminal device can select the user's first training movement from the part training movement set based on the user's body shape data, physical measurement data and fitness preference information.

[0097] In another embodiment of the present application, since the fitness element includes training movements and body shape data, the user's body shape data includes the user's target body shape data and human body index data, the terminal device can specifically perform the following steps: Figure 4 S401-S402 shown determine the first training action of the user, which is described in detail as follows:

[0098] In S401, a set of posture training movements associated with the target posture data is searched from the fitness knowledge graph.

[0099] It should be noted that the fitness knowledge graph pre-sets the correspondence between different body shape data and training movements, wherein each body shape data may correspond to at least one training movement.

[0100] In this embodiment, after the terminal device obtains the user's target body shape data, in combination with S101, when the terminal device detects that the user has body shape problems based on the target body shape data, it is necessary to give priority to avoiding certain training actions based on the user's body shape problems, and consider training actions that can correct the user's body shape problems. Therefore, the terminal device can search for a set of body shape training actions associated with the target body shape data from the fitness knowledge graph based on the user's target body shape data and the pre-set correspondence between different body shape data and training actions.

[0101] In S402, the first training action is selected from the body training action set according to the human body index data, the physical measurement data, the target training part and the fitness preference information.

[0102] In this embodiment, since the difficulty and requirements of each training movement are different, and the user's fitness preference information can also include the user's preferred training movements, in order to meet the user's specific fitness needs while ensuring the user's safety and avoiding physical injuries, the terminal device can select the user's first training movement from the body training movement set based on the user's human index data, physical measurement data, target training parts and fitness preference information.

[0103] In S203, a first training parameter corresponding to the first training action is determined according to the body shape data, the physical measurement data and the fitness preference information.

[0104] In practical applications, the first training parameters corresponding to each first training action include but are not limited to: the number of training sets, the number of training times, the training duration, the rest duration, etc.

[0105] In this embodiment, the terminal device can determine the specific value of the first training parameter corresponding to the first training action according to the user's body shape data, physical measurement data and fitness preference information.

[0106] In S204, the fitness guidance information is generated according to the first training action and the first training parameter.

[0107] In this embodiment, after determining the specific value of the first training parameter corresponding to the first training action, the terminal device may bind the specific value of the first training parameter with the first training action to generate fitness guidance information for the user.

[0108] From the above, it can be seen that the method for generating fitness guidance information provided by this embodiment determines the user's target training part according to the fitness preference information; determines the user's first training action according to the body shape data, physical measurement data, fitness preference information, the target training part and the fitness knowledge graph; determines the first training parameter corresponding to the first training action according to the body shape data, physical measurement data and fitness preference information; generates fitness guidance information according to the first training action and the first training parameter, thereby further improving the accuracy of the generated fitness guidance information.

[0109] See also Figure 5 , Figure 5 This is a method for generating fitness guidance information provided by another embodiment of the present application. Figure 3 Corresponding to the embodiment, the method for generating fitness guidance information provided in this embodiment may further include S501 to S502 before S302, which are described in detail as follows:

[0110] In S501, for each training action in the part training action set, the training action is scored according to the action type of the training action and a preset action scoring rule.

[0111] In S502, the training actions with scores less than a first threshold in the part training action set are deleted.

[0112] In this embodiment, each training action in the fitness knowledge graph corresponds to an action type, that is, each training action in the part training action set corresponds to an action type, wherein the action types include but are not limited to squat type and bench press type.

[0113] It should be noted that the terminal device pre-stores the correspondence between different action types and preset action scoring rules. Therefore, after obtaining the part training action set, the terminal device can determine the action type of each training action in the part training action set, and determine the action scoring rule corresponding to each training action in the part training action set according to the pre-stored correspondence between different action types and preset action scoring rules, and score each training action based on the action scoring rule corresponding to each training action. Among them, the preset action scoring rule can be determined according to actual needs and is not limited here.

[0114] In this embodiment, after obtaining the score of each training action, the terminal device may sequentially compare the score of each training action with the first threshold value, wherein the first threshold value may be determined according to actual needs and is not limited here.

[0115] For any training action in the part training action set, when the terminal device detects that the score of the training action is less than the first threshold, it indicates that the training action is not suitable for the user, so the terminal device can delete the training action from the part training action set.

[0116] Based on this, the terminal device may delete all training actions with scores less than the first threshold in the part training action set, thereby obtaining a deleted part training action set.

[0117] From the above, it can be seen that the method for generating fitness guidance information provided in this embodiment scores the training action for each training action in the part training action set according to the type of training action and preset action scoring rules; and deletes the training actions in the part training action set with a score less than a first threshold, thereby improving the accuracy of the subsequently selected first training action, and further improving the accuracy of the generated fitness guidance information.

[0118] See also Figure 6 , Figure 6 This is a method for generating fitness guidance information provided by another embodiment of the present application. Figure 3 Corresponding to the embodiment, the method for generating fitness guidance information provided in this embodiment may further include S601 to S602 before S302, which are described in detail as follows:

[0119] In S601, the desired exercise type of the user is determined according to the fitness preference information.

[0120] In S602, the training movements corresponding to the movement types different from the expected movement types in the body part training movement set are deleted.

[0121] It should be noted that each training action in the fitness knowledge graph corresponds to a sports type, that is, each training action in the part training action set corresponds to a sports type. Among them, sports types include but are not limited to aerobic sports types and anaerobic sports types.

[0122] In this embodiment, since the user's fitness preference information also includes the user's preferred exercise type, the terminal device can determine the user's desired exercise type based on the user's fitness preference information.

[0123] Based on this, the terminal device may delete the training actions whose corresponding movement types are different from the expected movement types in the part training action set, thereby obtaining the deleted part training action set.

[0124] From the above, it can be seen that the method for generating fitness guidance information provided in this embodiment determines the user's expected exercise type based on fitness preference information; and deletes the training actions in the part training action set whose corresponding exercise types are different from the expected exercise types, thereby improving the accuracy of the first training action selected subsequently, and further improving the accuracy of the generated fitness guidance information.

[0125] See also Figure 7 , Figure 7 This is a method for generating fitness guidance information provided by another embodiment of the present application. Figure 1 Corresponding to the embodiment, the method for generating fitness guidance information provided in this embodiment, step S102 may specifically include S701 to S706, which are described in detail as follows:

[0126] In S701, the training stage of the user is obtained.

[0127] In actual applications, a complete fitness cycle usually includes an adaptation period, an improvement period and a consolidation period. At the same time, the training movements corresponding to different stages are also different. Therefore, in this embodiment, in order to improve the accuracy of the determined training movements, the terminal device needs to determine the training stage of the user.

[0128] In one embodiment of the present application, the terminal device may determine the training stage of the target user based on the user's physical measurement data and / or body shape data.

[0129] In an implementation of this embodiment, in combination with S101, when the terminal device detects that the user has a posture problem, it can determine that the training stage of the target user is an adaptation stage.

[0130] In another implementation of this embodiment, in combination with S101, when the terminal device detects that the cardiopulmonary endurance of the user is lower than the first value and / or the maximum strength is lower than the second value, it can determine that the training stage of the target user is the adaptation stage. The first value and the second value can be determined according to actual needs and are not limited here.

[0131] In another implementation of this embodiment, when the terminal device detects that the target user has no posture problems, and the user's cardiopulmonary endurance is higher than the first value, and the maximum strength is higher than the second value, it can determine that the training stage of the target user is the progressive stage.

[0132] In S702, the body fat percentage of the user is calculated based on the body shape data.

[0133] It should be noted that body fat percentage refers to the percentage between the user's fat and body weight.

[0134] Therefore, in this embodiment, the terminal device can calculate the user's body fat percentage based on the weight and fat content in the body shape data.

[0135] In S703, a training theme of the user is determined from the fitness knowledge graph according to the body fat percentage.

[0136] It should be noted that, in this embodiment, the pre-constructed fitness knowledge graph is provided with a correspondence between different body fat percentages and different training themes. Therefore, the terminal device can determine the user's training theme from the fitness knowledge graph according to the user's body fat percentage.

[0137] In S704, a second training action of the user is determined from the fitness knowledge graph according to the training theme, the training stage, the physical measurement data, and the fitness preference information.

[0138] In this embodiment, the fitness preference information includes preferred body parts and preferred body types.

[0139] It should be noted that the pre-constructed fitness knowledge graph is provided with the correspondence between different training themes and different training movements, the correspondence between different physical test data and different training movements, the correspondence between different preferred parts and different training movements, the correspondence between different preferred body types and different training movements, and the correspondence between different training stages and different training movements. Therefore, the terminal device can accurately select the second training movement that meets the user's fitness needs from the fitness knowledge graph according to the user's training theme, the user's training stage, the user's physical test data, preferred parts, and preferred body types. Among them, the second training movement includes multiple training movements, and the multiple training movements can be aerobic exercise type training movements or anaerobic exercise type training movements.

[0140] Based on this, combined with S701 to S704, the fitness knowledge graph can achieve the purpose of sharing parameters (i.e. physical measurement data, body fat percentage, body shape data, etc.), and can fully display an explainable reasoning path, making it convenient for users to check the determination process of training actions related to themselves at any time.

[0141] In S705, a second training parameter corresponding to the second training action is determined according to the body shape data, the physical measurement data and the fitness preference information.

[0142] In practical applications, the second training parameters corresponding to each second training action include but are not limited to: the number of training sets, the number of training times, the training duration, the rest duration, etc.

[0143] In this embodiment, the terminal device can determine the specific value of the second training parameter corresponding to the second training action according to the user's body shape data, physical measurement data and fitness preference information.

[0144] In S706, the fitness guidance information is generated according to the second training action and the second training parameter.

[0145] In this embodiment, after determining the specific value of the second training parameter corresponding to the second training action, the terminal device may bind the specific value of the second training parameter with the second training action to generate fitness guidance information for the user.

[0146] From the above, it can be seen that the method for generating fitness guidance information provided by the present embodiment obtains the training stage of the user; calculates the body fat percentage of the user based on the body shape data; determines the training theme of the user from the fitness knowledge graph based on the body fat percentage; determines the second training action of the user from the fitness knowledge graph based on the training theme, training stage, physical measurement data and fitness preference information; determines the second training parameters corresponding to the second training action based on the body shape data, physical measurement data and fitness preference information; generates fitness guidance information based on the second training action and the second training parameters, thereby further improving the accuracy of the generated fitness guidance information.

[0147] See also Figure 8 , Figure 8 This is a method for generating fitness guidance information provided by another embodiment of the present application. Figure 1 Corresponding to the embodiment, the method for generating fitness guidance information provided in this embodiment may further include S801 to S802 after S102, which are described in detail as follows:

[0148] In S801, first training achievement data obtained by the user through training based on the fitness guidance information and second training achievement data obtained by the user without training based on the fitness guidance information are obtained.

[0149] In this embodiment, the training achievement data refers to the user's heart rate, maximum strength, muscle endurance level, cardiopulmonary endurance level, muscle explosiveness level and other data obtained after the user performs at least one fitness exercise.

[0150] In S802, the fitness guidance information is adjusted according to the first training achievement data and the second training achievement data.

[0151] In this embodiment, in order to further improve the accuracy of the user's fitness guidance information, the terminal device can adjust the user's fitness guidance information according to the user's first training result data and the second training result data. For example, the terminal device can adjust the first training parameters corresponding to certain training actions in the user's fitness guidance information according to the user's first training result data and the second training result data, or replace or delete a certain training action / actions, or add other training actions.

[0152] As can be seen from the above, the method for generating fitness guidance information provided by this embodiment obtains the first training result data obtained by the user through training based on the fitness guidance information, and the second training result data obtained by the user without training based on the fitness guidance information; and adjusts the fitness guidance information according to the first training result data and the second training result data. The method provided by this embodiment can adjust the user's fitness guidance information in real time, thereby improving the flexibility and practicality of the generated fitness guidance information.

[0153] In another embodiment of the present application, since the user's body shape data, physical measurement data and / or fitness preference information will change according to the length of the user's fitness time, in order to further improve the accuracy of the generated fitness guidance information and improve the practicality of the fitness guidance information, the terminal device can obtain the user's current body shape data, physical measurement data and fitness guidance information again at preset time intervals after step S102, and regenerate the fitness guidance information based on the pre-constructed fitness knowledge graph and the body shape data, physical measurement data and / or fitness guidance information at the current moment. Among them, the preset time can be set according to actual needs, and there is no limitation here. For example, the preset time can be set to 30 days.

[0154] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0155] Corresponding to the method for generating fitness guidance information described in the above embodiment, Fig. 9 The structure block diagram of a device for generating fitness guidance information provided by an embodiment of the present application is shown. For the sake of convenience, only the part related to the embodiment of the present application is shown. Fig. 9 The fitness guidance information generation device 100 includes: a first acquisition unit 11 and a first generation unit 12. Wherein:

[0156] The first acquisition unit 11 is used to acquire the user's body shape data, physical measurement data and fitness preference information.

[0157] The first generating unit 12 is used to generate fitness guidance information for the user based on the body shape data, the physical measurement data, the fitness preference information and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities.

[0158] In one embodiment of the present application, the first generating unit 12 specifically includes: a part determining unit, a first action determining unit, a first parameter determining unit and a second generating unit. Among them:

[0159] The part determination unit is used to determine the target training part of the user according to the fitness preference information.

[0160] The first action determination unit is used to determine the first training action of the user according to the body shape data, the physical measurement data, the fitness preference information, the target training part and the fitness knowledge graph.

[0161] The first parameter determination unit is used to determine a first training parameter corresponding to the first training action according to the body shape data, the physical measurement data and the fitness preference information.

[0162] The second generating unit is used to generate the fitness guidance information according to the first training action and the first training parameter.

[0163] In one embodiment of the present application, the fitness elements include training actions and training parts; the action determination unit specifically includes: a first search unit and a first selection unit. Among them:

[0164] The first search unit is used to search for a part training action set associated with the target training part from the fitness knowledge graph.

[0165] The first selection unit is used to select the first training action from the body part training action set according to the body shape data, the body measurement data and the fitness preference information.

[0166] In one embodiment of the present application, the fitness guidance information generating device 100 further includes: a scoring unit and a first deleting unit.

[0167] The scoring unit is used to score each training action in the part training action set according to the action type of the training action and a preset action scoring rule.

[0168] The first deleting unit is used to delete the training actions in the part training action set whose scores are less than a first threshold.

[0169] In one embodiment of the present application, each training action in the part training action set corresponds to a sports type; the fitness guidance information generation device 100 further includes: a type determination unit and a second deletion unit. Among them:

[0170] The type determination unit is used to determine the user's desired exercise type according to the fitness preference information.

[0171] The second deleting unit is used to delete the training actions in the part training action set whose corresponding movement types are different from the expected movement type.

[0172] In one embodiment of the present application, the fitness elements include training movements and body shape data; the body shape data includes target body shape data and human body index data; the movement determination unit specifically includes: a second search unit and a second selection unit. Among them:

[0173] The second search unit is used to search for a set of posture training movements associated with the target posture data from the fitness knowledge graph.

[0174] The second selection unit is used to select the first training action from the body training action set according to the human body index data, the physical measurement data, the target training part and the fitness preference information.

[0175] In one embodiment of the present application, the first generating unit 12 specifically includes: a second acquiring unit, a calculating unit, a theme determining unit, a second action determining unit, a second parameter determining unit and a third generating unit. Among them:

[0176] The second acquisition unit is used to acquire the training stage of the user.

[0177] The calculation unit is used to calculate the body fat percentage of the user according to the body shape data.

[0178] The theme determination unit is used to determine the training theme of the user from the fitness knowledge graph according to the body fat percentage.

[0179] The second action determination unit is used to determine the second training action of the user from the fitness knowledge graph according to the training theme, the training stage, the physical measurement data and the fitness preference information.

[0180] The second parameter determination unit is used to determine the second training parameter corresponding to the second training action according to the body shape data, the physical measurement data and the fitness preference information.

[0181] The third generating unit is used to generate the fitness guidance information according to the second training action and the second training parameter.

[0182] In one embodiment of the present application, the fitness guidance information generating device 100 further includes: a third obtaining unit and an adjusting unit.

[0183] The second acquisition unit is used to acquire first training achievement data obtained by the user through training based on the fitness guidance information, and second training achievement data obtained by the user without training based on the fitness guidance information.

[0184] The adjustment unit is used to adjust the fitness guidance information according to the first training achievement data and the second training achievement data.

[0185] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0186] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0187] Fig.10 This is a schematic diagram of the structure of a terminal device provided in an embodiment of the present application. Fig.10 As shown, the terminal device 2 of this embodiment includes: at least one processor 20 ( Fig.10 Only one is shown in the figure) a processor, a memory 21, and a computer program 22 stored in the memory 21 and executable on the at least one processor 20, and when the processor 20 executes the computer program 22, the steps in any of the above-mentioned embodiments of the method for generating fitness guidance information are implemented.

[0188] The terminal device may include, but is not limited to, a processor 20 and a memory 21. Those skilled in the art will appreciate that Fig.10It is only an example of the terminal device 2 and does not constitute a limitation on the terminal device 2. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0189] The processor 20 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0190] In some embodiments, the memory 21 may be an internal storage unit of the terminal device 2, such as the memory of the terminal device 2. In other embodiments, the memory 21 may also be an external storage device of the terminal device 2, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 2. Further, the memory 21 may also include both the internal storage unit of the terminal device 2 and an external storage device. The memory 21 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 21 may also be used to temporarily store data that has been output or is to be output.

[0191] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0192] An embodiment of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0193] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the terminal device, a recording medium, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), an electric carrier signal, a telecommunication signal and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0194] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0195] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for generating fitness guidance information, characterized in that: include: Acquire the user's body shape data, physical measurement data, and fitness preference information; the body shape data includes human body index data and target body shape data; The target body shape data is used to describe the body shape problems of the user; the physical test data is used to describe the data of the comprehensive sports function of the user, and the physical test data includes cardiopulmonary endurance, muscle endurance and muscle explosiveness; the fitness preference information is used to describe the training preference of the user, and the fitness preference information includes the preferred body parts, preferred training duration and preferred training frequency of the user during fitness; Generate fitness guidance information for the user according to the body shape data, the physical measurement data, the fitness preference information and a pre-constructed fitness knowledge graph; wherein the fitness knowledge graph is a knowledge graph that uses fitness elements as entities and describes the connection relationship between the entities; After generating the user's fitness guidance information according to the body shape data, the physical measurement data, the fitness preference information and the pre-constructed fitness knowledge graph, the method further includes: Acquire first training result data obtained by the user through training based on the fitness guidance information, and second training result data obtained by the user without training based on the fitness guidance information; The fitness guidance information is adjusted according to the first training achievement data and the second training achievement data.

2. The generation method according to claim 1, characterized in that: Generating the user's fitness guidance information according to the body shape data, the physical measurement data, the fitness preference information and the pre-constructed fitness knowledge graph includes: Determining a target training part of the user according to the fitness preference information; Determining a first training action of the user according to the body shape data, the physical measurement data, the fitness preference information, the target training part, and the fitness knowledge graph; Determining a first training parameter corresponding to the first training action according to the body shape data, the physical measurement data and the fitness preference information; The fitness guidance information is generated according to the first training action and the first training parameter.

3. The generation method according to claim 2, characterized in that: The fitness elements include training actions and training parts; determining the first training action of the user according to the body shape data, the physical measurement data, the fitness preference information, the target training part and the fitness knowledge graph includes: Searching for a set of body part training actions associated with the target training body part from the fitness knowledge graph; The first training action is selected from the body part training action set according to the body shape data, the physical measurement data and the fitness preference information.

4. The generation method according to claim 3, characterized in that: Before selecting the first training action from the body part training action set according to the body shape data, the physical measurement data and the fitness preference information, the method further includes: For each training action in the part training action set, scoring the training action according to the action type of the training action and a preset action scoring rule; The training actions in the part training action set whose scores are less than a first threshold are deleted.

5. The generation method according to claim 3, characterized in that: Each training action in the part training action set corresponds to a sport type; before selecting the first training action from the part training action set according to the body shape data, the physical measurement data and the fitness preference information, the method further includes: Determining the desired exercise type of the user according to the fitness preference information; In the part training action set, the training actions whose corresponding exercise types are different from the expected exercise type are deleted.

6. The generation method according to claim 2, characterized in that: The fitness elements include training actions and body shape data; the body shape data include target body shape data and human body index data; and determining the first training action of the user according to the body shape data, the physical measurement data, the fitness preference information, the target training part and the fitness knowledge graph includes: Searching for a set of posture training actions associated with the target posture data from the fitness knowledge graph; The first training action is selected from the body training action set according to the human body index data, the physical measurement data, the target training part and the fitness preference information.

7. The generation method according to claim 1, characterized in that: Generating the user's fitness guidance information according to the body shape data, the physical measurement data, the fitness preference information and the pre-constructed fitness knowledge graph includes: Obtaining the training stage of the user; Calculating the body fat percentage of the user according to the body shape data; Determining a training theme for the user from the fitness knowledge graph according to the body fat percentage; Determining a second training action of the user from the fitness knowledge graph according to the training theme, the training stage, the physical measurement data, and the fitness preference information; Determining a second training parameter corresponding to the second training action according to the body shape data, the physical measurement data and the fitness preference information; The fitness guidance information is generated according to the second training action and the second training parameter.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for generating fitness guidance information according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for generating fitness guidance information according to any one of claims 1 to 7 is implemented.

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