Intelligent device and intelligent fitness system and method

Abstract

The embodiment of the invention discloses an intelligent device and a fitness system and method, and the intelligent device comprises an attachment structure which is configured to be selectively attached to fitness equipment; the first sensor is configured to collect action data of the fitness equipment; a second sensor for acquiring an attachment state of the attachment structure; and a processor, a memory, a communication module, and a power supply module. The fitness system comprises a data terminal and an intelligent device. The data terminal comprises an obtaining module used for obtaining action data collected by the intelligent device; the processing module is used for obtaining action track information according to the action data; and the analysis module is used for analyzing the action track information to obtain the standard degree of the action. The intelligent device is independent of the fitness equipment, is attached to the fitness equipment through the attachment structure, and can actively obtain the attachment state and actively send out a starting signal. The intelligent device can obtain the action data in real time for standard analysis of the action and obtain the standard degree of the action.

Description

Technical Field

[0001] Embodiments of the present application relate to a smart device, a smart fitness system, and a method. Background Art

[0002] With the development of the fitness industry, more and more users are seeking personalized and intelligent fitness experience. At present, some fitness equipment integrates the function of collecting motion status; some fitness equipment does not have the function of motion collection, and needs to use other equipment to record or only use time as a node as a reference for exercise volume. The training plan can only be recorded in a traditional way, and then the training results can be analyzed. Whether the action is correct needs to be judged by yourself, or a fitness coach can track it one-on-one and give professional guidance and suggestions. Summary of the invention

[0003] The embodiments of the present application provide a smart device, a smart fitness system and a method for solving at least one technical problem in the prior art.

[0004] A first aspect of an embodiment of the present application provides a smart device, comprising:

[0005] an attachment structure configured to be selectively attached to a fitness equipment;

[0006] a first sensor, wherein the first sensor is configured to collect motion data of the fitness equipment;

[0007] a second sensor for acquiring an attachment state of the attachment structure; and

[0008] A processor, and a memory, a communication module, and a power module electrically connected to the processor;

[0009] The first sensor and the second sensor are both electrically connected to the processor.

[0010] A second aspect of the embodiment of the present application provides an intelligent fitness system, which includes a data terminal and the above-mentioned intelligent device;

[0011] The data terminal comprises:

[0012] An acquisition module, used to acquire the motion data collected by the smart device;

[0013] A processing module, used for obtaining motion trajectory information according to the motion data; and

[0014] The analysis module is used to analyze the motion trajectory information to obtain the degree of standardization of the motion.

[0015] A third aspect of the embodiments of the present application provides an intelligent fitness method, which is attached to fitness equipment and triggers a start signal;

[0016] Get action data;

[0017] Obtaining motion trajectory information according to the motion data;

[0018] The motion trajectory information is compared and analyzed to confirm the standardization of the motion.

[0019] Compared with the prior art, the smart device of the embodiment of the present application is independent of the fitness equipment, attached to the fitness equipment through the attachment structure, and can actively obtain the attachment state and actively send a start signal. The smart device can obtain motion data in real time for normative analysis of the action, and obtain the degree of normativeness of the action. The embodiment of the present application combines the smart device to build an intelligent fitness system and method, wherein the system also includes a data terminal, the data terminal includes software, and optionally configured with hardware. The data terminal can be configured on an operating device, and the operating device has display and operation functions to display and configure the training goals. The data terminal can obtain the motion data collected by the smart device and analyze it to confirm the degree of normativeness of the action, and record and feed back the confirmed results to the smart device. The smart device responds to the feedback information so that the user can understand the normative situation of the action, adjust or maintain the action to complete the training goal. The system can also be optionally configured with a server, and both the data terminal and the server can be configured with a deep learning model, an AI model, and a standard action library for matching and confirming the action. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. Among them:

[0021] Figure 1 This is a schematic diagram of the structure of an intelligent fitness system in an embodiment of the present application;

[0022] Figure 2 This is a schematic diagram of the structure of an intelligent fitness system in another embodiment of the present application;

[0023] Figure 3 is a schematic diagram of the structure of a smart device in an embodiment of the present application;

[0024] Figure 4 is a schematic diagram of the structure of a smart device in another embodiment of the present application;

[0025] Figure 5 is a schematic diagram of the structure of a smart device in an embodiment of the present application;

[0026] Figure 6 for Figure 5 In the flowchart of , the expanded flowchart of step S13;

[0027] Figure 7 This is a flow chart of an intelligent fitness method in another embodiment of the present application;

[0028] Figure 8 This is a flow chart of an intelligent fitness method in another embodiment of the present application.

[0029] Explanation of the accompanying drawings: 1-smart device; 2-data terminal; 3-server. DETAILED DESCRIPTION

[0030] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments. Each example is provided by way of explanation of the present application and does not limit the present application. In fact, it will be clear to those skilled in the art that modifications and variations may be made in the present application without departing from the scope or spirit of the present application. For example, a feature shown or described as a part of an embodiment may be used in another embodiment to produce yet another embodiment. Therefore, it is desired that the present application includes such modifications and variations within the scope of the appended claims and their equivalents.

[0031] In the description of the present application, the terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present application and do not require that the present application must be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on the present application. The terms "connected", "connected", and "set" used in the present application should be understood in a broad sense. For example, it can be a fixed connection or a detachable connection; it can be a direct connection or an indirect connection through an intermediate component; it can be a wired electrical connection, a radio connection, or a wireless communication signal connection. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0032] One or more examples of the present application are shown in the accompanying drawings. The detailed description uses numbers and letter marks to refer to features in the drawings. Similar or similar marks in the drawings and description have been used to refer to similar or similar parts of the present application. As used herein, the terms "first", "second", and "third", etc. are used interchangeably to distinguish one component from another and are not intended to indicate the location or importance of individual components.

[0033] like Figure 1 As shown, an embodiment of the present application provides an intelligent fitness system, which includes an intelligent device 1. The intelligent device 1 includes a hardware structure. The intelligent device can be selectively attached to fitness equipment, and the intelligent device can actively obtain the attached status.

[0034] The smart device 1 is provided with a sensor for monitoring the attachment status, and the sensor may include one or more of a magnetometer sensor, a pressure sensor, a contact electrode induction sensor, an infrared sensor, an ultrasonic sensor, and a position sensor, and may also be one or more of a touch switch, a proximity switch, and a photoelectric switch, and no specific limitation is made here.

[0035] The attachment methods of the smart device 1 to the fitness equipment include one or more of adsorption (magnetic attraction, vacuum, static electricity), binding, hanging, and clamping, and no specific limitation is made here.

[0036] The smart device 1 can obtain the motion data of the fitness equipment during use. The smart device 1 is provided with a data acquisition sensor, which includes one or more of an accelerometer, a gyroscope, and a magnetometer, and no specific limitation is made here.

[0037] The smart device 1 can establish a connection with the data terminal 2 and send the collected motion data to the data terminal 2. The data terminal 2 includes software and / or hardware. The data terminal 2 can be configured on an operating device, such as a smart phone, a computer, a tablet, etc., which is not specifically limited here. The smart device 1 and the data terminal 2 can establish a connection through a wireless data transmission method, such as Bluetooth, WIFI, mobile communication technology, Star Flash, etc., which is not specifically limited here. The smart device 1 is equipped with a corresponding wireless communication module so that it can establish a connection with the data terminal 2 and realize data transmission.

[0038] The smart device 1 has a built-in battery to ensure normal operation of the components therein, and the type of battery is not specifically limited here.

[0039] In some embodiments, a smart fitness system includes a smart device 1 and a data terminal 2. After the smart device 1 is turned on, it will actively establish a connection with the data terminal 2. Here, the data terminal 2 is configured on the mobile phone in the form of a terminal APP. After the smart device 1 and the mobile phone are paired via Bluetooth, a data connection is established. The user can select fitness equipment according to the situation, and then attach the smart device 1 to the fitness equipment. The sensor of the smart device 1 can monitor the state of attachment. After obtaining the monitoring signal of the completion of attachment, the smart device 1 will send a completion signal of attachment to the mobile phone.

[0040] The terminal APP is used to manage the connected smart device 1, obtain the motion data collected by the smart device 1, analyze the motion data, store the motion data, etc. After the terminal APP receives the signal that the smart device 1 completes the attachment, the fitness equipment adaptation interface will pop up for the user to select the type, model and some parameters of the fitness equipment to be matched.

[0041] Taking one of the fitness equipment as an example, the user is going to use dumbbells for fitness training (the following embodiments are all explained with dumbbells as examples). The equipment type selected by the user on the adaptation interface popped up by the terminal APP is dumbbells, the model is fixed weight, and the weight value is 2Kg. After confirming the option, the terminal APP enters the state of waiting to receive action data. Of course, some prompt information can also be given, for example, a "Ready to Start" interface can be popped up, and a countdown process is given to let the user get ready, and when the "Ready to Start" interface ends, the training begins.

[0042] When the user starts training, the smart device 1 collects motion data in real time and sends the motion data to the data terminal 2 synchronously. The terminal APP analyzes the motion data and confirms the standardization of the motion. The standardization of the motion can be obtained through a comprehensive analysis of multiple technical parameters. The standards to be considered for each fitness equipment are not exactly the same, so there will be certain differences in the corresponding technical parameters. Commonly used technical parameters include speed, amplitude, time, and inferred posture, proficiency, etc. In addition, standardization can also be optionally combined with the goals of training, such as fat loss, muscle gain, endurance, etc. The training goal is also the basic parameter for standardization judgment, or in other words, other technical indicators and execution standards must be set in combination with the training goals. In addition, it can also be optionally combined with training scenes, such as home, gym, outdoor, etc., and there is no specific restriction here.

[0043] In some embodiments, the motion data is composed of a motion signal, and the motion signal includes an acceleration signal; and / or an angular motion signal; or / and a fusion signal of the acceleration signal and the angular motion signal.

[0044] The terminal APP constructs the motion trajectory information based on the acquired motion data, and then matches the motion trajectory information with the standard motion library. If the recognition is successful, the motion trajectory information is recorded and the action success information is fed back to the smart device; if the recognition fails, the motion trajectory information is recorded and the action failure information is fed back to the smart device.

[0045] In some embodiments, the smart device 1 can make corresponding interactive responses according to the feedback information received from the data terminal 2, and the interactive responses include one or more of light, sound, and vibration, which are not specifically limited here. This allows the user to understand the performance of the training and make appropriate adjustments. For example, the smart device 1 can emit green light when receiving action success information, and can emit flashing red light if receiving action failure information. The user can distinguish whether the action is standardized according to the color of the light, so as to adjust the action and complete the purpose of training.

[0046] In addition, in some embodiments, if the user receives multiple exercise failure information prompts, he or she may choose to stop training. The user may replay the history records on the data terminal 2 to understand the failed movements and the reasons for the failure. Moreover, the system may also provide standard movements for the user to make correct adjustments.

[0047] In some embodiments, a deep learning model such as a convolutional neural network (CNN) model or a long short-term memory (LSTM) model can be constructed to analyze and process the motion trajectory information to determine whether the action meets the standard. The deep learning model can be configured in the data terminal. In this way, a lightweight deep learning model can be selected to reduce the hardware requirements of the data terminal.

[0048] In addition, if Figure 2 As shown, in some embodiments, the smart fitness system is also configured with a server 3 for motion recognition, which can be optionally set at a remote end, and the smart device 1 or / and the data terminal 2 establishes a connection with the server 3 through the network and realizes data transmission. The server 3 identifies the received motion data and / or motion trajectory information, and feeds back the identification results to the smart device 1 and / or the data terminal 2. The server 3 can optionally be configured with a higher-level deep learning model. Compared with the data terminal 2, the server 3 has stronger computing power, can process the motion data of multiple users at the same time, and can also store the data on the server. By aggregating the training data of different users, the server 3 can further modify the motion recognition, train the deep learning model, and improve the overall performance of the system.

[0049] For the user's movements during training, the data terminal 2 can provide standard movements according to the selected equipment type, training goals and personal physical fitness, and the user can complete the movements after watching. In some embodiments, the system can help the user standardize the movements according to historical records. For example, the system can analyze the user's movement trajectory and make a comprehensive analysis, determine which movements are suitable for the user, and dynamically adjust the difficulty coefficient of the movements. There is no specific limitation here.

[0050] In some embodiments, for actions, it is usually a reciprocating training, which can be understood as the reciprocating execution of an action to form a group of actions. Usually, an action will have an initial position and an end position; or, an action will have an initial position, at least one intermediate position and an end position; or, an action will have an initial position, at least one intermediate position, and the end position is not limited; or, at least one intermediate position, one end position, and the initial position is not limited; or at least one intermediate position, the initial position and the end position are not limited. The system matches the corresponding action according to the selected equipment, training goals and personal physical fitness. The data terminal obtains the data collected by the intelligent device in real time to construct the action trajectory information, analyzes the action trajectory information according to the necessary position required for an action, and determines whether an action meets the necessary action conditions to determine whether an action is successful. The trajectory characteristics presented by an action may include a straight line, an arc, or a multi-segment type, etc., and there is no specific limitation here.

[0051] The motion trajectory information of each group of actions can be output as a waveform on the time axis. The waveform includes several peaks and troughs. The waveform can be segmented by peak segmentation, or / and trough segmentation, or / and center point segmentation to form multiple actions, each of which is an action. The segmentation method can be selected according to the necessary position required for the action. An action can be compared to determine whether the action is successful, and the degree of error can also be selected.

[0052] In some embodiments, the necessary position is not a fixed value, but has a range as a position tolerance, and actions within the position tolerance can be understood as correct actions. The position tolerance can be dynamically adjusted or set to a fixed value according to the type of equipment, training goals, personal physical fitness, environment, etc.

[0053] Since the amplitude of the movement varies reasonably due to differences in users, such as height, total arm length, upper arm length, forearm length, total leg length, thigh length, calf length, weight, age, gender, etc., no specific restrictions are made here. Therefore, in some embodiments, the system needs to set personal physical information at the beginning of use. Of course, personal information belongs to personal privacy, and the user can enter it selectively. Moreover, the system can selectively record the data in encrypted form and will not display it in plain text. When the system analyzes the motion trajectory information, it will combine the individual's physical information for personality analysis to obtain a more accurate analysis result.

[0054] Moreover, the system can optionally provide personalized training plans in combination with personal information. For example, the system can be connected to an AI big model, and can generate standard or relatively standard action tutorials based on personal information, which can be presented to users in the form of pictures, videos, voice, etc.

[0055] In some embodiments, the system scores the action based on the acquired action data and gives optimization suggestions based on the score. The user can intuitively judge the standardization of the action based on the score. For the user, the score can be used to quantify the effect of the training and adjust the training goals according to his or her own acceptance.

[0056] In some embodiments, the data terminal 2 can also be connected to other data acquisition terminals, including wearable devices, image sensing devices, environmental sensing devices, etc., and there are no specific restrictions here. The data terminal can integrate the data of the acquisition terminal for further comprehensive analysis. For example, the user's blood pressure, heart rate, respiratory rate, body temperature, etc. are integrated, and there are no specific restrictions here. The training goals are dynamically adjusted according to the results of the comprehensive analysis. For example, the user's fatigue level during training can be evaluated, and the training duration, or / and the intensity of training, or / and the interval duration of each group, or / and the training goals of the day, etc. can be adjusted. There are no specific restrictions here.

[0057] In some embodiments, the system may select or periodically generate training reports with charts and data comparisons to help users understand the effects of training. The system may also give suggestions based on the historical records of training, including good aspects, deficient aspects, aspects that can be improved, etc., without specific limitations here. The system may give the user's proficiency, disadvantages, aspects that can be improved, etc., without specific limitations here. The system may generate analysis reports, data reports, etc., and the user may share the reports with the coach for further analysis.

[0058] In some embodiments, the system can also be connected to a voice system, and the data terminal or / and the smart device can send and receive voice content. The user can communicate with the system in real time through voice and understand the training situation, including selecting equipment, setting parameters, understanding training goals, rest between groups, time control, and completion of actions, etc., without specific limitations here.

[0059] Figure 3 Schematic diagram of the structure of a smart device in an embodiment of the present application.

[0060] like Figure 3 As shown, the embodiment of the present application discloses a smart device 1, which includes:

[0061] An attachment structure for attachment to a selected fitness equipment.

[0062] During training, you can select fitness equipment in sequence according to the training plan to achieve your training goals. When you are ready, you need to attach the smart device to the equipment.

[0063] In some embodiments, the attachment structure includes an annular structure, which can be selectively split into two half rings or selectively combined into a circular ring. The annular structure is provided with a magnet, which can be selectively adsorbed on the fitness equipment to achieve attachment with the equipment. The annular structure can be selectively split and combined according to the type of equipment to achieve attachment with the equipment. For example, it can be sleeved on the handle of a dumbbell, can be sleeved on the barbell bar of a barbell, can be magnetically attracted to the outer wall of the bell plate, can be magnetically attracted to the outer wall of the counterweight block, etc., and no specific restrictions are made here. It can be selectively placed in different positions of the equipment in a split state, or it can be attached to the equipment in a combined state.

[0064] In some embodiments, the attachment structure includes a belt-like structure, which is configured with a magnet and can be selectively tied to the equipment or magnetically attracted to the equipment to achieve attachment to the equipment.

[0065] The smart device 1 also includes a first sensor for collecting the movement trajectory of the equipment.

[0066] The first sensor includes one or more of an accelerometer, a gyroscope, and a magnetometer, and no specific limitation is made here. After the training starts, the first sensor obtains the motion data of the equipment in real time.

[0067] The smart device 1 further comprises a communication module for establishing a network connection with the data terminal 2 and / or the server 3 to achieve data transmission.

[0068] The communication module includes one or more of Bluetooth, WIFI, mobile communication technology, and Star Flash, and there is no specific limitation here.

[0069] The intelligent device 1 also includes one or more processors, as well as a memory and a power module electrically connected to the processor. The first sensor and the communication module are electrically connected to the processor. Of course, an adapter circuit is also included to complete the connection and circuit support between the processor and other electronic components.

[0070] In some embodiments, the smart device 1 further includes a second sensor for confirming the attached state, and the second sensor is electrically connected to the processor.

[0071] The second sensor includes one or more of a magnetometer sensor, a pressure sensor, a contact electrode induction sensor, an infrared sensor, an ultrasonic sensor, and a position sensor, and may also be one or more of a touch switch, a proximity switch, and a photoelectric switch, and there is no specific limitation here. The second sensor is triggered during or / and after the smart device 1 is attached to the equipment, and the smart device sends a trigger signal to the data terminal to confirm one of the operations during the training process.

[0072] Figure 4Schematic diagram of the structure of a smart device in an embodiment of the present application.

[0073] like Figure 4 As shown, in some embodiments, the smart device 1 further includes a third sensor for acquiring environmental information, and the third sensor is electrically connected to the processor.

[0074] The third sensor can obtain one or more environmental information including temperature, humidity, air pressure, ambient light, and noise, and there is no specific limitation here.

[0075] like Figure 4 As shown, in some embodiments, the smart device 1 further includes a response module for feeding back the state of the action, and the response module is electrically connected to the processor.

[0076] The response module includes one or more of light, sound, and vibration, and there is no specific limitation here. The data terminal or / server analyzes the action data uploaded by the smart device and optionally feeds back the analysis results to the smart device. The smart device responds accordingly to the feedback results so that the user can understand and adjust the training actions. Alternatively, different responses can also bring different experiences to the user to adjust the atmosphere during training.

[0077] In some embodiments, the above sensors all include a low power consumption mode, which can automatically reduce power consumption when the user is resting or inactive, thereby extending the battery life of the device.

[0078] like Figure 5 As shown, an intelligent fitness method comprises:

[0079] S10, attach and trigger the start signal.

[0080] The smart device is attached to the fitness equipment and sends a start signal to the data terminal and / or the server.

[0081] S11, obtaining action data.

[0082] The intelligent device acquires the motion signals during the training process in real time and forms motion data for the data terminal and / or the server to analyze the motion.

[0083] S12, obtaining motion trajectory information according to the motion data.

[0084] The data terminal and / or the server converts the motion data into motion trajectory information with time as the axis, and the motion trajectory information can be viewed as a waveform graph.

[0085] S13, performing comparative analysis on the action trajectory information to confirm the standardization of the action.

[0086] The data terminal and / or the server compare and analyze the motion trajectory information through a standard motion library, and / or compare and analyze the motion trajectory information through a deep learning model to determine the standardization of the action.

[0087] like Figure 6 As shown, in some embodiments, S13, performing comparative analysis on the action trajectory information to confirm the standardization of the action includes:

[0088] S131, processing the motion trajectory information to obtain a motion trajectory.

[0089] The motion trajectory information is usually composed of a set of reciprocating motions. The motion comparison requires the analysis of each complete motion. Therefore, the motion trajectory information needs to be decomposed to obtain a motion trajectory.

[0090] S132, comparing the movement trajectory to confirm the standardization of the movement.

[0091] The data terminal and / or the server compare and analyze an action trajectory through a standard action library, or / and compare and analyze an action trajectory through a deep learning model to determine the standardization of the action.

[0092] In some embodiments, S131, processing the motion trajectory information to obtain a motion trajectory includes:

[0093] The waveform diagram includes several peaks and troughs, and the waveform diagram can be segmented by a peak segmentation method, or / and a trough segmentation method, or / and a center point segmentation method to form multiple actions, each of which is an action.

[0094] like Figure 7 As shown, an intelligent fitness method comprises:

[0095] S20, input physical information.

[0096] The user's physical condition will affect the posture and amplitude of the movement, so physical information may affect the analysis of the movement.

[0097] S21, attach and trigger the start signal.

[0098] S22, obtaining action data.

[0099] S23, obtaining motion trajectory information according to the motion data.

[0100] S24, processing the motion trajectory information to obtain a motion trajectory.

[0101] S25, comparing the movement trajectory to confirm the standardization of the movement.

[0102] like Figure 8 As shown, an intelligent fitness method comprises:

[0103] The data terminal is equipped with an APP. When using the APP for the first time, you will be asked whether to enter personal information. Of course, personal information belongs to personal privacy, and the user can choose to enter it. Moreover, the system can choose to encrypt and record the data, and will not display it in plain text.

[0104] Then, the APP establishes a physical connection with the smart device through the data terminal. When used for the first time, the data terminal and the smart device need to be matched with each other. For example, if Bluetooth connection is used, pairing is required before the network connection can be completed; WIFI and NFC fast pairing are also supported, and no specific restrictions are made here.

[0105] Before training begins, you can use the big model to generate a training plan. The big model will give you the fitness equipment and training goals you can choose based on your personal information. The training plan can be based on the number of sets of movements you need to do, the duration of each set of movements, the time interval between each set of movements, etc. There are no specific restrictions here.

[0106] Attach the smart device to the selected fitness equipment. After attachment, the first sensor of the smart device is triggered, and the APP will receive the trigger signal and pop up an inquiry message, which includes the type of equipment selected, parameters (weight, tension, number of times, etc., no specific restrictions are made here), etc., no specific restrictions are made here.

[0107] Start training. The smart device can inform the user that training can start through sound, light, etc.

[0108] The smart device collects every action during the training process and sends the action data to the APP. The APP recognizes the action. If the action is correct, the action data is recorded and the correct result is fed back to the smart device to determine whether the group of actions is completed. If the action fails, the failure result is fed back to the smart device. Of course, failed actions can also be recorded for later analysis.

[0109] There is an interval between each set of movements, and you can enter the next set of movements after resting. Or, if you need to change equipment, you can attach the smart device to other equipment and then enter a new training cycle. Until the entire training plan is completed.

[0110] In addition, users can also record their own movements and upload them to the cloud for manual verification before adding them to the movement library. The cloud can build a fitness community, and the uploaded movements can be annotated and verified by community members to enrich the standard movement library.

[0111] The above description is only some examples of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A smart device, characterized in that: include: an attachment structure configured to be selectively attached to a fitness equipment; a first sensor, wherein the first sensor is configured to collect motion data of the fitness equipment; a second sensor, the second sensor being used to obtain an attachment state of the attachment structure; and A processor, and a memory, a communication module, and a power module electrically connected to the processor; Wherein, the first sensor and the second sensor are both electrically connected to the processor.

2. The smart device according to claim 1, characterized in that: Also includes: A third sensor is used to obtain environmental information, and the third sensor is electrically connected to the processor; or / and A response module is electrically connected to the processor.

3. The smart device according to claim 1 or 2, characterized in that: The attachment structure comprises: two half rings, the two half rings being configured to selectively join into a ring so that at least a portion of the fitness equipment is attached between the two half rings; or / and At least a portion of the magnetic structure is configured to be selectively magnetically attracted to the fitness equipment.

4. An intelligent fitness system, characterized in that: A data terminal and the smart device according to any one of claims 1 to 3; The data terminal comprises: An acquisition module, used to acquire the motion data collected by the smart device; A processing module, used for obtaining motion trajectory information according to the motion data; and The analysis module is used to analyze the motion trajectory information to obtain the degree of standardization of the motion.

5. The intelligent fitness system according to claim 4, characterized in that: The data terminal further comprises a matching module, which is used to prompt the user to select the type and parameters of matching fitness equipment when receiving the completion of the attachment of the smart device.

6. The intelligent fitness system according to claim 4, characterized in that: The analysis module feeds back the standardization degree of the action to the smart device, and the response module of the smart device presents the standardization degree in a preset state.

7. The intelligent fitness system according to claim 4, characterized in that: It also includes a server, which is communicatively connected to the data terminal and / or the intelligent device. The server analyzes the action and obtains the degree of standardization of the action based on the action data and / or the action trajectory information.

8. An intelligent fitness method, characterized in that: Attached to fitness equipment and triggering a start signal; Get action data; Obtaining motion trajectory information according to the motion data; The motion trajectory information is compared and analyzed to confirm the standardization of the motion.

9. The intelligent fitness method according to claim 8, characterized in that: Compare and analyze the action trajectory information to confirm the standardization of the action, including: Processing the motion trajectory information to obtain a motion trajectory; Compare and analyze the trajectory of an action to confirm the standardization of the action.

10. The intelligent fitness method according to claim 9, characterized in that: Process the motion trajectory information to obtain a motion trajectory, including: The motion trajectory information is segmented by using a peak segmentation method, or / and a trough segmentation method, or / and a center point segmentation method to obtain a motion trajectory.

11. The intelligent fitness method according to claim 8, characterized in that: The motion trajectory information is compared and analyzed to confirm the standardization of the motion, including: fusing the user's personal information to confirm the amplitude, and / or speed, and / or angle of the motion.

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