Upper and lower limb muscle training system based on VR

Abstract

The invention relates to the field of muscle training, in particular to an upper and lower limb muscle training system based on VR. A specific muscle training device is arranged and is combined with a data acquisition unit, a data processing unit and a data display unit, and basic data including acceleration data, position data and angle data are obtained through an accelerometer, a position sensor and an angle sensor in the data acquisition unit respectively; then, the data processing unit is used for processing, each motion period of the sliding sleeve is used as a unit, intermediate data including acceleration change frequency, motion speed and angle interval are calculated, and the intermediate data are compared with preset theoretical data to obtain comparison data, so that motion suggestions are further given; therefore, corresponding exercise suggestions can be given in real time in the use process of the user, and the training effect of the user is improved; the problem that according to an existing upper and lower limb muscle training device, it is difficult for a user to obtain exercise suggestions according to the use condition of the user is solved.

Description

Technical Field

[0001] The present invention relates to the field of muscle training, and particularly to a VR-based upper and lower limb muscle training system. Background Art

[0002] There are many existing arm strengtheners and leg press machines. During use, the arm strengthener and leg press machine are mainly used by cooperating with two legs or two arms to achieve the purpose of exercise. However, when using these tools, there are only some general usage methods, lacking the function of providing further suggestions according to the user's usage process, resulting in users being difficult to specifically change the exercise method. For example, for the leg press machine, place the leg press machine at the corresponding part of the thigh between the two legs, apply force with the legs to move the corresponding part on the leg press machine, and use the elastic resistance of the corresponding components on the leg press machine to apply resistance to the user's legs to achieve the purpose of exercise. However, during the actual exercise process, the speed at which the user's legs clamp the leg press machine is positively correlated with the load on the user's legs. Therefore, it is not necessarily known to the user how to reasonably select the speed to improve the exercise effect. Summary of the Invention

[0003] Aiming at the deficiencies of the prior art, the present invention provides a VR-based upper and lower limb muscle training system, which solves the problem that it is difficult for users of existing upper and lower limb muscle training devices to obtain exercise suggestions according to their own usage situations.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A VR-based upper and lower limb muscle training system, comprising:

[0006] A muscle training device, the muscle training device includes a slide rail as an installation carrier, and elastic sleeves for sliding towards the center direction are provided at both ends of the slide rail, and an operating member for contacting the limb is rotatably installed below the slide sleeve;

[0007] A data acquisition unit, the data acquisition unit includes an accelerometer provided in the slide rail for collecting the acceleration change of the slide rail position, a position sensor provided on the slide rail for detecting the position of the slide sleeve, and an angle sensor for collecting the relative rotation angle between the operating member and the slide sleeve, and transmits the collected basic data including acceleration data, position data, and angle data to the data processing unit;

[0008] A data processing unit, the data processing unit is used to calculate intermediate data including acceleration change frequency, movement speed, and angle range according to the basic data collected by the data acquisition unit, compare it with the theoretical data preset in the data processing unit to obtain comparison data, give exercise suggestions, and output the comparison data and exercise suggestions to the data display unit;

[0009] A data display unit, which is configured to correct a preset three-dimensional stereoscopic image according to intermediate data of a data processing unit and display it, and display corresponding motion suggestions on the three-dimensional stereoscopic image.

[0010] Preferably, the data processing unit includes:

[0011] An acceleration change frequency module, which is configured to obtain the number of acceleration changes of two operating members from leaving the end to returning to the end according to the acceleration data collected in real time by an accelerometer output by a data acquisition unit and the position data collected by a position sensor, so as to obtain an acceleration change frequency;

[0012] A motion speed module, which is configured to calculate the motion speed of a sliding sleeve per unit time according to the position data obtained in real time by a position sensor;

[0013] An angle interval module, which is configured to obtain the maximum and minimum values of the rotation angles of two operating members from leaving the end to returning to the end according to the position data of a position sensor, so as to obtain an angle interval;

[0014] A data storage module, which is configured to store the standard ranges of acceleration change frequency, motion speed and angle interval;

[0015] A data comparison module, which is configured to output comparison data on whether the intermediate data is within the standard range of the data storage module, give motion suggestions, and output the comparison data and motion suggestions to the data display unit.

[0016] Preferably, the acceleration change frequency module includes:

[0017] A statistical period acquisition module, which is configured to obtain the statistical period of two operating members from leaving the end to returning to the end according to the position data collected by a position sensor;

[0018] A threshold setting module, which is configured to set numerical thresholds and angle thresholds for the numerical value and direction change of acceleration data;

[0019] An acceleration change module, which is configured to set a calculation period and calculate the acceleration numerical change amount and direction change amount of acceleration data within each calculation period;

[0020] A number statistics module, which is configured to count the number of calculation periods in which the acceleration numerical change amount is greater than the acceleration numerical threshold or the acceleration direction change amount is greater than the angle threshold within the statistical period, so as to obtain an acceleration change frequency.

[0021] Preferably, in the acceleration change module, the calculation formula for the change amount of the acceleration value is:

[0022] Δa = a 1 - a 2

[0023] In the above formula, Δa represents the change amount of the acceleration value, and a 1 represents the acceleration value at the end of each calculation period, and a 2 represents the acceleration value at the beginning of each calculation period;

[0024] The calculation formula for the change amount of the acceleration direction is:

[0025]

[0026] In the above formula, θ represents the change amount of the acceleration direction, represents the direction vector of the acceleration at the end of each calculation period, represents the direction vector of the acceleration at the beginning of each calculation period.

[0027] Preferably, the data comparison module includes:

[0028] A comparison data module, which is used to output comparison data on whether the intermediate data is within the standard range of the data storage module, and output the comparison data to the data display unit;

[0029] A motion suggestion module, which is used to set a dispersion interval, calculate the dispersion of each intermediate data within a period of time, and output a preset motion suggestion according to whether the dispersion is within the dispersion interval, whether the dispersion is greater than the maximum value of the dispersion interval, and whether the dispersion is less than the minimum value of the dispersion interval.

[0030] Preferably, the calculation formula for the dispersion in the motion suggestion module is:

[0031]

[0032] In the above formula, σ represents the dispersion, N represents the number of intermediate data used to calculate the dispersion, and x i represents the i-th intermediate data, represents the average value of the intermediate data used to calculate the dispersion.

[0033] Preferably, the data display unit includes:

[0034] An image storage module, which is used to store a three-dimensional stereoscopic image including the muscle training device;

[0035] An image display module, which is used to use the intermediate data of the data processing unit as the motion parameters of each component in the three-dimensional stereoscopic image stored in the image storage module, and dynamically display the motion process of the three-dimensional stereoscopic image;

[0036] An image annotation module, which is used to display the comparison data and motion suggestions on the three-dimensional stereoscopic image in the image display module.

[0037] Compared with the prior art, the present invention provides a VR-based upper and lower limb muscle training system, which has the following beneficial effects:

[0038] 1. By setting specific muscle training devices and combining them with a data acquisition unit, a data processing unit, and a data display unit, the present invention respectively obtains basic data including acceleration data, position data, and angle data through the accelerometer, position sensor, and angle sensor in the data acquisition unit. Subsequently, it is processed by the data processing unit. Taking each motion cycle of the sliding sleeve as a unit, intermediate data including acceleration change frequency, motion speed, and angle interval is calculated, and based on this, it is compared with the preset theoretical data to obtain comparison data, thereby further giving motion suggestions, so that corresponding motion suggestions can be given in real time during the user's use process, improving the user's training effect.

[0039] 2. The present invention comprehensively reflects the user's situation in the corresponding motion state through three parameters: acceleration change frequency, motion speed, and angle interval, judges whether the current motion state is suitable for the user, calculates the dispersion degree and compares it with the dispersion degree interval to give corresponding motion suggestions, which is convenient for the user to improve.

[0040] 3. By designing an acceleration change frequency calculation method suitable for the exercise situation of this device, by counting the number of calculation cycles in the statistical period where the acceleration value change amount is greater than the acceleration value threshold, or the acceleration direction change amount is greater than the angle threshold, the acceleration change frequency is obtained, which can more reasonably remove the normal jitter during the user's exercise process and only count the abnormal motions with larger amplitudes, so as to more objectively reflect whether the user's motion state is stable. Description of the Drawings

[0041] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0042] Figure 1 It is the structural block diagram of the VR-based upper and lower limb muscle training system of the present invention;

[0043] Figure 2It is the structural block diagram of the acceleration change frequency module of the present invention;

[0044] Figure 3 It is the structural block diagram of the data comparison module of the present invention;

[0045] Figure 4 It is the schematic diagram of the muscle training device of the present invention.

[0046] In the figure: 1. Muscle training device; 11. Slide rail; 12. Slide sleeve; 13. Operating member; 2. Data acquisition unit; 3. Data processing unit; 31. Acceleration change frequency module; 311. Statistical period acquisition module; 312. Threshold setting module; 313. Acceleration change module; 314. Times statistics module; 32. Movement speed module; 33. Angle interval module; 34. Data storage module; 35. Data comparison module; 351. Comparison data module; 352. Movement suggestion module; 4. Data display unit; 41. Image storage module; 42. Image display module; 43. Image annotation module. Detailed implementation manners

[0047] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific implementation manners. Thereby, a full understanding of how the present application uses technical means to solve technical problems and achieve technical effects can be obtained and implemented accordingly.

[0048] Those of ordinary skill in the art can understand that all or part of the steps in the following implementation methods can be completed by instructing relevant hardware through a program. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0049] In order to solve the problem that it is difficult for users to obtain exercise suggestions according to their own usage situations in existing upper and lower limb muscle training devices, the present invention provides a VR-based upper and lower limb muscle training system, provides a training device, and through parameter collection during the use of the training device, such as Figures 1 - 3 As shown, the system includes:

[0050] A muscle training device 1 including a slide rail 11 as an installation carrier, as Figure 4As shown in the figure, elastic sleeves 12 for sliding towards the center are arranged at both ends of the sliding rail 11. An operating member 13 for contacting the limb is rotatably installed below the elastic sleeve 12. During use, by grasping the two operating members 13 with both hands or placing the two legs outside the operating member 13, the elastic sleeve 12 is restricted by its own elastic force and is located at both ends of the sliding rail 11 in the free state. By applying force to make the operating members 13 move towards each other, the reaction force of the elastic force can be received, and the elastic force can become larger and larger as the two operating members 13 approach each other. Thus, the approach of the two operating members 13 can be blocked by the reaction force of the elastic force, and the reaction force can be applied to the user's legs or hands through the elastic force to achieve the exercise effect;

[0051] A data acquisition unit 2 composed of an accelerometer, a position sensor, and an angle sensor. The accelerometer is arranged inside the sliding rail 11 to collect the acceleration change of the position of the sliding rail 11. The position sensor is arranged on the sliding rail 11 to detect the position of the elastic sleeve 12. The angle sensor is used to collect the relative rotation angle between the operating member 13 and the elastic sleeve 12, and transmit the basic data including acceleration data, position data, and angle data collected to a data processing unit 3; A data processing unit 3 for calculating intermediate data including acceleration change frequency, movement speed, and angle range based on the basic data collected by the data acquisition unit 2, comparing with the preset theoretical data in the data processing unit 3 to obtain comparison data, and giving exercise suggestions. The corresponding exercise suggestions can be given according to the result of the preset comparison data, and the comparison data and exercise suggestions are output to a data display unit 4; A data display unit 4 for correcting and displaying the preset three-dimensional stereo image according to the intermediate data of the data processing unit 3. The three-dimensional stereo image is a three-dimensional stereo map including the muscle training device 1. Here, VR technology can be used for the display of the three-dimensional stereo image, and its display methods can include projection, mobile phone App, VR glasses, VR helmets, etc., to generate the motion state of the muscle training device 1 during use according to the intermediate data, reflect the state of the muscle training device 1 in real-time synchronization, and display the corresponding exercise suggestions on the three-dimensional stereo image. The corresponding exercise suggestions can be displayed in text beside the three-dimensional stereo image or reminded in real-time by voice, so as to provide more targeted exercise suggestions for customers.

[0052] In order to further describe the calculation method of the data processing unit 3 for calculating the acceleration change frequency, movement speed, and angle range, and give the specific method of providing exercise suggestions according to the calculation results, this module specifically includes:

[0053] An acceleration change frequency module 31 for obtaining the number of acceleration changes of two operating members 13 from leaving the end to returning to the end based on the acceleration data collected in real time by the accelerometer output by the data acquisition unit 2 and the position data collected by the position sensor, so as to obtain the acceleration change frequency. The greater the acceleration change frequency, it indicates that the user's hand or leg shakes relatively frequently during exercise, indicating poor stability. At this time, it can be recommended to reduce the movement speed or reduce the maximum distance that the two operating members 13 leave the end; a movement speed module 32 for calculating the movement speed of the sliding sleeve 12 per unit time according to the position data obtained in real time by the position sensor. When other variables remain unchanged, the faster the movement speed, it indicates that the user's physical fitness is better, and the slower the speed, it indicates that the user is more strenuous during exercise; an angle interval module 33 for obtaining the maximum and minimum rotation angles of the two operating members 13 from leaving the end to returning to the end based on the position data of the position sensor, so as to obtain the angle interval. When the user's angle interval is larger, it reflects that the user's hand is more unstable during a single exercise. At this time, it can be recommended to reduce the movement speed during exercise or reduce the maximum distance that the two operating members 13 leave the end; a data storage module 34 for storing the standard ranges of the acceleration change frequency, movement speed, and angle interval; a data comparison module 35 for outputting whether the intermediate data is within the standard range of the data storage module 34 and giving exercise suggestions, and outputting the comparison data and exercise suggestions to the data display unit 4. During exercise, one exercise cycle is defined as the two operating members 13 moving from leaving the end to returning to the end, and taking this as a unit to reflect the user's exercise status.

[0054] To further describe the calculation method of the acceleration change frequency, according to the actual usage situation, a further calculation description is carried out. This module includes:

[0055] A statistical cycle acquisition module 311 for obtaining the statistical cycle of the two operating members 13 from leaving the end to returning to the end based on the position data collected by the position sensor, so that only the corresponding data in the corresponding time period needs to be obtained during subsequent calculations; a threshold setting module 312 for setting the numerical threshold and angle threshold for the numerical and direction changes of the acceleration data. For example, the numerical threshold is set to 1 m / s 2 , and the angle threshold is set to 40 degrees; an acceleration change module 313 for setting the calculation cycle and calculating the acceleration numerical change amount and direction change amount of the acceleration data in each calculation cycle.

[0056] The calculation formula for the acceleration numerical change amount is:

[0057] Δa = a 1 - a 2

[0058] In the above formula, Δa represents the change amount of the acceleration value, and a 1 represents the acceleration value at the end of each calculation period, and a 2 represents the acceleration value at the beginning of each calculation period;

[0059] The calculation formula for the change amount of the acceleration direction is:

[0060]

[0061] In the above formula, θ represents the change amount of the acceleration direction, represents the direction vector of the acceleration at the end of each calculation period, represents the direction vector of the acceleration at the beginning of each calculation period.

[0062] The number statistic module 314 is used to count the number of calculation periods in the statistical period where the change amount of the acceleration value is greater than the acceleration value threshold or the change amount of the acceleration direction is greater than the angle threshold, so as to obtain the acceleration change frequency. Because it is difficult for a person's arms and legs to be absolutely stable during exercise, small-range normal fluctuations are filtered out through the value threshold and the angle threshold, so that the statistical result can better conform to the actual exercise situation and more truly reflect the number of unstable situations of the user during exercise.

[0063] In order to further describe the preset method of the exercise advice and facilitate giving corresponding exercise advice in a timely and accurate manner during exercise, this module includes:

[0064] The comparison data module 351 is used to output the comparison data on whether the intermediate data is within the standard range of the data storage module 34, that is, the comparison data is a judgment result, so as to reflect whether the intermediate data is abnormal. For example, if the acceleration change frequency is large and exceeds the corresponding standard range, this comparison data can be output to the data display unit 4. The exercise advice module 352 is used to set the dispersion interval, calculate the dispersion of each intermediate data within a period of time, and output the preset exercise advice according to whether the dispersion is within the dispersion interval, whether the dispersion is greater than the maximum value of the dispersion interval, and whether the dispersion is less than the minimum value of the dispersion interval. For example, for the exercise speed, if the dispersion of the exercise speed is within the dispersion interval, a suggestion to maintain the current exercise parameters will be output. If the dispersion of the exercise speed is greater than the maximum value of the dispersion interval, it will be suggested to reduce the exercise intensity by reducing the exercise speed, etc. If the dispersion of the exercise speed is less than the minimum value of the dispersion interval, it will be suggested to increase the exercise intensity by increasing the exercise speed. The calculation formula for the dispersion in the exercise advice module 352 is:

[0065]

[0066] In the above formula, σ represents the dispersion degree, N represents the number of intermediate data used for calculating the dispersion degree, and x i represents the i-th intermediate data, represents the average value of the intermediate data used for calculating the dispersion degree.

[0067] In order to further display the detailed content displayed by the data display unit 4 and describe its implementation manner, this unit includes:

[0068] An image storage module 41 for storing a three-dimensional stereoscopic image of the muscle training device 1; an image display module 42 for using the intermediate data of the data processing unit 3 as the motion parameters of each component in the three-dimensional stereoscopic image stored in the image storage module 41 and dynamically displaying the motion process of the three-dimensional stereoscopic image. For example, if the motion speed is 2 m / s, the operating member 13 and the sliding sleeve 12 are moved on the slide rail 11 at this motion speed. If the speed is too high during the motion process, a corresponding prompt will pop up, that is, the content corresponding to the image annotation module 43; an image annotation module 43 for displaying the comparison data and motion suggestions on the three-dimensional stereoscopic image in the image display module 42.

[0069] The above embodiments have introduced the present invention in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A VR-based upper and lower limb muscle training system, characterized in that: The training system includes: A muscle training device (1), the muscle training device (1) comprising a slide rail (11) as a mounting carrier, both ends of the slide rail (11) being elastically provided with slide sleeves (12) for sliding toward the center, and an operating member (13) for contacting a limb being rotatably mounted below the slide sleeve (12); A data acquisition unit (2), the data acquisition unit (2) comprising an accelerometer arranged in the slide rail (11) for acquiring acceleration changes of the position of the slide rail (11), a position sensor arranged on the slide rail (11) for detecting the position of the slide sleeve (12), and an angle sensor for acquiring a relative rotation angle between the operating member (13) and the slide sleeve (12), and transmitting the acquired basic data including acceleration data, position data and angle data to the data processing unit (3); A data processing unit (3), the data processing unit (3) being used to calculate intermediate data including acceleration change frequency, movement speed and angle interval based on the basic data collected by the data collection unit (2), and to compare the intermediate data with theoretical data preset in the data processing unit (3) to obtain comparative data, and to give exercise suggestions, and to output the comparative data and exercise suggestions to the data display unit (4); A data display unit (4) is used to correct and display a preset three-dimensional stereoscopic image based on the intermediate data of the data processing unit (3), and to display corresponding exercise suggestions on the three-dimensional stereoscopic image.

2. The muscle training system according to claim 1, characterized in that: The data processing unit (3) comprises: An acceleration change frequency module (31), the acceleration change frequency module (31) being used to obtain the number of acceleration changes of the two operating members (13) from the leaving end to the returning end based on the acceleration data collected in real time by the accelerometer output by the data collection unit (2) and the position data collected by the position sensor, so as to obtain the acceleration change frequency; A movement speed module (32), the movement speed module (32) being used to calculate the movement speed of the sliding sleeve (12) in unit time according to the position data acquired in real time by the position sensor; An angle interval module (33), the angle interval module (33) being used to obtain the maximum and minimum values ​​of the rotation angles of the two operating members (13) from the departure end to the return end according to the position data of the position sensor, so as to obtain the angle interval; A data storage module (34), the data storage module (34) is used to store the standard range of acceleration change frequency, movement speed and angle interval; A data comparison module (35) is used to output comparison data of whether the intermediate data is within the standard range of the data storage module (34), give exercise suggestions, and output the comparison data and exercise suggestions to the data display unit (4).

3. The muscle training system according to claim 2, characterized in that: The acceleration change frequency module (31) comprises: A statistical cycle acquisition module (311), the statistical cycle acquisition module (311) being used to acquire the statistical cycle of the two operating members (13) from leaving the end to returning to the end according to the position data collected by the position sensor; A threshold setting module (312), the threshold setting module (312) is used to set a numerical threshold and an angle threshold for the change in the value and direction of the acceleration data; An acceleration change module (313), the acceleration change module (313) is used to set a calculation cycle and calculate the acceleration value change and direction change of the acceleration data in each calculation cycle; A frequency statistics module (314), the frequency statistics module (314) is used to count the number of calculation cycles in which the acceleration value change is greater than the acceleration value threshold, or the acceleration direction change is greater than the angle threshold within the statistical period, so as to obtain the acceleration change frequency.

4. The muscle training system according to claim 3, characterized in that: In the acceleration change module (313), the calculation formula of the acceleration value change is: Δa=a1-a2 In the above formula, Δa represents the acceleration value change, a1 represents the acceleration value at the end of each calculation cycle, and a2 represents the acceleration value at the beginning of each calculation cycle; The calculation formula for the change in acceleration direction is: In the above formula, θ represents the change in the acceleration direction. represents the direction vector of the acceleration at the end of each calculation cycle, The direction vector representing the acceleration at the beginning of each computation cycle.

5. The muscle training system according to claim 2, characterized in that: The data comparison module (35) comprises: A comparison data module (351), the comparison data module (351) is used to output comparison data of whether the intermediate data is within the standard range of the data storage module (34), and output the comparison data to the data display unit (4); The exercise suggestion module (352) is used to set a discreteness interval, calculate the discreteness of each intermediate data within a period of time, and output a preset exercise suggestion according to whether the discreteness is within the discreteness interval, whether the discreteness is greater than the maximum value of the discreteness interval, and whether the discreteness is less than the minimum value of the discreteness interval.

6. The muscle training system according to claim 5, characterized in that: The calculation formula of the discreteness in the movement suggestion module (352) is: In the above formula, σ represents the discreteness, N represents the number of intermediate data used to calculate the discreteness, and x i represents the i-th intermediate data, Represents the average of the intermediate data used to calculate the dispersion.

7. The muscle training system according to claim 1, characterized in that: The data display unit (4) comprises: An image storage module (41), the image storage module (41) being used to store a three-dimensional image of the muscle training device (1); An image display module (42), the image display module (42) being used to use the intermediate data of the data processing unit (3) as the motion parameters of each component in the three-dimensional stereoscopic image stored by the image storage module (41), and dynamically display the motion process of the three-dimensional stereoscopic image; An image annotation module (43), wherein the image annotation module (43) is used to display the comparison data and the motion suggestion on the three-dimensional image in the image display module (42).

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