Method and device for processing motion data

Abstract

The motion data processing method and device provided in the embodiment of the present application first obtain the motion data of the user, and determine the motion trajectory of the user during the motion process and the motion stimulation degree of the user during the motion process according to the motion data; and then display the motion curve. It can be seen that, unlike the prior art, when displaying the motion record to the user, the motion curve used to indicate the motion trajectory of the user during the motion process and the motion stimulation degree during the motion process is first determined, so that when performing the visual display, not only the motion trajectory during the motion process is displayed to the user, but also the motion stimulation degree during the motion process is displayed to the user, enriching the display content, thereby improving the user experience.

Description

Technical Field

[0001] The present application relates to the field of terminal technology, and in particular to a method and device for processing motion data. Background Art

[0002] With the continuous development of sensor technology and artificial intelligence technology, wearable devices play an increasingly important role in daily life. Among them, smart perception technology and visualization technology are two important technologies for wearable devices. Smart perception technology is the ability to use wearable devices to provide smart perception and smart judgment, such as wearing detection technology and gesture recognition technology. Visualization technology is the ultimate value presentation medium for wearable devices to interact with users, such as running track records, swimming track records, etc.

[0003] When using visualization technology to display the user's motion trajectory record to the user, taking running as an example, during the user's running process, the wearable device worn on the user's wrist will use the global positioning system (GPS) technology to obtain the user's coordinates at different times, and use curve fitting technology to perform curve fitting on the coordinate points at these different times to obtain the user's motion trajectory curve for the entire running process, and combined with the map engine, the user's motion trajectory curve is displayed to the user, and the displayed content is single, resulting in a poor user experience. Summary of the invention

[0004] The embodiments of the present application provide a method and device for processing motion data, which enrich the display content and thus improve the user experience.

[0005] In a first aspect, an embodiment of the present application provides a method for processing motion data, which may include:

[0006] Get the user's motion data.

[0007] The user's motion curve is determined based on the motion data; the motion curve is used to indicate the motion trajectory of the user during the motion process, and the degree of motion stimulation during the motion process.

[0008] Displays the motion curve.

[0009] It can be seen that the method for processing motion data provided by the embodiment of the present application first obtains the motion data of the user, and determines the motion trajectory of the user during the motion process and the motion stimulation degree of the user during the motion process according to the motion data; and then displays the motion curve. It can be seen that, unlike the prior art, when displaying the motion record to the user, the motion curve used to indicate the motion trajectory of the user during the motion process and the motion stimulation degree during the motion process is first determined, so that when performing a visual display, not only the motion trajectory during the motion process is displayed to the user, but also the motion stimulation degree during the motion process is displayed to the user, enriching the display content, thereby improving the user experience.

[0010] In a possible implementation, determining the motion curve of the user according to the motion data may include:

[0011] A motion trajectory curve and a motion stimulation degree curve are determined according to the motion data; wherein the motion trajectory curve is used to represent the motion trajectory of the user during the motion process, and the motion stimulation degree curve is used to represent the corresponding relationship between time and motion stimulation degree during the motion process.

[0012] The motion curve is determined according to the motion trajectory curve and the motion stimulation degree curve. In this way, when performing visual display, not only the motion trajectory during the motion process is displayed to the user, but also the motion stimulation degree during the motion process is displayed to the user, enriching the display content and thus improving the user experience.

[0013] In a possible implementation, determining the motion curve according to the motion trajectory curve and the motion stimulation degree curve may include:

[0014] According to the mapping relationship between the motion stimulation degree and the color, the color corresponding to the motion stimulation degree at at least two first time points in the motion stimulation degree curve is determined.

[0015] The color corresponding to each of at least two first time points in the motion trajectory curve is modified to the color corresponding to the degree of motion stimulation at the first time point to obtain a motion curve. In this way, when performing a visual display, not only the motion trajectory during the motion process is displayed to the user, but also the degree of motion stimulation during the motion process can be intuitively displayed to the user through the color of the motion curve, thereby enriching the display content and improving the user experience.

[0016] In a possible implementation, determining the motion trajectory curve according to the motion data may include:

[0017] Based on big data analysis technology, determine the sports events corresponding to the sports data.

[0018] Determine the motion trajectory curve according to the sport.

[0019] In a possible implementation, determining a motion trajectory curve according to a sport may include:

[0020] If the motion trajectory corresponding to the sports item belongs to the first type, the preset motion trajectory curve corresponding to the sports item is determined as the motion trajectory curve; wherein the sports items belonging to the first type all correspond to their own motion trajectory curves.

[0021] If the motion trajectory corresponding to the sports item belongs to the second type, the curve fitting technology is used to fit the motion data to obtain a motion trajectory curve; wherein the complexity of the motion trajectory of the sports item belonging to the second type is higher than the complexity of the motion trajectory of the sports item belonging to the first type.

[0022] It can be seen that in the embodiment of the present application, for sports items with simple and less complex motion trajectories, when determining the corresponding motion trajectory curve, it is not necessary to calculate the motion trajectory curve corresponding to the sports item based on the currently acquired motion data, but by reading the preset motion trajectory curve corresponding to the sports item, and determining the preset motion trajectory curve corresponding to the sports item as the motion trajectory curve corresponding to the sports item, which can not only reduce the complexity of terminal calculation, but also optimize the motion trajectory and improve the accuracy of the motion trajectory curve. For motion trajectories with higher complexity, curve fitting technology is used to fit the motion data to obtain the motion trajectory curve.

[0023] In a possible implementation, the motion data includes at least one of motion speed, motion acceleration, motion height, or heart rate, and determining the motion stimulation degree curve according to the motion data may include:

[0024] The degree of exercise stimulation at each second time point in at least two time points during the exercise process is determined.

[0025] The polynomial fitting technology is used to fit the motion stimulation degree at at least two time points to obtain a motion stimulation degree curve. In this way, when performing subsequent visualization, the motion stimulation degree curve can be superimposed on the motion trajectory curve for display, which not only shows the user the motion trajectory during the exercise, but also shows the user the motion stimulation degree during the exercise, enriching the display content and thus improving the user experience.

[0026] In a possible implementation, the motion data includes motion speed, motion acceleration, motion height, and heart rate, and determining the motion stimulation degree at the second time point according to the motion data at each second time point in at least two time points during the motion process may include:

[0027] The movement speed, movement acceleration, movement height and heart rate corresponding to the second time point are respectively normalized to obtain processed movement speed, movement acceleration, movement height and heart rate.

[0028] The degree of exercise stimulation at the second time point is determined based on the processed exercise speed, exercise acceleration, exercise altitude and heart rate.

[0029] In a possible implementation, the motion data processing method may further include:

[0030] Display key information during exercise; wherein the key information includes at least one of the maximum exercise height, the maximum exercise speed, the maximum heart rate or the exercise stimulation degree score. In this way, the user can be provided with such key information while displaying the user's exercise trajectory and the exercise stimulation degree during exercise, which can further enrich the display content and improve the user experience.

[0031] In a possible implementation, the motion data processing method may further include:

[0032] The motion stimulation degree curve is integrated to obtain the integral result.

[0033] The exercise stimulation degree score is determined according to the ratio of the integral result and the duration of the exercise process; wherein, the duration of the exercise process is determined according to the end time and the start time of the exercise process. In this way, after obtaining the exercise stimulation degree score, the exercise stimulation degree score can be displayed to the user, thereby enriching the display content and improving the user experience.

[0034] In a possible implementation, determining the exercise stimulation degree score according to the ratio of the integral result to the duration of the exercise process may include:

[0035] The comparison values ​​are normalized to obtain a normalized ratio.

[0036] The normalized ratio is processed based on a preset scoring interval to obtain a sports stimulation degree score, so that the sports stimulation degree score value obtained falls within the preset scoring interval.

[0037] In a possible implementation, the motion data includes motion speed and motion height, and the method for processing the motion data may further include:

[0038] If the movement speed is greater than the first speed threshold, and / or the movement height is greater than the first height threshold, it is determined that the user has entered the movement state. If the movement speed is less than the second speed threshold, and the movement height is less than the second height threshold, it is determined that the user has exited the movement state. In this way, it is possible to determine whether the user has entered the movement state by the movement speed and / or the movement height, and to determine whether the user has exited the movement state by the movement speed and the movement height, without the user having to manually click to enter the movement state, and manually click to exit the movement state, thereby realizing automatic control.

[0039] In a second aspect, an embodiment of the present application further provides a motion data processing device, which may include:

[0040] The acquisition unit is used to acquire the user's motion data.

[0041] The processing unit is used to determine the user's motion curve according to the motion data; the motion curve is used to indicate the motion trajectory of the user during the motion process, and the degree of motion stimulation during the motion process.

[0042] The display unit is used to display the motion curve.

[0043] In one possible implementation, the processing unit is used to determine a motion trajectory curve and a motion stimulation degree curve according to the motion data, respectively; and determine the motion curve according to the motion trajectory curve and the motion stimulation degree curve; wherein the motion trajectory curve is used to represent the motion trajectory of the user during the motion process, and the motion stimulation degree curve is used to represent the correspondence between time and motion stimulation degree during the motion process.

[0044] In one possible implementation, the processing unit is used to determine the colors corresponding to the motion stimulation degrees at least two first time points in the motion stimulation degree curve according to the mapping relationship between the motion stimulation degree and the color; and modify the color corresponding to each of the at least two first time points in the motion trajectory curve to the color corresponding to the motion stimulation degree at the first time point, so as to obtain the motion curve.

[0045] In a possible implementation, the processing unit is specifically used to determine the sports event corresponding to the sports data based on big data analysis technology; and determine the sports trajectory curve according to the sports event.

[0046] In one possible implementation, the processing unit is specifically used to determine a preset motion trajectory curve corresponding to the sports item as the motion trajectory curve if the motion trajectory corresponding to the sports item belongs to the first type; wherein the sports items belonging to the first type all have their own corresponding motion trajectory curves; if the motion trajectory corresponding to the sports item belongs to the second type, curve fitting technology is used to fit the motion data to obtain the motion trajectory curve; wherein the complexity of the motion trajectory of the sports items belonging to the second type is higher than the complexity of the motion trajectory of the sports items belonging to the first type.

[0047] In a possible implementation, the motion data includes at least one of motion speed, motion acceleration, motion altitude or heart rate.

[0048] The processing unit is specifically used to determine the degree of exercise stimulation at a second time point according to the exercise data of each second time point in at least two time points during the exercise process; and use polynomial fitting technology to fit the degree of exercise stimulation at at least two time points to obtain a motion stimulation degree curve.

[0049] In a possible implementation, the motion data includes motion speed, motion acceleration, motion altitude, and heart rate.

[0050] The processing unit is specifically used to normalize the movement speed, movement acceleration, movement height and heart rate corresponding to the second time point, respectively, to obtain the processed movement speed, movement acceleration, movement height and heart rate; and determine the degree of movement stimulation at the second time point based on the processed movement speed, movement acceleration, movement height and heart rate.

[0051] In a possible implementation, the display unit is also used to display key information during exercise; wherein the key information includes at least one of maximum exercise height, maximum exercise speed, maximum heart rate or exercise stimulation level score.

[0052] In a possible implementation, the processing unit is also used to integrate the motion stimulation degree curve to obtain an integral result; and determine the motion stimulation degree score based on the ratio of the integral result and the duration of the motion process; wherein the duration of the motion process is determined based on the end time and start time of the motion process.

[0053] In a possible implementation, the processing unit is specifically configured to normalize the comparison value to obtain a normalized ratio; and to process the normalized ratio based on a preset scoring interval to obtain a motion stimulation degree score.

[0054] In one possible implementation, the motion data includes motion speed and motion height, and the processing unit is further used to determine that the user enters a motion state if the motion speed is greater than a first speed threshold, and / or the motion height is greater than a first height threshold; if the motion speed is less than a second speed threshold, and the motion height is less than a second height threshold, then determine that the user exits the motion state.

[0055] In a third aspect, an embodiment of the present application further provides a communication device, comprising a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program stored in the memory so that the device performs a method for processing motion data as described in any possible implementation of the first aspect above.

[0056] In a fourth aspect, an embodiment of the present application further provides a communication device, comprising: a processor and an interface circuit.

[0057] The interface circuit is used to receive code instructions and transmit them to the processor.

[0058] The processor is used to run the code instructions to execute the motion data processing method as described in any possible implementation of the first aspect above.

[0059] In a fifth aspect, an embodiment of the present application further provides a readable storage medium for storing instructions, which, when executed, implements the motion data processing method as described in any possible implementation of the first aspect above.

[0060] The motion data processing method and device provided in the embodiment of the present application first obtain the user's motion data, and determine the motion trajectory of the user during the motion process and the motion stimulation degree of the user during the motion process according to the motion data; and then display the motion curve. It can be seen that, unlike the prior art, when displaying the motion record to the user, the motion curve used to indicate the motion trajectory of the user during the motion process and the motion stimulation degree during the motion process is first determined, so that when performing a visual display, not only the motion trajectory during the motion process is displayed to the user, but also the motion stimulation degree during the motion process is displayed to the user, enriching the display content, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A schematic diagram of a possible application scenario provided for an embodiment of the present application;

[0062] Figure 2 A schematic diagram of a flow chart of a method for processing motion data provided in an embodiment of the present application;

[0063] Figure 3A flowchart of another method for processing motion data provided in an embodiment of the present application;

[0064] Figure 4 A schematic diagram of manually opening the amusement park mode of a smart bracelet provided in an embodiment of the present application;

[0065] Figure 5 A schematic diagram of determining a motion trajectory curve according to motion data provided in an embodiment of the present application;

[0066] Figure 6 A schematic diagram of a motion trajectory curve corresponding to a roller coaster project provided in an embodiment of the present application;

[0067] Figure 7 A schematic diagram of a motion stimulation degree curve corresponding to a roller coaster project provided in an embodiment of the present application;

[0068] Figure 8 A schematic diagram of a curve for determining a degree of motion stimulation provided in an embodiment of the present application;

[0069] Fig. 9 A schematic diagram of a motion curve corresponding to a roller coaster project provided in an embodiment of the present application;

[0070] Fig.10 A schematic diagram showing a motion curve corresponding to a roller coaster project provided in an embodiment of the present application;

[0071] Fig.11 A schematic diagram of a motion curve including key information provided in an embodiment of the present application;

[0072] Fig.12 A schematic diagram of viewing a motion curve provided in an embodiment of the present application;

[0073] Fig.13 A schematic diagram of the structure of a motion data processing device provided in an embodiment of the present application;

[0074] Fig.14 A schematic diagram of the structure of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0075] The motion data processing method provided in the embodiment of the present application can be applied to a terminal with a display screen, or other terminals with screen display functions that may appear in the future, etc., and the embodiment of the present application is not limited to this.

[0076] In the embodiments of the present application, "at least one" means one or more, and "more" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In the text description of the present application, the character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0077] The motion data processing method provided in the embodiment of the present application can be applied to amusement park projects, such as roller coasters, pendulums, Ferris wheels and other amusement projects with high altitude or stimulating attributes. Of course, it can also be applied to other sports projects with high altitude or stimulating attributes, such as gliding, bungee jumping, rafting, parachuting and other scenes. For examples, please refer to Figure 1 As shown, Figure 1 A schematic diagram of a possible application scenario provided for an embodiment of the present application, the application scenario may include a wearable device and a terminal. After the user turns on the amusement park mode of the wearable device, the wearable device begins to continuously detect the user status. If it is detected that the user has entered the play state, the wearable device begins to collect relevant motion data of the user; if it is detected that the user has exited the play state, the motion data collection stops, and the relevant motion data collected during the user's motion is sent to the terminal. The terminal generates a motion trajectory curve of the user based on the motion data, and combines with the map engine to display the user's motion trajectory curve to the user. The displayed content is single, resulting in a poor user experience.

[0078] In order to solve the problem that the existing technology displays a single content, which makes the user experience poor, after long-term experiments, the embodiment of the present application provides a method for processing motion data, which can be seen in Figure 2 As shown, Figure 2 A flow chart of a method for processing motion data provided in an embodiment of the present application, the method for processing motion data may include: S201 obtaining the motion data of the user; S202 determining the motion curve of the user according to the motion data; wherein the motion curve is used to indicate the motion trajectory of the user during the motion process, and the degree of motion stimulation during the motion process; S203 displaying the motion curve. It can be seen that compared with the prior art of only displaying the motion trajectory to the user, the method for processing motion data provided in an embodiment of the present application first determines a motion curve used to indicate the motion trajectory of the user during the motion process and the degree of motion stimulation during the motion process, so that when performing a visual display, not only the motion trajectory during the motion process is displayed to the user, but also the degree of motion stimulation during the motion process is displayed to the user, enriching the display content, thereby improving the user experience.

[0079] It is not difficult to see from the above description that in the embodiment of the present application, when displaying the motion trajectory of the user during the motion process and the degree of motion stimulation during the motion process, these two different types of information are displayed through a motion curve. When the motion data processing method provided by the embodiment of the present application is described in detail later, the two different types of information are displayed through a motion curve as an example. Of course, it can also be displayed through two curves, that is, one motion curve represents the motion trajectory of the user during the motion process, and one motion curve represents the degree of motion stimulation during the motion process. Here, the embodiment of the present application is only described by using a motion curve to represent the motion trajectory of the user during the motion process and the degree of motion stimulation during the motion process, but it does not mean that the embodiment of the present application is limited to this.

[0080] It should be noted that when implementing the technical solution provided in the embodiment of the present application, in a possible scenario, the execution subject of the motion data processing method provided in the embodiment of the present application is a terminal, such as a mobile phone, a tablet computer, a laptop computer, a PDA, a mobile Internet device (MID), etc. When the execution subject is a terminal, please refer to Figure 1 As shown, wearable devices, such as smart watches and smart bracelets, are mainly responsible for collecting motion data during exercise. Due to the limited data processing capabilities and screens of wearable devices, the collected motion data will be sent to the terminal, and the terminal will perform the motion data processing method provided by the embodiment of the present application based on the received motion data. In another possible scenario, if the data processing capabilities and screens of the wearable device are not considered to be limited, the execution subject of the motion data processing method provided by the embodiment of the present application can also be a wearable device, that is, the wearable device is not only responsible for collecting motion data during exercise, but also after the collected motion data, the motion data processing method provided by the embodiment of the present application will be performed based on the motion data. Under normal circumstances, in the process of motion data processing, it will be considered that due to the limited data processing capabilities and screens of the wearable device, the wearable device only needs to be responsible for collecting motion data during exercise, and the collected motion data will be sent to the terminal. The terminal performs the motion data processing method provided by the embodiment of the present application based on the received motion data, that is, the first possible scenario. Later, the first possible scenario will be taken as an example to describe the motion data processing method provided by the embodiment of the present application in detail.

[0081] The following will describe the technical solution of the motion data processing method provided by the present application in detail through detailed embodiments. It is understandable that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0082] Figure 3A flowchart of another method for processing motion data provided in an embodiment of the present application is provided. For example, see Figure 3 As shown, the motion data processing method may include:

[0083] S301: Obtain user's exercise data.

[0084] Wherein, the motion data is the motion data of the user during the entire motion process, and the motion data includes not only data for calculating the user's motion trajectory, but also motion data for calculating the degree of motion stimulation. For example, the data for calculating the user's motion trajectory can be obtained by GPS, or by a nine-axis sensor (three-axis accelerometer, three-axis gyroscope, three-axis magnetometer). For example, in an embodiment of the present application, the factors affecting the degree of motion stimulation may include at least one of motion speed, motion acceleration, motion height or heart rate. When the factors affecting the degree of motion stimulation include motion speed, motion acceleration, motion height and heart rate, the motion data for calculating the degree of motion stimulation may include GPS data, barometer data and heart rate data, wherein the coordinate data is used to calculate the user's motion speed and motion acceleration; the barometer data is used to calculate the user's motion height; the heart rate data is used to calculate the user's heart rate when exercising.

[0085] It is understandable that, when calculating the degree of motion stimulation, the more factors are considered, the more accurate the value of the corresponding calculated degree of motion stimulation is. It should be noted that, in the embodiment of the present application, the factors affecting the degree of motion stimulation may include at least one of motion speed, motion acceleration, motion height or heart rate as an example for description, but it does not represent that the embodiment of the present application is limited to this. Later, when describing the degree of motion stimulation, in order to improve the accuracy of the degree of motion stimulation, the factors affecting the degree of motion stimulation include four factors of motion speed, motion acceleration, motion height and heart rate as an example for description.

[0086] When the terminal obtains the user's motion data, it can receive the motion data sent by the wearable device through Bluetooth or wireless network. Taking the wearable device as a smart bracelet as an example, after the user turns on the amusement park mode of the smart bracelet, the smart bracelet continues to collect the user's motion data, and determines whether the user enters the play state based on the user's motion data. For example, if the smart bracelet determines that the user's motion speed is greater than the first speed threshold and / or the motion height is greater than the first height threshold based on the motion data collected at the first moment, it means that the user enters the play state at the first moment, and after determining that the user enters the play state, the user's motion data is continuously collected. If the smart bracelet determines that the motion speed is less than the second speed threshold and the motion height is less than the second height threshold based on the motion data collected at the second moment, it means that the user has exited the motion state at the second moment, and when it is determined that the user exits the play state, the user's motion data is stopped, thereby collecting the user's motion data from the first moment to the second moment during the entire motion process; and after collecting the motion data during the entire motion process, the motion data during the entire process is sent to the terminal via Bluetooth or wireless network, so that the terminal obtains the user's motion data during the entire motion process. For example, the values ​​of the first speed threshold, the first height threshold, the second speed threshold and the second height threshold can be set according to actual needs. Here, the embodiments of the present application do not impose specific restrictions on the values ​​of the first speed threshold, the first height threshold, the second speed threshold and the second height threshold.

[0087] It is understandable that before the smart bracelet sends the motion data of the entire process to the terminal via Bluetooth or wireless network, it first determines the duration of the entire process based on the difference between the second moment and the first moment. If the duration is less than the time threshold, it means that the entire process is not a complete project play process. Therefore, the motion data collected during the movement is some invalid data. The motion data collected during the entire process can be abandoned, and the user's motion data can be re-collected when entering the play state next time. If the duration is greater than or equal to the time threshold, it means that the entire process is a complete project play process. Therefore, the motion data collected during the movement is valid data, and the motion data collected during the entire process is sent to the terminal via Bluetooth or wireless network, so that the terminal obtains the motion data of the user during the entire movement process and processes the motion data. By comparing the duration with the time threshold, the smart bracelet can effectively filter out invalid motion data and avoid sending invalid motion data to the terminal, so that the terminal does not need to process these invalid motion data, thereby reducing the power consumption of the terminal.

[0088] Among them, in the above description, the smart bracelet needs to calculate the movement speed and / or movement height at the first moment before judging whether the user enters the play state at the first moment according to the movement speed and / or movement height at the first moment; similarly, before judging whether the user exits the play state at the second moment according to the movement speed and movement height at the second moment, it needs to calculate the movement speed and movement height at the second moment. The calculation method of the movement speed at the first moment and the calculation method of the movement height at the first moment are respectively similar to the calculation method of the movement speed at the second moment and the calculation method of the movement height at the second moment. Taking the calculation of the movement speed at the first moment t0 and the movement height at the first moment as an example, when calculating the movement speed at the first moment, the movement speed V at the first moment t0 can be obtained by using GPS. t0 , see the following formula 1.

[0089]

[0090] Among them, S(GPS t0 ,GPS t0-1 ) represents the physical distance between the first moment t0 and its previous moment t0-1, and Δt represents the time difference between the first moment t0 and its previous moment t0-1.

[0091] When calculating the movement height at the first time t0, the movement height ΔH at the first time t0 can be calculated using the barometer data. t0 , see the following formula 2.

[0092] ΔH t0 =44300*((Pa ref / Pa0) 1 / 5.256 -(Pa t0 / Pa0) 1 / 5.256 ) Formula 2

[0093] Among them, Pa t0 represents the atmospheric pressure at the first moment t0, Pa ref It represents the atmospheric pressure in the initial state, and Pa0 represents the local standard atmospheric pressure.

[0094] After respectively calculating the movement speed at the first moment t0 and the movement height at the first moment t0 by the above formula 1 and formula 2, it can be determined whether the user enters the play state at the first moment based on the movement speed at the first moment t0 and / or the movement height. If the user's movement speed is greater than the first speed threshold, and / or the movement height is greater than the first height threshold, it means that the user enters the play state at the first moment. The first moment t0 can be understood as the starting moment of the sports event, and the second moment t1 can be understood as the ending moment of the sports event.

[0095] It should be noted that since the method for calculating the movement speed at the second moment t1 and the method for calculating the movement height at the second moment t1 are respectively similar to the method for calculating the movement speed at the first moment and the method for calculating the movement height at the first moment, please refer to the relevant description of the method for calculating the movement speed at the first moment and the method for calculating the movement height at the first moment. Here, the method for calculating the movement speed at the second moment and the method for calculating the movement height at the second moment are respectively similar to the method for calculating the movement speed at the first moment, and the embodiments of the present application will not be repeated again.

[0096] In the above description, when turning on the amusement park mode of the smart bracelet, for example, at least three possible implementation methods can be included. In one possible implementation method, the smart bracelet can use the positioning system and the map to automatically turn on the amusement park mode of the smart bracelet when it determines that the user is currently entering the amusement park area. Although this method realizes intelligent control, there may be a situation where the amusement park mode is turned on by mistake. For example, the user may just pass by the amusement park area instead of going to the amusement park to play. In another possible implementation method, the user can manually turn on the amusement park mode of the smart bracelet. For example, please refer to Figure 4 As shown, Figure 4 A schematic diagram of manually opening the amusement park mode of a smart bracelet provided in an embodiment of the present application. Since the screen size of the smart bracelet is limited, you can first manually click on the screen of the terminal to enter the control program of the smart bracelet, select the amusement park mode, and then control the smart bracelet to open the amusement park mode by clicking the open button in the amusement park mode. Although this method requires manual operation by the user compared to the first possible implementation method, the complexity is higher, but it can avoid the amusement park mode from being mistakenly opened, thereby improving the accuracy of opening the amusement park mode. In another possible implementation method, you can enter the control program of the smart bracelet through voice control, select the amusement park mode, and then control the smart bracelet to open the amusement park mode through voice control. Compared with the previous two possible implementation methods, not only can intelligent control be achieved, but also the accuracy of opening the amusement park mode is improved. Of course, you can also operate directly on the screen of the smart bracelet to control the smart bracelet to open the amusement park mode. It can be set according to actual needs. Here, the embodiment of the present application is just to illustrate this by these several methods as an example, but it does not mean that the embodiment of the present application is limited to this.

[0097] After the user's motion data is acquired through S301, the motion trajectory curve and the motion stimulation degree curve can be determined according to the motion data, that is, the following S302 is executed:

[0098] S302: Determine a motion trajectory curve and a motion stimulation degree curve according to the motion data.

[0099] The motion trajectory curve is used to represent the motion trajectory of the user during the motion process, and the motion stimulation degree curve is used to represent the corresponding relationship between time and motion stimulation degree during the motion process.

[0100] When determining the motion trajectory curve based on motion data, for example, see Figure 5 As shown, Figure 5 A schematic diagram of determining a motion trajectory curve according to motion data provided in an embodiment of the present application can determine the sports project corresponding to the motion data based on big data analysis technology; for example, the sports project can be any sports project in amusement park projects such as a large pendulum, a free fall or a roller coaster. If the motion trajectory corresponding to the sports project belongs to the first type, the motion trajectory of the first type can be understood as a motion trajectory with low complexity. Since each sports project belonging to the first type is preset with its own motion trajectory curve, the preset motion trajectory curve corresponding to the sports project is read, and the preset motion trajectory curve corresponding to the sports project is determined as the motion trajectory curve corresponding to the sports project. For example, if the motion trajectory corresponding to the sports project belongs to the second type, the motion trajectory of the second type can be understood as a motion trajectory with high complexity, then the curve fitting technology is used to fit the motion data to obtain the motion trajectory curve. Among them, the complexity of the motion trajectory of the sports project belonging to the second type is higher than the complexity of the motion trajectory of the sports project belonging to the first type. For example, the motion trajectory corresponding to sports projects such as a large pendulum or a free fall belongs to the first type, and the motion trajectory corresponding to sports projects such as a roller coaster belongs to the second type.

[0101] It can be understood that in the embodiments of the present application, for sports items with simple, low-complexity motion trajectories, when determining the corresponding motion trajectory curve, it is not necessary to calculate the motion trajectory curve corresponding to the sports item based on the currently acquired motion data, but rather to read the preset motion trajectory curve corresponding to the sports item and determine the preset motion trajectory curve corresponding to the sports item as the motion trajectory curve corresponding to the sports item. This can not only reduce the complexity of terminal calculations, but also optimize the motion trajectory and improve the accuracy of the motion trajectory curve. For example, in the embodiments of the present application, taking the sports item of roller coaster as an example, the motion trajectory curve corresponding to the roller coaster item can be found in Figure 6 As shown, Figure 6 A schematic diagram of a motion trajectory curve corresponding to a roller coaster project provided in an embodiment of the present application.

[0102] When determining the motion stimulation degree curve based on motion data, for example, the motion stimulation degree at the second time point can be determined based on the motion data of each second time point in at least two time points during the motion process; and the polynomial fitting technology is used to fit the motion stimulation degree of at least two time points to obtain the motion stimulation degree curve. It can be understood that when fitting the motion stimulation degree of the second time point to obtain the motion stimulation degree curve, the more second time points are used, the higher the accuracy of the motion stimulation degree curve obtained through fitting. For example, in an embodiment of the present application, the motion stimulation degree of each second time point in the motion process can be determined based on the motion data of the second time point in the motion process, and then the polynomial fitting technology is used to fit the motion stimulation degree of each second time point in the motion process to obtain a motion stimulation degree curve with higher accuracy. Similarly, taking the roller coaster as an example, the motion stimulation degree curve corresponding to the roller coaster project can be found in Figure 7 As shown, Figure 7 A schematic diagram of a motion stimulation degree curve corresponding to a roller coaster project provided in an embodiment of the present application.

[0103] It can be seen that when fitting the motion stimulation degree curve, it is necessary to calculate the motion stimulation degree at each second time point. Referring to the previous description, it can be seen that in the embodiment of the present application, the factors affecting the motion stimulation degree include four factors: motion speed, motion acceleration, motion height and heart rate. Therefore, when calculating the stimulation degree at the second time point based on the four factors of motion speed, motion acceleration, motion height and heart rate at the second time point, the motion speed, motion acceleration, motion height and heart rate corresponding to the second time point can be normalized to obtain the normalized motion speed, motion acceleration, motion height and heart rate; and then the motion stimulation degree at the second time point can be determined based on the normalized motion speed, motion acceleration, motion height and heart rate. In this way, after determining the motion stimulation degree at the second time point, the polynomial fitting technology can be used to fit the motion stimulation degree at each second time point in the motion process to obtain a motion stimulation degree curve used to represent the corresponding relationship between time and motion stimulation degree during the motion process. See. Figure 8 As shown, Figure 8 A schematic diagram of a curve for determining the degree of motion stimulation provided in an embodiment of the present application.

[0104] When normalizing the motion speed, motion acceleration, motion height, and heart rate corresponding to any second time point t2, the normalization processing method of the motion speed, the normalization processing method of the motion acceleration, the normalization processing method of the motion height, and the normalization processing method of the heart rate are similar. Taking the normalization processing method of the motion speed as an example, when normalizing the motion speed V t2Perform normalization processing, see the following formula 3.

[0105]

[0106] Among them, V t2 ' represents the normalized motion speed at the second time point t2, V t2 represents the movement speed at the second time point t2, V max and V min It represents the theoretical maximum value and the theoretical minimum value of the movement speed, which can be obtained by big data analysis technology.

[0107] It should be noted that since the normalized processing method of motion acceleration, the normalized processing method of motion height and the normalized processing method of heart rate at the second time point t2 are similar to the normalized processing method of motion speed at the second time point t2, please refer to the relevant description of the normalized processing method of motion speed at the second time point t2. Here, the normalized processing method of motion acceleration, the normalized processing method of motion height and the normalized processing method of heart rate at the second time point t2 will not be repeated in the embodiments of the present application.

[0108] The normalized motion speed V at the second time point is calculated and obtained respectively. t2 ', motion acceleration, a t2 'Movement height ΔH t2 ' and heart rate Hr t2 'After that, the normalized motion speed V at the second time point can be used t2 ', motion acceleration, a t2 'Movement height ΔH t2 ' and heart rate Hr t2 ', the motion stimulation degree F at the second time point can be calculated according to the following formula 4 t2 .

[0109] F t2 =α*V′ t2 +β*a′ t2 +λ*ΔH′ t2 +μ*Hr′ t2 Formula 4

[0110] Among them, F t2 Indicates the degree of motion stimulation at the second time point F t2 , α, β, λ and μ represent the movement speed, movement acceleration, movement height and heart rate weight coefficient, which are obtained by big data analysis technology.

[0111] After calculating the degree of motion stimulation at each second time point t2 during the exercise process by the above formulas 3 and 4, the polynomial fitting technology can be used to fit the degree of motion stimulation at each second time point during the exercise process to obtain a motion stimulation degree curve F(t) used to represent the corresponding relationship between time and the degree of motion stimulation during the exercise process, as shown in the following formula 5.

[0112]

[0113] Where M represents the polynomial order, ω0,...,ω M represents the coefficient of the polynomial, t represents time, and F(t) represents the stimulus level corresponding to time point t. t .

[0114] In this way, after obtaining a motion trajectory curve for representing the motion trajectory of the user during the motion process and a motion stimulation degree curve for representing the corresponding relationship between time and the motion stimulation degree during the motion process according to the motion data, if these two curves are displayed separately during display, then after executing S302, the motion trajectory curve and the motion stimulation degree curve can be directly displayed on the screen. In order to make the display effect of the screen more concise when displaying the motion trajectory and the motion stimulation degree to the user through the screen, the calculated motion trajectory curve and the motion stimulation degree curve can be superimposed to obtain a motion curve for indicating the motion trajectory of the user during the motion process and the motion stimulation degree during the motion process, that is, the following S303 is executed:

[0115] S303: Determine a motion curve according to the motion trajectory curve and the motion stimulation degree curve.

[0116] For example, when the motion trajectory curve and the motion stimulation degree curve are superimposed to obtain the motion curve, at least two possible implementation methods may be included. In one possible implementation method, the colors corresponding to the motion stimulation degrees at at least two first time points in the motion stimulation degree curve may be first determined based on the mapping relationship between the motion stimulation degree and the color; and the colors corresponding to each of the at least two first time points in the motion trajectory curve may be modified to the colors corresponding to the motion stimulation degrees at the first time points to obtain the motion curve.

[0117] It is understandable that when the color corresponding to the first time point in the motion trajectory curve is modified to the color corresponding to the degree of motion stimulation at the first time point, the more the number of first time points modified, the higher the accuracy of the corresponding superimposed motion curve. In an embodiment of the present application, in order to improve the accuracy of the motion curve, the color corresponding to each first time point in the motion trajectory curve can be modified to the color corresponding to the degree of motion stimulation at the first time point. For example, when the degree of motion stimulation is represented by color, the darker the color, the more intense the degree of motion stimulation.

[0118] In this possible implementation, when the color corresponding to the first time point in the motion trajectory curve is modified to the color corresponding to the motion stimulation degree at the first time point according to the mapping relationship between the motion stimulation degree and the color, the mapping relationship between the motion stimulation degree and the color may include but is not limited to the mapping relationship between the motion stimulation degree and the color temperature, the mapping relationship between the motion stimulation degree and the spectrum, and of course, other motion stimulation degrees and mapping relationships between real numbers and colors. The mapping relationship between the motion stimulation degree and the color temperature can be found in the following formula 6.

[0119] K t =99000*F t +1000 Formula 6

[0120] Among them, F t Indicates the stimulation level corresponding to time point t; K t Represents the color temperature value at time t, in Kelvin.

[0121] By using the above formula 6, the color temperature value corresponding to the motion stimulation degree at each time point in the motion stimulation degree curve can be determined, and then the color corresponding to each first time point in the motion trajectory curve is modified to the color temperature value corresponding to the motion stimulation degree at the first time point. Taking the first three time points in the motion stimulation degree curve as an example, through the above formula 6, it is determined that the color temperature value corresponding to the motion stimulation degree corresponding to the first time point in the motion stimulation degree curve is the first color temperature value, the color temperature value corresponding to the motion stimulation degree corresponding to the second time point in the motion stimulation degree curve is the second color temperature value, and the color temperature value corresponding to the motion stimulation degree corresponding to the third time point in the motion stimulation degree curve is the third color temperature value, then the color corresponding to the first time point in the motion trajectory curve is modified to the first color temperature value, the color corresponding to the second time point in the motion trajectory curve is modified to the second color temperature value, and the color corresponding to the third time point in the motion trajectory curve is modified to the third color temperature value; it can be understood that the modification of the colors corresponding to other time points in the motion trajectory curve is similar to the modification method of the first three time points in the motion trajectory curve, so that after the color corresponding to each first time point in the motion trajectory curve is modified to the color temperature value corresponding to the motion stimulation degree at the first time point, the superimposed motion curve can be obtained, which is not only used to indicate the motion trajectory of the user during the motion process, but also to indicate the degree of motion stimulation during the motion process.

[0122] In another possible implementation, the line type corresponding to the motion stimulation degree at at least two first time points in the motion stimulation degree curve can be determined based on the mapping relationship between the motion stimulation degree and the line type; and the line type corresponding to each of the at least two first time points in the motion trajectory curve is modified to the line type corresponding to the motion stimulation degree at the first time point, to obtain a motion curve. For example, the line type can be divided according to the thickness of the line. For example, when the motion stimulation degree is represented by the thickness of the line, the darker the line, the more intense the motion stimulation degree. Of course, it can also be divided with solid lines or dotted lines. For example, see Fig. 9 As shown, Fig. 9 A schematic diagram of a motion curve corresponding to a roller coaster project provided in an embodiment of the present application.

[0123] It is understandable that when the line type corresponding to the first time point in the motion trajectory curve is modified to the line type corresponding to the degree of motion stimulation at the first time point, the more the number of modified first time points is, the higher the accuracy of the corresponding superimposed motion curve is. In the embodiment of the present application, in order to improve the accuracy of the motion curve, the line type corresponding to each first time point in the motion trajectory curve can be modified to the line type corresponding to the degree of motion stimulation at the first time point.

[0124] It is understandable that in the embodiment of the present application, when the motion trajectory curve and the motion stimulation degree curve are superimposed to obtain a motion curve for indicating the motion trajectory of the user during the motion process and the motion stimulation degree during the motion process, the above two possible implementation methods are used as examples for explanation, but it does not mean that the embodiment of the present application is limited to this. After obtaining the motion curve for indicating the motion trajectory of the user during the motion process and the motion stimulation degree during the motion process, the motion curve can be stored and displayed. By storing the motion curve, it is convenient for the user to view the motion curve later, so as to help the user recall the wonderful moments in the entire motion process, thereby improving the user experience.

[0125] S304: Display the motion curve.

[0126] After determining the motion curve according to the motion trajectory curve and the motion stimulation degree curve, prompt information may be output to the user, for example, whether to view the motion curve, and the motion curve may be displayed to the user upon receiving the user's viewing instruction; of course, after determining the motion curve according to the motion trajectory curve and the motion stimulation degree curve, it is also possible to directly display the motion curve to the user without outputting prompt information. Usually, since the display screen of the terminal is larger than the display screen of the smart bracelet, in order to improve the user's viewing experience, the motion curve may be directly displayed on the display screen of the terminal. For an example, see Fig.10 As shown, Fig.10 A schematic diagram of a motion curve corresponding to a roller coaster project provided in an embodiment of the present application. Of course, if the display screen of the smart bracelet is small, after generating the motion curve, the terminal can also send the motion curve to the smart bracelet via Bluetooth or wireless network, and display the motion curve on the display screen of the smart bracelet.

[0127] It can be seen that the method for processing motion data provided by the embodiment of the present application first obtains the motion data of the user, and determines the motion trajectory of the user during the motion process and the motion stimulation degree of the user during the motion process according to the motion data; and then displays the motion curve. It can be seen that, unlike the prior art, when displaying the motion record to the user, the motion curve used to indicate the motion trajectory of the user during the motion process and the motion stimulation degree during the motion process is first determined, so that when performing a visual display, not only the motion trajectory during the motion process is displayed to the user, but also the motion stimulation degree during the motion process is displayed to the user, enriching the display content, thereby improving the user experience.

[0128] Above Figure 3The embodiment shown describes in detail that in order to enrich the display content, to improve the user experience, when visually displaying to the user, in addition to displaying the motion track of the user in the motion process to the user, the degree of motion stimulation in the motion process can also be synchronously displayed to the user, enriching the display content, thereby improving the user experience. In an embodiment of the present application, in addition to synchronously displaying the degree of motion stimulation in the motion process to the user, the key information in the motion process can also be further displayed to the user, wherein the key information includes at least one of the maximum motion height, the maximum motion speed, the maximum heart rate or the motion stimulation degree score. It is understandable that when displaying the key information, the more key information displayed, the richer the corresponding display content, and the better the user experience. In order to make the display content richer, in an embodiment of the present application, the maximum motion height, the maximum motion speed, the maximum heart rate and the motion stimulation degree score can also be displayed to the user.

[0129] For example, when determining the maximum movement height during the entire exercise process, since the movement height corresponding to each time during the entire exercise process can be calculated, the maximum movement height during the entire exercise process can be determined through comparison; similarly, when determining the maximum movement height and heart rate during the entire exercise process, since the movement speed and heart rate corresponding to each time during the entire exercise process can be calculated, the maximum movement speed and maximum heart rate during the entire exercise process can be determined through comparison.

[0130] For example, when determining the exercise stimulation degree score, the exercise stimulation degree curve obtained in S302 may be integrated to obtain an integral result; then the ratio of the integral result to the duration of the exercise process is calculated, and the exercise stimulation degree score S of the entire exercise process may be calculated based on the ratio of the integral result to the duration of the exercise process, as shown in the following formula 7. thrill Among them, the duration of the movement process is determined according to the end time and start time of the movement process.

[0131]

[0132] Among them, S thrill It represents the sports stimulation degree score of the sports event, t0 represents the starting time of the sports event, and t1 represents the ending time of the sports event.

[0133] It is understandable that when determining the sports stimulation degree score of the entire sports process according to the ratio of the integral result and the duration of the sports process, the calculated ratio can be directly determined as the sports stimulation degree score of the entire sports process, that is, the ratio calculated by the above formula 7 is determined as the sports stimulation degree score of the entire sports process; of course, in order to make the sports stimulation degree score fall within a certain scoring interval, the ratio of the integral result and the duration of the sports process can be normalized first to obtain the normalized ratio; and the normalized ratio is processed based on the preset scoring interval to obtain the sports stimulation degree score. Taking the scoring interval as [0,100] as an example, the normalized ratio can be processed by the following formula 8 to obtain the sports stimulation degree score S.

[0134] S = round(100*S′ thrill ) Formula 8

[0135] Among them, S represents the sports stimulation level score, S′ thrill Represents the normalized ratio; round() represents the rounding function.

[0136] After determining the maximum exercise height, maximum exercise speed, maximum heart rate and exercise stimulation level score during exercise, you can display the user's exercise trajectory and exercise stimulation level during exercise to the user, and at the same time provide the user with such key information. For example, see Fig.11 As shown, Fig.11 A schematic diagram of a motion curve of a roller coaster project including key information provided in an embodiment of the present application can further enrich the display content, thereby improving the user experience.

[0137] It can be seen that through the above Figure 3In the embodiment shown, when playing a sports project, such as a roller coaster project, the terminal can generate a motion curve corresponding to the roller coaster project based on the motion data during the exercise process, and display the motion curve to the user. If the wearable device detects that the user has entered the play state again, the motion data during the exercise process can also be collected, and the motion data can be sent to the terminal, so that the terminal can determine the motion curve corresponding to the sports project based on the motion data. Taking the sports project as a large pendulum project as an example, the method for obtaining the motion curve corresponding to the large pendulum project is similar to the method for obtaining the motion curve corresponding to the roller coaster project in the embodiment shown in Figure 3. Please refer to the above description of the method for obtaining the motion curve corresponding to the roller coaster project. The embodiment of the present application will not be repeated here. It can be seen that the motion data processing method provided in the embodiment of the present application can continuously identify different sports projects through motion data, and by obtaining the motion data of each sports process, and generating the motion curve corresponding to the sports project based on the motion data of each sports process, and storing the motion curve corresponding to each sports project, when the user views the motion curve later, the motion curve can help the user recall the wonderful moments of the entire sports process. For an example, please refer to Fig.12 As shown, Fig.12 A schematic diagram of viewing a motion curve provided in an embodiment of the present application shows that when the user subsequently views the motion curve, the user can first enter the amusement park mode. After entering the amusement park mode, the terminal will display to the user the historical play items that have been played before. When it is determined that the user clicks on a certain sports item, for example, the user clicks on a roller coaster item, the motion curve corresponding to the roller coaster item is displayed to the user, so as to help the user recall the wonderful moments of the entire motion process through the motion curve. Compared with the prior art in which only the motion trajectory is displayed to the user, the motion data processing method provided in the embodiment of the present application, when performing a visual display, not only displays the motion trajectory during the motion process to the user, but also displays the degree of motion stimulation during the motion process to the user, thereby enriching the display content and improving the user experience.

[0138] Fig.13 This is a structural diagram of a motion data processing device 130 provided in an embodiment of the present application. For example, see Fig.13 As shown, the motion data processing device 130 may include:

[0139] The acquisition unit 1301 is used to acquire the user's motion data.

[0140] The processing unit 1302 is used to determine the user's motion curve according to the motion data; the motion curve is used to indicate the motion trajectory of the user during the motion process, and the degree of motion stimulation during the motion process.

[0141] The display unit 1303 is used to display the motion curve.

[0142] Optionally, the processing unit 1302 is used to determine a motion trajectory curve and a motion stimulation degree curve according to the motion data respectively; and determine the motion curve according to the motion trajectory curve and the motion stimulation degree curve; wherein the motion trajectory curve is used to represent the motion trajectory of the user during the motion process, and the motion stimulation degree curve is used to represent the correspondence between time and motion stimulation degree during the motion process.

[0143] Optionally, processing unit 1302 is used to determine the colors corresponding to the motion stimulation degrees at least two first time points in the motion stimulation degree curve according to the mapping relationship between the motion stimulation degree and the color; and modify the color corresponding to each of the at least two first time points in the motion trajectory curve to the color corresponding to the motion stimulation degree at the first time point, so as to obtain the motion curve.

[0144] Optionally, the processing unit 1302 is specifically used to determine the sports event corresponding to the sports data based on big data analysis technology; and determine the sports trajectory curve according to the sports event.

[0145] Optionally, the processing unit 1302 is specifically used to determine a preset motion trajectory curve corresponding to the sports item as the motion trajectory curve if the motion trajectory corresponding to the sports item belongs to the first type; wherein the sports items belonging to the first type all have their own corresponding motion trajectory curves; if the motion trajectory corresponding to the sports item belongs to the second type, curve fitting technology is used to fit the motion data to obtain the motion trajectory curve; wherein the complexity of the motion trajectory of the sports items belonging to the second type is higher than the complexity of the motion trajectory of the sports items belonging to the first type.

[0146] Optionally, the motion data includes at least one of motion speed, motion acceleration, motion altitude or heart rate.

[0147] Processing unit 1302 is specifically used to determine the degree of exercise stimulation at a second time point according to the exercise data of each second time point in at least two time points during the exercise process; and use polynomial fitting technology to fit the degree of exercise stimulation at at least two time points to obtain a motion stimulation degree curve.

[0148] Optionally, the motion data includes motion speed, motion acceleration, motion altitude and heart rate.

[0149] Processing unit 1302 is specifically used to normalize the movement speed, movement acceleration, movement height and heart rate corresponding to the second time point, respectively, to obtain the processed movement speed, movement acceleration, movement height and heart rate; and determine the degree of movement stimulation at the second time point based on the processed movement speed, movement acceleration, movement height and heart rate.

[0150] Optionally, the display unit 1303 is also used to display key information during the exercise process; wherein the key information includes at least one of the maximum exercise height, the maximum exercise speed, the maximum heart rate or the exercise stimulation degree score.

[0151] Optionally, the processing unit 1302 is further used to integrate the motion stimulation degree curve to obtain an integral result; and determine the motion stimulation degree score based on the ratio of the integral result and the duration of the motion process; wherein the duration of the motion process is determined based on the end time and start time of the motion process.

[0152] Optionally, the processing unit 1302 is specifically configured to normalize the comparison value to obtain a normalized ratio; and process the normalized ratio based on a preset scoring interval to obtain a motion stimulation degree score.

[0153] Optionally, the motion data includes motion speed and motion height, and the processing unit 1302 is also used to determine that the user enters the motion state if the motion speed is greater than a first speed threshold, and / or the motion height is greater than a first height threshold; if the motion speed is less than a second speed threshold, and the motion height is less than a second height threshold, determine that the user exits the motion state.

[0154] The motion data processing device 130 shown in the embodiment of the present application can execute the technical solution of the motion data processing method shown in any of the above embodiments. Its implementation principle and beneficial effects are similar to the implementation principle and beneficial effects of the motion data processing method, and will not be repeated here.

[0155] Fig.14 A schematic diagram of the structure of a communication device 140 provided in an embodiment of the present application, for example, see Fig.14 As shown, the communication device 140 includes a processor 1401 and a memory 1402, in which a computer program is stored. The processor 1401 executes the computer program stored in the memory 1402 so that the device executes the technical solution of the motion data processing method shown in any of the above embodiments. The implementation principle and beneficial effects are similar to the implementation principle and beneficial effects of the motion data processing method, and will not be repeated here.

[0156] An embodiment of the present application also provides a communication device, which may include: a processor and an interface circuit.

[0157] The interface circuit is used to receive code instructions and transmit them to the processor.

[0158] The processor is used to run the code instructions to execute the technical solution of the motion data processing method shown in any of the above embodiments. Its implementation principle and beneficial effects are similar to the implementation principle and beneficial effects of the motion data processing method, and will not be repeated here.

[0159] An embodiment of the present application also provides a readable storage medium for storing instructions. When the instructions are executed, the motion data processing method shown in any of the above embodiments is implemented. The implementation principle and beneficial effects are similar to the implementation principle and beneficial effects of the motion data processing method, and will not be repeated here.

[0160] In the above-mentioned embodiments, the processor may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, and discrete hardware components. The methods, steps, and logic block diagrams disclosed in the embodiments of the present application may be implemented or executed. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed by a hardware decoding processor, or may be executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory (RAM), a flash memory, a read-only memory (ROM), a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the instructions in the memory and completes the steps of the above-mentioned method in combination with its hardware.

[0161] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0162] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

Claims

1. A method for processing motion data, characterized in that: include: Get the user's sports data; Determine the sport event corresponding to the sport data based on big data analysis technology; If the motion trajectory corresponding to the sports item belongs to the first type, the preset motion trajectory curve corresponding to the sports item is determined as the motion trajectory curve; wherein the sports items belonging to the first type all correspond to their own motion trajectory curves; If the motion trajectory corresponding to the sports item belongs to the second type, a curve fitting technique is used to fit the motion data to obtain the motion trajectory curve; wherein the complexity of the motion trajectory of the sports item belonging to the second type is higher than the complexity of the motion trajectory of the sports item belonging to the first type; Determine a motion stimulation degree curve according to the motion data; the motion trajectory curve is used to indicate the motion trajectory of the user during the motion process, and the motion stimulation degree curve is used to indicate the corresponding relationship between time and motion stimulation degree during the motion process; Determining a motion curve corresponding to the sport according to the motion trajectory curve and the motion stimulation degree curve; The motion curve is displayed.

2. The method according to claim 1, characterized in that Determining the motion curve corresponding to the sport item according to the motion trajectory curve and the motion stimulation degree curve includes: Determining, according to a mapping relationship between the motion stimulation degree and the color, the color corresponding to the motion stimulation degree at least two first time points in the motion stimulation degree curve; The motion curve is obtained by modifying the color corresponding to each of the at least two first time points in the motion trajectory curve to a color corresponding to the motion stimulation degree at the first time point.

3. The method according to claim 1 or 2, characterized in that: The motion data includes at least one of motion speed, motion acceleration, motion height or heart rate, and determining the motion stimulation degree curve according to the motion data includes: Determining the degree of exercise stimulation at each second time point in at least two time points during the exercise process; The motion stimulation degree curve is obtained by fitting the motion stimulation degree at the at least two time points using a polynomial fitting technique.

4. The method according to claim 3, characterized in that The motion data includes motion speed, motion acceleration, motion height and heart rate, and determining the motion stimulation degree at each second time point in at least two time points during the motion process according to the motion data at the second time point includes: Normalizing the movement speed, movement acceleration, movement height, and heart rate corresponding to the second time point to obtain processed movement speed, movement acceleration, movement height, and heart rate; The degree of exercise stimulation at the second time point is determined according to the processed exercise speed, exercise acceleration, exercise altitude and heart rate.

5. The method according to any one of claims 1-2 and 4, characterized in that: The method further comprises: Display key information during the exercise process; wherein the key information includes at least one of the maximum exercise height, the maximum exercise speed, the maximum heart rate or the exercise stimulation level score.

6. The method according to claim 5, characterized in that The method further comprises: Integrating the motion stimulation degree curve to obtain an integral result; The exercise stimulation degree score is determined according to the ratio of the integral result and the duration of the exercise process; wherein the duration of the exercise process is determined according to the end time and the start time of the exercise process.

7. The method according to claim 6, characterized in that Determining the exercise stimulation degree score according to the ratio of the integral result to the duration of the exercise process includes: Normalizing the ratio to obtain a normalized ratio; The normalized ratio is processed based on a preset scoring interval to obtain the exercise stimulation degree score.

8. The method according to any one of claims 1-2, 4, 6-7, characterized in that: The motion data includes motion speed and motion height, and the method further includes: If the movement speed is greater than a first speed threshold, and / or the movement height is greater than a first height threshold, it is determined that the user enters a movement state; If the movement speed is less than a second speed threshold, and the movement height is less than a second height threshold, it is determined that the user has exited the movement state.

9. A motion data processing device, characterized in that: include: An acquisition unit, used for acquiring the user's motion data; A processing unit, configured to determine the sport event corresponding to the sport data based on big data analysis technology; If the motion trajectory corresponding to the sports item belongs to the first type, the preset motion trajectory curve corresponding to the sports item is determined as the motion trajectory curve; wherein the sports items belonging to the first type all correspond to their own motion trajectory curves; If the motion trajectory corresponding to the sports item belongs to the second type, a curve fitting technique is used to fit the motion data to obtain the motion trajectory curve; wherein the complexity of the motion trajectory of the sports item belonging to the second type is higher than the complexity of the motion trajectory of the sports item belonging to the first type; Determine a motion stimulation degree curve according to the motion data; the motion trajectory curve is used to indicate the motion trajectory of the user during the motion process, and the motion stimulation degree curve is used to indicate the corresponding relationship between time and motion stimulation degree during the motion process; Determining a motion curve corresponding to the sport according to the motion trajectory curve and the motion stimulation degree curve; A display unit is used to display the motion curve.

10. The device according to claim 9, characterized in that The processing unit is used to determine the colors corresponding to the motion stimulation degrees at least two first time points in the motion stimulation degree curve according to the mapping relationship between the motion stimulation degree and the color; and modify the color corresponding to each of the at least two first time points in the motion trajectory curve to the color corresponding to the motion stimulation degree at the first time point, so as to obtain the motion curve.

11. The device according to claim 9 or 10, characterized in that The motion data includes at least one of motion speed, motion acceleration, motion altitude or heart rate; The processing unit is specifically used to determine the degree of exercise stimulation at each of the at least two time points in the exercise process according to the exercise data of the second time point; and use polynomial fitting technology to fit the degree of exercise stimulation at the at least two time points to obtain the exercise stimulation degree curve.

12. The device according to claim 11, characterized in that The exercise data includes exercise speed, exercise acceleration, exercise altitude and heart rate; The processing unit is specifically used to normalize the movement speed, movement acceleration, movement height and heart rate corresponding to the second time point, respectively, to obtain the processed movement speed, movement acceleration, movement height and heart rate; and determine the degree of movement stimulation at the second time point based on the processed movement speed, movement acceleration, movement height and heart rate.

13. The device according to any one of claims 9 to 10 and 12, characterized in that: The display unit is also used to display key information during the exercise process; wherein the key information includes at least one of the maximum exercise height, the maximum exercise speed, the maximum heart rate or the exercise stimulation degree score.

14. The device according to claim 13, characterized in that The processing unit is also used to integrate the motion stimulation degree curve to obtain an integral result; and determine the motion stimulation degree score based on the ratio of the integral result and the duration of the motion process; wherein the duration of the motion process is determined based on the end time and start time of the motion process.

15. The device according to claim 14, characterized in that The processing unit is specifically used to normalize the ratio to obtain a normalized ratio; and to process the normalized ratio based on a preset scoring interval to obtain the sports stimulation degree score.

16. The device according to any one of claims 9-10, 12, 14-15, characterized in that: The motion data includes motion speed and motion height. The processing unit is further used to determine that the user has entered a motion state if the motion speed is greater than a first speed threshold and / or the motion height is greater than a first height threshold; and to determine that the user has exited a motion state if the motion speed is less than a second speed threshold and the motion height is less than a second height threshold.

17. A communication device, characterized in that: The device includes a processor and a memory, wherein a computer program is stored in the memory, and the processor executes the computer program stored in the memory so that the device performs the motion data processing method according to any one of claims 1 to 8.

18. A communication device, characterized in that: include: processor and interface circuits; The interface circuit is used to receive code instructions and transmit them to the processor; The processor is used to run the code instructions to execute the motion data processing method according to any one of claims 1 to 8.

19. A readable storage medium, characterized in that: The device is used for storing instructions, and when the instructions are executed, the method for processing motion data according to any one of claims 1 to 8 is implemented.

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